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1,063 results for “Search”
"Histopathology Slide Indexing and Search: Are We There Yet?" - UCLA Test Slides
<p>In-House UCLA test slides used for the case report in "Histopathology Slide Indexing and Search: Are We There Yet?" submitted to NEJM AI.</p>
1st International Workshop on Open Web Search #wows2024 at ECIR 2024: Document Processors
<p><a href="https://opensearchfoundation.org/en/events-osf/wows2024/#osf-callforcontributions">The First International Workshop on Open Web Search</a> (WOWS) hosted at [ECIR 2024](https://www.ecir2024.org/) aimed to promote and discuss ideas and approaches to open up the web search ecosystem so that small research groups and young startups can leverage the web to foster an open and diverse search market. The workshop had two calls that support collaborative and open web search engines: (1) for scientific contributions, and (2) for open-source implementations. This repository collects the outputs of all submitted document processing components on public datasets for the second call aims to gather open-source prototypes and gain practical experience with collaborative, cooperative evaluation of search engines and their components using the [TIREx Information Retrieval Evaluation Platform](https://www.tira.io/tirex) hosted on [TIRA](https://www.tira.io).</p> <p> </p> <p> </p> <h2>Citations</h2> <p>If you reuse the resources, please ensure to cite TIRA and TIREx and the corresponding datasets, the corresponding bib-entries are:</p> <p>For TIREx:</p> <pre><code>@InProceedings{froebe:2023e,<br> author = {Maik Fr{\"o}be and {Jan Heinrich} Reimer and Sean MacAvaney and Niklas Deckers and Simon Reich and Janek Bevendorff and Benno Stein and Matthias Hagen and Martin Potthast},<br> booktitle = {46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)},<br> doi = {10.1145/3539618.3591888},<br> editor = {Hsin{-}Hsi Chen and Wei{-}Jou (Edward) Duh and Hen{-}Hsen Huang and Makoto P. Kato and Josiane Mothe and Barbara Poblete},<br> ids = {potthast:2023t},<br> isbn = {9781450394086},<br> month = jul,<br> numpages = 11,<br> pages = {2826--2836},<br> publisher = {ACM},<br> site = {Taipei, Taiwan},<br> title = {{The Information Retrieval Experiment Platform}},<br> url = {https://dl.acm.org/doi/10.1145/3539618.3591888},<br> year = 2023<br>}<br></code></pre> <p>for TIRA:</p> <pre><code>@InProceedings{froebe:2023b,<br> address = {Berlin Heidelberg New York},<br> author = {Maik Fr{\"o}be and Matti Wiegmann and Nikolay Kolyada and Bastian Grahm and Theresa Elstner and Frank Loebe and Matthias Hagen and Benno Stein and Martin Potthast},<br> booktitle = {Advances in Information Retrieval. 45th European Conference on {IR} Research ({ECIR} 2023)},<br> doi = {10.1007/978-3-031-28241-6_20},<br> editor = {Jaap Kamps and Lorraine Goeuriot and Fabio Crestani and Maria Maistro and Hideo Joho and Brian Davis and Cathal Gurrin and Udo Kruschwitz and Annalina Caputo},<br> ids = {potthast:2023h},<br> month = apr,<br> pages = {236--241},<br> publisher = {Springer},<br> series = {Lecture Notes in Computer Science},<br> site = {Dublin, Irland},<br> title = {{Continuous Integration for Reproducible Shared Tasks with TIRA.io}},<br> url = {https://link.springer.com/chapter/10.1007/978-3-031-28241-6_20},<br> year = 2023<br>}</code><br><br>All query processors are described in the corresponding WOWS paper, please cite the papers and underlying approaches accordingly.</pre> <p>Forthermore, please cite the datasets that you use.</p> <h3>Args.me</h3> <p>If you re-use the Args.me indices, please additionally cite:</p> <pre><code>@InProceedings{bondarenko:2021d,<br> address = {Berlin Heidelberg New York},<br> author = {Alexander Bondarenko and Lukas Gienapp and Maik Fr{\"o}be and Meriem Beloucif and Yamen Ajjour and Alexander Panchenko and Chris Biemann and Benno Stein and Henning Wachsmuth and Martin Potthast and Matthias Hagen},<br> booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. 12th International Conference of the CLEF Association (CLEF 2021)},<br> editor = {{K. Sel{\c{c}}uk} Candan and Bogdan Ionescu and Lorraine Goeuriot and Henning M{\"u}ller and Alexis Joly and Maria Maistro and Florina Piroi and Guglielmo Faggioli and Nicola Ferro},<br> ids = {potthast:2021t},<br> month = sep,<br> pages = {450-467},<br> publisher = {Springer},<br> series = {Lecture Notes in Computer Science},<br> site = {Bucharest, Romania},<br> title = {{Overview of Touch{\'e} 2021: Argument Retrieval}},<br> volume = 12880,<br> year = 2021<br>}<br></code><br><code>@InProceedings{bondarenko:2022f,<br> address = {Berlin Heidelberg New York},<br> author = {Alexander Bondarenko and Maik Fr{\"o}be and Johannes Kiesel and Shahbaz Syed and Timon Gurcke and Meriem Beloucif and Alexander Panchenko and Chris Biemann and Benno Stein and Henning Wachsmuth and Martin Potthast and Matthias Hagen},<br> booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. 13th International Conference of the CLEF Association (CLEF 2022)},<br> editor = {Alberto Barr{\'o}n-Cede{\~n}o and Giovanni Da San Martino and Mirko Degli Esposti and Fabrizio Sebastiani and Craig Macdonald and Gabriella Pasi and Allan Hanbury and Martin Potthast and Guglielmo Faggioli and Nicola Ferro},<br> ids = {potthast:2022j},<br> month = sep,<br> numpages = 29,<br> publisher = {Springer},<br> series = {Lecture Notes in Computer Science},<br> site = {Bologna, Italy},<br> title = {{Overview of Touch{\'e} 2022: Argument Retrieval}},<br> year = 2022<br>}</code></pre> <h3>Antique</h3> <p>If you re-use the Antique indices, please additionally cite:</p> <pre><code>@inproceedings{hashemi:2020,<br> author = {Helia Hashemi and Mohammad Aliannejadi and Hamed Zamani and W. Bruce Croft},<br> editor = {Joemon M. Jose and Emine Yilmaz and Jo{\~{a}}o Magalh{\~{a}}es and Pablo Castells and Nicola Ferro and M{\'{a}}rio J. Silva and Fl{\'{a}}vio Martins},<br> title = {{ANTIQUE:} {A} Non-factoid Question Answering Benchmark},<br> booktitle = {Advances in Information Retrieval - 42nd European Conference on {IR} Research, {ECIR} 2020, Lisbon, Portugal, April 14-17, 2020, Proceedings, Part {II}},<br> series = {Lecture Notes in Computer Science},<br> volume = {12036},<br> pages = {166--173},<br> publisher = {Springer},<br> year = {2020},<br>}</code><br><br></pre> <h3>CORD-19</h3> <p>If you re-use the CORD-19 indices, please additionally cite:</p> <pre><code>@article{voorhees:2020,<br> author = {Ellen M. Voorhees and Tasmeer Alam and Steven Bedrick and Dina Demner{-}Fushman and William R. Hersh and Kyle Lo and Kirk Roberts and Ian Soboroff and Lucy Lu Wang},<br> title = {{TREC-COVID:} constructing a pandemic information retrieval test collection},<br> journal = {{SIGIR} Forum},<br> volume = {54},<br> number = {1},<br> pages = {1:1--1:12},<br> year = {2020},<br>}<br><br>@article{wang:2020,<br> author = {Lucy Lu Wang and Kyle Lo and Yoganand Chandrasekhar and Russell Reas and Jiangjiang Yang and Darrin Eide and Kathryn Funk and Rodney Kinney and Ziyang Liu and William Merrill and Paul Mooney and Dewey A. Murdick and Devvret Rishi and Jerry Sheehan and Zhihong Shen and Brandon Stilson and Alex D. Wade and Kuansan Wang and Chris Wilhelm and Boya Xie and Douglas Raymond and Daniel S. Weld and Oren Etzioni and Sebastian Kohlmeier},<br> title = {{CORD-19:} The Covid-19 Open Research Dataset},<br> journal = {CoRR},<br> volume = {abs/2004.10706},<br> year = {2020},<br> eprinttype = {arXiv},<br> eprint = {2004.10706},<br>}<br><br></code></pre> <h3>Cranfield</h3> <p>If you re-use the Cranfield indices, please additionally cite:</p> <pre><code>@inproceedings{cleverdon:1967,<br> title={The {C}ranfield tests on index language devices},<br> author={Cleverdon, Cyril},<br> booktitle={{ASLIB} Proceedings},<br> year={1967},<br> pages = {173--192},<br> organization={MCB UP Ltd. (Reprinted in Readings in Information Retrieval, Karen Sparck-Jones and Peter Willett, editors, Morgan Kaufmann, 1997)}<br>}<br><br>@inproceedings{cleverdon:1991,<br> author = {Cyril W. Cleverdon},<br> editor = {Abraham Bookstein and Yves Chiaramella and Gerard Salton and Vijay V. Raghavan},<br> title = {The Significance of the {C}ranfield Tests on Index Languages},<br> booktitle = {Proceedings of the 14th Annual International {ACM} {SIGIR} Conference on Research and Development in Information Retrieval. Chicago, Illinois, USA, October 13-16, 1991 (Special Issue of the {SIGIR} Forum)},<br> pages = {3--12},<br> publisher = {{ACM}},<br> year = {1991},<br>}</code></pre> <h3>Medline TREC Genomics</h3> <p>If you re-use the Medline TREC Genomics indices, please additionally cite:</p> <pre><code>@inproceedings{hersh:2004,<br> author = {William R. Hersh and Ravi Teja Bhupatiraju and L. Ross and Aaron M. Cohen and Dale Kraemer and Phoebe Johnson},<br> editor = {Ellen M. Voorhees and Lori P. Buckland},<br> title = {{TREC} 2004 Genomics Track Overview},<br> booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},<br> series = {{NIST} Special Publication},<br> volume = {500-261},<br> publisher = {National Institute of Standards and Technology {(NIST)}},<br> year = {2004},<br>}<br><br>@inproceedings{hersh:2005,<br> author = {William R. Hersh and Aaron M. Cohen and Jianji Yang and Ravi Teja Bhupatiraju and Phoebe M. Roberts and Marti A. Hearst},<br> editor = {Ellen M. Voorhees and Lori P. Buckland},<br> title = {{TREC} 2005 Genomics Track Overview},<br> booktitle = {Proceedings of the Fourteenth Text REtrieval Conference, {TREC} 2005, Gaithersburg, Maryland, USA, November 15-18, 2005},<br> series = {{NIST} Special Publication},<br> volume = {500-266},<br> publisher = {National Institute of Standards and Technology {(NIST)}},<br> year = {2005},<br>}</code><br><br><br></pre> <h3>Medline TREC Precision Medicine</h3> <p>If you re-use the Medline TREC Precision Medicine indices, please additionally cite:</p> <pre><code>@inproceedings{roberts:2017,<br> author = {Kirk Roberts and Dina Demner{-}Fushman and Ellen M. Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar and Shubham Pant},<br> editor = {Ellen M. Voorhees and Angela Ellis},<br> title = {Overview of the {TREC} 2017 Precision Medicine Track},<br> booktitle = {Proceedings of The Twenty-Sixth Text REtrieval Conference, {TREC} 2017, Gaithersburg, Maryland, USA, November 15-17, 2017},<br> series = {{NIST} Special Publication},<br> volume = {500-324},<br> publisher = {National Institute of Standards and Technology {(NIST)}},<br> year = {2017},<br>}<br><br>@inproceedings{roberts:2018,<br> author = {Kirk Roberts and Dina Demner{-}Fushman and Ellen M. Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar},<br> editor = {Ellen M. Voorhees and Angela Ellis},<br> title = {Overview of the {TREC} 2018 Precision Medicine Track},<br> booktitle = {Proceedings of the Twenty-Seventh Text REtrieval Conference, {TREC} 2018, Gaithersburg, Maryland, USA, November 14-16, 2018},<br> series = {{NIST} Special Publication},<br> volume = {500-331},<br> publisher = {National Institute of Standards and Technology {(NIST)}},<br> year = {2018},<br>}</code><br><br></pre> <h3>MS MARCO (TREC Deep Learning 2019 and 2020</h3> <p>If you re-use the MS MARCO indices, please additionally cite:</p> <pre><code>@inproceedings{craswell:2019,<br> author = {Nick Craswell and Bhaskar Mitra and Emine Yilmaz and Daniel Campos and Ellen M. Voorhees},<br> booktitle = {28th International Text Retrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA},<br> editor = {{Ellen M.} Voorhees and Angela Ellis},<br> month = nov,<br> title = {{Overview of the {TREC} 2019 Deep Learning Track}},<br> publisher = {National Institute of Standards and Technology (NIST)},<br> series = {NIST Special Publication},<br> year = {2019}<br>}<br><br>@inproceedings{craswell:2020,<br> author = {Nick Craswell and Bhaskar Mitra and Emine Yilmaz and Daniel Campos},<br> editor = {Ellen M. Voorhees and Angela Ellis},<br> title = {{Overview of the {TREC} 2020 Deep Learning Track}},<br> booktitle = {Proceedings of the 29th Text REtrieval Conference, {TREC} 2020, Virtual Event, Gaithersburg, MD, USA, November 16-20, 2020},<br> series = {{NIST} Special Publication},<br> volume = {1266},<br> publisher = {National Institute of Standards and Technology {(NIST)}},<br> year = {2020},<br>}</code></pre> <pre> </pre> <h3>NFCorpus</h3> <p>If you re-use the next indices, please additionally cite:</p> <pre><code>@inproceedings{boteva:2016,<br> author = {Vera Boteva and Demian Gholipour Ghalandari and Artem Sokolov and Stefan Riezler},<br> editor = {Nicola Ferro and Fabio Crestani and Marie{-}Francine Moens and Josiane Mothe and Fabrizio Silvestri and Giorgio Maria Di Nunzio and Claudia Hauff and Gianmaria Silvello},<br> title = {A Full-Text Learning to Rank Dataset for Medical Information Retrieval},<br> booktitle = {Advances in Information Retrieval - 38th European Conference on {IR} Research, {ECIR} 2016, Padua, Italy, March 20-23, 2016. Proceedings},<br> series = {Lecture Notes in Computer Science},<br> volume = {9626},<br> pages = {716--722},<br> publisher = {Springer},<br> year = {2016},<br>}</code></pre> <h3>LongEval</h3> <p>Please cite the [corresponding dataset](https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-5151).:</p> <pre><code>@misc{11234/1-5151, title = {{LongEval} Click-Model Relevance Judgements (Qrels)}, author = {Galu{\v s}{\v c}{\'a}kov{\'a}, Petra and Devaud, Romain and Gonzalez-Saez, Gabriela and Mulhem, Philippe and Goeuriot, Lorraine and Piroi, Florina and Popel, Martin}, url = {http://hdl.handle.net/11234/1-5151}, note = {{LINDAT}/{CLARIAH}-{CZ} digital library at the Institute of Formal and Applied Linguistics ({{\'U}FAL}), Faculty of Mathematics and Physics, Charles University}, copyright = {Qwant {LongEval} Attribution-{NonCommercial}-{ShareAlike} License}, year = {2023} }</code><br><br></pre> <p>The index can be re-used in the [LongEval 2024](https://clef-longeval.github.io/) shared task hosted at [CLEF 2024](https://clef2024.imag.fr/). The documents (and thereby the derived PyTerrier Index are under the <a href="https://lindat.mff.cuni.cz/repository/xmlui/page/Qwant_LongEval_BY-NC-SA_License">Qwant LongEval Attribution-NonCommercial-ShareAlike License</a> and by reusing the indices you also accept and aggree to do this under the sharealike qwant license.</p>
The best of both worlds: highlighting the synergies of combining knowledge modelling and automated techniques to improve information search and discovery in oil and gas exploration
<p><span>Research suggests organizations across all sectors waste a significant amount of time looking for information and often fail to leverage the information they have. In response, many organizations have deployed some form of enterprise search to improve the ‘findability’ of information. Debates persist as to whether thesauri and manual indexing or automated machine learning techniques should be used to enhance discovery of information. In addition, the extent to which a Knowledge Organization System (KOS) enhances discoveries or indeed blinds us to new ones remains a moot point. The oil and gas industry is used as a case study using a representative organization. Drawing on prior research, a theoretical model is presented which aims to overcome the shortcomings of each approach. This synergistic model could help to re-conceptualize the ‘manual’ versus ‘automatic’ debate in many enterprises, accommodating a broader range of information needs. This may enable enterprises to develop more effective information and knowledge management strategies and ease the tension between what are often perceived as mutually exclusive competing approaches. Certain aspects of the theoretical model may be transferable to other industries, which is an area for further research.</span></p>
Supplementary Table 1: Search terms used for each database.
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Implementation and Results of a Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation using Different Objective Functions
<p><strong><em>1. Introduction</em></strong></p> <p>In this archive, we provide the implementation and experimental results of a Randomized Local Search (RLS) applied to the two-dimensional bin packing problem without orientation (where items can be rotated by 90 degrees). As benchmark dataset, we use the <code>beng</code>, <code>A</code>, and <code>class</code> instances from <a href="https://site.unibo.it/operations-research/en/research/2dpacklib">2DPackLib</a> as well as the four non-trivial Almost Squares in Almost Squares (<a href="https://math.vu.nl/~sbhulai/publications/data_analytics2016b.pdf"><code>Asqas</code></a>) instances</p> <p>These are the data used in the paper below, which contains the exact specification of all algorithms, objective functions, and the encoding we applied.</p> <p>Rui Zhao, Tianyu Liang, Zhize Wu, Daan van den Berg, Matthias Thürer, and Thomas Weise. 2024. Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation. In <em>Genetic and Evolutionary Computation Conference (GECCO'24 Companion),</em> July 14–18, 2024, Melbourne, VIC, Australia. ACM, New York, NY, USA, 4 pages. doi:<a href="https://doi.org/10.1145/3638530.3654139">10.1145/3638530.3654139</a>.</p> <p>To run the experiments, you need <a href="https://thomasweise.github.io/moptipyapps">moptipyapps</a> version 0.8.34 and <a href="https://thomasweise.github.io/moptipy">moptipy</a> version 0.9.98, which contain the actual algorithm implementations. Both packages are available on GitHub and on PyPI. However, we include several versions of them in the folder <code>source/packages</code>, just in case.</p> <p><strong><em>2. Directory Structure</em></strong></p> <p>This archive contains the following directories:</p> <ul> <li><code>source</code> contains the Python source codes needed to run the experiment.</li> <li><code>source/packages</code> contains the source codes of the Python packages with the actual algorithm implementations.</li> <li><code>data</code> is the directory with the results and their evaluation.</li> <li><code>data/results</code> is the directory with the log files generated by the experiment. In this folder, there are two sub-folders, <code>ibf1</code> and <code>ibf2</code>. We tested two different encodings, but found that the second one (<code>ibf2</code>) is too slow to do meaningful experiments. Thus, the experiments with it were abandoned and only one objective function was tested. We include <code>ibf2</code> for the sake of completeness, whereas <code>ibf1</code> was used in our paper. Either way, both <code>ibfX</code> folders contain one directory for each objective function applied to them. In each such directory, there is one folder (for the single algorithm applied) and this folder, in return, contains one folder per benchmark instance. The benchmark instance folders contain the three log files of the three runs that we applied to each instance/algorithm/objective combination.<br>Each log file contains information of one run, i.e., one execution of one algorithm on one problem instance. All improving moves of a run as well as the final solution are stored in the log file.</li> <li><code>data/evaluator</code> is the folder containing Python scripts that were used to evaluate these results. Two scripts are provided: <code>evaluator_short.py</code> was used for generating the tables used in the final paper version. <code>evaluator_full.py</code> provides larger tables, which could not be included in the final paper due to space reasons.</li> <li>Folder <code>evaluation_full</code> was generated using <code>evaluator_full.py</code> and contains tables and figures and a result summary in CSV format.</li> <li>Folder <code>evaluation_short</code> was generated using <code>evaluator_short.py</code> and contains both the tables used in the paper as well as a result summary in CSV format.</li> </ul> <p><strong><em>3. License</em></strong></p> <p>The files in this repository are under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a>, with the exception of the files of <a href="https://site.unibo.it/operations-research/en/research/2dpacklib">2DPackLib</a> and other benchmark datasets included, which are under copyright of their respective owner (we believe that they are in the public domain, as they are provided by many sources, included in many software packages under various open source licenses, and on many websites). The license is contained as file <code>LICENSE.txt</code> in this archive.</p> <p><strong><em>4. Contact</em></strong></p> <p>If you have any questions or suggestions, please contact</p> <p>Mr. Rui ZHAO (赵睿) of the Institute of Applied Optimization (应用优化研究所, <a href="http://iao.hfuu.edu.cn">IAO</a>) of the School of Artificial Intelligence and Big Data (<a href="http://www.hfuu.edu.cn/aibd/">人工智能与大数据学院</a>) at <a href="http://www.hfuu.edu.cn/english/">Hefei University</a> (<a href="http://www.hfuu.edu.cn/">合肥大学</a>) in Hefei, Anhui, China (中国安徽省合肥市) via email to <a href="mailto:zr1329142665@163.com">zr1329142665@163.com</a>.</p>
Search strategies for extending BowelScreen to those aged 50 to 54 years
<p>The dataset includes the complete, reproducible search strategies for all bibliographic databases searched during this project. The search strategies were designed to answer the following research questions: </p> <ul> <li>Does test accuracy of FIT at a threshold of 45ug/g vary by age?</li> <li>Does test accuracy of FIT vary by age?</li> <li>What is the test accuracy of faecal immunochemical test (FIT) at a threshold of 45ug/g (225ng/mL)?</li> </ul>
Appendix 2 Search strings
<p>Appendix 2 of the paper "<span>Between source language constructions and target language expectations. </span>An analysis of passive constructions in translated and non-translated Spanish", published in <em>Review of Cognitive Linguistics.</em></p> <p>It contains the CQP search strings used to retrieve all instances of passive constructions (in Spanish, English, and German) in the COVALT corpus. </p>
illegal gambling cases, searching from Chinese Judgement Online (裁判文书网)
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Searching result of VenueT in Chinese Rednote
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Leveraging Search-Based and Pre-Trained Code Language Models for Automated Program Repair
<p>This page serves as supplementary material for the article: <strong>Leveraging Search-Based and Pre-Trained Code Language Models for Automated Program Repair</strong>. Here, we provide the ARJACLM code utilized in the study, enabling other researchers to replicate the experiments and further develop the tool. </p>
Screencast of the Lokahi2 Prototype: Search Engine with Interactive Knowledge Network Browser Extracted from Text
<p>This video shows a recording of the prototype system Lokahi2. It supports concept surfing for interacting with the search engine, automated document tagging, exploring tags, generating tags for text, and changing depth and dimension of the graph.</p>
Searching for the causes of decline in the Dutch population of turtle doves Streptopelia turtur
<p>European Turtle Doves <i>Streptopelia turtur</i> have experienced a sharp decline in population numbers over past decades. Much uncertainty exists about the main cause or causes. Several pressures have been suggested, but because they affect different stages of the life cycle of the Turtle Dove, it is difficult to compare their contributions to population decline. Here we applied a full life cycle approach to study how different pressures may have resulted in the decline. This was achieved by combining a review of existing literature on possible threats, pressures, and the vital rates they concerned, with the analysis of an age-structured matrix model. The population model was parameterized using estimates from a mark-recapture analysis and supplemented with vital rate estimates from the literature. Comparison with a Life Table Response Experiment (LTRE) was used to determine whether the Turtle Dove literature focusses on those vital rates in which the most important changes have taken place over time. The population model projected a similar decline to that observed in population counts. The LTRE analysis showed that declines in the number of clutches (halved since the 1960s) and in juvenile survival (relative annual rate of change of -1.33% since the 1950s) contributed most to the decline in the projected population growth rate. Although these vital rates are often reported as possible causes of population decline, the reviewed studies often focused on specific reproductive stages, such as egg survival or nestling survival, which did not show a large temporal change. Thus, there is a partial mismatch between our modelling results and the focus in the literature. Juvenile survival is thought to be affected by hunting, degradation of wintering habitat and infection with <i>Trichomonas gallinae</i>, while loss of foraging habitat seems to affect the number of clutches. The focus of conservation measures should therefore be on these threats and pressures. The first steps have already been taken with completion of the international single species action plan for the conservation of the Turtle Dove and the implementation of the first conservation measures on the breeding grounds.</p>
Data from: Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers
<p>Visual search is a work-horse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified "feature columns" which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4's superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.</p>
Datasets from the publication "Delineating the geographic context of physical activities: A systematic search and scoping review of the methodological approaches used in social ecological research over two decades"
<p>Data from research article Rinne, T., Kajosaari, A., Söderholm, M., Berg, B., Pesola, A.J., Smith, M., Kyttä, M. (2022). Delineating the geographic context of physical activities: A systematic search and scoping review of the methodological approaches used in social ecological research over two decades, <em>Health and Place</em>.</p> <p>This data includes supplementary materials 1, 2, 3 and 4, PRISMA checklist and a translated research protocol.</p>
Data collected from user evaluation of dataset search using similarity methods
<p>The data in this dataset was collected from a user evaluation of dataset search using similarity methods in data catalogs. It is linked to the dataset metadata in the data catalog used for the evaluation, which is available in https://doi.org/10.5281/zenodo.4433464.</p>
Ground truths for dataset search using similarity methods generated from a user evaluation
<p>The dataset contains ground truths for 6 different use cases and 10 levels of agreement among 10 users participating in a user evaluation of dataset search using similarity methods in data catalogs. The data contains collections linking to dataset metadata available in https://doi.org/10.5281/zenodo.4433464.</p>
A comparison of citation sources for reference and citations based search in systematic literature reviews
<p>Context: In software engineering, snowball sampling has been used as a supplementary and primary search strategy. The current guidelines recommend the use of Google Scholar (GS) for snowball sampling. However, the use of GS presents several challenges when using it as a source for citations and references.</p> <p>Objective: To compare the effectiveness and usefulness of two leading citation databases (GS and Scopus) for use in snowball sampling search.Method: We relied on a published study that has used snowball sampling as a search strategy and GS as the citation source. We used its primary studies to compute precision and recall for Scopus.</p> <p>Results: In this particular case, Scopus was highly effective with 95% recall and had better precision of 5.1%compared to GS’s 2.8%. On average, one would read 15 extra papers in GS than Scopus to identify an additional relevant paper. Moreover, Scopus supports batch downloading of both citations to a paper and the papers’ references, has better quality metadata, and does better source filtering.</p> <p>Conclusion: This study suggests that Scopus seems to be more effective and useful for snowball sampling than GS for systematic secondary studies attempting to identify peer-reviewed literature.</p>
High time resolution search for prompt radio emission from the long GRB 210419A with the Murchison Widefield Array
<p>The time series of Stokes parameters in the PSRFITS format formed from the MWA data at the position of GRB 210419A.</p>
Online Supplement: Search-based Diverse Sampling from Real-world Software Product Lines
<p>This is the online supplement for the following paper: Yi Xiang, Han Huang, Yuren Zhou, Sizhe Li, Chuan Luo, Qingwei Lin, Miqing Li, and Xiaowei Yang. 2022. Search-based Diverse Sampling from Real-world Software Product Lines. In 44th International Conference on Software Engineering (ICSE’22), May 21-29, 2022, Pittsburgh, PA, USA. ACM, New York, NY, USA, 13 pages. https://doi.org/10.1145/3510003.3510053</p>
In search of an honest butterfly: Sexually selected wing coloration and reproductive traits from wild populations of the Cabbage White Butterfly
Abstract <p></p><p>Sexual selection is central to many theories on mate selection and individual behavior. Relatively little is known, however, about the impacts that human-induced rapid environmental change are having on secondary sexually selected characteristics. Honest signals function as an indicator of mate quality when there are differences in nutrient acquisition and are thus potentially sensitive to anthropogenically altered nutrient inputs. We used the cabbage white butterfly, Pieris rapae (L.) (Lepidoptera: Pieridae), to investigate differences in color and testes size in a system that is often exposed to agricultural landscapes with nitrogen addition. We collected individuals from four sites in California and Nevada to investigate variation in key traits and the possibility that any relationship between wing color and a reproductive trait (testes size) could vary among locations in the focal butterfly. Coloration variables and testes size were positively albeit weakly associated across sites, consistent with the hypothesis that females could use nitrogen-based coloration in the cabbage white as an indicator for a male mating trait that has the potential to confer elevated mating success in progeny. However, variation in testes size and in the relationship between testes size and wing color suggest complexities that need exploration, including the possibility that the signal is not of equal value in all populations. Thus these results advance our understanding of complex relationships among environmental change and sexual selection in the wild.</p><p></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.