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value="clinpract" > Clinics and Practice </option> <option value="clockssleep" > Clocks & Sleep </option> <option value="coasts" > Coasts </option> <option value="coatings" > Coatings </option> <option value="colloids" > Colloids and Interfaces </option> <option value="colorants" > Colorants </option> <option value="commodities" > Commodities </option> <option value="complications" > Complications </option> <option value="compounds" > Compounds </option> <option value="computation" > Computation </option> <option value="csmf" > Computer Sciences & Mathematics Forum </option> <option value="computers" > Computers </option> <option value="condensedmatter" > Condensed Matter </option> <option value="conservation" > Conservation </option> <option value="constrmater" > Construction Materials </option> <option value="cmd" > Corrosion and Materials Degradation (CMD) </option> <option value="cosmetics" > Cosmetics </option> <option value="covid" > COVID </option> <option value="crops" > Crops </option> <option value="cryo" > Cryo </option> <option value="cryptography" > Cryptography </option> <option value="crystals" > Crystals </option> <option value="cimb" > Current Issues in Molecular Biology (CIMB) </option> <option value="curroncol" > Current Oncology </option> <option value="dairy" > Dairy </option> <option value="data" > Data </option> <option value="dentistry" > Dentistry Journal </option> <option value="dermato" > Dermato </option> <option value="dermatopathology" > Dermatopathology </option> <option value="designs" > Designs </option> <option value="diabetology" > Diabetology </option> <option value="diagnostics" > Diagnostics </option> <option value="dietetics" > Dietetics </option> <option value="digital" > Digital </option> <option value="disabilities" > Disabilities </option> <option value="diseases" > Diseases </option> <option value="diversity" > Diversity </option> <option value="dna" > DNA </option> <option value="drones" > Drones </option> <option value="ddc" > Drugs and Drug Candidates (DDC) </option> <option value="dynamics" > Dynamics </option> <option value="earth" > Earth </option> <option value="ecologies" > Ecologies </option> <option value="econometrics" > Econometrics </option> <option value="economies" > Economies </option> <option value="education" > Education Sciences </option> <option value="electricity" > Electricity </option> <option value="electrochem" > Electrochem </option> <option value="electronicmat" > Electronic Materials </option> <option value="electronics" > Electronics </option> <option value="ecm" > Emergency Care and Medicine </option> <option value="encyclopedia" > Encyclopedia </option> <option value="endocrines" > Endocrines </option> <option value="energies" > Energies </option> <option value="esa" > Energy Storage and Applications (ESA) </option> <option value="eng" > Eng </option> <option value="engproc" > Engineering Proceedings </option> <option value="entropy" > Entropy </option> <option value="environsciproc" > Environmental Sciences Proceedings </option> <option value="environments" > Environments </option> <option value="epidemiologia" > Epidemiologia </option> <option value="epigenomes" > Epigenomes </option> <option value="ebj" > European Burn Journal (EBJ) </option> <option value="ejihpe" > European Journal of Investigation in Health, Psychology and Education (EJIHPE) </option> <option value="fermentation" > Fermentation </option> <option value="fibers" > Fibers </option> <option value="fintech" > FinTech </option> <option value="fire" > Fire </option> <option value="fishes" > Fishes </option> <option value="fluids" > Fluids </option> <option value="foods" > Foods </option> <option value="forecasting" > Forecasting </option> <option value="forensicsci" > Forensic Sciences </option> <option value="forests" > Forests </option> <option value="fossstud" > Fossil Studies </option> <option value="foundations" > Foundations </option> <option value="fractalfract" > Fractal and Fractional (Fractal Fract) </option> <option value="fuels" > Fuels </option> <option value="future" > Future </option> <option value="futureinternet" > Future Internet </option> <option value="futurepharmacol" > Future Pharmacology </option> <option value="futuretransp" > Future Transportation </option> <option value="galaxies" > Galaxies </option> <option value="games" > Games </option> <option value="gases" > Gases </option> <option value="gastroent" > Gastroenterology Insights </option> <option value="gastrointestdisord" > Gastrointestinal Disorders </option> <option value="gastronomy" > Gastronomy </option> <option value="gels" > Gels </option> <option value="genealogy" > Genealogy </option> <option value="genes" > Genes </option> <option value="geographies" > Geographies </option> <option value="geohazards" > GeoHazards </option> <option value="geomatics" > Geomatics </option> <option value="geometry" > Geometry </option> <option value="geosciences" > Geosciences </option> <option value="geotechnics" > Geotechnics </option> <option value="geriatrics" > Geriatrics </option> <option value="glacies" > Glacies </option> <option value="gucdd" > Gout, Urate, and Crystal Deposition Disease (GUCDD) </option> <option value="grasses" > Grasses </option> <option value="hardware" > Hardware </option> <option value="healthcare" > Healthcare </option> <option value="hearts" > Hearts </option> <option value="hemato" > Hemato </option> <option value="hematolrep" > Hematology Reports </option> <option value="heritage" > Heritage </option> <option value="histories" > Histories </option> <option value="horticulturae" > Horticulturae </option> <option value="hospitals" > Hospitals </option> <option value="humanities" > Humanities </option> <option value="humans" > Humans </option> <option value="hydrobiology" > Hydrobiology </option> <option value="hydrogen" > Hydrogen </option> <option value="hydrology" > Hydrology </option> <option value="hygiene" > Hygiene </option> <option value="immuno" > Immuno </option> <option value="idr" > Infectious Disease Reports </option> <option value="informatics" > Informatics </option> <option value="information" > Information </option> <option value="infrastructures" > Infrastructures </option> <option value="inorganics" > Inorganics </option> <option value="insects" > Insects </option> <option value="instruments" > Instruments </option> <option value="iic" > Intelligent Infrastructure and Construction </option> <option value="ijerph" > International Journal of Environmental Research and Public Health (IJERPH) </option> <option value="ijfs" > International Journal of Financial Studies (IJFS) </option> <option value="ijms" > International Journal of Molecular Sciences (IJMS) </option> <option value="IJNS" > International Journal of Neonatal Screening (IJNS) </option> <option value="ijpb" > International Journal of Plant Biology (IJPB) </option> <option value="ijt" > International Journal of Topology 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Compos. Sci.) </option> <option value="jcp" > Journal of Cybersecurity and Privacy (JCP) </option> <option value="jdad" > Journal of Dementia and Alzheimer's Disease (JDAD) </option> <option value="jdb" > Journal of Developmental Biology (JDB) </option> <option value="jeta" > Journal of Experimental and Theoretical Analyses (JETA) </option> <option value="jfb" > Journal of Functional Biomaterials (JFB) </option> <option value="jfmk" > Journal of Functional Morphology and Kinesiology (JFMK) </option> <option value="jof" > Journal of Fungi (JoF) </option> <option value="jimaging" > Journal of Imaging (J. Imaging) </option> <option value="jintelligence" > Journal of Intelligence (J. Intell.) </option> <option value="jlpea" > Journal of Low Power Electronics and Applications (JLPEA) </option> <option value="jmmp" > Journal of Manufacturing and Materials Processing (JMMP) </option> <option value="jmse" > Journal of Marine Science and Engineering (JMSE) </option> <option value="jmahp" > Journal of Market Access & Health Policy (JMAHP) </option> <option value="jmp" > Journal of Molecular Pathology (JMP) </option> <option value="jnt" > Journal of Nanotheranostics (JNT) </option> <option value="jne" > Journal of Nuclear Engineering (JNE) </option> <option value="ohbm" > Journal of Otorhinolaryngology, Hearing and Balance Medicine (JOHBM) </option> <option value="jop" > Journal of Parks </option> <option value="jpm" > Journal of Personalized Medicine (JPM) </option> <option value="jpbi" > Journal of Pharmaceutical and BioTech Industry (JPBI) </option> <option value="jor" > Journal of Respiration (JoR) </option> <option value="jrfm" > Journal of Risk and Financial Management (JRFM) </option> <option value="jsan" > Journal of Sensor and Actuator Networks (JSAN) </option> <option value="joma" > Journal of the Oman Medical Association (JOMA) </option> <option value="jtaer" > Journal of Theoretical and Applied Electronic Commerce Research (JTAER) </option> <option value="jvd" > Journal of Vascular Diseases (JVD) </option> <option value="jox" > Journal of Xenobiotics (JoX) </option> <option value="jzbg" > Journal of Zoological and Botanical Gardens (JZBG) </option> <option value="journalmedia" > Journalism and Media </option> <option value="kidneydial" > Kidney and Dialysis </option> <option value="kinasesphosphatases" > Kinases and Phosphatases </option> <option value="knowledge" > Knowledge </option> <option value="labmed" > LabMed </option> <option value="laboratories" > Laboratories </option> <option value="land" > Land </option> <option value="languages" > Languages </option> <option value="laws" > Laws </option> <option value="life" > Life 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Med.) </option> <option value="resources" > Resources </option> <option value="rheumato" > Rheumato </option> <option value="risks" > Risks </option> <option value="robotics" > Robotics </option> <option value="ruminants" > Ruminants </option> <option value="safety" > Safety </option> <option value="sci" > Sci </option> <option value="scipharm" > Scientia Pharmaceutica (Sci. Pharm.) </option> <option value="sclerosis" > Sclerosis </option> <option value="seeds" > Seeds </option> <option value="sensors" > Sensors </option> <option value="separations" > Separations </option> <option value="sexes" > Sexes </option> <option value="signals" > Signals </option> <option value="sinusitis" > Sinusitis </option> <option value="smartcities" > Smart Cities </option> <option value="socsci" > Social Sciences </option> <option value="siuj" > Société Internationale d’Urologie Journal (SIUJ) </option> <option value="societies" > Societies </option> <option value="software" > Software </option> <option value="soilsystems" > Soil Systems </option> <option value="solar" > Solar </option> <option value="solids" > Solids </option> <option value="spectroscj" > Spectroscopy Journal </option> <option value="sports" > Sports </option> <option value="standards" > Standards </option> <option value="stats" > Stats </option> <option value="stresses" > Stresses </option> <option value="surfaces" > Surfaces </option> <option value="surgeries" > Surgeries </option> <option value="std" > Surgical Techniques Development </option> <option value="sustainability" > Sustainability </option> <option value="suschem" > Sustainable Chemistry </option> <option value="symmetry" > Symmetry </option> <option value="synbio" > SynBio </option> <option value="systems" > Systems </option> <option value="targets" > Targets </option> <option value="taxonomy" > Taxonomy </option> <option value="technologies" > Technologies </option> <option value="telecom" > Telecom </option> <option value="textiles" > Textiles </option> <option value="thalassrep" > Thalassemia Reports </option> <option value="therapeutics" > Therapeutics </option> <option value="thermo" > Thermo </option> <option value="timespace" > Time and Space </option> <option value="tomography" > Tomography </option> <option value="tourismhosp" > Tourism and Hospitality </option> <option value="toxics" > Toxics </option> 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value="women" > Women </option> <option value="world" > World </option> <option value="wevj" > World Electric Vehicle Journal (WEVJ) </option> <option value="youth" > Youth </option> <option value="zoonoticdis" > Zoonotic Diseases </option> </select> </div> <div class="large-2 medium-2 small-6 columns "> <div class=""> <div class="search-input-label">Article Type</div> </div> <select id="article_type" tabindex="4" name="article_type" class="chosen-select"> <option value="">All Article Types</option> <option value="research-article">Article</option> <option value="review-article">Review</option> <option value="rapid-communication">Communication</option> <option value="editorial">Editorial</option> <option value="abstract">Abstract</option> <option value="book-review">Book Review</option> <option value="brief-communication">Brief Communication</option> <option value="brief-report">Brief Report</option> <option value="case-report">Case Report</option> <option 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class="custom-accordion-for-small-screen-link " > <h2>Saved Queries</h2> </div> <div class="target-item custom-accordion-for-small-screen-content show-for-medium-up"> <div class="generic-item refind-item-wrap no-border last-item no-padding-top"> <a class="bold" href="/user/login">Sign in</a> to use this feature. </div> </div> </div> <div class="content__container " > <div class="custom-accordion-for-small-screen-link " data-callback=processResetAllVisibility> <h2> Search Filter <a href="#" class="remove-refines remove-refines-all link--red right">Reset All</a> </h2> </div> <div class="target-item custom-accordion-for-small-screen-content show-for-medium-up"> <div class="generic-item refind-item-wrap no-border no-padding-top"> <h3>Years</h3> <span>Between:</span> <input type="number" id="refine_year_from" style="display: inline-block; font-size: 12px;" name="year_from" value="1996" min="1996" max="2024"> - <input type="number" id="refine_year_to" style="display: inline-block; font-size: 12px;" name="year_to" value="2024" min="1996" max="2024"> <div id="year-range"></div> <div style="clear:both;"></div> </div> <div class="generic-item refind-item-wrap filter-container filter-container-featured" style="display: none;"> <h3>Feature Papers</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_featured_1"> <i class="material-icons">remove_circle_outline</i> </a> <label> Feature Papers </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-featured" data-filter="featured"><strong>Add Feature Papers</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="featured"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button 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data-filterid="refine_subjects_engineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_environment"> <i class="material-icons">remove_circle_outline</i> </a> <label> Environmental & Earth Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_chem-materials"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemistry & Materials Science </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_computer-math"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computer Science & Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_bio-life"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biology & Life Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_physics-astronomy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Physical Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_med-pharma"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medicine & Pharmacology </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_health"> <i class="material-icons">remove_circle_outline</i> </a> <label> Public Health & Healthcare </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_business-econ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Business & Economics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_arts-humanity"> <i class="material-icons">remove_circle_outline</i> </a> <label> Social Sciences, Arts and Humanities </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-subjects" data-filter="subjects"><strong>Add Subjects</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="subjects"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-subjects" data-filter="subjects" class="all">Select Subjects</a> </div> <div style="clear:both;"></div> <div id="refine-modal-subjects" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Subjects</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Subjects" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select subjects you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="engineering" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_engineering" value="engineering"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_engineering">Engineering (17841)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="environmental & earth sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_environment" value="environment"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_environment">Environmental & Earth Sciences (15202)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="chemistry & materials science" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_chem-materials" value="chem-materials"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_chem-materials">Chemistry & Materials Science (12421)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="computer science & mathematics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_computer-math" value="computer-math"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_computer-math">Computer Science & Mathematics (9107)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="biology & life sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_bio-life" value="bio-life"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_bio-life">Biology & Life Sciences (7248)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="physical sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_physics-astronomy" value="physics-astronomy"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_physics-astronomy">Physical Sciences (6253)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="medicine & pharmacology" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_med-pharma" value="med-pharma"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_med-pharma">Medicine & Pharmacology (2804)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="public health & healthcare" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_health" value="health"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_health">Public Health & Healthcare (2398)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="business & economics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_business-econ" value="business-econ"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_business-econ">Business & Economics (648)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="social sciences, arts and humanities" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_arts-humanity" value="arts-humanity"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_arts-humanity">Social Sciences, Arts and Humanities (624)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="subjects" onclick="$('#refine-modal-subjects').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="subjects" id="refine_subjects_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-journals" style=""> <h3>Journals</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sensors"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sensors </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_remotesensing"> <i class="material-icons">remove_circle_outline</i> </a> <label> Remote Sensing </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_applsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Applied Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_electronics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Electronics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_entropy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Entropy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_energies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Energies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_diagnostics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Diagnostics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mathematics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_symmetry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Symmetry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sustainability"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sustainability </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_cancers"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cancers </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_information"> <i class="material-icons">remove_circle_outline</i> </a> <label> Information </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijgi"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJGI </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_molecules"> <i class="material-icons">remove_circle_outline</i> </a> <label> Molecules </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_agriculture"> <i class="material-icons">remove_circle_outline</i> </a> <label> Agriculture </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jmse"> <i class="material-icons">remove_circle_outline</i> </a> <label> JMSE </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijms"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJMS </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_agronomy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Agronomy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_machines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Machines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_processes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Processes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_bioengineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bioengineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_algorithms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Algorithms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_forests"> <i class="material-icons">remove_circle_outline</i> </a> <label> Forests </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jimaging"> <i class="material-icons">remove_circle_outline</i> </a> <label> J. Imaging </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_brainsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brain Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijerph"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJERPH </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_foods"> <i class="material-icons">remove_circle_outline</i> </a> <label> Foods </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_water"> <i class="material-icons">remove_circle_outline</i> </a> <label> Water </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_drones"> <i class="material-icons">remove_circle_outline</i> </a> <label> Drones </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_plants"> <i class="material-icons">remove_circle_outline</i> </a> <label> Plants </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_futureinternet"> <i class="material-icons">remove_circle_outline</i> </a> <label> Future Internet </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jcm"> <i class="material-icons">remove_circle_outline</i> </a> <label> JCM </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_materials"> <i class="material-icons">remove_circle_outline</i> </a> <label> Materials </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_micromachines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Micromachines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_atmosphere"> <i class="material-icons">remove_circle_outline</i> </a> <label> Atmosphere </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_animals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Animals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_minerals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Minerals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_engproc"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jpm"> <i class="material-icons">remove_circle_outline</i> </a> <label> JPM </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_aerospace"> <i class="material-icons">remove_circle_outline</i> </a> <label> Aerospace </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_computers"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computers </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_polymers"> <i class="material-icons">remove_circle_outline</i> </a> <label> Polymers </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_buildings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Buildings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_marinedrugs"> <i class="material-icons">remove_circle_outline</i> </a> <label> Marine Drugs </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_BDCC"> <i class="material-icons">remove_circle_outline</i> </a> <label> BDCC </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_healthcare"> <i class="material-icons">remove_circle_outline</i> </a> <label> Healthcare </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_life"> <i class="material-icons">remove_circle_outline</i> </a> <label> Life </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_land"> <i class="material-icons">remove_circle_outline</i> </a> <label> Land </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomedicines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biomedicines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biosensors"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biosensors </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_genes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Genes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_coatings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Coatings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomolecules"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biomolecules </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_metabolites"> <i class="material-icons">remove_circle_outline</i> </a> <label> Metabolites </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_proceedings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_photonics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Photonics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomimetics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biomimetics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_nanomaterials"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nanomaterials </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_wevj"> <i class="material-icons">remove_circle_outline</i> </a> <label> WEVJ </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_antioxidants"> <i class="material-icons">remove_circle_outline</i> </a> <label> Antioxidants </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_nutrients"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nutrients </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_make"> <i class="material-icons">remove_circle_outline</i> </a> <label> MAKE </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biology"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biology </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_technologies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Technologies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_tomography"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tomography </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_metals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Metals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_actuators"> <i class="material-icons">remove_circle_outline</i> </a> <label> Actuators </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_cells"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cells </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_geosciences"> <i class="material-icons">remove_circle_outline</i> </a> <label> Geosciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_batteries"> <i class="material-icons">remove_circle_outline</i> </a> <label> Batteries </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_crystals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Crystals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_data"> <i class="material-icons">remove_circle_outline</i> </a> <label> Data </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_horticulturae"> <i class="material-icons">remove_circle_outline</i> </a> <label> Horticulturae </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_asi"> <i class="material-icons">remove_circle_outline</i> </a> <label> ASI </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ai"> <i class="material-icons">remove_circle_outline</i> </a> <label> AI </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_pharmaceuticals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pharmaceuticals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_informatics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Informatics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_pharmaceutics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pharmaceutics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_microorganisms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Microorganisms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fractalfract"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fractal Fract </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_computation"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computation </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_chemosensors"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemosensors </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fire"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fire </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_separations"> <i class="material-icons">remove_circle_outline</i> </a> <label> Separations </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_medicina"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medicina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_robotics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Robotics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_systems"> <i class="material-icons">remove_circle_outline</i> </a> <label> Systems </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomedinformatics"> <i class="material-icons">remove_circle_outline</i> </a> <label> BioMedInformatics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_lubricants"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lubricants </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_universe"> <i class="material-icons">remove_circle_outline</i> </a> <label> Universe </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_inventions"> <i class="material-icons">remove_circle_outline</i> </a> <label> Inventions </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_signals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Signals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_axioms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Axioms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_languages"> <i class="material-icons">remove_circle_outline</i> </a> <label> Languages </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_antibiotics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Antibiotics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jmmp"> <i class="material-icons">remove_circle_outline</i> </a> <label> JMMP </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_agriengineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> AgriEngineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_curroncol"> <i class="material-icons">remove_circle_outline</i> </a> <label> Current Oncology </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jsan"> <i class="material-icons">remove_circle_outline</i> </a> <label> JSAN </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mca"> <i class="material-icons">remove_circle_outline</i> </a> <label> MCA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_insects"> <i class="material-icons">remove_circle_outline</i> </a> <label> Insects </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fishes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fishes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_toxins"> <i class="material-icons">remove_circle_outline</i> </a> <label> Toxins </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_children"> <i class="material-icons">remove_circle_outline</i> </a> <label> Children </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fluids"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fluids </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_vibration"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vibration </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_heritage"> <i class="material-icons">remove_circle_outline</i> </a> <label> Heritage </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_membranes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Membranes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_gels"> <i class="material-icons">remove_circle_outline</i> </a> <label> Gels </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fermentation"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fermentation </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_smartcities"> <i class="material-icons">remove_circle_outline</i> </a> <label> Smart Cities </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_diversity"> <i class="material-icons">remove_circle_outline</i> </a> <label> Diversity </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_pathogens"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pathogens </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jof"> <i class="material-icons">remove_circle_outline</i> </a> <label> JoF </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_infrastructures"> <i class="material-icons">remove_circle_outline</i> </a> <label> Infrastructures </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mti"> <i class="material-icons">remove_circle_outline</i> </a> <label> MTI </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jlpea"> <i class="material-icons">remove_circle_outline</i> </a> <label> JLPEA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_behavsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Behavioral Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_education"> <i class="material-icons">remove_circle_outline</i> </a> <label> Education Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_cosmetics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cosmetics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_dentistry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Dentistry Journal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jrfm"> <i class="material-icons">remove_circle_outline</i> </a> <label> JRFM </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_acoustics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Acoustics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_viruses"> <i class="material-icons">remove_circle_outline</i> </a> <label> Viruses </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jfb"> <i class="material-icons">remove_circle_outline</i> </a> <label> JFB </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_hydrology"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hydrology </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jcs"> <i class="material-icons">remove_circle_outline</i> </a> <label> J. Compos. Sci. </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_modelling"> <i class="material-icons">remove_circle_outline</i> </a> <label> Modelling </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_automation"> <i class="material-icons">remove_circle_outline</i> </a> <label> Automation </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_environsciproc"> <i class="material-icons">remove_circle_outline</i> </a> <label> Environmental Sciences Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_geomatics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Geomatics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jtaer"> <i class="material-icons">remove_circle_outline</i> </a> <label> JTAER </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_risks"> <i class="material-icons">remove_circle_outline</i> </a> <label> Risks </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_beverages"> <i class="material-icons">remove_circle_outline</i> </a> <label> Beverages </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jcdd"> <i class="material-icons">remove_circle_outline</i> </a> <label> JCDD </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mps"> <i class="material-icons">remove_circle_outline</i> </a> <label> MPs </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sci </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_vehicles"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vehicles </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jcp"> <i class="material-icons">remove_circle_outline</i> </a> <label> JCP </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_eng"> <i class="material-icons">remove_circle_outline</i> </a> <label> Eng </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_metrology"> <i class="material-icons">remove_circle_outline</i> </a> <label> Metrology </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_blsf"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biology and Life Sciences Forum </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_csmf"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computer Sciences & Mathematics Forum </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_catalysts"> <i class="material-icons">remove_circle_outline</i> </a> <label> Catalysts </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_galaxies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Galaxies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_environments"> <i class="material-icons">remove_circle_outline</i> </a> <label> Environments </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_resources"> <i class="material-icons">remove_circle_outline</i> </a> <label> Resources </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ChemEngineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> ChemEngineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_inorganics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Inorganics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_toxics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Toxics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_urbansci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Urban Science </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_forecasting"> <i class="material-icons">remove_circle_outline</i> </a> <label> Forecasting </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_chemproc"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemistry Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_cimb"> <i class="material-icons">remove_circle_outline</i> </a> <label> CIMB </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijpb"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJPB </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_socsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Social Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_vaccines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vaccines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jintelligence"> <i class="material-icons">remove_circle_outline</i> </a> <label> J. Intell. </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_logistics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Logistics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_vetsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Veterinary Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_magnetochemistry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Magnetochemistry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_safety"> <i class="material-icons">remove_circle_outline</i> </a> <label> Safety </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_colloids"> <i class="material-icons">remove_circle_outline</i> </a> <label> Colloids and Interfaces </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_chemistry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemistry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_IoT"> <i class="material-icons">remove_circle_outline</i> </a> <label> IoT </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_forensicsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Forensic Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomechanics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biomechanics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_covid"> <i class="material-icons">remove_circle_outline</i> </a> <label> COVID </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_medsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medical Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_religions"> <i class="material-icons">remove_circle_outline</i> </a> <label> Religions </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_challenges"> <i class="material-icons">remove_circle_outline</i> </a> <label> Challenges </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fibers"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fibers </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_econometrics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Econometrics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_climate"> <i class="material-icons">remove_circle_outline</i> </a> <label> Climate </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_condensedmatter"> <i class="material-icons">remove_circle_outline</i> </a> <label> Condensed Matter </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_instruments"> <i class="material-icons">remove_circle_outline</i> </a> <label> Instruments </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_vision"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vision </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_designs"> <i class="material-icons">remove_circle_outline</i> </a> <label> Designs </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_tropicalmed"> <i class="material-icons">remove_circle_outline</i> </a> <label> TropicalMed </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijtpp"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJTPP </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_scipharm"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sci. Pharm. </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_neurosci"> <i class="material-icons">remove_circle_outline</i> </a> <label> NeuroSci </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_hearts"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hearts </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jne"> <i class="material-icons">remove_circle_outline</i> </a> <label> JNE </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_digital"> <i class="material-icons">remove_circle_outline</i> </a> <label> Digital </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mining"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mining </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_pediatrrep"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pediatric Reports </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_biomed"> <i class="material-icons">remove_circle_outline</i> </a> <label> BioMed </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_foundations"> <i class="material-icons">remove_circle_outline</i> </a> <label> Foundations </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_knowledge"> <i class="material-icons">remove_circle_outline</i> </a> <label> Knowledge </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_msf"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medical Sciences Forum </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_solar"> <i class="material-icons">remove_circle_outline</i> </a> <label> Solar </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_societies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Societies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_humanities"> <i class="material-icons">remove_circle_outline</i> </a> <label> Humanities </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_arts"> <i class="material-icons">remove_circle_outline</i> </a> <label> Arts </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_atoms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Atoms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_diseases"> <i class="material-icons">remove_circle_outline</i> </a> <label> Diseases </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_pharmacy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pharmacy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_publications"> <i class="material-icons">remove_circle_outline</i> </a> <label> Publications </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_geriatrics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Geriatrics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ncrna"> <i class="material-icons">remove_circle_outline</i> </a> <label> ncRNA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_carbon"> <i class="material-icons">remove_circle_outline</i> </a> <label> C </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sinusitis"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sinusitis </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_IJNS"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJNS </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_cryptography"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cryptography </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_qubs"> <i class="material-icons">remove_circle_outline</i> </a> <label> QuBS </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ceramics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ceramics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_reports"> <i class="material-icons">remove_circle_outline</i> </a> <label> Reports </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_gastrointestdisord"> <i class="material-icons">remove_circle_outline</i> </a> <label> Gastrointestinal Disorders </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_plasma"> <i class="material-icons">remove_circle_outline</i> </a> <label> Plasma </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_particles"> <i class="material-icons">remove_circle_outline</i> </a> <label> Particles </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_telecom"> <i class="material-icons">remove_circle_outline</i> </a> <label> Telecom </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_clockssleep"> <i class="material-icons">remove_circle_outline</i> </a> <label> Clocks & Sleep </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_dairy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Dairy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_J"> <i class="material-icons">remove_circle_outline</i> </a> <label> J </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_applmech"> <i class="material-icons">remove_circle_outline</i> </a> <label> Applied Mechanics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_soilsystems"> <i class="material-icons">remove_circle_outline</i> </a> <label> Soil Systems </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jnt"> <i class="material-icons">remove_circle_outline</i> </a> <label> JNT </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_oceans"> <i class="material-icons">remove_circle_outline</i> </a> <label> Oceans </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_optics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Optics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_prosthesis"> <i class="material-icons">remove_circle_outline</i> </a> <label> Prosthesis </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_suschem"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sustainable Chemistry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_organics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Organics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_livers"> <i class="material-icons">remove_circle_outline</i> </a> <label> 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class="refine_checkbox refine_journals" id="refine_journals_fintech" value="fintech"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_fintech">FinTech (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="physical sciences forum" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_psf" value="psf"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_psf">Physical Sciences Forum (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="applied biosciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_applbiosci" value="applbiosci"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_applbiosci">Applied Biosciences (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="air" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_air" value="air"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_air">Air (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ddc" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_ddc" value="ddc"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_ddc">DDC (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ndt" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_ndt" value="ndt"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_ndt">NDT (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="limnological review" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_limnolrev" value="limnolrev"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_limnolrev">Limnological Review (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="real estate" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_realestate" value="realestate"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_realestate">Real Estate (1)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="journals" onclick="$('#refine-modal-journals').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="journals" id="refine_journals_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-article_types" style=""> <h3>Article Types</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_research-article"> <i class="material-icons">remove_circle_outline</i> </a> <label> Article </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_review-article"> <i class="material-icons">remove_circle_outline</i> </a> <label> Review </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_rapid-communication"> <i class="material-icons">remove_circle_outline</i> </a> <label> Communication </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_proceedings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Proceeding Paper </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_technical-note"> <i class="material-icons">remove_circle_outline</i> </a> <label> Technical Note </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_systematic_review"> <i class="material-icons">remove_circle_outline</i> </a> <label> Systematic Review </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_letter"> <i class="material-icons">remove_circle_outline</i> </a> <label> Letter </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_abstract"> <i class="material-icons">remove_circle_outline</i> </a> <label> Abstract </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_case-report"> <i class="material-icons">remove_circle_outline</i> </a> <label> Case Report </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_editorial"> <i class="material-icons">remove_circle_outline</i> </a> <label> Editorial </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_brief-report"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brief Report </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_data-descriptor"> <i class="material-icons">remove_circle_outline</i> </a> <label> Data Descriptor </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_perspective"> <i class="material-icons">remove_circle_outline</i> </a> <label> Perspective </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_protocol"> <i class="material-icons">remove_circle_outline</i> </a> <label> Protocol </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_essay"> <i class="material-icons">remove_circle_outline</i> </a> <label> Essay </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_concept-paper"> <i class="material-icons">remove_circle_outline</i> </a> <label> Concept Paper </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_opinion"> <i class="material-icons">remove_circle_outline</i> </a> <label> Opinion </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_study-protocol"> <i class="material-icons">remove_circle_outline</i> </a> <label> Study Protocol </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_correction"> <i class="material-icons">remove_circle_outline</i> </a> <label> Correction </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_tutorial"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tutorial </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_article-commentary"> <i class="material-icons">remove_circle_outline</i> </a> <label> Comment </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_hypothesis"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hypothesis </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-article_types" data-filter="article_types"><strong>Add Article Types</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="article_types"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-article_types" data-filter="article_types" class="all">Select Article Types</a> </div> <div style="clear:both;"></div> <div id="refine-modal-article_types" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Article Types</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Article Types" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select article types you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="article" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_research-article" value="research-article"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_research-article">Article (23197)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="review" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_review-article" value="review-article"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_review-article">Review (852)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="communication" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_rapid-communication" value="rapid-communication"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_rapid-communication">Communication (164)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="proceeding paper" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_proceedings" value="proceedings"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_proceedings">Proceeding Paper (145)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="technical note" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_technical-note" value="technical-note"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_technical-note">Technical Note (110)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="systematic review" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_systematic_review" value="systematic_review"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_systematic_review">Systematic Review (79)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="letter" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_letter" value="letter"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_letter">Letter (46)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="abstract" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_abstract" value="abstract"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_abstract">Abstract (20)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="case report" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_case-report" value="case-report"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_case-report">Case Report (16)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="editorial" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_editorial" value="editorial"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_editorial">Editorial (14)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="brief report" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_brief-report" value="brief-report"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_brief-report">Brief Report (13)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="data descriptor" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_data-descriptor" value="data-descriptor"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_data-descriptor">Data Descriptor (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="perspective" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_perspective" value="perspective"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_perspective">Perspective (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="protocol" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_protocol" value="protocol"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_protocol">Protocol (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="essay" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_essay" value="essay"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_essay">Essay (4)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="concept paper" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_concept-paper" value="concept-paper"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_concept-paper">Concept Paper (4)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="opinion" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_opinion" value="opinion"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_opinion">Opinion (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="study protocol" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_study-protocol" value="study-protocol"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_study-protocol">Study Protocol (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="correction" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_correction" value="correction"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_correction">Correction (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="tutorial" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_tutorial" value="tutorial"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_tutorial">Tutorial (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="comment" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_article-commentary" value="article-commentary"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_article-commentary">Comment (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="hypothesis" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_hypothesis" value="hypothesis"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_hypothesis">Hypothesis (1)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="article_types" onclick="$('#refine-modal-article_types').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="article_types" id="refine_article_types_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-countries" style=""> <h3>Countries / Regions</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> China </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_STATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> USA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KOREA_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Republic of Korea </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ITALY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Italy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SAUDI_ARABIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Saudi Arabia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_KINGDOM"> <i class="material-icons">remove_circle_outline</i> </a> <label> UK </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GERMANY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Germany </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SPAIN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Spain </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> India </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TAIWAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Taiwan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CANADA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Canada </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JAPAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Japan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PAKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pakistan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRALIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Australia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FRANCE"> <i class="material-icons">remove_circle_outline</i> </a> <label> France </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_POLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Poland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_EGYPT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Egypt </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MALAYSIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Malaysia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GREECE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Greece </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PORTUGAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Portugal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BRAZIL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brazil </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TURKEY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Turkey (Türkiye) </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAN_ISLAMIC_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iran </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NETHERLANDS"> <i class="material-icons">remove_circle_outline</i> </a> <label> The Netherlands </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MEXICO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mexico </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_RUSSIAN_FEDERATION"> <i class="material-icons">remove_circle_outline</i> </a> <label> Russia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ROMANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Romania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SINGAPORE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Singapore </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_ARAB_EMIRATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> United Arab Emirates </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NORWAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Norway </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BELGIUM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Belgium </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWITZERLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Switzerland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWEDEN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sweden </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Austria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BANGLADESH"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bangladesh </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_THAILAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Thailand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_VIETNAM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vietnam </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SOUTH_AFRICA"> <i class="material-icons">remove_circle_outline</i> </a> <label> South Africa </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FINLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Finland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRELAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ireland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDONESIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Indonesia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAQ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iraq </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CZECH_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Czech Republic </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_COLOMBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Colombia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JORDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Jordan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_DENMARK"> <i class="material-icons">remove_circle_outline</i> </a> <label> Denmark </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LITHUANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lithuania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TUNISIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tunisia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NEW_ZEALAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> New Zealand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ALGERIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Algeria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MOROCCO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Morocco </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHILE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chile </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVENIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovenia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_HUNGARY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hungary </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_QATAR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Qatar </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SERBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Serbia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KUWAIT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kuwait </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_YEMEN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Yemen </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NIGERIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nigeria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ISRAEL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Israel </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BULGARIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bulgaria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ECUADOR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ecuador </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LEBANON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lebanon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_HONG_KONG"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hong Kong </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CROATIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Croatia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVAKIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovakia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PHILIPPINES"> <i class="material-icons">remove_circle_outline</i> </a> <label> Philippines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UKRAINE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ukraine </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ARGENTINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Argentina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BRUNEI"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brunei </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KAZAKHSTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kazakhstan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ETHIOPIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ethiopia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UZBEKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uzbekistan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CYPRUS"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cyprus </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SRI_LANKA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sri Lanka </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ICELAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iceland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KENYA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kenya </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ESTONIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Estonia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GHANA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ghana </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LATVIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Latvia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_OMAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Oman </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SUDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sudan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PERU"> <i class="material-icons">remove_circle_outline</i> </a> <label> Peru </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LIBYAN_ARAB_JAMAHIRIYA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Libya </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MONGOLIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mongolia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NEPAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nepal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_VENEZUELA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Venezuela </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NORTH_MACEDONIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> North Macedonia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CUBA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cuba </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PALESTINE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Palestine </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ANGOLA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Angola </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PARAGUAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Paraguay </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TANZANIA_UNITED_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tanzania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BURKINA_FASO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Burkina Faso </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CAMEROON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cameroon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GABON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Gabon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SYRIAN_ARAB_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Syrian Arab Republic </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ALBANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Albania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BAHRAIN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bahrain </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BOSNIA_AND_HERZEGOVINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bosnia and Herzegovina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FIJI"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fiji </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_RWANDA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Rwanda </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UGANDA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uganda </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AZERBAIJAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Azerbaijan </label> </div/> <div 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data-filterid="refine_countries_MALAWI"> <i class="material-icons">remove_circle_outline</i> </a> <label> Malawi </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MAURITIUS"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mauritius </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MYANMAR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Myanmar </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PANAMA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Panama </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link 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id="refine_countries_IRAN_ISLAMIC_REPUBLIC_OF" value="IRAN_ISLAMIC_REPUBLIC_OF"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_IRAN_ISLAMIC_REPUBLIC_OF">Iran (214)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="the netherlands" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NETHERLANDS" value="NETHERLANDS"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NETHERLANDS">The Netherlands (211)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="mexico" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_MEXICO" value="MEXICO"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_MEXICO">Mexico (206)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="russia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_RUSSIAN_FEDERATION" value="RUSSIAN_FEDERATION"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_RUSSIAN_FEDERATION">Russia (195)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="romania" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ROMANIA" value="ROMANIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ROMANIA">Romania (188)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="singapore" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SINGAPORE" value="SINGAPORE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SINGAPORE">Singapore (166)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="united arab emirates" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UNITED_ARAB_EMIRATES" value="UNITED_ARAB_EMIRATES"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UNITED_ARAB_EMIRATES">United Arab Emirates (166)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="norway" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NORWAY" value="NORWAY"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NORWAY">Norway (147)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="belgium" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BELGIUM" value="BELGIUM"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BELGIUM">Belgium (146)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="switzerland" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SWITZERLAND" value="SWITZERLAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SWITZERLAND">Switzerland (135)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="sweden" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SWEDEN" value="SWEDEN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SWEDEN">Sweden (130)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="austria" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_AUSTRIA" value="AUSTRIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_AUSTRIA">Austria (126)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="bangladesh" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BANGLADESH" value="BANGLADESH"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BANGLADESH">Bangladesh (115)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="thailand" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_THAILAND" value="THAILAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_THAILAND">Thailand (115)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="vietnam" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_VIETNAM" value="VIETNAM"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_VIETNAM">Vietnam (108)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="south africa" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SOUTH_AFRICA" value="SOUTH_AFRICA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SOUTH_AFRICA">South Africa (106)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="finland" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_FINLAND" value="FINLAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_FINLAND">Finland (104)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ireland" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_IRELAND" value="IRELAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_IRELAND">Ireland (102)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="indonesia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_INDONESIA" value="INDONESIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_INDONESIA">Indonesia (97)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="iraq" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_IRAQ" value="IRAQ"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_IRAQ">Iraq (97)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="czech republic" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CZECH_REPUBLIC" value="CZECH_REPUBLIC"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CZECH_REPUBLIC">Czech Republic (87)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="colombia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_COLOMBIA" value="COLOMBIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_COLOMBIA">Colombia (86)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="jordan" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_JORDAN" value="JORDAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_JORDAN">Jordan (83)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="denmark" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_DENMARK" value="DENMARK"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_DENMARK">Denmark (79)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="lithuania" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_LITHUANIA" value="LITHUANIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_LITHUANIA">Lithuania (78)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="tunisia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_TUNISIA" value="TUNISIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_TUNISIA">Tunisia (76)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="new zealand" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NEW_ZEALAND" value="NEW_ZEALAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NEW_ZEALAND">New Zealand (75)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="algeria" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ALGERIA" value="ALGERIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ALGERIA">Algeria (69)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="morocco" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_MOROCCO" value="MOROCCO"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_MOROCCO">Morocco (67)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="chile" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CHILE" value="CHILE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CHILE">Chile (59)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="slovenia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SLOVENIA" value="SLOVENIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SLOVENIA">Slovenia (53)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="hungary" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_HUNGARY" value="HUNGARY"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_HUNGARY">Hungary (52)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="qatar" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_QATAR" value="QATAR"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_QATAR">Qatar (51)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="serbia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SERBIA" value="SERBIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SERBIA">Serbia (50)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="kuwait" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_KUWAIT" value="KUWAIT"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_KUWAIT">Kuwait (44)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="yemen" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_YEMEN" value="YEMEN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_YEMEN">Yemen (44)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="nigeria" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NIGERIA" value="NIGERIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NIGERIA">Nigeria (42)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="israel" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ISRAEL" value="ISRAEL"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ISRAEL">Israel (41)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="bulgaria" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BULGARIA" value="BULGARIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BULGARIA">Bulgaria (40)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ecuador" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ECUADOR" value="ECUADOR"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ECUADOR">Ecuador (40)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="lebanon" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_LEBANON" value="LEBANON"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_LEBANON">Lebanon (37)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="hong kong" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_HONG_KONG" value="HONG_KONG"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_HONG_KONG">Hong Kong (34)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="croatia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CROATIA" value="CROATIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CROATIA">Croatia (33)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="slovakia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SLOVAKIA" value="SLOVAKIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SLOVAKIA">Slovakia (33)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="philippines" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PHILIPPINES" value="PHILIPPINES"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_PHILIPPINES">Philippines (27)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ukraine" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UKRAINE" value="UKRAINE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UKRAINE">Ukraine (23)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="argentina" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ARGENTINA" value="ARGENTINA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ARGENTINA">Argentina (21)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="brunei" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BRUNEI" value="BRUNEI"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BRUNEI">Brunei (21)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="kazakhstan" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_KAZAKHSTAN" value="KAZAKHSTAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_KAZAKHSTAN">Kazakhstan (21)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ethiopia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ETHIOPIA" value="ETHIOPIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ETHIOPIA">Ethiopia (19)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="uzbekistan" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UZBEKISTAN" value="UZBEKISTAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UZBEKISTAN">Uzbekistan (18)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="cyprus" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CYPRUS" value="CYPRUS"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CYPRUS">Cyprus (17)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="sri lanka" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SRI_LANKA" value="SRI_LANKA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SRI_LANKA">Sri Lanka (16)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="iceland" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ICELAND" value="ICELAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ICELAND">Iceland (14)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="kenya" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_KENYA" value="KENYA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_KENYA">Kenya (14)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="estonia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ESTONIA" value="ESTONIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ESTONIA">Estonia (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ghana" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_GHANA" value="GHANA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_GHANA">Ghana (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="latvia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_LATVIA" value="LATVIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_LATVIA">Latvia (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="oman" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_OMAN" value="OMAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_OMAN">Oman (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="sudan" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SUDAN" value="SUDAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SUDAN">Sudan (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="peru" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PERU" value="PERU"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_PERU">Peru (10)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="libya" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_LIBYAN_ARAB_JAMAHIRIYA" value="LIBYAN_ARAB_JAMAHIRIYA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_LIBYAN_ARAB_JAMAHIRIYA">Libya (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="mongolia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_MONGOLIA" value="MONGOLIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_MONGOLIA">Mongolia (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="nepal" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NEPAL" value="NEPAL"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NEPAL">Nepal (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="venezuela" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_VENEZUELA" value="VENEZUELA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_VENEZUELA">Venezuela (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="north macedonia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_NORTH_MACEDONIA" value="NORTH_MACEDONIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_NORTH_MACEDONIA">North Macedonia (9)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="cuba" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CUBA" value="CUBA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CUBA">Cuba (8)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="palestine" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PALESTINE" value="PALESTINE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_PALESTINE">Palestine (8)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="angola" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ANGOLA" value="ANGOLA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ANGOLA">Angola (7)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="paraguay" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PARAGUAY" value="PARAGUAY"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_PARAGUAY">Paraguay (7)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="tanzania" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_TANZANIA_UNITED_REPUBLIC_OF" value="TANZANIA_UNITED_REPUBLIC_OF"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_TANZANIA_UNITED_REPUBLIC_OF">Tanzania (7)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="burkina faso" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BURKINA_FASO" value="BURKINA_FASO"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BURKINA_FASO">Burkina Faso (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="cameroon" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CAMEROON" value="CAMEROON"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CAMEROON">Cameroon (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="gabon" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_GABON" value="GABON"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_GABON">Gabon (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="syrian arab republic" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SYRIAN_ARAB_REPUBLIC" value="SYRIAN_ARAB_REPUBLIC"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SYRIAN_ARAB_REPUBLIC">Syrian Arab Republic (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="albania" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ALBANIA" value="ALBANIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ALBANIA">Albania (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="bahrain" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BAHRAIN" value="BAHRAIN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BAHRAIN">Bahrain (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="bosnia and herzegovina" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BOSNIA_AND_HERZEGOVINA" value="BOSNIA_AND_HERZEGOVINA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BOSNIA_AND_HERZEGOVINA">Bosnia and Herzegovina (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="fiji" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_FIJI" value="FIJI"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_FIJI">Fiji (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="rwanda" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_RWANDA" value="RWANDA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_RWANDA">Rwanda (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="uganda" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UGANDA" value="UGANDA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UGANDA">Uganda (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="azerbaijan" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_AZERBAIJAN" value="AZERBAIJAN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_AZERBAIJAN">Azerbaijan (4)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="luxembourg" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_LUXEMBOURG" value="LUXEMBOURG"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_LUXEMBOURG">Luxembourg (4)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="uruguay" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input 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for="refine_countries_BELARUS">Belarus (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="benin" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BENIN" value="BENIN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_BENIN">Benin (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="cambodia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CAMBODIA" value="CAMBODIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CAMBODIA">Cambodia (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="costa rica" style="padding-top: 0px; padding-bottom: 0px; 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style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_COTE_DIVOIRE" value="COTE_DIVOIRE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_COTE_DIVOIRE">Côte d'Ivoire (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="dominican republic" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_DOMINICAN_REPUBLIC" value="DOMINICAN_REPUBLIC"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_DOMINICAN_REPUBLIC">Dominican Republic (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="eritrea" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox 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<div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="mauritius" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_MAURITIUS" value="MAURITIUS"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_MAURITIUS">Mauritius (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="myanmar" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_MYANMAR" value="MYANMAR"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_MYANMAR">Myanmar (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="panama" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" 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class="UD_Listings_ArticlePDF" title="Article PDF" data-name="KoHMT: A Multimodal Emotion Recognition Model Integrating KoELECTRA, HuBERT with Multimodal Transformer" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4674">KoHMT: A Multimodal Emotion Recognition Model Integrating KoELECTRA, HuBERT with Multimodal Transformer</a> <div class="authors"> by <span class="inlineblock "><strong>Moung-Ho Yi</strong>, </span><span class="inlineblock "><strong>Keun-Chang Kwak</strong> and </span><span class="inlineblock "><strong>Ju-Hyun Shin</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4674; https://doi.org/10.3390/electronics13234674 (registering DOI) - 27 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> With the advancement of human-computer interaction, the role of emotion recognition has become increasingly significant. Emotion recognition technology provides practical benefits across various industries, including user experience enhancement, education, and organizational productivity. For instance, in educational settings, it enables real-time understanding of students’ <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4674/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> With the advancement of human-computer interaction, the role of emotion recognition has become increasingly significant. Emotion recognition technology provides practical benefits across various industries, including user experience enhancement, education, and organizational productivity. For instance, in educational settings, it enables real-time understanding of students’ emotional states, facilitating tailored feedback. In workplaces, monitoring employees’ emotions can contribute to improved job performance and satisfaction. Recently, emotion recognition has also gained attention in media applications such as automated movie dubbing, where it enhances the naturalness of dubbed performances by synchronizing emotional expression in both audio and visuals. Consequently, multimodal emotion recognition research, which integrates text, speech, and video data, has gained momentum in diverse fields. In this study, we propose an emotion recognition approach that combines text and speech data, specifically incorporating the characteristics of the Korean language. For text data, we utilize KoELECTRA to generate embeddings, and for speech data, we extract features using HuBERT embeddings. The proposed multimodal transformer model processes text and speech data independently, subsequently learning interactions between the two modalities through a Cross-Modal Attention mechanism. This approach effectively combines complementary information from text and speech, enhancing the accuracy of emotion recognition. Our experimental results demonstrate that the proposed model surpasses single-modality models, achieving a high accuracy of 77.01% and an F1-Score of 0.7703 in emotion classification. This study contributes to the advancement of emotion recognition technology by integrating diverse language and modality data, suggesting the potential for further improvements through the inclusion of additional modalities in future work. <a href="/2079-9292/13/23/4674">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/CW964112RW ">Application of Data Mining in Social Media</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4674/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1530346"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1530346"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1530346" data-cycle-prev="#prev1530346" data-cycle-progressive="#images1530346" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1530346-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g001-550.jpg?1732681410" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1530346" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1530346-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g002-550.jpg?1732681411'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1530346-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g003-550.jpg?1732681412'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1530346-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g004-550.jpg?1732681413'><p>Figure 4</p></div></script></div></div><div id="article-1530346-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g001-550.jpg?1732681410" title=" <strong>Figure 1</strong><br/> <p>Research structure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4674'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g002-550.jpg?1732681411" title=" <strong>Figure 2</strong><br/> <p>Accuracy and loss change graph based on epoch by model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4674'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g003-550.jpg?1732681412" title=" <strong>Figure 3</strong><br/> <p>Confusion Matrix heatmap for each emotion class.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4674'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04674/article_deploy/html/images/electronics-13-04674-g004-550.jpg?1732681413" title=" <strong>Figure 4</strong><br/> <p>Comprehensive results of Accuracy, Precision, Recall, and F1-Score by model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4674'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530324" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 26 pages, 20446 KiB   </span> <a href="/2227-9717/12/12/2671/pdf?version=1732672119" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Gas Content and Geological Control of Deep Jurassic Coalbed Methane in Baijiahai Uplift, Junggar Basin" data-journal="processes"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2227-9717/12/12/2671">Gas Content and Geological Control of Deep Jurassic Coalbed Methane in Baijiahai Uplift, Junggar Basin</a> <div class="authors"> by <span class="inlineblock "><strong>Bing Luo</strong>, </span><span class="inlineblock "><strong>Haichao Wang</strong>, </span><span class="inlineblock "><strong>Bin Sun</strong>, </span><span class="inlineblock "><strong>Zheyuan Ouyang</strong>, </span><span class="inlineblock "><strong>Mengmeng Yang</strong>, </span><span class="inlineblock "><strong>Yan Wang</strong> and </span><span class="inlineblock "><strong>Xiang Zhou</strong></span> </div> <div class="color-grey-dark"> <em>Processes</em> <b>2024</b>, <em>12</em>(12), 2671; https://doi.org/10.3390/pr12122671 (registering DOI) - 27 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Deep coalbed methane (CBM) resources are abundant in China, and in the last few years, the country’s search for and extraction of CBM have intensified, progressively moving from shallow to deep strata and from high-rank coal to medium- and low-rank coal. On the <a href="#" data-counterslink = "https://www.mdpi.com/2227-9717/12/12/2671/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Deep coalbed methane (CBM) resources are abundant in China, and in the last few years, the country’s search for and extraction of CBM have intensified, progressively moving from shallow to deep strata and from high-rank coal to medium- and low-rank coal. On the other hand, little is known about the gas content features of deep coal reservoirs in the eastern Junggar Basin, especially with regard to the gas content and the factors that affect it. Based on data from CBM drilling, logging, and seismic surveys, this study focuses on the gas content of Baijiahai Uplift’s primary Jurassic coal seams through experiments on the microscopic components of coal, industrial analysis, isothermal adsorption, low-temperature CO<sub>2</sub>, low-temperature N<sub>2</sub>, and high-pressure mercury injection. A systematic investigation of the controlling factors, including the depth, thickness, and quality of the coal seam and pore structure; tectonics; and lithology and thickness of the roof, was conducted. The results indicate that the Xishanyao Formation in the Baijiahai Uplift usually has a larger gas content than that in the Badaowan Formation, with the Xishanyao Formation showing that free gas and adsorbed gas coexist, while the Badaowan Formation primarily consists of adsorbed gas. The coal seams in the Baijiahai Uplift are generally deep and thick, and the coal samples from the Xishanyao and Badawan formations have a high vitrinite content, which contributes to their strong gas generation capacity. Additionally, low moisture and ash contents enhance the adsorption capacity of the coal seams, facilitating the storage of CBM. The pore-specific surface area of the coal samples is primarily provided by micropores, which is beneficial for CBM adsorption. Furthermore, a fault connecting the Carboniferous and Permian systems (C-P) developed in the northeastern part of the Baijiahai Uplift allows gas to migrate into the Xishanyao and Badaowan formations, resulting in a higher gas content in the coal seams. The roof lithology is predominantly mudstone with significant thickness, effectively reducing the dissipation of coalbed methane and promoting its accumulation. <a href="/2227-9717/12/12/2671">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/processes/special_issues/97S25A639J ">Exploration, Exploitation and Utilization of Coal and Gas Resources, 2nd Edition</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2227-9717/12/12/2671/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1530324"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1530324"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1530324" 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src='https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g017-550.jpg?1732672253'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-1530324-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g018-550.jpg?1732672254'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-1530324-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g019-550.jpg?1732672256'><p>Figure 19</p></div> --- <div class='openpopupgallery' data-imgindex='19' data-target='article-1530324-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g020-550.jpg?1732672256'><p>Figure 20</p></div></script></div></div><div id="article-1530324-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g001-550.jpg?1732672237" title=" <strong>Figure 1</strong><br/> <p>Geological background map and comprehensive histogram of coal-bearing strata [<a href="#B21-processes-12-02671" class="html-bibr">21</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g002-550.jpg?1732672238" title=" <strong>Figure 2</strong><br/> <p>Isothermal adsorption curve. Note: (<b>a</b>) is the isothermal adsorption curve of Xishanyao Formation and (<b>b</b>) is the isothermal adsorption curve of Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g003-550.jpg?1732672239" title=" <strong>Figure 3</strong><br/> <p>Measured and anticipated gas contents in the Baijiahai Uplift. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g004-550.jpg?1732672240" title=" <strong>Figure 4</strong><br/> <p>Neural network model calculation process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g005-550.jpg?1732672241" title=" <strong>Figure 5</strong><br/> <p>Comparison of adsorption gas content between adsorption model and neural network model. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g006-550.jpg?1732672242" title=" <strong>Figure 6</strong><br/> <p>Distribution of adsorbed gas content in Baijiahai Uplift. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g007-550.jpg?1732672242" title=" <strong>Figure 7</strong><br/> <p>Distribution of free gas content in Baijiahai Uplift.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g008-550.jpg?1732672243" title=" <strong>Figure 8</strong><br/> <p>Gas content distribution in Baijiahai Uplift.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g009-550.jpg?1732672244" title=" <strong>Figure 9</strong><br/> <p>Contour map of buried depth of Baijiahai Uplift. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g010-550.jpg?1732672244" title=" <strong>Figure 10</strong><br/> <p>Variation diagram of gas content with buried depth of coal seam.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g011-550.jpg?1732672245" title=" <strong>Figure 11</strong><br/> <p>Contour map of Baijiahai Uplift thickness. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g012-550.jpg?1732672245" title=" <strong>Figure 12</strong><br/> <p>Variation diagram of gas content with coal seam thickness.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g013-550.jpg?1732672248" title=" <strong>Figure 13</strong><br/> <p>(<b>a</b>) Relationship between VL and vitrinite content; (<b>b</b>) relationship between VL and moisture content; (<b>c</b>) relationship between VL and ash yield of Xishanyao Formation; (<b>d</b>) relationship between VL and ash yield of Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g014-550.jpg?1732672249" title=" <strong>Figure 14</strong><br/> <p>Characterization of pore volume’s full pore size of DN141 well. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g015-550.jpg?1732672251" title=" <strong>Figure 15</strong><br/> <p>Characterization of pore-specific surface area and full pore size of DN141 well. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g016-550.jpg?1732672252" title=" <strong>Figure 16</strong><br/> <p>(<b>a</b>) The relationship between adsorption gas content and pore-specific surface area and (<b>b</b>) the relationship between free gas content and pore volume.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g017-550.jpg?1732672253" title=" <strong>Figure 17</strong><br/> <p>Distribution map of the Baijiahai Uplift traps.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g018-550.jpg?1732672254" title=" <strong>Figure 18</strong><br/> <p>Seismic geological interpretation section (Reference: PetroChina). (<b>a</b>) The seismic profiles of wells DN11, DN18, C49, C504, C17, BJ3, and C32 are shown. (<b>b</b>) Well location distribution map.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g019-550.jpg?1732672256" title=" <strong>Figure 19</strong><br/> <p>Relationship diagram of roof lithology and gas content. (<b>a</b>) Xishanyao Formation and (<b>b</b>) Badaowan Formation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/processes/processes-12-02671/article_deploy/html/images/processes-12-02671-g020-550.jpg?1732672256" title=" <strong>Figure 20</strong><br/> <p>Lithology and thickness of main coal seam roof in Baijiahai Uplift. (<b>a</b>) Jurassic roof lithology frequency distribution histogram and (<b>b</b>) Jurassic roof thickness box diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9717/12/12/2671'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530305" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 29 pages, 4818 KiB   </span> <a href="/2075-4418/14/23/2666/pdf?version=1732640711" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals" data-journal="diagnostics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2075-4418/14/23/2666">ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals</a> <div class="authors"> by <span class="inlineblock "><strong>Omer Bektas</strong>, </span><span class="inlineblock "><strong>Serkan Kirik</strong>, </span><span class="inlineblock "><strong>Irem Tasci</strong>, </span><span class="inlineblock "><strong>Rena Hajiyeva</strong>, </span><span class="inlineblock "><strong>Emrah Aydemir</strong>, </span><span class="inlineblock "><strong>Sengul Dogan</strong> and </span><span class="inlineblock "><strong>Turker Tuncer</strong></span> </div> <div class="color-grey-dark"> <em>Diagnostics</em> <b>2024</b>, <em>14</em>(23), 2666; https://doi.org/10.3390/diagnostics14232666 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Background and Objectives: Electroencephalography (EEG) signals, often termed the letters of the brain, are one of the most cost-effective methods for gathering valuable information about brain activity. This study presents a new explainable feature engineering (XFE) model designed to classify EEG data for <a href="#" data-counterslink = "https://www.mdpi.com/2075-4418/14/23/2666/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Background and Objectives: Electroencephalography (EEG) signals, often termed the letters of the brain, are one of the most cost-effective methods for gathering valuable information about brain activity. This study presents a new explainable feature engineering (XFE) model designed to classify EEG data for violence detection. The primary objective is to assess the classification capability of the proposed XFE model, which uses a next-generation feature extractor, and to obtain interpretable findings for EEG-based violence and stress detection. Materials and Methods: In this research, two distinct EEG signal datasets were used to obtain classification and explainable results. The recommended XFE model utilizes a channel-based minimum and maximum pattern (ChMinMaxPat) feature extraction function, which generates 15 distinct feature vectors from EEG data. Cumulative weight-based neighborhood component analysis (CWNCA) is employed to select the most informative features from these vectors. Classification is performed by applying an iterative and ensemble t-algorithm-based k-nearest neighbors (tkNN) classifier to each feature vector. Information fusion is achieved through iterative majority voting (IMV), which consolidates the 15 tkNN classification results. Finally, the Directed Lobish (DLob) symbolic language generates interpretable outputs by leveraging the identities of the selected features. Together, the tkNN classifier, IMV-based information fusion, and DLob-based explainable feature extraction transform the model into a self-organizing explainable feature engineering (SOXFE) framework. Results: The ChMinMaxPat-based model achieved over 70% accuracy on both datasets with leave-one-record-out (LORO) cross-validation (CV) and over 90% accuracy with 10-fold CV. For each dataset, 15 DLob strings were generated, providing explainable outputs based on these symbolic representations. Conclusions: The ChMinMaxPat-based SOXFE model demonstrates high classification accuracy and interpretability in detecting violence and stress from EEG signals. This model contributes to both feature engineering and neuroscience by enabling explainable EEG classification, underscoring the potential importance of EEG analysis in clinical and forensic applications. <a href="/2075-4418/14/23/2666">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/diagnostics/special_issues/0MH57B8133 ">EEG Analysis in Diagnostics</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2075-4418/14/23/2666/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1530305"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1530305"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1530305" data-cycle-prev="#prev1530305" data-cycle-progressive="#images1530305" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1530305-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g001-550.jpg?1732640821" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1530305" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g002-550.jpg?1732640822'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g003-550.jpg?1732640823'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g004-550.jpg?1732640826'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g005-550.jpg?1732640828'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g006-550.jpg?1732640830'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g007-550.jpg?1732640832'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g008a-550.jpg?1732640833'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g008b-550.jpg?1732640834'><p>Figure 8 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A1a-550.jpg?1732640839'><p>Figure A1</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A1b-550.jpg?1732640841'><p>Figure A1 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A2a-550.jpg?1732640845'><p>Figure A2</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1530305-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A2b-550.jpg?1732640847'><p>Figure A2 Cont.</p></div></script></div></div><div id="article-1530305-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g001-550.jpg?1732640821" title=" <strong>Figure 1</strong><br/> <p>Sample EEG signals with 14 channels. Here, each color defines each channel.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g002-550.jpg?1732640822" title=" <strong>Figure 2</strong><br/> <p>A graphical overview of the presented ChMinMaxPat-based SOXFE model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g003-550.jpg?1732640823" title=" <strong>Figure 3</strong><br/> <p>Confusion matrices of the datasets used. (i) The EEG violence detection dataset. Herein, 0 is the control, and 1 is violence; (<b>a</b>) 10-fold CV; (b) LORO CV. (ii) The EEG stress detection dataset. Herein, 1 is stress, and 2 is the control; (<b>c</b>) 10-fold CV; (<b>d</b>) LORO CV.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g004-550.jpg?1732640826" title=" <strong>Figure 4</strong><br/> <p>Analysis of the violence detection DLob strings. (<b>a</b>) Entropy; (<b>b</b>) Histogram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g005-550.jpg?1732640828" title=" <strong>Figure 5</strong><br/> <p>Analysis of the stress detection DLob strings. (<b>a</b>) Entropy; (<b>b</b>) Histogram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g006-550.jpg?1732640830" title=" <strong>Figure 6</strong><br/> <p>Comparison of the feature vectors’ classification abilities. (<b>a</b>) Violence detection; (<b>b</b>) Stress detection.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g007-550.jpg?1732640832" title=" <strong>Figure 7</strong><br/> <p>A performance comparison of the classifiers using the 14th feature of the EEG violence detection dataset. Herein, DT: Decision Tree; LD: Linear Discriminant; LR: Logistic Regression; NB: Naïve Bayes; SVM: support vector machine; ESkNN: Ensemble Subspace kNN; MLP: Multi-Layer Perceptron; BT: Bagged Tree.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g008a-550.jpg?1732640833" title=" <strong>Figure 8</strong><br/> <p>The average classification accuracies of the voted outcomes and the tkNN-based outcomes. (<b>a</b>) Violence; (<b>b</b>) Stress.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g008b-550.jpg?1732640834" title=" <strong>Figure 8 Cont.</strong><br/> <p>The average classification accuracies of the voted outcomes and the tkNN-based outcomes. (<b>a</b>) Violence; (<b>b</b>) Stress.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A1a-550.jpg?1732640839" title=" <strong>Figure A1</strong><br/> <p>Connectome diagrams from EEG violence detection; (<b>a</b>) Selected feature vector 1; (<b>b</b>) Selected feature vector 2; (<b>c</b>) Selected feature vector 3; (<b>d</b>) Selected feature vector 4; (<b>e</b>) Selected feature vector 5; (<b>f</b>) Selected feature vector 6; (<b>g</b>) Selected feature vector 7; (<b>h</b>) Selected feature vector 8; (<b>i</b>) Selected feature vector 9; (<b>j</b>) Selected feature vector 10; (<b>k</b>) Selected feature vector 11; (<b>l</b>) Selected feature vector 12; (<b>m</b>) Selected feature vector 13; (<b>n</b>) Selected feature vector 14; (<b>o</b>) Selected feature vector 15.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A1b-550.jpg?1732640841" title=" <strong>Figure A1 Cont.</strong><br/> <p>Connectome diagrams from EEG violence detection; (<b>a</b>) Selected feature vector 1; (<b>b</b>) Selected feature vector 2; (<b>c</b>) Selected feature vector 3; (<b>d</b>) Selected feature vector 4; (<b>e</b>) Selected feature vector 5; (<b>f</b>) Selected feature vector 6; (<b>g</b>) Selected feature vector 7; (<b>h</b>) Selected feature vector 8; (<b>i</b>) Selected feature vector 9; (<b>j</b>) Selected feature vector 10; (<b>k</b>) Selected feature vector 11; (<b>l</b>) Selected feature vector 12; (<b>m</b>) Selected feature vector 13; (<b>n</b>) Selected feature vector 14; (<b>o</b>) Selected feature vector 15.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A2a-550.jpg?1732640845" title=" <strong>Figure A2</strong><br/> <p>Connectome diagrams from EEG stress detection. (<b>a</b>) Selected feature vector 1; (<b>b</b>) Selected feature vector 2; (<b>c</b>) Selected feature vector 3; (<b>d</b>) Selected feature vector 4; (<b>e</b>) Selected feature vector 5; (<b>f</b>) Selected feature vector 6; (<b>g</b>) Selected feature vector 7; (<b>h</b>) Selected feature vector 8; (<b>i</b>) Selected feature vector 9; (<b>j</b>) Selected feature vector 10; (<b>k</b>) Selected feature vector 11; (<b>l</b>) Selected feature vector 12; (<b>m</b>) Selected feature vector 13; (<b>n</b>) Selected feature vector 14; (<b>o</b>) Selected feature vector 15.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/diagnostics/diagnostics-14-02666/article_deploy/html/images/diagnostics-14-02666-g0A2b-550.jpg?1732640847" title=" <strong>Figure A2 Cont.</strong><br/> <p>Connectome diagrams from EEG stress detection. (<b>a</b>) Selected feature vector 1; (<b>b</b>) Selected feature vector 2; (<b>c</b>) Selected feature vector 3; (<b>d</b>) Selected feature vector 4; (<b>e</b>) Selected feature vector 5; (<b>f</b>) Selected feature vector 6; (<b>g</b>) Selected feature vector 7; (<b>h</b>) Selected feature vector 8; (<b>i</b>) Selected feature vector 9; (<b>j</b>) Selected feature vector 10; (<b>k</b>) Selected feature vector 11; (<b>l</b>) Selected feature vector 12; (<b>m</b>) Selected feature vector 13; (<b>n</b>) Selected feature vector 14; (<b>o</b>) Selected feature vector 15.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-4418/14/23/2666'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530250" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 806 KiB   </span> <a href="/1424-8220/24/23/7549/pdf?version=1732637346" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding" data-journal="sensors"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1424-8220/24/23/7549">MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding</a> <div class="authors"> by <span class="inlineblock "><strong>Dehao Zhang</strong>, </span><span class="inlineblock "><strong>Tao Zhang</strong>, </span><span class="inlineblock "><strong>Haijiang Sun</strong>, </span><span class="inlineblock "><strong>Yanhui Tang</strong> and </span><span class="inlineblock "><strong>Qiaoyuan Liu</strong></span> </div> <div class="color-grey-dark"> <em>Sensors</em> <b>2024</b>, <em>24</em>(23), 7549; https://doi.org/10.3390/s24237549 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning methods based on optical flow and Transformer have achieved <a href="#" data-counterslink = "https://www.mdpi.com/1424-8220/24/23/7549/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning methods based on optical flow and Transformer have achieved excellent results in this field, but most of the current algorithms are mainly concentrated on establishing a serialized token through the self-attention model, and they do not take into account the spatial relationship between facial landmarks. For the locality and changes in the micro-facial conditions themselves, we propose the deep learning model MCCA-VNET on the basis of Transformer. We effectively extract the changing features as the input of the model, fusing channel attention and spatial attention into Vision Transformer to capture correlations between features in different dimensions, which enhances the accuracy of the identification of micro-expressions. In order to verify the effectiveness of the algorithm mentioned, we conduct experimental testing in the SAMM, CAS (ME) II, and SMIC datasets and compared the results with other former best algorithms. Our algorithms can improve the UF1 score and UAR score to, respectively, 0.8676 and 0.8622 for the composite dataset, and they are better than other algorithms on multiple indicators, achieving the best comprehensive performance. <a href="/1424-8220/24/23/7549">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/sensors/sections/optical_sensors">Optical Sensors</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530242" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 2579 KiB   </span> <a href="/2075-5309/14/12/3780/pdf?version=1732636887" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Multi-Point Correlation Model to Predict and Impute Earth-Rock Dam Displacement Data for Deformation Monitoring" data-journal="buildings"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2075-5309/14/12/3780">A Multi-Point Correlation Model to Predict and Impute Earth-Rock Dam Displacement Data for Deformation Monitoring</a> <div class="authors"> by <span class="inlineblock "><strong>Lilang Pi</strong>, </span><span class="inlineblock "><strong>Chunfang Yue</strong> and </span><span class="inlineblock "><strong>Jiachen Shi</strong></span> </div> <div class="color-grey-dark"> <em>Buildings</em> <b>2024</b>, <em>14</em>(12), 3780; https://doi.org/10.3390/buildings14123780 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Deformation is a critical indicator of structural integrity, and monitoring deformation is essential for ensuring the long-term safety of dams. However, characterizing the spatial correlations among dam deformation sequences and the similarity between displacements at various measurement points poses significant challenges when using <a href="#" data-counterslink = "https://www.mdpi.com/2075-5309/14/12/3780/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Deformation is a critical indicator of structural integrity, and monitoring deformation is essential for ensuring the long-term safety of dams. However, characterizing the spatial correlations among dam deformation sequences and the similarity between displacements at various measurement points poses significant challenges when using single-point measurement models. Considering the limitations inherent in conventional models for processing spatiotemporal data, this paper introduces a novel model for predicting and imputing multi-point displacement monitoring data from earth-rock dams. The model integrates a convolutional neural network (CNN) with a bidirectional long short-term memory neural network (BiLSTM) while also incorporating an attention mechanism (AM). The CNN captures the spatial features of the displacement data, while the BiLSTM extracts temporal features. The AM assigns varying weights to input features, thereby enhancing the predictive accuracy of the model. The proposed model was experimentally validated, demonstrating its robust capabilities in data prediction and the imputation of missing data. The model provides a new strategy for forecasting dam deformation and addressing issues related to incomplete data. <a href="/2075-5309/14/12/3780">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/buildings/sections/BS">Building Structures</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530178" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 2365 KiB   </span> <a href="/1424-8220/24/23/7547/pdf?version=1732635231" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy" data-journal="sensors"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1424-8220/24/23/7547">Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy</a> <div class="authors"> by <span class="inlineblock "><strong>Dimitrios S. Kasampalis</strong>, </span><span class="inlineblock "><strong>Pavlos I. Tsouvaltzis</strong> and </span><span class="inlineblock "><strong>Anastasios S. Siomos</strong></span> </div> <div class="color-grey-dark"> <em>Sensors</em> <b>2024</b>, <em>24</em>(23), 7547; https://doi.org/10.3390/s24237547 (registering DOI) - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested <a href="#" data-counterslink = "https://www.mdpi.com/1424-8220/24/23/7547/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400–2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 °C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes’ activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H<sub>2</sub>O<sub>2</sub>] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H<sub>2</sub>O<sub>2</sub>, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products. <a href="/1424-8220/24/23/7547">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/sensors/sections/chemicalsensors">Chemical Sensors</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1424-8220/24/23/7547/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1530178"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1530178"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1530178" data-cycle-prev="#prev1530178" data-cycle-progressive="#images1530178" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1530178-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g001-550.jpg?1732635295" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1530178" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1530178-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g002-550.jpg?1732635297'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1530178-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g003-550.jpg?1732635298'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1530178-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g004-550.jpg?1732635300'><p>Figure 4</p></div></script></div></div><div id="article-1530178-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g001-550.jpg?1732635295" title=" <strong>Figure 1</strong><br/> <p>Classification rate (%) of pesticide-free and pesticide-treated baby lettuce leaves based on reflectance spectra data (340–2500 nm) within each day of pre-harvest production or postharvet storage, as well as average means for the whole period upon pooling the data of all individual days.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7547'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g002-550.jpg?1732635297" title=" <strong>Figure 2</strong><br/> <p>Spectra reflectance (%) of pesticide-free (blue line) and pesticide-treated (red line) baby lettuce leaves in the vis-NIR part (340–2500 nm) as average means for the whole period upon pooling the data captured in all individual days. The eleven green areas represent the parts of the spectrum that exhibited the most significant effect on the partial least squares discrimination analysis classifier and were detected using the genetic algorithm (GA).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7547'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g003-550.jpg?1732635298" title=" <strong>Figure 3</strong><br/> <p>The variable importance in projection scores (VIP) in the vis/NIR part (340–2500 nm), which represents the individual effect of each wavelength on the partial least squares discrimination analysis classifier. The vertical green lines correspond to the wavelengths with the highest VIP scores. The red dot line corresponds to the lowest limit above which a wavelength exhibits a significant effect in the discriminant analysis algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7547'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07547/article_deploy/html/images/sensors-24-07547-g004-550.jpg?1732635300" title=" <strong>Figure 4</strong><br/> <p>Classification rate (%) of pesticide-free and pesticide-treated baby lettuce leaves based on the reflectance spectra data at 377, 517, 689, 959, 994, 1361, 1390, 1875, and 2177 nm that were selected using the VIP scores analysis, within each day of pre-harvest production or post-harvest storage, as well as average for the whole period upon pooling the data captured in all individual days.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7547'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530071" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 31 pages, 2692 KiB   </span> <a href="/2072-4292/16/23/4427/pdf?version=1732631976" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Single-Scene SAR Image Data Augmentation Based on SBR and GAN for Target Recognition" data-journal="remotesensing"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-4292/16/23/4427">Single-Scene SAR Image Data Augmentation Based on SBR and GAN for Target Recognition</a> <div class="authors"> by <span class="inlineblock "><strong>Shangchen Feng</strong>, </span><span class="inlineblock "><strong>Xikai Fu</strong>, </span><span class="inlineblock "><strong>Yanlin Feng</strong> and </span><span class="inlineblock "><strong>Xiaolei Lv</strong></span> </div> <div class="color-grey-dark"> <em>Remote Sens.</em> <b>2024</b>, <em>16</em>(23), 4427; <a href="https://doi.org/10.3390/rs16234427">https://doi.org/10.3390/rs16234427</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> High-performance neural networks for synthetic aperture radar (SAR) automatic target recognition (ATR) often encounter the challenge of data scarcity. The lack of sufficient labeled SAR image datasets leads to the consideration of using simulated data to supplement the dataset. On the one hand, <a href="#" data-counterslink = "https://www.mdpi.com/2072-4292/16/23/4427/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> High-performance neural networks for synthetic aperture radar (SAR) automatic target recognition (ATR) often encounter the challenge of data scarcity. The lack of sufficient labeled SAR image datasets leads to the consideration of using simulated data to supplement the dataset. On the one hand, electromagnetic computation simulations provide high amplitude accuracy but are inefficient for large-scale datasets due to their complex computations and physical models. On the other hand, ray tracing simulations offer high geometric accuracy and computational efficiency but struggle with low amplitude correctness, hindering accurate numerical feature extraction. Furthermore, the emergence of generative adversarial networks (GANs) provides a way to generate simulated datasets, trying to balance computational efficiency with image quality. Nevertheless, the simulated SAR images generated based on random noise lack constraints, and it is also difficult to generate images that exceed the parameter conditions of the real image’s training set. Hence, it is essential to integrate physics-based simulation techniques into GANs to enhance the generalization ability of the imaging parameters. In this paper, we present the SingleScene-SAR Simulator, an efficient framework for SAR image simulation that operates under limited real SAR data. This simulator integrates rasterized shooting and bouncing rays (SBR) with cycle GAN, effectively achieving both amplitude correctness and geometric accuracy. The simulated images are appropriate for augmenting datasets in target recognition networks. Firstly, the SingleScene-SAR Simulator employs a rasterized SBR algorithm to generate radar cross section (RCS) images of target models. Secondly, a specific training pattern for cycle GAN is established to translate noisy RCS images into simulated SAR images that closely resemble real ones. Finally, these simulated images are utilized for data augmentation. Experimental results based on the constructed dataset show that with only one scene SAR image containing 30 target chips, the SingleScene-SAR Simulator can efficiently produce simulated SAR images that exhibit high similarity in both spatial and statistical distributions compared with real images. By employing simulated SAR images for data augmentation, the accuracy of target recognition networks can be consistently and significantly enhanced. <a href="/2072-4292/16/23/4427">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/remotesensing/special_issues/1N26L02PPJ ">Advances in Synthetic Aperture Radar (SAR) Data Processing and Applications</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530034" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 6267 KiB   </span> <a href="/2227-7390/12/23/3705/pdf?version=1732630592" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Precision Denoising in Medical Imaging via Generative Adversarial Network-Aided Low-Noise Discriminator Technique" data-journal="mathematics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2227-7390/12/23/3705">Precision Denoising in Medical Imaging via Generative Adversarial Network-Aided Low-Noise Discriminator Technique</a> <div class="authors"> by <span class="inlineblock "><strong>Turki M. Alanazi</strong> and </span><span class="inlineblock "><strong>Paolo Mercorelli</strong></span> </div> <div class="color-grey-dark"> <em>Mathematics</em> <b>2024</b>, <em>12</em>(23), 3705; <a href="https://doi.org/10.3390/math12233705">https://doi.org/10.3390/math12233705</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Medical imaging is significant for accurate diagnosis, and here, noise often degrades image quality, thus making it challenging to identify important information. Denoising is a component of traditional image pre-processing that helps prevent incorrect disease diagnosis. Mitigating the noise becomes difficult if there <a href="#" data-counterslink = "https://www.mdpi.com/2227-7390/12/23/3705/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Medical imaging is significant for accurate diagnosis, and here, noise often degrades image quality, thus making it challenging to identify important information. Denoising is a component of traditional image pre-processing that helps prevent incorrect disease diagnosis. Mitigating the noise becomes difficult if there are differences in the low-level segment features. Therefore, a Generative Adversarial Network (GAN)-aided Low-Noise Discriminator (LND) is introduced to improve the denoising effectiveness in medical images with a balanced image resolution with noise mitigation. The LND function is a key that distinguishes between high- and low-noise areas based on segmented features, which are also achieved by tuning the peak signal-to-noise ratio (PSNR). Considering the training sequences, the LND-identified intervals lessen the sequences to improve the changes in pixel reconstruction. The generator function in this method is responsible for increasing the PSNR improvements over the different pixels cumulatively. The proposed method successfully improves the pixel reconstruction by 11.05% and PSNR by 9.75%, with 9.75% less reconstruction time and 13.11% less extraction error for the higher pixel distribution ratios than other contemporary methods. <a href="/2227-7390/12/23/3705">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/mathematics/special_issues/704APW88SF ">Deep Neural Networks: Theory, Algorithms and Applications</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1530020" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 8899 KiB   </span> <a href="/2226-4310/11/12/976/pdf?version=1732630120" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Feature Coding and Graph via Transformer: Different Granularities Classification for Aircraft" data-journal="aerospace"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2226-4310/11/12/976">Feature Coding and Graph via Transformer: Different Granularities Classification for Aircraft</a> <div class="authors"> by <span class="inlineblock "><strong>Jianghao Rao</strong>, </span><span class="inlineblock "><strong>Senlin Qin</strong>, </span><span class="inlineblock "><strong>Zongyan An</strong>, </span><span class="inlineblock "><strong>Jianlin Zhang</strong>, </span><span class="inlineblock "><strong>Qiliang Bao</strong> and </span><span class="inlineblock "><strong>Zhenming Peng</strong></span> </div> <div class="color-grey-dark"> <em>Aerospace</em> <b>2024</b>, <em>11</em>(12), 976; <a href="https://doi.org/10.3390/aerospace11120976">https://doi.org/10.3390/aerospace11120976</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Against the background of the sky, imaging and perception of aircraft are crucial for various vision applications. Thanks to the ever-evolving nature of the convolutional neural network (CNN), it has become easier to distinguish and recognize different types of aircraft. Nevertheless, accurate classification <a href="#" data-counterslink = "https://www.mdpi.com/2226-4310/11/12/976/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Against the background of the sky, imaging and perception of aircraft are crucial for various vision applications. Thanks to the ever-evolving nature of the convolutional neural network (CNN), it has become easier to distinguish and recognize different types of aircraft. Nevertheless, accurate classification for sub-categories of aircraft still poses great challenges. On one hand, fine-grained recognition focuses on exploring and studying such problems. On the other hand, aircraft under different sub-categories and granularities put forward higher requirements for feature representation to classify, which led us to rethink the in-depth application of features. We noticed that information in the swin-transformer effectively represents the features in neural network layers, fully showcasing encoding and indexing for information. Through further research based on this, we proposed a better understanding of encoding and reuse for features, and innovatively performed feature coding graphically for classification. In this paper, our approach shows the effects on aircraft feature representation and classification, manifested from the flexible recognition effect at different aircraft category granularities, and outperforms other famous fine-grained classification models on this vision task. Not only did the approach we proposed demonstrate adaptability to aircraft at different classification granularities, but it also revealed the mechanisms and characteristics of feature encoding under different sample space partitions for classification. The relationship between the oriented representation of aircraft features and various classification granularities, which is manifested through different classification criteria, shows that feature coding and graph construction via the transformer opens a new door for specific defined classification tasks where objects are divided under various partition criteria, and provides another perspective on calculation and feature extraction in fine-grained classification. <a href="/2226-4310/11/12/976">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/aerospace/sections/aeronautics">Aeronautics</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529965" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 20 pages, 9751 KiB   </span> <a href="/1099-4300/26/12/1022/pdf?version=1732628313" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="6D Pose Estimation of Industrial Parts Based on Point Cloud Geometric Information Prediction for Robotic Grasping" data-journal="entropy"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1099-4300/26/12/1022">6D Pose Estimation of Industrial Parts Based on Point Cloud Geometric Information Prediction for Robotic Grasping</a> <div class="authors"> by <span class="inlineblock "><strong>Qinglei Zhang</strong>, </span><span class="inlineblock "><strong>Cuige Xue</strong>, </span><span class="inlineblock "><strong>Jiyun Qin</strong>, </span><span class="inlineblock "><strong>Jianguo Duan</strong> and </span><span class="inlineblock "><strong>Ying Zhou</strong></span> </div> <div class="color-grey-dark"> <em>Entropy</em> <b>2024</b>, <em>26</em>(12), 1022; <a href="https://doi.org/10.3390/e26121022">https://doi.org/10.3390/e26121022</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In industrial robotic arm gripping operations within disordered environments, the loss of physical information on the object’s surface is often caused by changes such as varying lighting conditions, weak surface textures, and sensor noise. This leads to inaccurate object detection and pose estimation <a href="#" data-counterslink = "https://www.mdpi.com/1099-4300/26/12/1022/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In industrial robotic arm gripping operations within disordered environments, the loss of physical information on the object’s surface is often caused by changes such as varying lighting conditions, weak surface textures, and sensor noise. This leads to inaccurate object detection and pose estimation information. A method for industrial object pose estimation using point cloud data is proposed to improve pose estimation accuracy. During the feature extraction process, both global and local information are captured by integrating the appearance features of RGB images with the geometric features of point clouds. Integrating semantic information with instance features effectively distinguishes instances of similar objects. The fusion of depth information and RGB color channels enriches spatial context and structure. A cross-entropy loss function is employed for multi-class target classification, and a discriminative loss function enables instance segmentation. A novel point cloud registration method is also introduced to address re-projection errors when mapping 3D keypoints to 2D planes. This method utilizes 3D geometric information, extracting edge features using point cloud curvature and normal vectors, and registers them with models to obtain accurate pose information. Experimental results demonstrate that the proposed method is effective and superior on the LineMod and YCB-Video datasets. Finally, objects are grasped by deploying a robotic arm on the grasping platform. <a href="/1099-4300/26/12/1022">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/entropy/sections/multidisciplinary_applications">Multidisciplinary Applications</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1099-4300/26/12/1022/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529965"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529965"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529965" data-cycle-prev="#prev1529965" data-cycle-progressive="#images1529965" data-cycle-slides=">div" data-cycle-log="false"><div 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data-imgindex='3' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g004-550.jpg?1732628396'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g005-550.jpg?1732628396'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g006-550.jpg?1732628397'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g007-550.jpg?1732628399'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g008-550.jpg?1732628401'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g009-550.jpg?1732628402'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g010-550.jpg?1732628404'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g011-550.jpg?1732628404'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g012-550.jpg?1732628407'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g013-550.jpg?1732628409'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g014-550.jpg?1732628411'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g015-550.jpg?1732628413'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g016a-550.jpg?1732628415'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-1529965-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g016b-550.jpg?1732628417'><p>Figure 16 Cont.</p></div></script></div></div><div id="article-1529965-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g001-550.jpg?1732628393" title=" <strong>Figure 1</strong><br/> <p>Posture estimation network structure. Feature extraction is performed on the given scene RGB and point cloud images, matching the target pose through semantic and instance prediction and designing a priority grasping strategy to achieve accurate grasping by the robotic arm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g002-550.jpg?1732628394" title=" <strong>Figure 2</strong><br/> <p>Instance segmentation branch network.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g003-550.jpg?1732628395" title=" <strong>Figure 3</strong><br/> <p>Hash table framework. For two point pairs in the model edge appearance, keypoint pair features are calculated and saved in the hash table for subsequent feature matching of the template point cloud with the instance point cloud.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g004-550.jpg?1732628396" title=" <strong>Figure 4</strong><br/> <p>Definition of B2B-DL descriptors. In order to find corresponding pairs of points between the scene and the model, a descriptor was devised by calculating the tangent lines and considering their direction as the direction of the points.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g005-550.jpg?1732628396" title=" <strong>Figure 5</strong><br/> <p>The coordinate transformation relationship between the instance and model point clouds. The inverse transformation <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>T</mi> </mrow> <mrow> <mi>p</mi> <mo>→</mo> <mi>g</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msubsup> </mrow> </semantics></math> repositions the reference point <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>p</mi> </mrow> <mrow> <mi>r</mi> </mrow> </msub> </mrow> </semantics></math> of the example point cloud to the origin, and the normal direction is aligned parallel to the <math display="inline"><semantics> <mrow> <mi>x</mi> </mrow> </semantics></math>-axis of the coordinate system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g006-550.jpg?1732628397" title=" <strong>Figure 6</strong><br/> <p>Positional information for each instance obtained by aligning the model point cloud with the field instance point cloud.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g007-550.jpg?1732628399" title=" <strong>Figure 7</strong><br/> <p>The experimental platform dominated by the 3D industrial camera, KUKA robotic arm, target object, and PLCS7-1200 is mainly used for industrial parts disordered gripping use.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g008-550.jpg?1732628401" title=" <strong>Figure 8</strong><br/> <p>In the suction device, each part corresponds to one kind of suction device; the first row consists of two sets of fixtures: the beam fixture and the roller fixture. The second row includes the suction device for the wheel fixture and the base fixture; the left side of each set of fixtures is its 3D model, and the right side is the real fixture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g009-550.jpg?1732628402" title=" <strong>Figure 9</strong><br/> <p>Coordinate transformation between the camera, robotic arm and object of the robotic gripping platform.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g010-550.jpg?1732628404" title=" <strong>Figure 10</strong><br/> <p>Four low-textured industrial parts. The first row shows, from left to right, the real object’s beam, hub, roller, and base. The second row shows the CAD models of the beam, hub, roller, and base from left to right.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g011-550.jpg?1732628404" title=" <strong>Figure 11</strong><br/> <p>The robot arm first gets the signal from PLC to grasp the target workpiece, then sucks up the corresponding fixture, returns to the home position, waits for the gripping position information, and executes the gripping operation, and the whole process is shown above.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g012-550.jpg?1732628407" title=" <strong>Figure 12</strong><br/> <p>Pose estimation results on LineMod dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g013-550.jpg?1732628409" title=" <strong>Figure 13</strong><br/> <p>Pose estimation results on the YCB-Video dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g014-550.jpg?1732628411" title=" <strong>Figure 14</strong><br/> <p>Pose estimation results on a real dataset. The results after instance segmentation clustering is shown in the second column, and the third column shows the attitude estimation results of the target object.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g015-550.jpg?1732628413" title=" <strong>Figure 15</strong><br/> <p>Pose estimation results obtained from testing in cluttered and occluded scenes. Each of these columns gives the RGB image, depth map, depth map converted point cloud, example point cloud clustering, edge estimation, and pose estimation results. This is a figure; schemes follow the same formatting.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g016a-550.jpg?1732628415" title=" <strong>Figure 16</strong><br/> <p>Some results of the robotic arm gripping experiments are performed in the real scene. Two kinds of workpieces are selected as gripping objects: a hub and eight wheels. Each column shows the process of converting the positional results obtained with the algorithm into positional information in robotic arm coordinates to make the robotic arm grasp each object.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/entropy/entropy-26-01022/article_deploy/html/images/entropy-26-01022-g016b-550.jpg?1732628417" title=" <strong>Figure 16 Cont.</strong><br/> <p>Some results of the robotic arm gripping experiments are performed in the real scene. Two kinds of workpieces are selected as gripping objects: a hub and eight wheels. Each column shows the process of converting the positional results obtained with the algorithm into positional information in robotic arm coordinates to make the robotic arm grasp each object.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1099-4300/26/12/1022'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529948" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 25 pages, 84107 KiB   </span> <a href="/2076-2615/14/23/3415/pdf?version=1732627498" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="SMEA-YOLOv8n: A Sheep Facial Expression Recognition Method Based on an Improved YOLOv8n Model" data-journal="animals"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-2615/14/23/3415">SMEA-YOLOv8n: A Sheep Facial Expression Recognition Method Based on an Improved YOLOv8n Model</a> <div class="authors"> by <span class="inlineblock "><strong>Wenbo Yu</strong>, </span><span class="inlineblock "><strong>Xiang Yang</strong>, </span><span class="inlineblock "><strong>Yongqi Liu</strong>, </span><span class="inlineblock "><strong>Chuanzhong Xuan</strong>, </span><span class="inlineblock "><strong>Ruoya Xie</strong> and </span><span class="inlineblock "><strong>Chuanjiu Wang</strong></span> </div> <div class="color-grey-dark"> <em>Animals</em> <b>2024</b>, <em>14</em>(23), 3415; <a href="https://doi.org/10.3390/ani14233415">https://doi.org/10.3390/ani14233415</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Sheep facial expressions are valuable indicators of their pain levels, playing a critical role in monitoring their health and welfare. In response to challenges such as missed detections, false positives, and low recognition accuracy in sheep facial expression recognition, this paper introduces an <a href="#" data-counterslink = "https://www.mdpi.com/2076-2615/14/23/3415/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Sheep facial expressions are valuable indicators of their pain levels, playing a critical role in monitoring their health and welfare. In response to challenges such as missed detections, false positives, and low recognition accuracy in sheep facial expression recognition, this paper introduces an enhanced algorithm based on YOLOv8n, referred to as SimAM-MobileViTAttention-EfficiCIoU-AA2_SPPF-YOLOv8n (SMEA-YOLOv8n). Firstly, the proposed method integrates the parameter-free Similarity-Aware Attention Mechanism (SimAM) and MobileViTAttention modules into the CSP Bottleneck with 2 Convolutions(C2f) module of the neck network, aiming to enhance the model’s feature representation and fusion capabilities in complex environments while mitigating the interference of irrelevant background features. Additionally, the EfficiCIoU loss function replaces the original Complete IoU(CIoU) loss function, thereby improving bounding box localization accuracy and accelerating model convergence. Furthermore, the Spatial Pyramid Pooling-Fast (SPPF) module in the backbone network is refined with the addition of two global average pooling layers, strengthening the extraction of sheep facial expression features and bolstering the model’s core feature fusion capacity. Experimental results reveal that the proposed method achieves a <a href="/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="92ffd3c2d2a2bca7">[email protected]</a> of 92.5%, a Recall of 91%, a Precision of 86%, and an F1-score of 88.0%, reflecting improvements of 4.5%, 9.1%, 2.8%, and 6.0%, respectively, compared to the baseline model. Notably, the <a href="/cdn-cgi/l/email-protection" class="__cf_email__" data-cfemail="600d213020504e55">[email protected]</a> for normal and abnormal sheep facial expressions increased by 3.7% and 5.3%, respectively, demonstrating the method’s effectiveness in enhancing recognition accuracy under complex environmental conditions. <a href="/2076-2615/14/23/3415">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/animals/sections/Small_Ruminant">Small Ruminants</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529821" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 2948 KiB   </span> <a href="/2072-4292/16/23/4422/pdf?version=1732618320" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing" data-journal="remotesensing"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-4292/16/23/4422">First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing</a> <div class="authors"> by <span class="inlineblock "><strong>Seyed Mostafa Mehrdad</strong>, </span><span class="inlineblock "><strong>Bo Zhang</strong>, </span><span class="inlineblock "><strong>Wenqi Guo</strong>, </span><span class="inlineblock "><strong>Shan Du</strong> and </span><span class="inlineblock "><strong>Ke Du</strong></span> </div> <div class="color-grey-dark"> <em>Remote Sens.</em> <b>2024</b>, <em>16</em>(23), 4422; <a href="https://doi.org/10.3390/rs16234422">https://doi.org/10.3390/rs16234422</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Wastewater treatment (WWT) contributes 2–9% of global greenhouse gas (GHG) emissions. The noticeable uncertainty in emissions estimation is due in large part to the lack of measurement data. Several methods have recently been developed for monitoring fugitive GHG emissions from WWT. However, limited <a href="#" data-counterslink = "https://www.mdpi.com/2072-4292/16/23/4422/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Wastewater treatment (WWT) contributes 2–9% of global greenhouse gas (GHG) emissions. The noticeable uncertainty in emissions estimation is due in large part to the lack of measurement data. Several methods have recently been developed for monitoring fugitive GHG emissions from WWT. However, limited by the short duration of the monitoring, only “snapshot” data can be obtained, necessitating extrapolation of the limited data for estimating annual emissions. Extrapolation introduces substantial errors, as it fails to account for the spatial and temporal variations of fugitive emissions. This research evaluated the feasibility of studying the long-term CH<sub>4</sub> emissions from WWT by analyzing high spatial resolution Sentinel-2 data. Satellite images of a WWT plant in Calgary, Canada, taken between 2019 and 2023, were processed to retrieve CH<sub>4</sub> column concentration distributions. Digital image processing techniques were developed and used for extracting the time- and space-varying features of CH<sub>4</sub> emissions, which revealed daily, monthly, seasonal, and annual variations. Emission hotspots were also identified and corroborated with ground-based measurements. Despite limitations due to atmospheric scattering, cloud cover, and sensor resolution, which affect precise ground-level concentration assessments, the findings reveal the dynamic nature of fugitive GHG emissions from WWT, indicating the need for continuous monitoring. The results also show the potential of utilizing satellite images for cost-effectively evaluating fugitive CH4 emissions. <a href="/2072-4292/16/23/4422">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/remotesensing/sections/environmental_remote_sensing">Environmental Remote Sensing</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-4292/16/23/4422/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529821"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529821"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529821" data-cycle-prev="#prev1529821" data-cycle-progressive="#images1529821" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529821-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g001-550.jpg?1732618387" alt="" style="border: 0;"><p>Figure 1</p></div><script data-cfasync="false" src="/cdn-cgi/scripts/5c5dd728/cloudflare-static/email-decode.min.js"></script><script id="images1529821" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529821-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g002-550.jpg?1732618388'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529821-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g003-550.jpg?1732618390'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529821-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g004-550.jpg?1732618392'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529821-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g005-550.jpg?1732618393'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529821-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g006-550.jpg?1732618395'><p>Figure 6</p></div></script></div></div><div id="article-1529821-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g001-550.jpg?1732618387" title=" <strong>Figure 1</strong><br/> <p>The satellite image of the WWTP in this study.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g002-550.jpg?1732618388" title=" <strong>Figure 2</strong><br/> <p>Flowchart diagram of data processing steps.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g003-550.jpg?1732618390" title=" <strong>Figure 3</strong><br/> <p>Variations of average methane column concentrations inside the WWTP site from 2019 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g004-550.jpg?1732618392" title=" <strong>Figure 4</strong><br/> <p>Seasonally weighted average of column concentration inside the WWTP facility.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g005-550.jpg?1732618393" title=" <strong>Figure 5</strong><br/> <p>Variation of average column concentrations at hotspots and wastewater temperature.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/remotesensing/remotesensing-16-04422/article_deploy/html/images/remotesensing-16-04422-g006-550.jpg?1732618395" title=" <strong>Figure 6</strong><br/> <p>Seasonal dynamics of CH4 emission locations from 2019 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-4292/16/23/4422'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529761" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 3912 KiB   </span> <a href="/2673-2688/5/4/121/pdf?version=1732616299" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals" data-journal="ai"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2673-2688/5/4/121">Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals</a> <div class="authors"> by <span class="inlineblock "><strong>Ahmed Elhadad</strong>, </span><span class="inlineblock "><strong>Safwat Hamad</strong>, </span><span class="inlineblock "><strong>Noha Elfiky</strong>, </span><span class="inlineblock "><strong>Fulayjan Alanazi</strong>, </span><span class="inlineblock "><strong>Ahmed I. Taloba</strong> and </span><span class="inlineblock "><strong>Rasha M. Abd El-Aziz</strong></span> </div> <div class="color-grey-dark"> <em>AI</em> <b>2024</b>, <em>5</em>(4), 2497-2517; <a href="https://doi.org/10.3390/ai5040121">https://doi.org/10.3390/ai5040121</a> - 26 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Intelligent Speech Technology (IST) is revolutionizing healthcare by enhancing transcription accuracy, disease diagnosis, and medical equipment control in smart hospital environments. This study introduces an innovative approach employing federated learning with Multi-Layer Perceptron (MLP) and Gated Recurrent Unit (GRU) neural networks to improve <a href="#" data-counterslink = "https://www.mdpi.com/2673-2688/5/4/121/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Intelligent Speech Technology (IST) is revolutionizing healthcare by enhancing transcription accuracy, disease diagnosis, and medical equipment control in smart hospital environments. This study introduces an innovative approach employing federated learning with Multi-Layer Perceptron (MLP) and Gated Recurrent Unit (GRU) neural networks to improve IST performance. Leveraging the “Medical Speech, Transcription, and Intent” dataset from Kaggle, comprising a variety of speech recordings and corresponding medical symptom labels, noise reduction was applied using a Wiener filter to improve audio quality. Feature extraction through MLP and sequence classification with GRU highlighted the model’s robustness and capacity for detailed medical understanding. The federated learning framework enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange. This distributed approach allowed the model to learn from diverse, real-world data while ensuring compliance with strict data protection standards. Through rigorous five-fold cross-validation, the proposed Fed MLP-GRU model demonstrated an accuracy of 98.6%, with consistently high sensitivity and specificity, highlighting its reliable generalization across multiple test conditions. In real-time applications, the model effectively performed medical transcription, provided symptom-based diagnostic insights, and facilitated hands-free control of healthcare equipment, reducing contamination risks and enhancing workflow efficiency. These findings indicate that IST, powered by federated neural networks, can significantly improve healthcare delivery, accuracy in patient diagnosis, and operational efficiency in clinical settings. This research underscores the transformative potential of federated learning and advanced neural networks for addressing pressing challenges in modern healthcare and setting the stage for future innovations in intelligent medical technology. <a href="/2673-2688/5/4/121">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2673-2688/5/4/121/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529761"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529761"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529761" data-cycle-prev="#prev1529761" data-cycle-progressive="#images1529761" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529761-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g001-550.jpg?1732616370" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529761" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g002-550.jpg?1732616372'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g003-550.jpg?1732616374'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g004-550.jpg?1732616375'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g005-550.jpg?1732616377'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g006-550.jpg?1732616380'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g007-550.jpg?1732616381'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g008-550.jpg?1732616384'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1529761-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g009-550.jpg?1732616386'><p>Figure 9</p></div></script></div></div><div id="article-1529761-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g001-550.jpg?1732616370" title=" <strong>Figure 1</strong><br/> <p>Proposed Fed MLP GRU Methodology for Intelligent Speech Technology in Smart Hospitals.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g002-550.jpg?1732616372" title=" <strong>Figure 2</strong><br/> <p>Architecture of MLP.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g003-550.jpg?1732616374" title=" <strong>Figure 3</strong><br/> <p>Architecture of GRU.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g004-550.jpg?1732616375" title=" <strong>Figure 4</strong><br/> <p>Architecture of Federated Learning.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g005-550.jpg?1732616377" title=" <strong>Figure 5</strong><br/> <p>Comparison of Training and Validation Accuracies Across Different Neural Network Models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g006-550.jpg?1732616380" title=" <strong>Figure 6</strong><br/> <p>Training and Testing Loss Curves. (<b>A</b>) Scenario A. (<b>B</b>) Scenario B. (<b>C</b>) Scenario C. (<b>D</b>) Federated: The federated model’s performance.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g007-550.jpg?1732616381" title=" <strong>Figure 7</strong><br/> <p>ROC Curves for FED LSTM Model across Different Sample Sizes.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g008-550.jpg?1732616384" title=" <strong>Figure 8</strong><br/> <p>Model Performance Convergence across Different Datasets and Thresholds.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ai/ai-05-00121/article_deploy/html/images/ai-05-00121-g009-550.jpg?1732616386" title=" <strong>Figure 9</strong><br/> <p>Performance Evaluation for Different Methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-2688/5/4/121'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529695" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 3409 KiB   </span> <a href="/1422-0067/25/23/12676/pdf?version=1732614730" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Incorporating Water Molecules into Highly Accurate Binding Affinity Prediction for Proteins and Ligands" data-journal="ijms"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1422-0067/25/23/12676">Incorporating Water Molecules into Highly Accurate Binding Affinity Prediction for Proteins and Ligands</a> <div class="authors"> by <span class="inlineblock "><strong>Diya Zhang</strong>, </span><span class="inlineblock "><strong>Qiaozhen Meng</strong> and </span><span class="inlineblock "><strong>Fei Guo</strong></span> </div> <div class="color-grey-dark"> <em>Int. J. Mol. Sci.</em> <b>2024</b>, <em>25</em>(23), 12676; <a href="https://doi.org/10.3390/ijms252312676">https://doi.org/10.3390/ijms252312676</a> - 26 Nov 2024 </div> Viewed by 19 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In the binding process between proteins and ligand molecules, water molecules play a pivotal role by forming hydrogen bonds that enable proteins and ligand molecules to bind more strongly. However, current methodologies for predicting binding affinity overlook the importance of water molecules. Therefore, <a href="#" data-counterslink = "https://www.mdpi.com/1422-0067/25/23/12676/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In the binding process between proteins and ligand molecules, water molecules play a pivotal role by forming hydrogen bonds that enable proteins and ligand molecules to bind more strongly. However, current methodologies for predicting binding affinity overlook the importance of water molecules. Therefore, we developed a model called GraphWater-Net, specifically designed for predicting protein–ligand binding affinity, by incorporating water molecules. GraphWater-Net employs topological structures to represent protein atoms, ligand atoms and water molecules, and their interactions. Leveraging the Graphormer network, the model extracts interaction features between nodes within the topology, alongside the interaction features of edges and nodes. Subsequently, it generates embeddings with attention weights, inputs them into a Softmax function for regression prediction, and ultimately outputs the predicted binding affinity value. Experimental results on the Comparative Assessment of Scoring Functions (CASF) 2016 test set show that the introduction of water molecules into the complex significantly improves the prediction performance of the proposed model for protein and ligand binding affinity. Specifically, the Pearson correlation coefficient (<i>R<sub>p</sub></i>) exceeds that of current state-of-the-art methods by a margin of 0.022 to 0.129. By integrating water molecules, GraphWater-Net has the potential to facilitate the rational design of protein–ligand interactions and aid in drug discovery. <a href="/1422-0067/25/23/12676">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/ijms/special_issues/BW455Q1K6F ">New Computational Methodologies for Biomolecule Sequence, Structure and Function Discovery</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1422-0067/25/23/12676/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529695"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529695"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1529695" data-cycle-prev="#prev1529695" data-cycle-progressive="#images1529695" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1529695-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g001-550.jpg?1732614826" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1529695" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g002-550.jpg?1732614828'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g003-550.jpg?1732614831'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g004-550.jpg?1732614832'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g005-550.jpg?1732614834'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g006-550.jpg?1732614836'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g007-550.jpg?1732614837'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529695-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g008-550.jpg?1732614839'><p>Figure 8</p></div></script></div></div><div id="article-1529695-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g001-550.jpg?1732614826" title=" <strong>Figure 1</strong><br/> <p><span class="html-italic">R<sub>p</sub></span> of different model parameters. The horizontal axis represents the <span class="html-italic">R<sub>p</sub></span> value of different parameter groups. The vertical axis represents the value of each parameter. Adjusted parameter groups of the same parameter type are represented by circles of the same color.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g002-550.jpg?1732614828" title=" <strong>Figure 2</strong><br/> <p><span class="html-italic">R<sub>p</sub></span> of state-of-the-art methods in grey bars and proposed method in a black bar. The horizontal axis represents the <span class="html-italic">R<sub>p</sub></span> value of different methods. The vertical axis represents the different methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g003-550.jpg?1732614831" title=" <strong>Figure 3</strong><br/> <p><span class="html-italic">RMSE</span> of state-of-the-art methods in grey bars and proposed method in a black bar. The horizontal axis represents the <span class="html-italic">RMSE</span> value of different methods. The vertical axis represents the different methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g004-550.jpg?1732614832" title=" <strong>Figure 4</strong><br/> <p>Correlation plot for prediction of GraphWater-Net and ground truth of experiment on CASF2016. The horizontal axis represents the ground truth values of different complexes. The vertical axis represents the predicted values of the different complexes. Each point represents a specific protein-ligand complex.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g005-550.jpg?1732614834" title=" <strong>Figure 5</strong><br/> <p>Water-mediated acetylcholinesterase-huprine X interactions in the crystal structure with PDB ID 1E66. Acetylcholinesterase is shown as a diagrammatic representation (cyan), with Tyr121 and Ser122 depicted as sticks (green). The hydroxyl groups of key residues are represented as sticks (orange). Huprine X is also represented as a stick model (yellow), with the amino groups shown as sticks (blue). Water molecules mediating protein–ligand interactions are shown as spheres (purple). Water-mediated interactions in hydrogen bonds are indicated as brown dashed lines with distance metrics (Å). Electrostatic interactions are shown as pink dashed lines, and Van Der Waals forces are shown as grey dashed lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g006-550.jpg?1732614836" title=" <strong>Figure 6</strong><br/> <p>Comparison of predicted and experimental locations of water molecules near or within the ligand-binding site in the 1E66 structure. Water molecules are represented by spheres, with experimental and correctly predicted water molecules shown as purple spheres, and incorrectly predicted water molecules as red spheres. The protein is displayed diagrammatically in cyan, and the ligand is represented a as a yellow stick.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g007-550.jpg?1732614837" title=" <strong>Figure 7</strong><br/> <p>The overall process of graph representation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/ijms/ijms-25-12676/article_deploy/html/images/ijms-25-12676-g008-550.jpg?1732614839" title=" <strong>Figure 8</strong><br/> <p>The structure of the proposed model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1422-0067/25/23/12676'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1529679" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 5357 KiB   </span> <a href="/1424-8220/24/23/7540/pdf?version=1732614498" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Planetary Gearboxes Fault Diagnosis Based on Markov Transition Fields and SE-ResNet" data-journal="sensors"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1424-8220/24/23/7540">Planetary Gearboxes Fault Diagnosis Based on Markov Transition Fields and SE-ResNet</a> <div class="authors"> by <span class="inlineblock "><strong>Yanyan Liu</strong>, </span><span class="inlineblock "><strong>Tongxin Gao</strong>, </span><span class="inlineblock "><strong>Wenxu Wu</strong> and </span><span class="inlineblock "><strong>Yongquan Sun</strong></span> </div> <div class="color-grey-dark"> <em>Sensors</em> <b>2024</b>, <em>24</em>(23), 7540; <a href="https://doi.org/10.3390/s24237540">https://doi.org/10.3390/s24237540</a> - 26 Nov 2024 </div> Viewed by 49 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The working conditions of planetary gearboxes are complex, and their structural couplings are strong, leading to low reliability. Traditional deep neural networks often struggle with feature learning in noisy environments, and their reliance on one-dimensional signals as input fails to capture the interrelationships <a href="#" data-counterslink = "https://www.mdpi.com/1424-8220/24/23/7540/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The working conditions of planetary gearboxes are complex, and their structural couplings are strong, leading to low reliability. Traditional deep neural networks often struggle with feature learning in noisy environments, and their reliance on one-dimensional signals as input fails to capture the interrelationships between data points. To address these challenges, we proposed a fault diagnosis method for planetary gearboxes that integrates Markov transition fields (MTFs) and a residual attention mechanism. The MTF was employed to encode one-dimensional signals into feature maps, which were then fed into a residual networks (ResNet) architecture. To enhance the network’s ability to focus on important features, we embedded the squeeze-and-excitation (SE) channel attention mechanism into the ResNet34 network, creating a SE-ResNet model. This model was trained to effectively extract and classify features. The developed method was validated using a specific dataset and achieved an accuracy of about 98.1%. The results demonstrate the effectiveness and reliability of the developed method in diagnosing faults in planetary gearboxes under strong noise conditions. <a href="/1424-8220/24/23/7540">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/sensors/special_issues/IWPTQ3YWB0 ">Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems: 2nd Edition</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1424-8220/24/23/7540/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1529679"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1529679"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" 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data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g007-550.jpg?1732614589'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g008-550.jpg?1732614590'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g009-550.jpg?1732614592'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g010-550.jpg?1732614593'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g011-550.jpg?1732614594'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g012-550.jpg?1732614595'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g013-550.jpg?1732614597'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g014-550.jpg?1732614598'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g015-550.jpg?1732614599'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-1529679-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g016-550.jpg?1732614599'><p>Figure 16</p></div></script></div></div><div id="article-1529679-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g001-550.jpg?1732614581" title=" <strong>Figure 1</strong><br/> <p>Diagram of fault diagnosis process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g002-550.jpg?1732614582" title=" <strong>Figure 2</strong><br/> <p>Convolution process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g003-550.jpg?1732614583" title=" <strong>Figure 3</strong><br/> <p>Residual block.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g004-550.jpg?1732614584" title=" <strong>Figure 4</strong><br/> <p>Residual network structure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g005-550.jpg?1732614586" title=" <strong>Figure 5</strong><br/> <p>Residual attention module.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g006-550.jpg?1732614589" title=" <strong>Figure 6</strong><br/> <p>MTF-SE-ResNet model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g007-550.jpg?1732614589" title=" <strong>Figure 7</strong><br/> <p>Schematic diagram of the full connectivity layer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g008-550.jpg?1732614590" title=" <strong>Figure 8</strong><br/> <p>Composition of the test bench and arrangement of measurement points.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g009-550.jpg?1732614592" title=" <strong>Figure 9</strong><br/> <p>Planetary gearbox fault forms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g010-550.jpg?1732614593" title=" <strong>Figure 10</strong><br/> <p>Data segmentation chart.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g011-550.jpg?1732614594" title=" <strong>Figure 11</strong><br/> <p>Logical block diagrams of the MTF-ResNet algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g012-550.jpg?1732614595" title=" <strong>Figure 12</strong><br/> <p>Comparison of original and downsampled signal spectra.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g013-550.jpg?1732614597" title=" <strong>Figure 13</strong><br/> <p>MTF-ResNet confusion matrix with ROC curves.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g014-550.jpg?1732614598" title=" <strong>Figure 14</strong><br/> <p>Heat map of the nodes of the residual network of solar wheel failures. (<b>a</b>) represents the output heatmap of the first Residual Block, (<b>b</b>) represents the output heatmap of the second Residual Block, (<b>c</b>) represents the output heatmap of the third Residual Block, and (<b>d</b>) represents the output heatmap of the fourth Residual Block.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g015-550.jpg?1732614599" title=" <strong>Figure 15</strong><br/> <p>T-SNE visualization of feature dimensionality reduction.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07540/article_deploy/html/images/sensors-24-07540-g016-550.jpg?1732614599" title=" <strong>Figure 16</strong><br/> <p>Fault classification accuracy analysis results for 10 tests on planetary gearboxes.orange stripes representing CNN accuracy, green for MTF-CNN, purple for ResNet34, and yellow for the method proposed in this paper.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/23/7540'>Full article</a></strong> "></a></div> </div> </div> <span class="more" style="display: none;"></span> </div> <div class="row footer"> <div class="listing-select-options"> <div class="columns small-12"> <div class="select generic-item"> <a href="#" class="export-options-show export-element export-expanded"> Show export options <i class="material-icons">expand_more</i> </a> <a href="#" class="export-options-show export-element"> Show export options <i class="material-icons">expand_less</i> </a> </div> <div class="listing-export-options export-element"> <div class="export-element" style="margin-top: 10px; margin-bottom: 10px;"> <input type="checkbox" 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