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type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.04493">arXiv:2502.04493</a> <span> [<a href="https://arxiv.org/pdf/2502.04493">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Medical Physics">physics.med-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> </div> </div> <p class="title is-5 mathjax"> LUND-PROBE -- LUND Prostate Radiotherapy Open Benchmarking and Evaluation dataset </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Rogowski%2C+V">Viktor Rogowski</a>, <a href="/search/physics?searchtype=author&query=Olsson%2C+L+E">Lars E Olsson</a>, <a href="/search/physics?searchtype=author&query=Scherman%2C+J">Jonas Scherman</a>, <a href="/search/physics?searchtype=author&query=Persson%2C+E">Emilia Persson</a>, <a href="/search/physics?searchtype=author&query=Kadhim%2C+M">Mustafa Kadhim</a>, <a href="/search/physics?searchtype=author&query=Wetterstedt%2C+S+a">Sacha af Wetterstedt</a>, <a href="/search/physics?searchtype=author&query=Gunnlaugsson%2C+A">Adalsteinn Gunnlaugsson</a>, <a href="/search/physics?searchtype=author&query=Nilsson%2C+M+P">Martin P. Nilsson</a>, <a href="/search/physics?searchtype=author&query=Vass%2C+N">Nandor Vass</a>, <a href="/search/physics?searchtype=author&query=Moreau%2C+M">Mathieu Moreau</a>, <a href="/search/physics?searchtype=author&query=Medhin%2C+M+G">Maria Gebre Medhin</a>, <a href="/search/physics?searchtype=author&query=B%C3%A4ck%2C+S">Sven B盲ck</a>, <a href="/search/physics?searchtype=author&query=Rosensch%C3%B6ld%2C+P+M+a">Per Munck af Rosensch枚ld</a>, <a href="/search/physics?searchtype=author&query=Engelholm%2C+S">Silke Engelholm</a>, <a href="/search/physics?searchtype=author&query=Gustafsson%2C+C+J">Christian Jamtheim Gustafsson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.04493v1-abstract-short" style="display: inline;"> Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for segmentation of target volumes and organs at risk (OARs). Manual segmentation of these volumes is regarded as the gold standard for ground truth in machine learning applications but to acquire such data is tedious and time-consuming. A publicly available clinical dataset is pre… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.04493v1-abstract-full').style.display = 'inline'; document.getElementById('2502.04493v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.04493v1-abstract-full" style="display: none;"> Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for segmentation of target volumes and organs at risk (OARs). Manual segmentation of these volumes is regarded as the gold standard for ground truth in machine learning applications but to acquire such data is tedious and time-consuming. A publicly available clinical dataset is presented, comprising MRI- and synthetic CT (sCT) images, target and OARs segmentations, and radiotherapy dose distributions for 432 prostate cancer patients treated with MRI-guided radiotherapy. An extended dataset with 35 patients is also included, with the addition of deep learning (DL)-generated segmentations, DL segmentation uncertainty maps, and DL segmentations manually adjusted by four radiation oncologists. The publication of these resources aims to aid research within the fields of automated radiotherapy treatment planning, segmentation, inter-observer analyses, and DL model uncertainty investigation. The dataset is hosted on the AIDA Data Hub and offers a free-to-use resource for the scientific community, valuable for the advancement of medical imaging and prostate cancer radiotherapy research. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.04493v1-abstract-full').style.display = 'none'; document.getElementById('2502.04493v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">4 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2104.11687">arXiv:2104.11687</a> <span> [<a href="https://arxiv.org/pdf/2104.11687">pdf</a>, <a href="https://arxiv.org/format/2104.11687">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Detectors">physics.ins-det</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Nuclear Experiment">nucl-ex</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1088/1748-0221/16/08/P08059">10.1088/1748-0221/16/08/P08059 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The SNO+ Experiment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Collaboration%2C+S">SNO+ Collaboration</a>, <a href="/search/physics?searchtype=author&query=%3A"> :</a>, <a href="/search/physics?searchtype=author&query=Albanese%2C+V">V. Albanese</a>, <a href="/search/physics?searchtype=author&query=Alves%2C+R">R. Alves</a>, <a href="/search/physics?searchtype=author&query=Anderson%2C+M+R">M. R. Anderson</a>, <a href="/search/physics?searchtype=author&query=Andringa%2C+S">S. Andringa</a>, <a href="/search/physics?searchtype=author&query=Anselmo%2C+L">L. Anselmo</a>, <a href="/search/physics?searchtype=author&query=Arushanova%2C+E">E. Arushanova</a>, <a href="/search/physics?searchtype=author&query=Asahi%2C+S">S. Asahi</a>, <a href="/search/physics?searchtype=author&query=Askins%2C+M">M. Askins</a>, <a href="/search/physics?searchtype=author&query=Auty%2C+D+J">D. J. Auty</a>, <a href="/search/physics?searchtype=author&query=Back%2C+A+R">A. R. Back</a>, <a href="/search/physics?searchtype=author&query=Back%2C+S">S. Back</a>, <a href="/search/physics?searchtype=author&query=Bar%C3%A3o%2C+F">F. Bar茫o</a>, <a href="/search/physics?searchtype=author&query=Barnard%2C+Z">Z. Barnard</a>, <a href="/search/physics?searchtype=author&query=Barr%2C+A">A. Barr</a>, <a href="/search/physics?searchtype=author&query=Barros%2C+N">N. Barros</a>, <a href="/search/physics?searchtype=author&query=Bartlett%2C+D">D. Bartlett</a>, <a href="/search/physics?searchtype=author&query=Bayes%2C+R">R. Bayes</a>, <a href="/search/physics?searchtype=author&query=Beaudoin%2C+C">C. Beaudoin</a>, <a href="/search/physics?searchtype=author&query=Beier%2C+E+W">E. W. Beier</a>, <a href="/search/physics?searchtype=author&query=Berardi%2C+G">G. Berardi</a>, <a href="/search/physics?searchtype=author&query=Bialek%2C+A">A. Bialek</a>, <a href="/search/physics?searchtype=author&query=Biller%2C+S+D">S. D. Biller</a>, <a href="/search/physics?searchtype=author&query=Blucher%2C+E">E. Blucher</a> , et al. (229 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2104.11687v3-abstract-short" style="display: inline;"> The SNO+ experiment is located 2 km underground at SNOLAB in Sudbury, Canada. A low background search for neutrinoless double beta ($0谓尾尾$) decay will be conducted using 780 tonnes of liquid scintillator loaded with 3.9 tonnes of natural tellurium, corresponding to 1.3 tonnes of $^{130}$Te. This paper provides a general overview of the SNO+ experiment, including detector design, construction of pr… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.11687v3-abstract-full').style.display = 'inline'; document.getElementById('2104.11687v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2104.11687v3-abstract-full" style="display: none;"> The SNO+ experiment is located 2 km underground at SNOLAB in Sudbury, Canada. A low background search for neutrinoless double beta ($0谓尾尾$) decay will be conducted using 780 tonnes of liquid scintillator loaded with 3.9 tonnes of natural tellurium, corresponding to 1.3 tonnes of $^{130}$Te. This paper provides a general overview of the SNO+ experiment, including detector design, construction of process plants, commissioning efforts, electronics upgrades, data acquisition systems, and calibration techniques. The SNO+ collaboration is reusing the acrylic vessel, PMT array, and electronics of the SNO detector, having made a number of experimental upgrades and essential adaptations for use with the liquid scintillator. With low backgrounds and a low energy threshold, the SNO+ collaboration will also pursue a rich physics program beyond the search for $0谓尾尾$ decay, including studies of geo- and reactor antineutrinos, supernova and solar neutrinos, and exotic physics such as the search for invisible nucleon decay. The SNO+ approach to the search for $0谓尾尾$ decay is scalable: a future phase with high $^{130}$Te-loading is envisioned to probe an effective Majorana mass in the inverted mass ordering region. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.11687v3-abstract-full').style.display = 'none'; document.getElementById('2104.11687v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 23 April, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">61 pages, 23 figures, 4 tables</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> The SNO+ collaboration, 2021 JINST 16 P08059 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1709.04576">arXiv:1709.04576</a> <span> [<a href="https://arxiv.org/pdf/1709.04576">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Materials Science">cond-mat.mtrl-sci</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> </div> </div> <p class="title is-5 mathjax"> Catalyst design using actively learned machine with non-ab initio input features towards CO2 reduction reactions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/physics?searchtype=author&query=Noh%2C+J">Juhwan Noh</a>, <a href="/search/physics?searchtype=author&query=Kim%2C+J">Jaehoon Kim</a>, <a href="/search/physics?searchtype=author&query=Back%2C+S">Seoin Back</a>, <a href="/search/physics?searchtype=author&query=Jung%2C+Y">Yousung Jung</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1709.04576v1-abstract-short" style="display: inline;"> In conventional chemisorption model, the d-band center theory (augmented sometimes with the upper edge of d-band for imporved accuarcy) plays a central role in predicting adsorption energies and catalytic activity as a function of d-band center of the solid surfaces, but it requires density functional calculations that can be quite costly for large scale screening purposes of materials. In this wo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1709.04576v1-abstract-full').style.display = 'inline'; document.getElementById('1709.04576v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1709.04576v1-abstract-full" style="display: none;"> In conventional chemisorption model, the d-band center theory (augmented sometimes with the upper edge of d-band for imporved accuarcy) plays a central role in predicting adsorption energies and catalytic activity as a function of d-band center of the solid surfaces, but it requires density functional calculations that can be quite costly for large scale screening purposes of materials. In this work, we propose to use the d-band width of the muffin-tin orbital theory (to account for local coordination environment) plus electronegativity (to account for adsorbate renormalization) as a simple set of alternative descriptors for chemisorption, which do not demand the ab initio calculations. This pair of descriptors are then combined with machine learning methods, namely, artificial neural network (ANN) and kernel ridge regression (KRR), to allow large scale materials screenings. We show, for a toy set of 263 alloy systems, that the CO adsorption energy can be predicted with a remarkably small mean absolute deviation error of 0.05 eV, a significantly improved result as compared to 0.13 eV obtained with descriptors including costly d-band center calculations in literature. We achieved this high accuracy by utilizing an active learning algorithm, without which the accuracy was 0.18 eV otherwise. As a practical application of this machine, we identified Cu3Y@Cu as a highly active and cost-effective electrochemical CO2 reduction catalyst to produce CO with the overpotential 0.37 V lower than Au catalyst. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1709.04576v1-abstract-full').style.display = 'none'; document.getElementById('1709.04576v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 September, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2017. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Under review and including Electronic Supplementary Information (ESI)</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: 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