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biomarker</title> <meta name="description" content="Search results for: predictive biomarker"> <meta name="keywords" content="predictive biomarker"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="predictive biomarker"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1247</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: predictive biomarker</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1247</span> The Predictive Significance of Metastasis Associated in Colon Cancer-1 (MACC1) in Primary Breast Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jasminka%20Mujic">Jasminka Mujic</a>, <a href="https://publications.waset.org/abstracts/search?q=Karin%20Milde-Langosch"> Karin Milde-Langosch</a>, <a href="https://publications.waset.org/abstracts/search?q=Volkmar%20Mueller"> Volkmar Mueller</a>, <a href="https://publications.waset.org/abstracts/search?q=Mirza%20Suljagic"> Mirza Suljagic</a>, <a href="https://publications.waset.org/abstracts/search?q=Tea%20Becirevic"> Tea Becirevic</a>, <a href="https://publications.waset.org/abstracts/search?q=Jozo%20Coric"> Jozo Coric</a>, <a href="https://publications.waset.org/abstracts/search?q=Daria%20Ler"> Daria Ler</a> </p> <p class="card-text"><strong>Abstract:</strong></p> MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=biomarker" title=" biomarker"> biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=HGF%2FMET" title=" HGF/MET"> HGF/MET</a>, <a href="https://publications.waset.org/abstracts/search?q=MACC1" title=" MACC1"> MACC1</a> </p> <a href="https://publications.waset.org/abstracts/86514/the-predictive-significance-of-metastasis-associated-in-colon-cancer-1-macc1-in-primary-breast-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/86514.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">233</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1246</span> GATA3-AS1 lncRNA as a Predictive Biomarker for Neoadjuvant Chemotherapy Response in Locally Advanced Luminal B Breast Cancer: An RNA ISH Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tania%20Vasquez%20Mata">Tania Vasquez Mata</a>, <a href="https://publications.waset.org/abstracts/search?q=Luis%20A.%20Herrera"> Luis A. Herrera</a>, <a href="https://publications.waset.org/abstracts/search?q=Cristian%20Arriaga%20Canon"> Cristian Arriaga Canon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Locally advanced breast cancer of the luminal B phenotype, poses challenges due to its variable response to neoadjuvant chemotherapy. A predictive biomarker is needed to identify patients who will not respond to treatment, allowing for alternative therapies. This study aims to validate the use of the lncRNA GATA3-AS1, as a predictive biomarker using RNA in situ hybridization. Research aim: The aim of this study is to determine if GATA3-AS1 can serve as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Methodology: The study utilizes RNA in situ hybridization with predesigned probes for GATA3-AS1 on Formalin-Fixed Paraffin-Embedded tissue sections. The samples underwent pretreatment and protease treatment to enable probe penetration. Chromogenic detection and signal evaluation were performed using specific criteria. Findings: Patients who did not respond to neoadjuvant chemotherapy showed a 3+ score for GATA3-AS1, while those who had a complete response had a 1+ score. Theoretical importance: This study demonstrates the potential clinical utility of GATA3-AS1 as a biomarker for resistance to neoadjuvant chemotherapy. Identifying non-responders early on can help avoid unnecessary treatment and explore alternative therapy options. Data collection and analysis procedures: Tissue samples from patients with locally advanced luminal B breast cancer were collected and processed using RNA in situ hybridization. Signal evaluation was conducted under a microscope, and scoring was based on specific criteria. Questions addressed: Can GATA3-AS1 serve as a predictive biomarker for neoadjuvant chemotherapy response in locally advanced luminal B breast cancer? Conclusion: The lncRNA GATA3-AS1 can be used as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Its identification through RNA in situ hybridization of tissue obtained from the initial biopsy can aid in treatment decision-making. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomarkers" title="biomarkers">biomarkers</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20neoplasms" title=" breast neoplasms"> breast neoplasms</a>, <a href="https://publications.waset.org/abstracts/search?q=genetics" title=" genetics"> genetics</a>, <a href="https://publications.waset.org/abstracts/search?q=neoadjuvant%20therapy" title=" neoadjuvant therapy"> neoadjuvant therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor" title=" tumor"> tumor</a> </p> <a href="https://publications.waset.org/abstracts/179253/gata3-as1-lncrna-as-a-predictive-biomarker-for-neoadjuvant-chemotherapy-response-in-locally-advanced-luminal-b-breast-cancer-an-rna-ish-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179253.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">57</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1245</span> Development of Programmed Cell Death Protein 1 Pathway-Associated Prognostic Biomarkers for Bladder Cancer Using Transcriptomic Databases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shu-Pin%20Huang">Shu-Pin Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Pai-Chi%20Teng"> Pai-Chi Teng</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao-Han%20Chang"> Hao-Han Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Hsin%20Liu"> Chia-Hsin Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yung-Lun%20Lin"> Yung-Lun Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Shu-Chi%20Wang"> Shu-Chi Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hsin-Chih%20Yeh"> Hsin-Chih Yeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Chih-Pin%20Chuu"> Chih-Pin Chuu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiun-Hung%20Geng"> Jiun-Hung Geng</a>, <a href="https://publications.waset.org/abstracts/search?q=Li-Hsin%20Chang"> Li-Hsin Chang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei-Chung%20Cheng"> Wei-Chung Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Yang%20Li"> Chia-Yang Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The emergence of immune checkpoint inhibitors (ICIs) targeting proteins like PD-1 and PD-L1 has changed the treatment paradigm of bladder cancer. However, not all patients benefit from ICIs, with some experiencing early death. There's a significant need for biomarkers associated with the PD-1 pathway in bladder cancer. Current biomarkers focus on tumor PD-L1 expression, but a more comprehensive understanding of PD-1-related biology is needed. Our study has developed a seven-gene risk score panel, employing a comprehensive bioinformatics strategy, which could serve as a potential prognostic and predictive biomarker for bladder cancer. This panel incorporates the FYN, GRAP2, TRIB3, MAP3K8, AKT3, CD274, and CD80 genes. Additionally, we examined the relationship between this panel and immune cell function, utilizing validated tools such as ESTIMATE, TIDE, and CIBERSORT. Our seven-genes panel has been found to be significantly associated with bladder cancer survival in two independent cohorts. The panel was also significantly correlated with tumor infiltration lymphocytes, immune scores, and tumor purity. These factors have been previously reported to have clinical implications on ICIs. The findings suggest the potential of a PD-1 pathway-based transcriptomic panel as a prognostic and predictive biomarker in bladder cancer, which could help optimize treatment strategies and improve patient outcomes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bladder%20cancer" title="bladder cancer">bladder cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=programmed%20cell%20death%20protein%201" title=" programmed cell death protein 1"> programmed cell death protein 1</a>, <a href="https://publications.waset.org/abstracts/search?q=prognostic%20biomarker" title=" prognostic biomarker"> prognostic biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20checkpoint%20inhibitors" title=" immune checkpoint inhibitors"> immune checkpoint inhibitors</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20biomarker" title=" predictive biomarker"> predictive biomarker</a> </p> <a href="https://publications.waset.org/abstracts/173666/development-of-programmed-cell-death-protein-1-pathway-associated-prognostic-biomarkers-for-bladder-cancer-using-transcriptomic-databases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173666.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1244</span> Oral Microbiota as a Novel Predictive Biomarker of Response To Immune Checkpoint Inhibitors in Advanced Non-small Cell Lung Cancer Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francesco%20Pantano">Francesco Pantano</a>, <a href="https://publications.waset.org/abstracts/search?q=Marta%20Fogolari"> Marta Fogolari</a>, <a href="https://publications.waset.org/abstracts/search?q=Michele%20Iuliani"> Michele Iuliani</a>, <a href="https://publications.waset.org/abstracts/search?q=Sonia%20Simonetti"> Sonia Simonetti</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvia%20Cavaliere"> Silvia Cavaliere</a>, <a href="https://publications.waset.org/abstracts/search?q=Marco%20Russano"> Marco Russano</a>, <a href="https://publications.waset.org/abstracts/search?q=Fabrizio%20Citarella"> Fabrizio Citarella</a>, <a href="https://publications.waset.org/abstracts/search?q=Bruno%20Vincenzi"> Bruno Vincenzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvia%20Angeletti"> Silvia Angeletti</a>, <a href="https://publications.waset.org/abstracts/search?q=Giuseppe%20Tonini"> Giuseppe Tonini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Although immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of non–small cell lung cancer (NSCLC), these drugs fail to elicit durable responses in the majority of NSCLC patients. The gut microbiota, able to regulate immune responsiveness, is emerging as a promising, modifiable target to improve ICIs response rates. Since the oral microbiome has been demonstrated to be the primary source of bacterial microbiota in the lungs, we investigated its composition as a potential predictive biomarker to identify and select patients who could benefit from immunotherapy. Methods: Thirty-five patients with stage IV squamous and non-squamous cell NSCLC eligible for an anti-PD-1/PD-L1 as monotherapy were enrolled. Saliva samples were collected from patients prior to the start of treatment, bacterial DNA was extracted using the QIAamp® DNA Microbiome Kit (QIAGEN) and the 16S rRNA gene was sequenced on a MiSeq sequencing instrument (Illumina). Results: NSCLC patients were dichotomized as “Responders” (partial or complete response) and “Non-Responders” (progressive disease), after 12 weeks of treatment, based on RECIST criteria. A prevalence of the phylum Candidatus Saccharibacteria was found in the 10 responders compared to non-responders (abundance 5% vs 1% respectively; p-value = 1.46 x 10-7; False Discovery Rate (FDR) = 1.02 x 10-6). Moreover, a higher prevalence of Saccharibacteria Genera Incertae Sedis genus (belonging to the Candidatus Saccharibacteria phylum) was observed in "responders" (p-value = 6.01 x 10-7 and FDR = 2.46 x 10-5). Finally, the patients who benefit from immunotherapy showed a significant abundance of TM7 Phylum Sp Oral Clone FR058 strain, member of Saccharibacteria Genera Incertae Sedis genus (p-value = 6.13 x 10-7 and FDR=7.66 x 10-5). Conclusions: These preliminary results showed a significant association between oral microbiota and ICIs response in NSCLC patients. In particular, the higher prevalence of Candidatus Saccharibacteria phylum and TM7 Phylum Sp Oral Clone FR058 strain in responders suggests their potential immunomodulatory role. The study is still ongoing and updated data will be presented at the congress. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oral%20microbiota" title="oral microbiota">oral microbiota</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20checkpoint%20inhibitors" title=" immune checkpoint inhibitors"> immune checkpoint inhibitors</a>, <a href="https://publications.waset.org/abstracts/search?q=non-small%20cell%20lung%20cancer" title=" non-small cell lung cancer"> non-small cell lung cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20biomarker" title=" predictive biomarker"> predictive biomarker</a> </p> <a href="https://publications.waset.org/abstracts/163788/oral-microbiota-as-a-novel-predictive-biomarker-of-response-to-immune-checkpoint-inhibitors-in-advanced-non-small-cell-lung-cancer-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163788.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">97</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1243</span> Role of Surfactant Protein D (SP-D) as a Biomarker of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lucia%20Salvioni">Lucia Salvioni</a>, <a href="https://publications.waset.org/abstracts/search?q=Pietro%20Giorgio%20Lovaglio"> Pietro Giorgio Lovaglio</a>, <a href="https://publications.waset.org/abstracts/search?q=Valerio%20Leoni"> Valerio Leoni</a>, <a href="https://publications.waset.org/abstracts/search?q=Miriam%20Colombo"> Miriam Colombo</a>, <a href="https://publications.waset.org/abstracts/search?q=Luisa%20Fiandra"> Luisa Fiandra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The involvement of plasmatic surfactant protein-D (SP-D) in pulmonary diseases has been long investigated, and over the last two years, more interest has been directed to determine its role as a marker of COVID-19. In this direction, several studies aimed to correlate pulmonary surfactant proteins with the clinical manifestations of the virus indicated SP-D as a prognostic biomarker of COVID-19 pneumonia severity. The present work has performed a retrospective study on a relatively large cohort of patients of Hospital Pio XI of Desio (Lombardia, Italy) with the aim to assess differences in the hematic SP-D concentrations among COVID-19 patients and healthy donors and the role of SP-D as a prognostic marker of severity and/or of mortality risk. The obtained results showed a significant difference in the mean of log SP-D levels between COVID-19 patients and healthy donors, so as between dead and survived patients. SP-D values were significantly higher for both hospitalized COVID-19 and dead patients, with threshold values of 150 and 250 ng/mL, respectively. SP-D levels at admission and increasing differences among follow-up and admission values resulted in the strongest significant risk factors of mortality. Therefore, this study demonstrated the role of SP-D as a predictive marker of SARS-CoV-2 infection and its outcome. A significant correlation of SP-D with patient mortality indicated that it is also a prognostic factor in terms of mortality, and its early detection should be considered to design adequate preventive treatments for COVID-19 patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SARS-CoV-2%20infection" title="SARS-CoV-2 infection">SARS-CoV-2 infection</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title=" COVID-19"> COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=surfactant%20protein-D%20%28SP-D%29" title=" surfactant protein-D (SP-D)"> surfactant protein-D (SP-D)</a>, <a href="https://publications.waset.org/abstracts/search?q=mortality" title=" mortality"> mortality</a>, <a href="https://publications.waset.org/abstracts/search?q=biomarker" title=" biomarker"> biomarker</a> </p> <a href="https://publications.waset.org/abstracts/164423/role-of-surfactant-protein-d-sp-d-as-a-biomarker-of-severe-acute-respiratory-syndrome-coronavirus-2-sars-cov-2-infection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164423.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">76</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1242</span> Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ameur%20Abdelkader">Ameur Abdelkader</a>, <a href="https://publications.waset.org/abstracts/search?q=Abed%20Bouarfa%20Hafida"> Abed Bouarfa Hafida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=predictive%20analysis" title="predictive analysis">predictive analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data"> big data</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20analysis%20algorithms" title=" predictive analysis algorithms"> predictive analysis algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=CART%20algorithm" title=" CART algorithm"> CART algorithm</a> </p> <a href="https://publications.waset.org/abstracts/101647/predictive-analysis-for-big-data-extension-of-classification-and-regression-trees-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101647.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">142</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1241</span> Estimating the Receiver Operating Characteristic Curve from Clustered Data and Case-Control Studies </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yalda%20Zarnegarnia">Yalda Zarnegarnia</a>, <a href="https://publications.waset.org/abstracts/search?q=Shari%20Messinger"> Shari Messinger</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomarker" title="biomarker">biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation" title=" correlation"> correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=familial%20paired%20design" title=" familial paired design"> familial paired design</a>, <a href="https://publications.waset.org/abstracts/search?q=ROC%20curve" title=" ROC curve"> ROC curve</a> </p> <a href="https://publications.waset.org/abstracts/76734/estimating-the-receiver-operating-characteristic-curve-from-clustered-data-and-case-control-studies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76734.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">239</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1240</span> The Identification of Combined Genomic Expressions as a Diagnostic Factor for Oral Squamous Cell Carcinoma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ki-Yeo%20Kim">Ki-Yeo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oral%20squamous%20cell%20carcinoma" title="oral squamous cell carcinoma">oral squamous cell carcinoma</a>, <a href="https://publications.waset.org/abstracts/search?q=combined%20biomarker" title=" combined biomarker"> combined biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray%20dataset" title=" microarray dataset"> microarray dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=correlated%20genes" title=" correlated genes"> correlated genes</a> </p> <a href="https://publications.waset.org/abstracts/35990/the-identification-of-combined-genomic-expressions-as-a-diagnostic-factor-for-oral-squamous-cell-carcinoma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35990.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">423</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1239</span> Application of Fractional Model Predictive Control to Thermal System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aymen%20Rhouma">Aymen Rhouma</a>, <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Hcheichi"> Khaled Hcheichi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sami%20Hafsi"> Sami Hafsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller<em>.</em> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20model%20predictive%20control" title="fractional model predictive control">fractional model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=fractional%20order%20systems" title=" fractional order systems"> fractional order systems</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20system" title=" thermal system"> thermal system</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20control" title=" predictive control"> predictive control</a> </p> <a href="https://publications.waset.org/abstracts/66187/application-of-fractional-model-predictive-control-to-thermal-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66187.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">411</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1238</span> Image Steganography Using Predictive Coding for Secure Transmission</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Baljit%20Singh%20Khehra">Baljit Singh Khehra</a>, <a href="https://publications.waset.org/abstracts/search?q=Jagreeti%20Kaur"> Jagreeti Kaur </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, steganographic strategy is used to hide the text file inside an image. To increase the storage limit, predictive coding is utilized to implant information. In the proposed plan, one can exchange secure information by means of predictive coding methodology. The predictive coding produces high stego-image. The pixels are utilized to insert mystery information in it. The proposed information concealing plan is powerful as contrasted with the existing methodologies. By applying this strategy, a provision helps clients to productively conceal the information. Entropy, standard deviation, mean square error and peak signal noise ratio are the parameters used to evaluate the proposed methodology. The results of proposed approach are quite promising. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cryptography" title="cryptography">cryptography</a>, <a href="https://publications.waset.org/abstracts/search?q=steganography" title=" steganography"> steganography</a>, <a href="https://publications.waset.org/abstracts/search?q=reversible%20image" title=" reversible image"> reversible image</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20coding" title=" predictive coding"> predictive coding</a> </p> <a href="https://publications.waset.org/abstracts/9850/image-steganography-using-predictive-coding-for-secure-transmission" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9850.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">417</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1237</span> Evaluating the Diagnostic Accuracy of the ctDNA Methylation for Liver Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maomao%20Cao">Maomao Cao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=liver%20cancer" title="liver cancer">liver cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=ctDNA%20methylation" title=" ctDNA methylation"> ctDNA methylation</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnostic%20performance" title=" diagnostic performance"> diagnostic performance</a> </p> <a href="https://publications.waset.org/abstracts/146512/evaluating-the-diagnostic-accuracy-of-the-ctdna-methylation-for-liver-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146512.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1236</span> Temperature Control Improvement of Membrane Reactor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pornsiri%20Kaewpradit">Pornsiri Kaewpradit</a>, <a href="https://publications.waset.org/abstracts/search?q=Chalisa%20Pourneaw"> Chalisa Pourneaw</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20predictive%20control" title="model predictive control">model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=batch%20reactor" title=" batch reactor"> batch reactor</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature%20control" title=" temperature control"> temperature control</a>, <a href="https://publications.waset.org/abstracts/search?q=membrane%20reactor" title=" membrane reactor "> membrane reactor </a> </p> <a href="https://publications.waset.org/abstracts/17487/temperature-control-improvement-of-membrane-reactor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17487.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">468</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1235</span> Metabolic Predictive Model for PMV Control Based on Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eunji%20Choi">Eunji Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Borang%20Park"> Borang Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Youngjae%20Choi"> Youngjae Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinwoo%20Moon"> Jinwoo Moon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=indoor%20quality" title=" indoor quality"> indoor quality</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolism" title=" metabolism"> metabolism</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20model" title=" predictive model"> predictive model</a> </p> <a href="https://publications.waset.org/abstracts/93271/metabolic-predictive-model-for-pmv-control-based-on-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93271.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">257</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1234</span> Detection of Telomerase Activity as Cancer Biomarker Using Nanogap-Rich Au Nanowire SERS Sensor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20Eom">G. Eom</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Kim"> H. Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Hwang"> A. Hwang</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kang"> T. Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Kim"> B. Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Telomerase activity is overexpressed in over 85% of human cancers while suppressed in normal somatic cells. Telomerase has been attracted as a universal cancer biomarker. Therefore, the development of effective telomerase activity detection methods is urgently demanded in cancer diagnosis and therapy. Herein, we report a nanogap-rich Au nanowire (NW) surface-enhanced Raman scattering (SERS) sensor for detection of human telomerase activity. The nanogap-rich Au NW SERS sensors were prepared simply by uniformly depositing nanoparticles (NPs) on single-crystalline Au NWs. We measured SERS spectra of methylene blue (MB) from 60 different nanogap-rich Au NWs and obtained the relative standard deviation (RSD) of 4.80%, confirming the superb reproducibility of nanogap-rich Au NW SERS sensors. The nanogap-rich Au NW SERS sensors enable us to detect telomerase activity in 0.2 cancer cells/mL. Furthermore, telomerase activity is detectable in 7 different cancer cell lines whereas undetectable in normal cell lines, which suggest the potential applicability of nanogap-rich Au NW SERS sensor in cancer diagnosis. We expect that the present nanogap-rich Au NW SERS sensor can be useful in biomedical applications including a diverse biomarker sensing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cancer%20biomarker" title="cancer biomarker">cancer biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=nanowires" title=" nanowires"> nanowires</a>, <a href="https://publications.waset.org/abstracts/search?q=surface-enhanced%20Raman%20scattering" title=" surface-enhanced Raman scattering"> surface-enhanced Raman scattering</a>, <a href="https://publications.waset.org/abstracts/search?q=telomerase" title=" telomerase"> telomerase</a> </p> <a href="https://publications.waset.org/abstracts/61763/detection-of-telomerase-activity-as-cancer-biomarker-using-nanogap-rich-au-nanowire-sers-sensor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61763.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">349</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1233</span> Use of Predictive Food Microbiology to Determine the Shelf-Life of Foods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatih%20Tarlak">Fatih Tarlak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=shelf-life" title="shelf-life">shelf-life</a>, <a href="https://publications.waset.org/abstracts/search?q=growth%20model" title=" growth model"> growth model</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20microbiology" title=" predictive microbiology"> predictive microbiology</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/133723/use-of-predictive-food-microbiology-to-determine-the-shelf-life-of-foods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133723.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">211</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1232</span> An Initial Evaluation of Newly Proposed Biomarker of Zinc Status in Humans: The Erythrocyte Linoleic Acid: Dihomo-γ-Linolenic Acid (LA:DGLA) Ratio</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marija%20Knez">Marija Knez</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20C.R.%20Stangoulis"> James C.R. Stangoulis</a>, <a href="https://publications.waset.org/abstracts/search?q=Manja%20Zec"> Manja Zec</a>, <a href="https://publications.waset.org/abstracts/search?q=Zoran%20Pavlovic"> Zoran Pavlovic</a>, <a href="https://publications.waset.org/abstracts/search?q=Jasmina%20D.%20Martacic"> Jasmina D. Martacic</a>, <a href="https://publications.waset.org/abstracts/search?q=Mirjana%20Gurinovic"> Mirjana Gurinovic</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Glibetic"> Maria Glibetic</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Zinc is an essential micronutrient for humans with important physiological functions. A sensitive and specific biomarker for assessing Zn status is still needed. Objective: The major aim of this study was to examine if the changes in the content of plasma phospholipid LA, DGLA and LA: DGLA ratio can be used to efficiently predict the dietary Zn intake and plasma Zn status of humans. Methods: The study was performed on apparently healthy human volunteers. The dietary Zn intake was assessed using 24h recall questionnaires. Plasma phospholipid fatty acid analysis was done by gas chromatography and plasma analysis of minerals by atomic absorption spectrometry. Biochemical, anthropometrical and hematological parameters were assessed. Results: No significant relationship was found between the dietary and plasma zinc status (r=0.07; p=0.6). There is a statistically significant correlation between DGLA and plasma Zn (r=0.39, p=0.00). No relationship was observed between the linoleic acid and plasma Zn, while there was a significant negative correlation between LA: DGLA ratio and plasma Zn status (r=-0.35, p=0.01). Similarly, there were statistically significant difference in DGLA status (p=0.004) and LA: DGLA ratio (p=0.042) between the Zn formed groups. Conclusions: This study is an initial step in evaluating LA: DGLA ratio as a biomarker of Zn status in humans. The results are encouraging as they show that concentration of DGLA is decreased and LA: DGLA ratio increased in people with lower dietary Zn intake. However, additional studies are needed to fully examine the sensitivity of this biomarker. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dietary%20Zn%20intake%20Zinc" title="dietary Zn intake Zinc">dietary Zn intake Zinc</a>, <a href="https://publications.waset.org/abstracts/search?q=fatty%20acid%20composition" title=" fatty acid composition"> fatty acid composition</a>, <a href="https://publications.waset.org/abstracts/search?q=LA%3A%20DGLA" title=" LA: DGLA"> LA: DGLA</a>, <a href="https://publications.waset.org/abstracts/search?q=healthy%20population" title=" healthy population"> healthy population</a>, <a href="https://publications.waset.org/abstracts/search?q=plasma%20Zn%20status" title=" plasma Zn status"> plasma Zn status</a>, <a href="https://publications.waset.org/abstracts/search?q=Zn%20biomarker" title=" Zn biomarker"> Zn biomarker</a> </p> <a href="https://publications.waset.org/abstracts/45975/an-initial-evaluation-of-newly-proposed-biomarker-of-zinc-status-in-humans-the-erythrocyte-linoleic-acid-dihomo-gh-linolenic-acid-ladgla-ratio" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45975.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">270</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1231</span> Computational Simulations on Stability of Model Predictive Control for Linear Discrete-Time Stochastic Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tomoaki%20Hashimoto">Tomoaki Hashimoto</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20simulations" title="computational simulations">computational simulations</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20control" title=" predictive control"> predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20systems" title=" stochastic systems"> stochastic systems</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete-time%20systems" title=" discrete-time systems"> discrete-time systems</a> </p> <a href="https://publications.waset.org/abstracts/35462/computational-simulations-on-stability-of-model-predictive-control-for-linear-discrete-time-stochastic-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35462.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">432</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1230</span> Evaluation of Longitudinal Relaxation Time (T1) of Bone Marrow in Lumbar Vertebrae of Leukaemia Patients Undergoing Magnetic Resonance Imaging</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20G.%20R.%20S.%20Perera">M. G. R. S. Perera</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20S.%20Weerakoon"> B. S. Weerakoon</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20P.%20G.%20Sherminie"> L. P. G. Sherminie</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20L.%20Jayatilake"> M. L. Jayatilake</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20D.%20Jayasinghe"> R. D. Jayasinghe</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Huang"> W. Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study was to measure and evaluate the Longitudinal Relaxation Times (T1) in bone marrow of an Acute Myeloid Leukaemia (AML) patient in order to explore the potential for a prognostic biomarker using Magnetic Resonance Imaging (MRI) which will be a non-invasive prognostic approach to AML. MR image data were collected in the DICOM format and MATLAB Simulink software was used in the image processing and data analysis. For quantitative MRI data analysis, Region of Interests (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4, and L5. T1 was evaluated using the T1 maps obtained. The estimated bone marrow mean value of T1 was 790.1 (ms) at 3T. However, the reported T1 value of healthy subjects is significantly (946.0 ms) higher than the present finding. This suggests that the T1 for bone marrow can be considered as a potential prognostic biomarker for AML patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acute%20myeloid%20leukaemia" title="acute myeloid leukaemia">acute myeloid leukaemia</a>, <a href="https://publications.waset.org/abstracts/search?q=longitudinal%20relaxation%20time" title=" longitudinal relaxation time"> longitudinal relaxation time</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetic%20resonance%20imaging" title=" magnetic resonance imaging"> magnetic resonance imaging</a>, <a href="https://publications.waset.org/abstracts/search?q=prognostic%20biomarker." title=" prognostic biomarker."> prognostic biomarker.</a> </p> <a href="https://publications.waset.org/abstracts/12985/evaluation-of-longitudinal-relaxation-time-t1-of-bone-marrow-in-lumbar-vertebrae-of-leukaemia-patients-undergoing-magnetic-resonance-imaging" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12985.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">531</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1229</span> Applications of Multivariate Statistical Methods on Geochemical Data to Evaluate the Hydrocarbons Source Rocks and Oils from Ghadames Basin, NW Libya</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Hrouda">Mohamed Hrouda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Principal Component Analysis (PCA) was performed on a dataset comprising 41 biomarker concentrations from twenty-three core source rocks samples and seven oil samples from different location, with the objective of establishing the major sources of variance within the steranes, tricyclic terpanes, hopanes, and triaromatic steroid. This type of analysis can be used as an aid when deciding which molecular biomarker maturity, source facies or depositional environment parameters should be plotted, because the principal component loadings plots tend to extract the biomarker variables related to maturity, source facies or depositional environment controls. Facies characterization of the source rock samples separate the Silurian and Devonian source rock samples into three groups. Maturity evaluation of source rock samples based on biomarker and aromatic hydrocarbon distributions indicates that not all the samples are strongly affected by maturity, the Upper Devonian samples from wells located in the northern part of the basin are immature, whereas the other samples which have been selected from the Lower Silurian are mature and have reached the main stage of the oil window, the Lower Silurian source rock strata revealed a trend of increasing maturity towards the south and southwestern part of Ghadames Basin. Most of the facies-based parameters employed in this project using biomarker distributions clearly separate the oil samples into three groups. Group I contain oil samples from wells within Al-Wafa oil field Located in the south western part of the basin, Group II contains oil samples collected from Al-Hamada oil field complex in the south and the third group contains oil samples collected from oil fields located in the north <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ghadamis%20basin" title="Ghadamis basin">Ghadamis basin</a>, <a href="https://publications.waset.org/abstracts/search?q=geochemistry" title=" geochemistry"> geochemistry</a>, <a href="https://publications.waset.org/abstracts/search?q=silurian" title=" silurian"> silurian</a>, <a href="https://publications.waset.org/abstracts/search?q=devonian" title=" devonian"> devonian</a> </p> <a href="https://publications.waset.org/abstracts/173750/applications-of-multivariate-statistical-methods-on-geochemical-data-to-evaluate-the-hydrocarbons-source-rocks-and-oils-from-ghadames-basin-nw-libya" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173750.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">62</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1228</span> Sampled-Data Model Predictive Tracking Control for Mobile Robot</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wookyong%20Kwon">Wookyong Kwon</a>, <a href="https://publications.waset.org/abstracts/search?q=Sangmoon%20Lee"> Sangmoon Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20predictive%20control" title="model predictive control">model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=sampled-data%20control" title=" sampled-data control"> sampled-data control</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20parameter%20varying%20systems" title=" linear parameter varying systems"> linear parameter varying systems</a>, <a href="https://publications.waset.org/abstracts/search?q=LPV" title=" LPV"> LPV</a> </p> <a href="https://publications.waset.org/abstracts/71683/sampled-data-model-predictive-tracking-control-for-mobile-robot" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71683.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">309</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1227</span> Role of von Willebrand Factor Antigen as Non-Invasive Biomarker for the Prediction of Portal Hypertensive Gastropathy in Patients with Liver Cirrhosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20El%20Horri">Mohamed El Horri</a>, <a href="https://publications.waset.org/abstracts/search?q=Amine%20Mouden"> Amine Mouden</a>, <a href="https://publications.waset.org/abstracts/search?q=Reda%20Messaoudi"> Reda Messaoudi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Chekkal"> Mohamed Chekkal</a>, <a href="https://publications.waset.org/abstracts/search?q=Driss%20Benlaldj"> Driss Benlaldj</a>, <a href="https://publications.waset.org/abstracts/search?q=Malika%20Baghdadi"> Malika Baghdadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahcene%20Benmahdi"> Lahcene Benmahdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Seghier"> Fatima Seghier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background/aim: Recently, the Von Willebrand factor antigen (vWF-Ag)has been identified as a new marker of portal hypertension (PH) and its complications. Few studies talked about its role in the prediction of esophageal varices. VWF-Ag is considered a non-invasive approach, In order to avoid the endoscopic burden, cost, drawbacks, unpleasant and repeated examinations to the patients. In our study, we aimed to evaluate the ability of this marker in the prediction of another complication of portal hypertension, which is portal hypertensive gastropathy (PHG), the one that is diagnosed also by endoscopic tools. Patients and methods: It is about a prospective study, which include 124 cirrhotic patients with no history of bleeding who underwent screening endoscopy for PH-related complications like esophageal varices (EVs) and PHG. Routine biological tests were performed as well as the VWF-Ag testing by both ELFA and Immunoturbidimetric techniques. The diagnostic performance of our marker was assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curves. Results: 124 patients were enrolled in this study, with a mean age of 58 years [CI: 55 – 60 years] and a sex ratio of 1.17. Viral etiologies were found in 50% of patients. Screening endoscopy revealed the presence of PHG in 20.2% of cases, while for EVsthey were found in 83.1% of cases. VWF-Ag levels, were significantly increased in patients with PHG compared to those who have not: 441% [CI: 375 – 506], versus 279% [CI: 253 – 304], respectively (p <0.0001). Using the area under the receiver operating characteristic curve (AUC), vWF-Ag was a good predictor for the presence of PHG. With a value higher than 320% and an AUC of 0.824, VWF-Ag had an 84% sensitivity, 74% specificity, 44.7% positive predictive value, 94.8% negative predictive value, and 75.8% diagnostic accuracy. Conclusion: VWF-Ag is a good non-invasive low coast marker for excluding the presence of PHG in patients with liver cirrhosis. Using this marker as part of a selective screening strategy might reduce the need for endoscopic screening and the coast of the management of these kinds of patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=von%20willebrand%20factor" title="von willebrand factor">von willebrand factor</a>, <a href="https://publications.waset.org/abstracts/search?q=portal%20hypertensive%20gastropathy" title=" portal hypertensive gastropathy"> portal hypertensive gastropathy</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=liver%20cirrhosis" title=" liver cirrhosis"> liver cirrhosis</a> </p> <a href="https://publications.waset.org/abstracts/143425/role-of-von-willebrand-factor-antigen-as-non-invasive-biomarker-for-the-prediction-of-portal-hypertensive-gastropathy-in-patients-with-liver-cirrhosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143425.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">205</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1226</span> Navigating Uncertainties in Project Control: A Predictive Tracking Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Byung%20Cheol%20Kim">Byung Cheol Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study explores a method for the signal-noise separation challenge in project control, focusing on the limitations of traditional deterministic approaches that use single-point performance metrics to predict project outcomes. We detail how traditional methods often overlook future uncertainties, resulting in tracking biases when reliance is placed solely on immediate data without adjustments for predictive accuracy. Our investigation led to the development of the Predictive Tracking Project Control (PTPC) framework, which incorporates network simulation and Bayesian control models to adapt more effectively to project dynamics. The PTPC introduces controlled disturbances to better identify and separate tracking biases from useful predictive signals. We will demonstrate the efficacy of the PTPC with examples, highlighting its potential to enhance real-time project monitoring and decision-making, marking a significant shift towards more accurate project management practices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=predictive%20tracking" title="predictive tracking">predictive tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20control" title=" project control"> project control</a>, <a href="https://publications.waset.org/abstracts/search?q=signal-noise%20separation" title=" signal-noise separation"> signal-noise separation</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20inference" title=" Bayesian inference"> Bayesian inference</a> </p> <a href="https://publications.waset.org/abstracts/192188/navigating-uncertainties-in-project-control-a-predictive-tracking-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192188.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">18</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1225</span> A Predictive Analytics Approach to Project Management: Reducing Project Failures in Web and Software Development Projects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tazeen%20Fatima">Tazeen Fatima</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Use of project management in web & software development projects is very significant. It has been observed that even with the application of effective project management, projects usually do not complete their lifecycle and fail. To minimize these failures, key performance indicators have been introduced in previous studies to counter project failures. However, there are always gaps and problems in the KPIs identified. Despite of incessant efforts at technical and managerial levels, projects still fail. There is no substantial approach to identify and avoid these failures in the very beginning of the project lifecycle. In this study, we aim to answer these research problems by analyzing the concept of predictive analytics which is a specialized technology and is very easy to use in this era of computation. Project organizations can use data gathering, compute power, and modern tools to render efficient Predictions. The research aims to identify such a predictive analytics approach. The core objective of the study was to reduce failures and introduce effective implementation of project management principles. Existing predictive analytics methodologies, tools and solution providers were also analyzed. Relevant data was gathered from projects and was analyzed via predictive techniques to make predictions well advance in time to render effective project management in web & software development industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=project%20management" title="project management">project management</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20analytics" title=" predictive analytics"> predictive analytics</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20analytics%20methodology" title=" predictive analytics methodology"> predictive analytics methodology</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20failures" title=" project failures"> project failures</a> </p> <a href="https://publications.waset.org/abstracts/69625/a-predictive-analytics-approach-to-project-management-reducing-project-failures-in-web-and-software-development-projects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69625.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">347</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1224</span> The Involvement of the Homing Receptors CCR7 and CD62L in the Pathogenesis of Graft-Versus-Host Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Federico%20Herrera">Federico Herrera</a>, <a href="https://publications.waset.org/abstracts/search?q=Valle%20Gomez%20Garc%C3%ADa%20de%20Soria"> Valle Gomez García de Soria</a>, <a href="https://publications.waset.org/abstracts/search?q=Itxaso%20Portero%20Sainz"> Itxaso Portero Sainz</a>, <a href="https://publications.waset.org/abstracts/search?q=Carlos%20Fern%C3%A1ndez%20Arandojo"> Carlos Fernández Arandojo</a>, <a href="https://publications.waset.org/abstracts/search?q=Mercedes%20Royg"> Mercedes Royg</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20Marcos%20Jimenez"> Ana Marcos Jimenez</a>, <a href="https://publications.waset.org/abstracts/search?q=Anna%20Kreutzman"> Anna Kreutzman</a>, <a href="https://publications.waset.org/abstracts/search?q=Cecilia%20Mu%C3%B1ozCalleja"> Cecilia MuñozCalleja </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Graft-versus-host disease (GVHD) still remains the major complication associated with allogeneic stem cell transplantation (SCT). The pathogenesis involves migration of donor naïve T-cells into recipient secondary lymphoid organs. Two molecules are important in this process: CD62L and CCR7, which are characteristically expressed in naïve/central memory T-cells. With this background, we aimed to study the influence of CCR7 and CD62L on donor lymphocytes in the development and severity of GVHD. Material and methods: This single center study included 98 donor-recipient pairs. Samples were collected prospectively from the apheresis product and phenotyped by flow cytometry. CCR7 and CD62L expression in CD4+ and CD8+ T-cells were compared between patients who developed acute (n=40) or chronic GVHD (n=33) and those who did not (n=38). Results: The patients who developed acute GVHD were transplanted with a higher percentage of CCR7+CD4+ T-cells (p = 0.05) compared to the no GVHD group. These results were confirmed when these patients were divided in degrees according to the severity of the disease; the more severe disease, the higher percentage of CCR7+CD4+ T-cells. Conversely, chronic GVHD patients received a higher percentage of CCR7+CD8+ T-cells (p=0.02) in comparison to those who did not develop the complication. These data were also confirmed when patients were subdivided in degrees of the disease severity. A multivariable analysis confirmed that percentage of CCR7+CD4+ T-cells is a predictive factor of acute GVHD whereas the percentage of CCR7+CD8+ T-cells is a predictive factor of chronic GVHD. In vitro functional assays (migration and activation assays) supported the idea of CCR7+ T-cells were involved in the development of GVHD. As low levels of CD62L expression were detected in all apheresis products, we tested the hypothesis that CD62L was shed during apheresis procedure. Comparing CD62L surface levels in T-cells from the same donor immediately before collecting the apheresis product, and the final apheresis product we found that this process down-regulated CD62L in both CD4+ and CD8+ T cells (p=0.008). Interestingly, when CD62L levels were analysed in days 30 or 60 after engraftment, they recovered to baseline (p=0.008). However, to investigate the relation between CD62L expression and the development of GVHD in the recipient samples after the engraftment, no differences were observed comparing patients with GVHD to those who did not develop the disease. Discussion: Our prospective study indicates that the CCR7+ T-cells from the donor, which include naïve and central memory T-cells, contain the alloreactive cells with a high ability to mediate GVHD (in the case of both migration and activation). Therefore we suggest that the proportion and functional properties of CCR7+CD4+ and CCR7+CD8+ T-cells in the apheresis could act as a predictive biomarker to both acute and chronic GVHD respectively. Importantly, our study precludes that CD62L is lost in the apheresis and therefore it is not a reliable biomarker for the development of GVHD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CCR7" title="CCR7">CCR7</a>, <a href="https://publications.waset.org/abstracts/search?q=CD62L" title=" CD62L"> CD62L</a>, <a href="https://publications.waset.org/abstracts/search?q=GVHD" title=" GVHD"> GVHD</a>, <a href="https://publications.waset.org/abstracts/search?q=SCT" title=" SCT"> SCT</a> </p> <a href="https://publications.waset.org/abstracts/31277/the-involvement-of-the-homing-receptors-ccr7-and-cd62l-in-the-pathogenesis-of-graft-versus-host-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31277.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">287</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1223</span> Learning Predictive Models for Efficient Energy Management of Exhibition Hall</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jeongmin%20Kim">Jeongmin Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Eunju%20Lee"> Eunju Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Kwang%20Ryel%20Ryu"> Kwang Ryel Ryu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=predictive%20control" title="predictive control">predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20management" title=" energy management"> energy management</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/59405/learning-predictive-models-for-efficient-energy-management-of-exhibition-hall" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59405.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">274</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1222</span> An Approach to Make an Adaptive Immunoassay to Detect an Unknown Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Josselyn%20Mata%20Calidonio">Josselyn Mata Calidonio</a>, <a href="https://publications.waset.org/abstracts/search?q=Arianna%20I.%20Maddox"> Arianna I. Maddox</a>, <a href="https://publications.waset.org/abstracts/search?q=Kimberly%20Hamad-Schifferli"> Kimberly Hamad-Schifferli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20immunoassay" title="adaptive immunoassay">adaptive immunoassay</a>, <a href="https://publications.waset.org/abstracts/search?q=detecting%20unknown%20viruses" title=" detecting unknown viruses"> detecting unknown viruses</a>, <a href="https://publications.waset.org/abstracts/search?q=gold%20nanoparticles" title=" gold nanoparticles"> gold nanoparticles</a>, <a href="https://publications.waset.org/abstracts/search?q=paper%20immunoassay" title=" paper immunoassay"> paper immunoassay</a>, <a href="https://publications.waset.org/abstracts/search?q=repurposing%20antibodies" title=" repurposing antibodies"> repurposing antibodies</a> </p> <a href="https://publications.waset.org/abstracts/180474/an-approach-to-make-an-adaptive-immunoassay-to-detect-an-unknown-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/180474.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">114</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1221</span> The Exploration Targets of the Nanpu Sag: Insight from Organic Geochemical Characteristics of Source Rocks and Oils</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lixin%20Pei">Lixin Pei</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhilong%20Huang"> Zhilong Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wenzhe%20Gang"> Wenzhe Gang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Organic geochemistry of source rocks and oils in the Nanpu Sag, Bohai Bay basin was studied on the basis of the results of Rock-Eval and biomarker. The possible source rocks consist of the third member (Es₃) and the first member (Es₁) of Shahejie formation and the third member of Dongying Formation (Ed₃) in the Nanpu Sag. The Es₃, Es₁, and Ed₃ source rock intervals in the Nanpu Sag all have high organic-matter richness and are at hydrocarbon generating stage, which are regarded as effective source rocks. The three possible source rock intervals have different biomarker associations and can be differentiated by gammacerane/αβ C₃₀ hopane, ETR ([C₂₈+C₂₉]/ [C₂₈+C₂₉+Ts]), C₂₇ diasterane/sterane and C₂₇/C₂₉ steranes, which suggests they deposited in different environments. Based on the oil-source rock correlation, the shallow oils mainly originated from the Es₃ and Es₁ source rocks in the Nanpu Sag. Through hydrocarbon generation and expulsion history of the source rocks, trap development history and accumulation history, the shallow oils mainly originated from paleo-reservoirs in the Es₃ and Es₁ during the period of Neotectonism, and the residual paleo-reservoirs in the Es₃ and Es₁ would be the focus targets in the Nanpu Sag; Bohai Bay Basin. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=source%20rock" title="source rock">source rock</a>, <a href="https://publications.waset.org/abstracts/search?q=biomarker%20association" title=" biomarker association"> biomarker association</a>, <a href="https://publications.waset.org/abstracts/search?q=Nanpu%20Sag" title=" Nanpu Sag"> Nanpu Sag</a>, <a href="https://publications.waset.org/abstracts/search?q=Bohai%20Bay%20Basin" title=" Bohai Bay Basin"> Bohai Bay Basin</a> </p> <a href="https://publications.waset.org/abstracts/79990/the-exploration-targets-of-the-nanpu-sag-insight-from-organic-geochemical-characteristics-of-source-rocks-and-oils" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79990.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">373</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1220</span> Model Predictive Control Using Thermal Inputs for Crystal Growth Dynamics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Shimizu">Takashi Shimizu</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomoaki%20Hashimoto"> Tomoaki Hashimoto</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20predictive%20control" title="model predictive control">model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20control" title=" process control"> process control</a>, <a href="https://publications.waset.org/abstracts/search?q=crystal%20growth" title=" crystal growth"> crystal growth</a> </p> <a href="https://publications.waset.org/abstracts/88644/model-predictive-control-using-thermal-inputs-for-crystal-growth-dynamics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88644.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">359</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1219</span> Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yishu%20Gong">Yishu Gong</a>, <a href="https://publications.waset.org/abstracts/search?q=Liangliang%20Yang"> Liangliang Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianyu%20Zhang"> Jianyu Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhengyu%20Chen"> Zhengyu Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Sihong%20He"> Sihong He</a>, <a href="https://publications.waset.org/abstracts/search?q=Xusheng%20Zhang"> Xusheng Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Zhang"> Wei Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20emotion%20recognition" title=" speech emotion recognition"> speech emotion recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=longitudinal%20biomarker" title=" longitudinal biomarker"> longitudinal biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/161096/using-speech-emotion-recognition-as-a-longitudinal-biomarker-for-alzheimers-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161096.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">113</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1218</span> Artificial Bee Colony Based Modified Energy Efficient Predictive Routing in MANET</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Akhil%20Dubey">Akhil Dubey</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajnesh%20Singh"> Rajnesh Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In modern days there occur many rapid modifications in field of ad hoc network. These modifications create many revolutionary changes in the routing. Predictive energy efficient routing is inspired on the bee’s behavior of swarm intelligence. Predictive routing improves the efficiency of routing in the energetic point of view. The main aim of this routing is the minimum energy consumption during communication and maximized intermediate node’s remaining battery power. This routing is based on food searching behavior of bees. There are two types of bees for the exploration phase the scout bees and for the evolution phase forager bees use by this routing. This routing algorithm computes the energy consumption, fitness ratio and goodness of the path. In this paper we review the literature related with predictive routing, presenting modified routing and simulation result of this algorithm comparison with artificial bee colony based routing schemes in MANET and see the results of path fitness and probability of fitness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mobile%20ad%20hoc%20network" title="mobile ad hoc network">mobile ad hoc network</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20bee%20colony" title=" artificial bee colony"> artificial bee colony</a>, <a href="https://publications.waset.org/abstracts/search?q=PEEBR" title=" PEEBR"> PEEBR</a>, <a href="https://publications.waset.org/abstracts/search?q=modified%20predictive%20routing" title=" modified predictive routing"> modified predictive routing</a> </p> <a href="https://publications.waset.org/abstracts/33480/artificial-bee-colony-based-modified-energy-efficient-predictive-routing-in-manet" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33480.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=predictive%20biomarker&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=predictive%20biomarker&page=3">3</a></li> <li class="page-item"><a class="page-link" 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