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2,371 results for “rights”
ALL-READY Questionnare on potential drivers and barriers to the adoption of innovation management, open science, and Intellectual Property Rights (IPR) among the members of the Pilot Network
<p><strong>Background & Summary</strong>: </p><p>The ALL-READY project unites a diverse consortium of Research Infrastructures (RI) and Living Labs, instrumental in developing new methodologies and technologies in agroecology. The project focuses on effective management of innovation, adherence to open science principles, and strategic application of Intellectual Property Rights (IPR). Task 6.4 of the project, which concentrates on Innovation and IPR Management, seeks to understand the dynamics influencing the adoption of these practices among its members. Recognizing the need for end-to-end data management, the project emphasizes standardized data collection and management while adhering to FAIR principles.</p><p><strong>Methods</strong>: </p><p>The questionnaire was developed by LifeWatch ERIC to capture data reflecting current practices and perceptions in agroecology. It included 26 questions divided into four sections, focusing on existing practices, potential drivers, and barriers in innovation management, open science, and IPR. The survey was disseminated via an online platform to the ALLREADY Pilot Network, ensuring a representative sample from diverse organizations. The data collection process was closely monitored, and the responses were analyzed using a mixed-methods approach to extract meaningful insights.</p><p><strong>Data Records of the ALLREADY Project Questionnaire</strong>: </p><p>The dataset, collected through an online survey platform, underwent a meticulous process of data preparation, download, formatting, and anonymization. It consists of one text file containing metadata (Readme.txt) and a single CSV file encompassing all questionnaire responses. The dataset provides a comprehensive view of innovation management, open science adoption, and IPR handling within the agroecology sector, particularly among the network of RIs and Living Labs involved in the project.</p><p><strong>Technical Validation of the ALLREADY Project Questionnaire</strong>: </p><p>Several critical steps were taken to ensure the accuracy, reliability, and overall quality of the data collected. This included development and testing of the questionnaire, rigorous monitoring of the data collection process, and thorough checks for data quality and completeness. The representativeness of the sample was analyzed specifically with respect to the Pilot Network rather than the broader population involved in agroecology. Strategies were employed to counter survey fatigue and maintain respondent engagement.</p><p><strong>Usage Notes for the ALLREADY Project Questionnaire</strong>: </p><p>The dataset's proper usage is vital for ensuring the validity and reproducibility of research. Researchers are advised to consider the nature of the data, the representativeness of the dataset, and its generalizability. The dataset allows for comprehensive analysis and integration of different sections, and analysts have the flexibility to handle open and write-in responses according to their research needs. Additional information to facilitate analysis is provided in a separate documentation file.</p><p> </p>
FAIR Data: just data done right
<p>An aphorism about FAIR Data, in graphical form, inspired by "Sticker open science: just science done right": Melanie Imming, & Jon Tennant. (2018). Sticker open science: just science done right (ENG). Zenodo. https://doi.org/10.5281/zenodo.1285575 <br> <br> . </p> <p> </p>
RIGHTS UP - Photographs from the RIGHTS UP project (2018-2020) [Visual data]
<p>This visual data was collected as part of the project RIGHTS UP with the objective of exploring the emergence of social movements critical of mass tourism in Venice, Amsterdam and Barcelona. These images include diverse 'protests' against mass tourism in the aforementioned cities, as well as photographs of tourists at these 'travel destinations'. The images were produced with ethical and privacy concerns as a priority. The attached table provides detail on each individual file, with a short description of the image, the city where it was captured, and the date.</p> <p>The unedited images are in .JPG format and all of them were produced with a Nikon D90 camera. The raw files of these images could be requested to the author, when necessary.</p>
Choice of the right supporting electrolyte in electrochemical reductions: a principal component analysis
<h2>Introduction</h2> <p>This dataset contains the raw data as well as an HTML-based visualization of our dataset using Python Bokeh. We have also added a feature to highlight commercially available supporting electrolytes. The data is taken from the PubChem database. For each of the 6650 cations, the known neutral compounds in the PubChem dataset were identified with their corresponding anions. For each of these compounds, the vendor information stored in PubChem was queried.</p> <h2>Directory structure</h2> <ul> <li>Raw Data <ul> <li>[<a href="../records/10813969/files/raw_data.tar.xz?download=1" target="_blank" rel="noopener">raw_data.tar.xz</a>] Compressed directory with the output from the automated feature calculation.</li> <li>[<a href="../records/10813969/files/raw_data.csv?download=1" target="_blank" rel="noopener">raw_data.csv</a>] CSV file with the values of the calculated properties of all cations.</li> </ul> </li> <li>Visualization <ul> <li>[<a href="../records/10813969/files/pca_qac_tool_QC.html?download=1" target="_blank" rel="noopener">pca_qac_tool_QC.html</a>] HTML page with Javascript to display PC1 and PC2 for the quantum chemical PCA model.</li> <li>[<a href="../records/10813969/files/pca_qac_tool_RDKit.html?download=1" target="_blank" rel="noopener">pca_qac_tool_RDKit.html</a>] HTML page with Javascript to display PC1 and PC2 for the PCA model based on non empirical RDKit descriptors.</li> </ul> </li> <li>Tools <ul> <li>[<a href="../records/10813969/files/pca_qac_tool.py?download=1" target="_blank" rel="noopener">pca_qac_tool.py</a>] Python script to generate the HTML output using Bokeh. Depends on the data_pca_qac.csv and the data_commercial.json file.</li> <li>[<a href="../records/10813969/files/PubChem_get_Vendor_information.py?download=1" target="_blank" rel="noopener">PubChem_get_Vendor_information.py</a>] Crawler that checks a list of PubChem CIDs for net-neutral compounds and whether they are commercially available.</li> <li>[<a href="../records/10813969/files/RDKit_Descriptor-2D.py?download=1" target="_blank" rel="noopener">RDKit_Descriptor-2D.py</a>] Python script to calculate all available 2D RDkit descriptors based on a list of SMILES strings.</li> <li>[<a href="../records/10813969/files/RDKit_Descriptor-3D.py?download=1" target="_blank" rel="noopener">RDKit_Descriptor-3D.py</a>] Python script to calculate the RDKit 3D descriptors based on the CREST and ORCA GeoOpt geometries.</li> </ul> </li> </ul>
Frauen* im Fokus. Transcriptions and full texts of letters and works of women's rights activists
<p>In winter 2023/24 the Berlin State Library and Potsdam University (chair for Comparative Literature) organized the citizen science workshop <a href="https://lab.sbb.berlin/events/frauen-im-fokus/">"Frauen* im Fokus"</a> (women* in focus).</p> <p>Within the project 48 participants transcribed 85 letters and documents by 19th- and early 20th-century women's rights activists held in the collections of the State Library. The transcriptions provided by the participants were aligned with the digital images of the items using the <a href="https://ocr-bw.bib.uni-mannheim.de/escriptorium/" target="_blank" rel="noopener">eScriptorium</a> platform and software and checked for potential errors. From eScriptorium, the transcriptions were exported as ALTO and PAGE files. From the PAGE files, TEI/XML files were created with added metadata about the correspondence (where applicable).</p> <p>In addition to these MS sources, 55 printed works of the same activists were OCRed and are included in the dataset as PAGE and ALTO-files; these files were not manually checked for quality.</p> <p>We would like to thank our trainees Lilly Bucksteeg and Lilly Welz for their valuable contribution to the creation of the data set.</p> <p>The data set consists of five zip-files containing:</p> <ul> <li>the print sources in PAGE format</li> <li>the print sources in ALTO format</li> <li>the manuscript sources in PAGE format</li> <li>the manuscript sources in ALTO format</li> <li>the manuscript sources in TEI format</li> </ul> <p>------------------</p> <p>Im Wintersemester 2023/24 führten die Staatsbibliothek zu Berlin und die Universität Potsdam (Professur für Allgemeine und Vergleichende Literaturwissenschaft) das <a href="https://lab.sbb.berlin/events/frauen-im-fokus/">Projekt "Frauen* im Fokus"</a> durch.</p> <p>Im Rahmen des Projekts transkribierten 48 Personen 85 Briefe und andere Nachlassdokumente von Frauenrechtlerinnen des 19. und frühen 20. Jahrhunderts. Das Organisationsteam nahm auf der Plattform <a href="https://ocr-bw.bib.uni-mannheim.de/escriptorium/" target="_blank" rel="noopener">eScriptorium</a> eine teilweise automatisierte Layoutanalyse und Zeilensegmentierung der Digitalisate vor und fügte nach erfolgter inhaltlicher Qualitätskontrolle die von den Teilnehmenden erstellten Transkriptionen dort ein, um sie dann als PAGE- und ALTO-Dateien zu exportieren; zusätzlich wurden aus den PAGE-Dateien TEI-Dateien der einzelnen Dokumente generiert, die (wo passend) mit Brief-Metadaten zu Absendern, Empfängern und Orten angereichert wurden.</p> <p>Im Rahmen des Projekts wurden zudem 55 Druckwerke der Frauenrechtlerinnen aus dem Bestand der Staatsbibliothek als Volltexte erschlossen. Die Segmentierung und Volltexterkennung der Druckwerke erfolgte automatisch in eScriptorium ohne zusätzliche manuelle Qualitätskontrolle. Die Daten liegen exportiert in den Formaten PAGE und ALTO vor.</p> <p>Besonderer Dank gebührt Lilly Bucksteeg und Lilly Welz, die als Praktiantinnen im Projekt maßgeblich zur Erstellung des Datensets beigetragen haben.</p> <p>Das Datenset besteht aus fünf zip-Dateien die folgende Dateien enthalten:</p> <ul> <li>die gedruckten Werke im PAGE-Format</li> <li>die gedruckten Werke im ALTO-Format</li> <li>die Manuskript-Transkriptionen im PAGE-Format</li> <li>die Manuskript-Transkriptionen im ALTO-Format</li> <li>die Manuskript-Transkriptionen im TEI-Format</li> </ul>
Universal Declaration of Human Rights, Volume 02
<p>Ανάγνωση για το LibriVox, στην Ελληνική γλώσσα για το έργο, 42 <a href="http://librivox.org/">LibriVox</a> recordings of The Universal Declaration of Human Rights in 39 languages.</p> <p>Ακολουθεί η περιγραφή του έργου από τον ιστότοπο του Internet Archive<br> The Universal Declaration of Human Rights (UDHR) is a declaration adopted by the United Nations General Assembly (10 December 1948 at Palais de Chaillot, Paris). The Guinness Book of Records describes the UDHR as the "Most Translated Document" in the world. It consists of 30 articles which outline the view of the General Assembly on the human rights guaranteed to all people.(Summary adapted from Wikipedia)<br> <br> This second Librivox collection contains 42 readings of this declaration, recorded by 35 volunteers in 39 different languages - to mark its 60th anniversary.<br> <br> In combination with <a href="http://librivox.org/the-universal-declaration-of-human-rights-by-the-united-nations/">an earlier Librivox collection</a> this brings the total number of languages of Librivox readings of the Universal Declaration of Human Rights to 53.<br> <br> For further information, including links to online text, reader information, RSS feeds, CD cover or other formats (if available), please go to the <a href="http://librivox.org/universal-declaration-of-human-rights-by-united-nations-volume-02/">LibriVox catalog page</a> for this recording.<br> <br> For more free audio books (in more than 25 languages) or to become a volunteer reader, visit <a href="http://librivox.org/">LibriVox.org</a>.<br> <br> <a href="https://archive.org/download/human_rights_02_0908_librivox/multiuniversalDeclarationOfHumanRightsVol02a_librivox.m4b">M4B audio book, part 1 (162MB)</a><br> <a href="https://archive.org/download/human_rights_02_0908_librivox/multiuniversalDeclarationOfHumanRightsVol02b_librivox.m4b">M4B audio book, part 2 (162MB)</a></p> <p>Boxid OL100020511</p> <p>Identifier human_rights_02_0908_librivox</p> <p>Run time 11:51:17</p> <p>Source <a href="https://archive.org/search.php?query=source%3A%22Librivox+recording+of+a+public-domain+text%22">Librivox recording of a public-domain text</a></p> <p>Taped by <a href="https://archive.org/search.php?query=taper%3A%22LibriVox%22">LibriVox</a></p> <p>Year <a href="https://archive.org/search.php?query=year%3A%222009%22">2009</a></p>
A right whale (Mysticeti, Balaenidae) from the Pleistocene of Taiwan
<p>Abstract</p> <p>Current patterns of biological distribution result from the deep past. Of particular interest, some closely related species appear at high latitudes of both hemispheres, but not in between, a pattern known as antitropical distribution. However, the timing, pathway, and drivers of antitropical distributions remain mostly unknown. Here we describe a new fossil, a left tympanic bulla (part of the ear bones), from the Middle/Late Pleistocene (0.78–0.01 mya, but not excluding the possibility of Holocene in age, as the specimen was dredged from the sea bottom and the geological horizon remains uncertain) of Taiwan. The tympanic bulla is diagnostic in baleen whales, and this specimen shows morphological features that are identical to extant <em>Eubalaena</em>, including: relatively large size (the anteroposterior length is 117 mm); rectangular outline in medial view; short anterior lobe, judging from the remaining of the lateral furrow; squared anterior margin; prominent transverse crease on the involucrum; transversely compressed in anterior view; well-developed and rounded outer lip; and parallel involucral and main ridges. Although incomplete, the morphological characters and overall similarity to extant <em>Eubalaena</em> allow a reliable taxonomic assignment to <em>Eubalaena</em> sp. The occurrence of a Pleistocene <em>Eubalaena</em> on the southern margin of the western North Pacific is the first balaenid fossil evidence indicative of the biotic interchange between two hemispheres leading to the origin of antitropical distribution in the Pleistocene; alternatively, this specimen might merely represent an extra-limital record of the North Pacific <em>Eubalaena</em>. Furthermore, this find suggests that the <em>Eubalaena</em> interchange, being one of the largest species displaying antitropical distribution pairs in the history of life, likely took place along the western Pacific. Notably, this does not preclude the <em>Eubalaena</em> interchange from other routes, such as the eastern Pacific or the Atlantic Ocean, and future finds should test the scenario for the biotic interchange between Northern and Southern Hemispheres of <em>Eubalaena</em>.</p>
MIGR-TWIT Corpus. Migration Tweets of right and far-right politics in Europe
<p><strong>Description</strong></p> <p>The <strong>MIGR-TWIT Corpus</strong> is a multilingual corpus of tweets about the topic of migration in Europe. Within the framework of the collaborative research project OLiNDiNUM (Observatoire LINguistique du DIscours NUMérique, Linguistic Observatory of Online Debate) the MIGR-TWIT Corpus is created with the aim of developing language databases of online debate. Considering the global issue of migration in line with British and French political contexts of last dozen years from 2011 to 2022, the corpus consists of two sub-corpora: </p> <ul> <li> <p><strong>FR-R-MIGR-TWIT-2011-2022 Corpus </strong>for French language data (1 January 2011 - 30 June 2022) and </p> </li> <li> <p><strong>UK-R-MIGR-RA-TWIT-2012-2022 Corpus </strong>for English language data (1 January 2012 - 5 September 2022) <strong> </strong></p> </li> </ul> <p>Using the Twitter API v2 Academic Research, tweets containing at least one occurrence of migration or refugee related words are retrieved automatically from 28 right and far-right political figures and parties. The whole corpus contains 18,233 tweets and 533,198 words. </p> <p><strong>Scientific reference:</strong></p> <p>Pietrandrea, P., Battaglia, E. (2022). “Migrants and the EU”. The diachronic construction of ad hoc categories in French far-right discourse. Journal of Pragmatics 192, 139-157.</p> <p>Blandino, G. (2023). <em>10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter</em>, MA University of Wolverhampton</p> <p>Jeon, S. (2025). Le discours numérique sur l'immigration en France entre 2011 et 2022. Une analyse de corpus (Online Discourse on Immigration in France between 2011 and 2022. A Corpus Analysis), PhD Thesis, Université de Lille, France.</p> <p><strong>Contents</strong></p> <p>The whole corpus contains two CSV Zip files (tabular format) corresponding to each sub-corpus. The complete corpus is presented in two versions, one version with the tweet identifier (<strong><em>data__id</em></strong>) and the text of the tweet (<strong><em>data__text</em></strong>) as a header (folders named <em>FR-R-MIGR-TWIT-2011-2022_textonly</em> and <em>UK-R-MIGR-RA-TWIT-2012-2022_textonly</em>, respectively composed of 12 and 11 Zip files of every single year), and the other version with all tweet fields information included as a header, such as the posting date (<em><strong>data__created__at</strong></em>), the username (<strong><em>author__name</em></strong>), the number of retweets (<em><strong>data__public_metrics__retweet_count</strong></em>), etc., with two folders named <em>FR-R-MIGR-TWIT-2011-2022_meta</em> and <em>UK-R-MIGR-RA-TWIT-2012-2022_meta</em>. Detailed information for each sub-corpus is illustrated below.</p> <p><strong>1. FR-R-MIGR-TWIT-2011-2022 </strong></p> <ul> <li><strong>Created at: </strong>2022-08-08</li> <li> <p><strong>Language: </strong>FR<strong> </strong></p> </li> <li> <p><strong>Coverage: </strong>16 user accounts; 11,761 tweets; 358,491 words</p> </li> <li> <p><strong>Time of data collection: </strong>start=2011-01-01; end=2022-06-30 </p> </li> <li> <p><strong>Keywords: </strong>words derived from a latin root “<em><strong>migr</strong></em>” of <em>migrare</em></p> </li> <li> <p><strong>Corpus composition: </strong></p> </li> </ul> <table> <tbody> <tr> <th> </th> <th>Political figure/party</th> <th>Username</th> <th>Tweets</th> <th>Year concerned</th> </tr> <tr> <th>1</th> <td>Michel Barnier</td> <td>@MichelBarnier</td> <td>31</td> <td>2017-22</td> </tr> <tr> <th>2</th> <td>Valérie Pécresse</td> <td>@vpecresse</td> <td>81</td> <td>2017-22</td> </tr> <tr> <th>3</th> <td>Rassemblement National</td> <td>@RNational_off</td> <td>3,347</td> <td>2017-22</td> </tr> <tr> <th>4</th> <td>Nicolas Dupont-aignan</td> <td>@dupontaignan</td> <td>663</td> <td>2011-22</td> </tr> <tr> <th>5</th> <td>Éric Ciotti</td> <td>@ECiotti</td> <td>1,007</td> <td>2012-22</td> </tr> <tr> <th>6</th> <td>Christian Estrosi</td> <td>@cestrosi</td> <td>137</td> <td>2011-22</td> </tr> <tr> <th>7</th> <td>Marine Le Pen</td> <td>@MLP_officiel</td> <td>1,650</td> <td>2011-22</td> </tr> <tr> <th>8</th> <td>Valérie Boyer</td> <td>@valerieboyer13</td> <td>837</td> <td>2012-22</td> </tr> <tr> <th>9</th> <td>Florian Philippot</td> <td>@f_philippot</td> <td>485</td> <td>2012-22</td> </tr> <tr> <th>10</th> <td>Xavier Bertrand</td> <td>@xavierbertrand</td> <td>70</td> <td>2017-22</td> </tr> <tr> <th>11</th> <td>Marion Maréchal</td> <td>@MarionMarechal</td> <td>479</td> <td>2012-17,19-22</td> </tr> <tr> <th>12</th> <td>Philippe Meunier</td> <td>@Meunier_Ph</td> <td>245</td> <td>2013-22</td> </tr> <tr> <th>13</th> <td>Jordan Bardella</td> <td>@J_Bardella</td> <td>1,095</td> <td>2013-22</td> </tr> <tr> <th>14</th> <td>Nicolas Bay</td> <td>@NicolasBay_</td> <td>1,260</td> <td>2017-22</td> </tr> <tr> <th>15</th> <td>Emmanuel Macron</td> <td>@EmmanuelMacron</td> <td>72</td> <td>2017-22</td> </tr> <tr> <th>16</th> <td>Éric Zemmour</td> <td>@ZemmourEric</td> <td>302</td> <td>2019-22</td> </tr> <tr> <th>17</th> <td>Jean Messiha*</td> <td>Banned from Twitter (since July 2021)</td> <td>-</td> <td>-</td> </tr> </tbody> </table> <ul> <li>Political figures and parties of table above are listed in chronological order according to the dates on which they posted their first tweet.</li> <li> <p><strong>*</strong>Before the launching of Twitter API v2 Academic Research, migr-tweets were collected from the database of Europresse.com including 1,453 tweets of Jean Messiha as part of the reference study (Pietrandrea & Battaglia 2022). However, the Twitter account in question has been permanently banned since July 2021. For our data collection using the Twitter API started in September 2021, we could not access this account. Therefore, we decided not to include his tweets in the FR-R-MIGR-TWIT-2011-2022 for the sake of consistency with the rest of twitter data that are automatically retrieved.</p> </li> <li> <p>The sub-corpus FR-R-MIGR-TWIT-2017-2022 is developed, annotated and analyzed as part of a doctoral thesis in progress (<a href="https://theses.fr/s360032">Jeon, 2025</a>) with the aim of studying the semantic construction of migr-lexicon over the period between 2011 and 2022. </p> </li> </ul> <p><strong> </strong></p> <p><strong>2. UK-R-MIGR-RA-TWIT-2012-2022 </strong></p> <ul> <li> <p><strong>Created at: </strong>2022-09-06</p> </li> <li> <p><strong>Language: </strong>EN</p> </li> <li> <p><strong>Coverage: </strong>12 user accounts; 6,472 tweets; 174,707 words </p> </li> <li> <p><strong>Time of data collection: </strong>start=2012-01-01; end=2022-09-05</p> </li> <li> <p><strong>Keywords: </strong>words derived from a latin root “<strong><em>migr</em></strong>” of <em>migrare </em>in addition to the keywords “<strong><em>refugee</em></strong>(<strong><em>s</em></strong>)” and “<strong><em>asylum</em></strong>”.</p> </li> <li> <p><strong>Corpus composition:</strong></p> </li> </ul> <table> <tbody> <tr> <th> </th> <th>Political figure/party</th> <th>Username</th> <th>Tweets</th> <th>Year concerned</th> </tr> </tbody> <tbody> <tr> <th>1</th> <td>David Cameron</td> <td>@David_Cameron</td> <td>32</td> <td>2012-22</td> </tr> <tr> <th>2</th> <td>Amber Rudd</td> <td>@AmberRuddUK</td> <td>29</td> <td>2012-22</td> </tr> <tr> <th>3</th> <td>Sajid Javid</td> <td>@sajidjavid</td> <td>84</td> <td>2012-22</td> </tr> <tr> <th>4</th> <td>Boris johnson</td> <td>@BorisJohnson</td> <td>80</td> <td>2015-22</td> </tr> <tr> <th>5</th> <td>Priti Patel</td> <td>@pritipatel</td> <td>304</td> <td>2012-22</td> </tr> <tr> <th>6</th> <td>UK Home Office</td> <td>@ukhomeoffice</td> <td>909</td> <td>2012-22</td> </tr> <tr> <th>7</th> <td>Nigel Farage</td> <td>@Nigel_Farage</td> <td>1,010</td> <td>2012-22</td> </tr> <tr> <th>8</th> <td>Richard Tice</td> <td>@TiceRichard</td> <td>180</td> <td>2013-22</td> </tr> <tr> <th>9</th> <td>UKIP</td> <td>@UKIP</td> <td>2,746</td> <td>2012-22</td> </tr> <tr> <th>10</th> <td>Neil Hamilton</td> <td>@NeilUKIP</td> <td>252</td> <td>2013-22</td> </tr> <tr> <th>11</th> <td>Nick Griffin</td> <td>@NickGriffinBU</td> <td>542</td> <td>2012-22</td> </tr> <tr> <th>12</th> <td>Robin Tilbrook</td> <td>@RobinTilbrook</td> <td>304</td> <td>2012-22</td> </tr> </tbody> </table> <p> </p> <ul> <li> <p>2 out of 12 accounts are official accounts belonging to the” UK Home Office” department and the “UKIP” (United Kingdom Independence Party) party. 10 out of 12 accounts are political figures’ accounts.</p> </li> <li> <p>The corpus UK-R-MIGR-RA-TWIT-2012-2022 will be exploited for the following master’s thesis: Blandino, G. (2023). <em>10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter</em>, MA University of Wolverhampton.</p> </li> </ul> <p> </p>
Evolution of left-right asymmetry in the sensory system and foraging behavior during adaptation to food-sparse cave environments
<p>Laterality in relation to behavior and sensory systems is found commonly in a variety of animal taxa. Despite the advantages conferred by laterality (e.g., the startle response and complex motor activities), little is known about the evolution of laterality and its plasticity in response to ecological demands. In the present study, a comparative study model, the Mexican tetra (<em>Astyanax mexicanus</em>), composed of two morphotypes, i.e., riverine surface fish and cave-dwelling cavefish, was used to address the relationship between environment and laterality. The use of a machine learning-based fish posture detection system and sensory ablation revealed that the left cranial lateral line significantly supports one type of foraging behavior, i.e., vibration attraction behavior, in one cave population. Additionally, left-right asymmetric approaches toward a vibrating rod became symmetrical after fasting in one cave population but not in the other populations. Based on these findings, we propose a model explaining how the observed sensory laterality and behavioral shift could help adaptation in terms of the tradeoff in energy gain and loss during foraging according to differences in food availability among caves.</p> <p>This repository contains all of raw videos used in this study.</p> <p>Please let us know if you have any question on these videos</p>
Finding the right XAI Method --- Dataset
<p>This dataset provides the complementary preprocessed data for the training of the neural networks used in Bommer et. al. and according source code (<a href="https://github.com/philine-bommer/Climate_X_Quantus">https://github.com/philine-bommer/Climate_X_Quantus</a>). In the publication , we introduce XAI evaluation in the context of climate research and assess different desired explanation properties, namely, robustness, faithfulness, randomization, complexity, and localization. To this end we build upon previous work (Labe and Barnes et. al. 2021) and<br> train a multi-layer perceptron (MLP) and a convolutional neural network (CNN) to predict the decade based on annual-mean temperature maps.</p> <p>Following Labe and Barnes et. al. 2021, we use data simulated by the general climate model, CESM1 (Hurrell et. al. 2013). We use the global 2-m air temperature (T2m) temperature maps from 1920 to 2080. The data consist of 40 ensemble members and each member is generated by varying the atmospheric initial conditions with fixed external forcing, i.e. historical forcings are imposed from 1920 to 2005 and Representative Concentration Pathways 8.5 for the following years (Kay et. al. 2015).<br> Following Labe and Barnes et. al. 2021, we compute annual averages and apply a bilinear interpolation. This results in T=161 temperature maps for each member, with v=144 longitude grid cells and h=95 latitude grid cells, given the 1.9° sampling in latitude and 2.5° sampling in longitude. The temperature maps are finally standardized by removing the multi-year (1920 to 2080) mean and subsequently dividing by the corresponding standard deviation.</p> <p>Unlike the flattened input used for the MLP (temperature maps are flattened into a vector), the CNN maintains the longitude-latitude grid of the temperature maps. Similar to Labe and Barnes et. al. 2021, for training, validation and testing we use the model data discussed above. For both MLP and CNN we consider 20% of the data as test set and the remaining 80% is split into a training (64%) and validation (16%) set. We train both networks to solve a fuzzy classification problem which combines classification and regression. In the classification setting, the network assigns each map to one of the 20 different classes, where each class corresponds to one decade between 1900 and 2100 (necessary class devision for later regression, as done by Labe and Barnes et. al. 2021). The network output thus, is a probability vector containing a probability for each class.</p> <p>To assess the network performance we use the monthly 2m air temperature of the 20th century Reanalysis data (V3) (Slivinski et. al. 2019) from 1920 to 2015.</p> <p>The dataset includes two compressed .npz-files and a Readme.md. A full description of the data contained in this dataset and instructions on the data usage are provided in the Readme-file. </p>
Japanese Expressions Dataset from Human Rights Infringement on Internet
<p>Japanese Expressions Dataset from Human Rights Infringement on Internet</p> <p>これは、言語処理学会2023において”<a href="https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/D2-2.pdf"><strong>権利侵害と不快さの間:日本語人権侵害表現データセット</strong></a>”の発表で用いた、誹謗中傷等の表現を集めたデータセットです。</p> <p>仕様は変更される可能性があります</p> <p>Release Date</p> <p>Version 0.1 2023/03/09</p> <p>Version 0.2 2023/06/01</p> <p> </p> <p>1.調査対象</p> <p>民事事件</p> <ul> <li>発信者情報開示請求事件</li> <li>損害賠償等請求事件</li> </ul> <p>インターネット上の投稿による人権侵害を争った事件よりこのデータセットは作成されています。</p> <p>Annotation Scheme</p> <p>1: Text in Dispute </p> <p>Text in Dispute is transcribed from the list of articles submitted or the facts and reasons section of the court cases.<br> This text is what the plaintiff alleges is infringing his or her rights.<br> <br> For example, we use the tag [Plaintiff] for descriptions related to plaintiffs, the tag [Defandant] for descriptions related to defandantss and [Third Party] for any mention of third parties.<br> The tag [Other] is designated for texts involving anonymized place names and any other content not covered by the preceding tags. <br> If distinguishing between tags proves challenging, we advise the use of [Other]. <br> Should a URL be present in the text, it is substituted with the [URL] tag.</p> <p>2: Context Utilized in Adjudication</p> <p>In some cases, the history of the conversation and previous postings are taken into account in determining whether or not an infringement has occurred.<br> Such text is transcribed from the fact-finding and judgment portions of the court case.<br> Contextual information that can be used for tasks other than proper understanding of the issue and accurate learning and classification.<br> Anonymization is applied in the same way as for [1: Text in Dispute].</p> <p>3: Allegedly Infringed Right and Judgement on the Infringement Allegation</p> <p>This category provides a label indicating the types of personal rights infringement complained of by the plaintiff against Text in Dispute and whether or not the infringement of that right was recognized by the trial court.<br> If there are more than two types of infringement of rights complained of by the plaintiff against one text, up to two labels are given.</p> <p>3-1a: The types of Allegedly Infringed Right 1</p> <p>Labels are assigned from the above types of personal rights, the right of reputation, the sense of honor, the right of peaceful private life, and other personal rights, from the complaint of infringement of rights by the plaintiff.</p> <p>3-1b: Judgement on the Infringement Allegation 1</p> <p>This category indicates whether the trial court granted the plaintiff's complaint against the text under consideration.<br> The annotator reads the result of the Judgement for each case from the court's judgment in the case.<br> If we find that the court has admitted the plaintiff's claim, we assign "1" label to the case concerning the infringement of personal rights.<br> If we find that the court has dismissed the plaintiff's claim, we assign "0" label to those cases that are not infringing.<br> We assign the label "UNJUDGE" to cases where we cannot find the court's Judgement. <br> This appears in cases where the plaintiff alleges multiple infringements and only one of the claims is adjudicated, or where the complaint is found to have been dismissed based on factors other than a determination of infringement by textual expression.</p> <p>3-2a & b:The types of Allegedly Infringed Right and Judgement on the Infringement Allegation 2</p> <p>If two infringements are complained of, the annotator assigns a label for the second right.</p> <p><br> 4: Index Information of Court Cases</p> <p>This section contains information about the cited court case.</p> <p>4-1: Case Number</p> <p>This is the case number of the court case and the court in which the case was argued.</p> <p>4-2: Case Name</p> <p>This is the case name of the court case and the court in which the case was argued.<br> Either a case requesting for disclosure of sender's information. or a case requesting compensation for damages is applicable.</p> <p>4-3: Bibliography</p> <p>This is the bibliography of the cited case.</p> <p>4-4: Article Number</p> <p>This is the number assigned to Text in Dispute in the court case.</p> <p>4-5: Online Platform</p> <p>If the online platform where Text in Dispute is explicitly indicated in the court case, it is stated.<br> Since the form of the text and context differs from platform to platform, considering the uniqueness of each service is an important factor to be taken into account.</p>
Pl. 15. — Structural characters of Malaysian species of Amphicnemis. 1 - 3. Male anal appendages, dorsal view and right side. 4. Right lateral view of prothorax . in Descriptions and records of South-East Asiatic Odonata (II)
Pl. 15. — Structural characters of Malaysian species of Amphicnemis. 1 - 3. Male anal appendages, dorsal view and right side. 4. Right lateral view of prothorax .
Text-fig. 5—Torosaurus utahensis (Gilmore) n. comb., TMM 41480-1, right parietal, a, dorsal view, b, ventral view. x 1/8. in Tyrannosaurus and Torosaurus, Maestrichtian Dinosaurs From Trans-Pecos, Texas
Text-fig. 5—Torosaurus utahensis (Gilmore) n. comb., TMM 41480-1, right parietal, a, dorsal view, b, ventral view. x 1/8.
Figure 50. Eosphaerophoria vietnamensis, male genitalia a left lateral view b right superior lobe, lateral view c right superior lobe, dorsal view d left superior lobe, dorsal view e tergite 9 in The flower fly genus Eosphaerophoria Frey (Diptera, Syrphidae)
Figure 50. Eosphaerophoria vietnamensis, male genitalia a left lateral view b right superior lobe, lateral view c right superior lobe, dorsal view d left superior lobe, dorsal view e tergite 9, cerci and surstyli, dorsal view.
Figure 49. Eosphaerophoria symmetrica, male genitalia a left lateral view b right superior lobe, dorsal view c tergite 9 in The flower fly genus Eosphaerophoria Frey (Diptera, Syrphidae)
Figure 49. Eosphaerophoria symmetrica, male genitalia a left lateral view b right superior lobe, dorsal view c tergite 9, cerci and surstyli, dorsal view.
Figure 46. Eosphaerophoria dentiscutellata, male genitalia a left lateral view b right superior lobe, lateral view c right superior lobe, dorsal view d left superior lobe, dorsal view e tergite 9 in The flower fly genus Eosphaerophoria Frey (Diptera, Syrphidae)
Figure 46. Eosphaerophoria dentiscutellata, male genitalia a left lateral view b right superior lobe, lateral view c right superior lobe, dorsal view d left superior lobe, dorsal view e tergite 9, cerci and surstyli, dorsal view.
Figure 22. Zehntnerobolus rubripes comb. n., A, C–G male lectotype, B female paratype, A telson B, C right midbody leg D anterior gonopod, anterior view E anterior gonopod, posterior view F left posterior gonopod, anterior view G in Review of the Spirobolida on Madagascar, with descriptions of twelve new genera, including three genera of 'fire millipedes' (Diplopoda)
Figure 22. Zehntnerobolus rubripes comb. n., A, C–G male lectotype, B female paratype, A telson B, C right midbody leg D anterior gonopod, anterior view E anterior gonopod, posterior view F left posterior gonopod, anterior view G left posterior gonopod, posterior view. Apo = apodeme; av = anal valves; Cx = coxite; Gr = groove; Pre = preanal ring; St = sternite; sub = subanal scale; T = telopodite; Tp = telopodite process. Scale bars = 1 mm.
Figures 19-22. D. shardana holotype, right male bulb 19 prolateral view, general 20 prolateral view, tip detail 21 anterior view 22 P in Systematics and phylogeography of the Dysdera erythrina species complex (Araneae, Dysderidae) in Sardinia
Figures 19-22. D. shardana holotype, right male bulb 19 prolateral view, general 20 prolateral view, tip detail 21 anterior view 22 P, prolateral view.
Top: puffs of cornstarch reveal dense and varied tiny cryptic webs in the Gaoligongshan. Shown here upper left to lower right are a symphytognathid Patu jidanweishi sp. n., a mysmenid Gaoligonga changya gen. n., sp. n., and an unidentified linyphiid. Bottom: this misty mountain landscape at QiQi is typical of the Gaoligongshan in The symphytognathoid spiders of the Gaoligongshan, Yunnan, China (Araneae: Araneoidea): Systematics and diversity of micro-orbweavers
Top: puffs of cornstarch reveal dense and varied tiny cryptic webs in the Gaoligongshan. Shown here upper left to lower right are a symphytognathid Patu jidanweishi sp. n., a mysmenid Gaoligonga changya gen. n., sp. n., and an unidentified linyphiid. Bottom: this misty mountain landscape at QiQi is typical of the Gaoligongshan
Fig. 5. Psammoecus grandis Grouvelle, 1908. A. Right antenna. B. Median lobe. C in Three new species and new records of African Psammoecus Latreille (Coleoptera, Silvanidae)
Fig. 5. Psammoecus grandis Grouvelle, 1908. A. Right antenna. B. Median lobe. C. Parameres. Scale lines = 0.5 mm.
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.