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1,970 results for “concepts”
A list of color, emotion, and human body part concepts
<p>The list includes 220 human body part, color, and emotion concepts. The concepts are based on the available concept sets in <a href="https://concepticon.clld.org/">Concepticon</a> (List et al. <a href="https://aclanthology.org/L16-1379/">2016</a>, <a href="https://doi.org/10.5281/zenodo.596412">2021</a>) and were tagged as <em>human body part </em>(136 concepts), <em>emotion </em>(62 concepts), or <em>color </em>(22 concepts).</p>
Corpus and list of keywords from Improving sustainable crop protection using population genetics concepts
<p>Corpus extracted in April 2021 from the ISI Web of Science portal (https://www.webofscience.com) with the following request: ‘Plant AND Resistan* AND Durab*’. A first corpus of 2522 articles was built considering all publication years for this extraction. This collection was then refined by categories to remove articles outwith the scope of our search (e.g. related to durable resistant materials for constructions). We also kept only articles cited at least once. The final corpus was composed of 1783 articles from 1979 to 2021:</p> <ul> <li>CORPUS_plant_resistance_durability.zip</li> </ul> <p>List of keywords used for the network presented in the article:</p> <ul> <li>keywords_list.csv</li> </ul>
Selective Oxidation of 5-Hydroxymethylfurfural to 2,5-Diformylfuran in Biphasic Media using Immobilized Galactose Oxidase: Proof of Concept and Limitations
<p>The oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF) is a key reaction in valorizing biomass. DFF is hardly soluble in water, while HMF is often obtained from biorefineries in crude wet organic fractions. Thus, the reaction is challenging for both biocatalysis performed in aqueous media, and for chemocatalysis where the presence of water often results in catalyst poisoning. Galactose oxidase (GalOx) can selectively oxidize HMF to DFF and displays promising activity in aqueous-organic media. In this study, GalOx was immobilized on ten carriers, assessing the immobilization yield, activity, and stability. Covalently immobilized GalOx catalyzed the oxidation of HMF to DFF in neat and water-saturated EtOAc, and in biphasic systems of various water contents. At 50 % v/v H<sub>2</sub>O, the reaction was conducted at a semi-preparative scale (50 mL) with no adverse effect on DFF yield. Some limitations arise, such as enzyme deactivation, and adsorption of DFF to the support, particularly in the aqueous fraction. Future options to upgrade the route may include designed stable enzymes under the presence of HMF/DFF, and the setup of microaqueous systems where DFF adsorption is minimized. The use of wet EtOAc media would be a promising approach in future biorefineries employing inexpensive crude wet organic fractions.</p>
Examining LGBTQ+-related Concepts in the Semantic Web: Link Discovery, Concept Drift, Ambiguity, and Multilingual Information Reuse
<div> <h1>Examining LGBTQ+-related Concepts in the Semantic Web</h1> </div> <div> <h2>Introduction</h2> </div> <p>Welcome to the project. We study the links between LGBTQ+ ontologies and structured vocabularies. More specifically, we focus on GSSO, Homosaurus, QLIT, and Wikidata. The code is free for use with the license GPL 3,0. You can resue/extend the code for free as long as you give credits to us in your publication/data. Citation information will be added after the corresponding paper gets accepted. The paper is under submission and will be included soon. </p> <p>If you would like to extend this work, you may want to contact the experts in the acknowledgement before releasing your data/code about legal and ethical issues. The DOI for this version is 10.5281/zenodo.12684870. The latest code can be found at https://github.com/Multilingual-LGBTQIA-Vocabularies/Examing_LGBTQ_Concepts. </p> <p>To reproduce the results or extend our work, you need to take the following steps.</p> <div> <h2>Step 1: Preparing the data</h2> </div> <p>In this project, the following datasets were used:</p> <ul> <li>QLIT: version 1.0</li> <li>Homosaurus: version 3.5 and version 2.3</li> <li>Wikidata: retrieved from the SPARQL Endpoint (<a href="https://query.wikidata.org/sparql" rel="nofollow">https://query.wikidata.org/sparql</a>) and processed between 5th May and 8th May, 2024.</li> <li>GSSO: we used gsso.owl (version 2.0.10) obtained from its Github (<a href="https://github.com/Superraptor/GSSO">https://github.com/Superraptor/GSSO</a>).</li> <li>LCSH was obtained from the official website: <a href="https://id.loc.gov/authorities/subjects.html" rel="nofollow">https://id.loc.gov/authorities/subjects.html</a> on 9th May, 2024. The LCSH data was converted to its HDT format.</li> </ul> <p>Please put the corresponding files in the following folders (and change its names where necessary) to make sure that the Python scripts can find your code.</p> <ul> <li>./data/GSSO/gsso.owl</li> <li>./data/Homosaurus/v2.ttl and ./data/Homosaurus/v3.ttl</li> <li>./data/LCSH/lcsh.hdt (we used its HDT format for fast query and analysis). The original file is also attached: subjects.skosrdf.nt.</li> <li>./data/QLIT/Qlit-v1.ttl</li> </ul> <p>The case of Wikidata is more complicated. The following scripts were used for the retrival of data. These scripts are all in the folder ./data/wikidata/</p> <ul> <li>We used the Wikidata SPARQL endpoint: <a href="https://query.wikidata.org/" rel="nofollow">https://query.wikidata.org/</a></li> </ul> <p>The following relations from Wikidata were used while extracting triples.</p> <ul> <li>Wikidata - GSSO: <a href="http://www.wikidata.org/prop/direct/P9827" rel="nofollow">http://www.wikidata.org/prop/direct/P9827</a></li> <li>Wikidata - Homosaurus 2: <a href="http://www.wikidata.org/prop/direct/P6417" rel="nofollow">http://www.wikidata.org/prop/direct/P6417</a></li> <li>Wikidata - Homosaurus 3: <a href="http://www.wikidata.org/prop/direct/P10192" rel="nofollow">http://www.wikidata.org/prop/direct/P10192</a></li> <li>Wikidata - LCSH: <a href="http://www.wikidata.org/prop/direct/P244" rel="nofollow">http://www.wikidata.org/prop/direct/P244</a></li> </ul> <p>The generated files are:</p> <ul> <li>'wikidata-homosaurus-v2-links.nt'</li> <li>'wikidata-homosaurus-v3-links.nt'</li> <li>'wikidata-gsso-links.nt'</li> <li>'wikidata-qlit-links.nt'</li> <li>'wikidata-lcsh-links-all.nt'</li> </ul> <p>Please note that the case of Wikdiata-LCSH is more complicated: there are so many links that are nothing to do with the entities in our scope. We restrict it to only entities in the scope of this paper. See below for more details.</p> <p>You can find all the scripts in the corresponding folder in the data folder.</p> <p>All the SPARQL queries used can be found in the folder ./SPARQL/</p> <p>Note! For GSSO, the following two mistakes were corrected while preprocessing:</p> <ul> <li><a href="https://www.wikidata.org/wiki/Q1823134" rel="nofollow">https://www.wikidata.org/wiki/Q1823134</a> should not be used as a relation. We have replaced it with <a href="http://www.wikidata.org/prop/direct/P244" rel="nofollow">http://www.wikidata.org/prop/direct/P244</a>.</li> <li>Instead of referring to the page, we refer to the entity. We use <a href="http://www.wikidata.org/entity/" rel="nofollow">http://www.wikidata.org/entity/</a>* instead of <a href="https://www.wikidata.org/wiki/" rel="nofollow">https://www.wikidata.org/wiki/</a>*</li> </ul> <p>The redirection test was conducted on 30th April, 2024, between 6PM and 8PM. The files can be found in the folder of ./data/Homosaurus/redirect/.</p> <div> <h2>Integrating the data</h2> </div> <p>In the folder ./integrated_data/, you can find all the scripts related to the integrated data. Unfortunately, due to the CC-BY-NC-ND license of GSSO and Homosaurus, the integrated data will not be made available. But you can generate it with the instructions above and by using the following scripts.</p> <p>The script ./integrated_data/integrate.py takes advantage of the data generated. It first integrates a list of files of links. Then we go through the links between Wikidata and LCSH. Only those that are in the scope of the study are included.</p> <ul> <li>If your steps are correct and using the same version as we did, you should be able to get four files:</li> <li>a) the integrated file as integrated.nt</li> <li>b) the links that are relevant for this study: wikidata-lcsh-links-selected.nt.</li> <li>c) a plot of the distribution of the size of WCCs</li> <li>d) a mapping of entities and their corresponding ID of WCCs.</li> </ul> <div> <h2>Weakly Connected Components</h2> </div> <p>The weakly connected components (WCCs) were computed for the following three purposes:</p> <p>a) Discovering missing links. See the section below for details.</p> <p>b) The WCCs can be used for manual examination. These are entities that form clusters about related concepts. The intuition is that the larger they are, the more likely there is concept drift/change, ambiguity, and mistakes.</p> <p>c) Multilingual information reuse. Smaller WCCs with exactly one entity from each dataset (e.g. Homosaurus and Wikidata) can then be used to suggest labels for the one with fewer labels for some given languages. See below for more details.</p> <p>As mentioned above, the distribution has been plotted. You can find this plot here: ./integrated_data/frequency.png</p> <p>In the folder ./integrated_data/weakly_connected_components/, you can find all the WCCs and their links.</p> <p>Two examples were given in the folder. The largest WCC about sex, gender, fucking, etc. The other is about BDSM and fetish.</p> <div> <h2>Discovering missing and outdated links</h2> </div> <p>Taking advantage of WCCs, we can further find missing and outdated links. The scripts are in the folder ./discover_missing_links.</p> <p>Three examples were given. The first two is about discovering missing links. The last one is about finding outdated links.</p> <ul> <li> <p>The script ./discover_missing_links/discover_H3_LCSH.py and ./discover_missing_links/discover_QLIT_LCSH.py are scripts that outputs links that could be missing in Homosaurus and QLIT respectively. This was computed by looking at the WCCs. If two entities are both involved in the same WCC, there could be a link between them. The csv files in the same folder are the corresponding links found.</p> </li> <li> <p>The script ./discover_missing_links/find_qlit_outdated_links/ is used to discover the outdated links between QLIT and Homosaurus v3. There was only one link found.</p> </li> <li> <p>The 105 potentially missing links were taken for further review by Swedish-speaking experts from the QLIT team, which showed that 78 (72.38%) suggested links should be included: 38 (36.19%) can be included using skos:exactMatch and another 38 (36.19%) using skos:closeMatch. 28 (26.67%) suggested links are incorrect. The manual annotation are included in the file ./discover_missing_links/Annotated_found_new_links_qlit-lcsh.xlsx.</p> </li> </ul> <div> <h2>Multilingual Information Reuse</h2> </div> <p>You can find two attempts in the folders about the use of GSSO and Wikidata for Homosaurus respectively.</p> <ul> <li>./WCC-based-gsso-multilingual_info_reuse/</li> <li>./WCC-based-wikidata-multilingual_info_reuse/</li> </ul> <p>Additionally, we provide also some code for the reuse of Wikidata multilingual info for QLIT. It's in the folder</p> <ul> <li>./WCC-based-QLIT-info-reuse-from-Wikidata/</li> </ul> <p>They follow very similar steps:</p> <ol> <li> <p>Compute the one-to-one mapping using the WCCs. The script is named compute-one-to-one-mapping.py</p> </li> <li> <p>Extract the multilingual labels from sources. The corresponding file is extract_multilingual_labels_from_one_to_one_mappings.py</p> </li> <li> <p>Provide the extracted multilingual as suggestions for targeting entities. The name of the corresponding files are like "*suggesting-labels.py", where the * is replaced by the actual source/target.</p> </li> </ol> <p>For GSSO, we use the following relations:</p> <ul> <li><a href="http://www.w3.org/2000/01/rdf-schema#label" rel="nofollow">http://www.w3.org/2000/01/rdf-schema#label</a></li> <li><a href="http://www.geneontology.org/formats/oboInOwl#hasRelatedSynonym" rel="nofollow">http://www.geneontology.org/formats/oboInOwl#hasRelatedSynonym</a></li> <li><a href="http://www.geneontology.org/formats/oboInOwl#hasSynonym" rel="nofollow">http://www.geneontology.org/formats/oboInOwl#hasSynonym</a></li> <li><a href="http://www.geneontology.org/formats/oboInOwl#hasExactSynonym" rel="nofollow">http://www.geneontology.org/formats/oboInOwl#hasExactSynonym</a></li> <li><a href="http://purl.org/dc/terms/replaces" rel="nofollow">http://purl.org/dc/terms/replaces</a></li> <li><a href="https://www.wikidata.org/wiki/Property:P5191" rel="nofollow">https://www.wikidata.org/wiki/Property:P5191</a></li> <li><a href="https://www.wikidata.org/wiki/Property:P1813" rel="nofollow">https://www.wikidata.org/wiki/Property:P1813</a></li> <li><a href="https://schema.org/alternateName" rel="nofollow">https://schema.org/alternateName</a></li> <li><a href="http://www.w3.org/2002/07/owl#annotatedTarget" rel="nofollow">http://www.w3.org/2002/07/owl#annotatedTarget</a></li> </ul> <p>Additioinally, we found the relation to be studied in the future: <a href="http://www.geneontology.org/formats/oboInOwl#hasNarrowSynonym" rel="nofollow">http://www.geneontology.org/formats/oboInOwl#hasNarrowSynonym</a></p> <p>For Wikidata, there are only two:</p> <ul> <li><a href="http://www.w3.org/2000/01/rdf-schema#label" rel="nofollow">http://www.w3.org/2000/01/rdf-schema#label</a></li> <li><a href="http://www.w3.org/2004/02/skos/core#altLabel" rel="nofollow">http://www.w3.org/2004/02/skos/core#altLabel</a></li> </ul> <div> <h2>Additional analysis</h2> </div> <p>Additionally, we perform an analysis using only redirection and replacement for GSSO and Homosaurus. The scripts are in the folder ./additional_test_gsso_multilingual_info_reuse. We consider also Homosaurus v2. This additional analysis shows the following:</p> <ul> <li> <p>For the Turkish language, in total there are 103 triples about labels about 23 entities. The average suggested labels per entity is 3.0.</p> </li> <li> <p>For the Spanish language, in total there are 205 triples about labels about 43 entities. The average suggested labels per entity is 2.12.</p> </li> <li> <p>For the French language, in total there are 277 triples about labels about 47 entities. The average suggested labels per entity is 2.19.</p> </li> <li> <p>For the Danish language, in total there are 115 triples about labels about 47 entities. The average suggested labels per entity is 2.70.</p> </li> </ul> <p>Some analysis about the replacement relations of Homosaurus is in the folder ./data/Homosaurus/replace_relations_homosaurus/.</p> <p>Finally, some additional analysis is included in the folder ./analysis_integrated_graph. Currently, there is only one that is about outdated entities in Homosaurus v3. Some more analysis will be added in the future.</p> <div> <h2>Acknowledgement</h2> </div> <p>The authors appreciate the help of the following researchers:</p> <ul> <li>Siska Humlesjö, QLIT, Göteborgs Universitet (<a href="mailto:siska.humlesjo@lir.gu.se">siska.humlesjo@lir.gu.se</a>)</li> <li>Olov Kriström, former member of QLIT</li> <li>Jack van der Wel, IHLIA (<a href="mailto:jack@ihlia.nl">jack@ihlia.nl</a>)</li> <li>Clair Kronk, GSSO (<a href="mailto:clair.kronk@mountsinai.org">clair.kronk@mountsinai.org</a>)</li> </ul> <div> <p>If you would like to extend this work, you may want to contact them before releasing your data/code about legal and ethical issues.</p> <h2>Contact</h2> </div> <ul> <li>Shuai Wang, Vrije Universiteit Amsterdam (<a href="mailto:shuai.wang@vu.nl">shuai.wang@vu.nl</a>)</li> <li>Maria Adamidou, Vrije Universiteit Amsterdam (<a href="mailto:m.adamidou@student.vu.nl">m.adamidou@student.vu.nl</a>)</li> </ul> <p> </p> <p>Thank you very much for your interest in our project!</p>
CLDF dataset derived from Aaley and Bodt's "New Kusunda data: A list of 250 concepts" from 2020
<p>Cite the source of the dataset as:</p> <blockquote> <p>Uday Raj Aaley and Timotheus A. Bodt (2020): New Kusunda data: A list of 250 concepts. Computer-Assisted Language Comparison in Practice 3.4 (08/04/2020), URL: https://calc.hypotheses.org/2414.</p> </blockquote>
Unpacking the concept of "educators' data literacy in Higher Education" - Systematic Review of the literature and Keyword Map
<p>As algorithmic decision-making and data collection become pervasive within higher education, how can educators make sense of the systems that shape life and learning in the 21st century? Through a systematic review of the literature, the paper investigates the gaps in the literature, which prevent the formulation of potential pathways and principles on which educators’ data literacy can - and should - be developed and fostered. The analysis of 137 papers through the methods of classification under relevant categories, and key words mapping, showed that there is little attention on HE teachers, and most approaches to educators’ data literacy address management and technical abilities for data processing, with less concern on critical, ethical and personal approaches to datafication in education.</p> <p>The present dataset shows the full list of articles analysed.</p> <p>The dataset, and ods file, is composed by the following sheets:</p> <ol> <li>Codebook</li> <li>List of articles extracted from SCOPUS</li> <li>List of articles extracted from WOS</li> <li>List of articles extracted from ERIC</li> <li>List of articles extracted from DOAJ</li> <li>Interrater Agreement</li> <li>PRISMA workflow</li> <li>Analysis - First Level (classification of 137 articles selected)</li> <li>Analysis - Second Level (List of articles relating faculty development)</li> <li>Supplementary tables (counting articles in relation to the categories of analysis).</li> </ol> <p>As for the Keywords' Map, a second file .csv displays the text over which basis was performed the keyword maps analysis. A .txt file shows notes relating the analysis procedures using the software VOS-Viewer <a href="http://www.vosviewer.com/">http://www.vosviewer.com/</a></p> <p> </p>
Suansu 250 concepts wordlist
<p>This dataset presents lexical data on Suansu (Glottocode: suan1234), a previously undocumented and unreported<br> Tibeto-Burman language spoken in North East India (25.4333° N, 94.5803° E). The datasheet comprises 250 lexical entries in Suansu (in broad IPA transcription) with English translation. The wordlist is based entirely on the Concepticon wordlist.</p> <p>Data is based on original fieldwork and it has been collected in Pune (Maharashtra, India), in November 2018. IPA transcription needs further stabilisation.<br> Data collector: Jessica Katiuscia Ivani (University of Kiel)</p> <p>The material in this file may be freely quoted, copied, or reproduced for non-commercial purposes. If used, a citation is required.</p>
Proof-of-Concept Measurement for "Radar Band Fusion Using Frame-Based Compressed Sensing"
<p>This data set was created for a proof-of-concept test of the method described in "Radar Band Fusion Using Frame-Based Compressed Sensing". It consists of a measurment against a metal plate.</p> <p> </p>
The conception of a solvated electron: X-ray-induced attosecond electron dynamics of aqueous ions - data
<p>Data set pertaining to the article "Attosecond formation of charge-transfer-to-solvent states of aqueous ions probed using the core-hole-clock technique", published in <a href="https://doi.org/10.1038/s41467-024-52740-5" target="_blank" rel="noopener">Nature Communications</a>.</p> <p>Here we describe the time-evolution of core level excited electronic states of metal ions in aqueous solution on an ultrashort time scale. Extensive simulations towards this project were carried out. Simulated data include geometries for solvated metal ion complexes and their X-Ray absorption spectra. Experimental data were recorded by photoemission spectroscopy from a liquid jet source using synchrotron radiation. </p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07, see<br>https://www.nexusformat.org/<br>https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br>* nexpy (distributed with python)<br>* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br>1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data') if applicable.<br>2. As-measured data ('raw').</p> <p>Files with extension .csv or .txt are comma-separated ascii-files, designed to be opened with a spreadsheet programme.</p> <p><br>The following files are provided:</p> <table> <tbody> <tr> <td>Filename</td> <td>Content</td> </tr> <tr> <td> </td> <td>Experimental Data:</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/na_mg_al_1s-resonance_cfs.h5/content" target="_blank" rel="noopener noreferrer">na_mg_al_1s-resonance_cfs.h5</a></td> <td>Series of experimental photoemission spectra recorded over the 1s - val resonances, for NaCl, MgCl2 andAlCl3 metallic salt solutions</td> </tr> <tr> <td><span><a href="https://zenodo.org/api/records/13862194/draft/files/SI-Fig6.zip/content" target="_blank" rel="noopener noreferrer">SI-Fig6.zip</a></span></td> <td>Ascii representation of the data and fit curves used to determine in 1s lifetime broadening, shown in Fig. 6 of the Supplementary Information.</td> </tr> <tr> <td> </td> <td>Theoretical Data:</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/th.geometries.zip/content" target="_blank" rel="noopener noreferrer">th.geometries.zip</a></td> <td>Cartesian coordinates of the constituents of metal-water clusters containing 6 water molecules and containing 18 water molecules. Unit of length is Ångström.</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/th.excitation_energy.zip/content" target="_blank" rel="noopener noreferrer">th.excitation_energy.zip</a></td> <td>Excitation energies for metal-water clusters containing 6 water molecules and containing 18 water molecule, at various levels of approximation. tddft-src2: at the SRC2-R2 level with a cc-pCVTZ basis set on the cations and a cc-pVTZ basis set on the water molecules in a polarizable continuum; eomccsd: at the EOM-EE-CCSD level with a cc-pCVTZ basis set on the cations and a cc-pVTZ basis set on the water molecules. For the purpose of spectra construction in Figure 1, each calculated spectral point was broadened by a phenomenological value of 0.2 eV. Energies are in eV, transition dipole moment components in e*bohr.</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/th.spektrum.pade.zip/content" target="_blank" rel="noopener noreferrer">th.spektrum.pade.zip</a></td> <td>Excitation energies for metal-water clusters containing 6 water molecules calculated at the RT-TDDFT level with a cc-pVTZ basis set. For each cation, 3 trajectories were run. Energies are in eV.</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/th.excitation_energy.zip/content" target="_blank" rel="noopener noreferrer">th.excitation_energy.zip</a></td> <td>Exciton analysis of the wave function (RMS electron size) for a set of 50 geometries of clusters containing 6 water molecules (small) or 18 water molecules (large) calculated at the SRC2-R2/cc-pVTZ level. The oscillator strengths are in a.u., the size of the electron is in Ångström.</td> </tr> <tr> <td><a href="../api/records/10600583/draft/files/description_zenodo.pdf/content" target="_blank" rel="noopener noreferrer">description_zenodo.pdf</a></td> <td>More detailed description of the theoretical data sets.</td> </tr> </tbody> </table> <p> </p> <p>Version history<br>v2: fixed incorrect choice of data file for Na scan. Data for lifetime-figure in SI added.<br>v1: initial upload</p> <p>If you use part or all of these data in your scientific work we kindly ask you to provide us a copy. Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Concept, Equation, and Applications of Sunya Bhutam and Quantum Energy
<p>This paper presents a theoretical framework exploring the relationship between vacuum energy (Sunya) and existential energy (Bhutam), inspired by the philosophical concept of Sunya Bhutam. Drawing parallels between ancient metaphysical ideas and modern quantum energy dynamics, the equation E = n × (V_empty + P_existence) is introduced to describe the total energy in a system. Here, n represents the number of quantum states, while vacuum energy (V_empty) and existential energy (P_existence) capture the contributions of emptiness and existence, respectively. This framework not only aligns with quantum mechanical phenomena such as vacuum fluctuations and dark energy but also offers a bridge between scientific and philosophical thought. Practical applications of this equation are explored in fields such as cosmology, energy systems, material science, and quantum computing. By integrating metaphysical insights with modern physics, this paper aims to foster a deeper understanding of energy dynamics in both scientific and philosophical contexts.</p>
BIOBUILD Innovative Concept
<p>BIOBUILD project infographic demonstrating the techological processes and methods. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or REA. Neither the European Union nor the granting authority can be held responsible for them.<br>Grant agreement ID: 101135629</p>
Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial'
<p>Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial' (trial registered at clinicaltrials.gov (<a href="https://clinicaltrials.gov/ct2/show/NCT04996654">NCT04996654</a>; date of registration: 11 July 2021), consisting of:</p> <p>(1) the original and complete data set for all primary outcomes ('Data_Primary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(2) the original and complete data set for all secondary outcomes ('Data_Secondary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(3) the original and complete data set for all other outcomes (i.e. baseline factors (demographic data, type of usual care interventions) and training heart rate; 'Data_Other-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(4) folder including the raw and processed heart rate variability (HRV) and electroencephalography (EEG) data for all participants and measurements (HRV-and-EEG_raw-and-processed-data.zip);</p> <p>(5) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.</p>
Supplementary material: Sagart 250-concept list for Caijia
<p>The word list is a supplementary material for the article "Phonological Features of Caijia that are Notable from a Diachronic Perspective" published in the <em>Journal of Historical Linguistics</em>. </p> <p>If you use this word list, please cite the original paper:</p> <p>Lee, Man Hei. 2023. Phonological Features of Caijia that are Notable from a Diachronic Perspective. <em>Journal of Historical Linguistics</em> 13:1. 82-114.</p> <p> </p>
Identification of grapevine clones via high-throughput amplicon sequencing: a proof-of-concept study VCF files
<p>VCF files used and cited in the article: Identification of grapevine clones via high-throughput amplicon sequencing: a proof-of-concept study</p>
Proof-of-concept AO telemetry data using the AOT standard format
<p>Dataset containing a demonstration of AO telemetry data using the AOT standard format. Contains data from 5 different systems (CIAO, ERIS, GALACSI, NAOMI and PAPYRUS).</p> <p>The data is as follows:</p> <ul> <li>4 CIAO files "CIAO#_*.fits" where # indicates the AT where the data was produced.</li> <li>2 ERIS files, one in LGS (LTAO) mode and another in NGS (SCAO) mode.</li> <li>1 GALACSI file.</li> <li>4 NAOMI files "NAOMI#_*.fits" where # indicates the AT where the data was produced.</li> <li>2 PAPYRUS files, one using a Shack-Hartmann wavefront sensor (SHWFS) and another using a Pyramid wavefront sensor (PWFS).</li> </ul> <p>GALACSI, CIAO, NAOMI and ERIS data were gathered under ESO's program IDs 60.A-9278(B), 60.A-9278(C), 60.A-9278(D) and 60.A-9278(E) respectively. The data was translated via the functions provided in the Python package <em>aotpy</em> (<a href="https://doi.org/10.5281/zenodo.8187230">10.5281/zenodo.8187230</a>).</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101004719 (OPTICON–RadioNet Pilot).</p>
Automatically computed correspondence patterns among six Burmish languages (based on 500 concepts in Huang 1992)
<p>This document is a printout of automatically computed correspondence patterns amount six Burmish languages (Old Burmese, Longchuan Achang, Xiandao, Atsi, Bola, and Maru). It uses as input 500 concepts taken from Huang 1992.</p>
Figure 18 in Expanded concept and revised taxonomy of the milliped family Xystodesmidae Cook, 1895 (Polydesmida: Leptodesmidea: Xystodesmoidea): incorporations of Euryuridae Pocock, 1909 and Eurymerodesmidae Causey, 1951, taxon revivals/proposals/ transferrals, and a distributional update
Figure 18. The East-Nearctic Region of Xystodesmidae. The eastern- and northernmost dots denote localities of the two Appalachian species of Rhysodesmus; the dot in Texas within the black line signifies the northernmost locality of R. texicolens (Chamberlin), San Diego, Duval Co. The arrow indicates Bald Head Island, NC, occupied by Apheloria (Xystodesminae: Apheloriini).
Figure 1 in Expanded concept and revised taxonomy of the milliped family Xystodesmidae Cook, 1895 (Polydesmida: Leptodesmidea: Xystodesmoidea): incorporations of Euryuridae Pocock, 1909 and Eurymerodesmidae Causey, 1951, taxon revivals/proposals/ transferrals, and a distributional update
Figure 1. Distribution of Euryurinae plotted against the maximal extent of the Cretaceous Western Inland Sea. Euryurina (Euryurini, red), Eurymerodesmina (Eurymerodesmini, black), Nannariina (Eurymerodesmini, green). The red line, Euryurina, in eastern North Carolina and southcentral Virginia connects disparate peripheral localities; the area of greatest euryurinan concentration is circumscribed by the red dots.
Figures 8–15 in Expanded concept and revised taxonomy of the milliped family Xystodesmidae Cook, 1895 (Polydesmida: Leptodesmidea: Xystodesmoidea): incorporations of Euryuridae Pocock, 1909 and Eurymerodesmidae Causey, 1951, taxon revivals/proposals/ transferrals, and a distributional update
Figures 8–15. Eurymerodesmini gonopodal tel-/acropodites; 8–11, Nannariina. 8) telopodite of Nannaria cayugae Chamberlin, Tompkins Co., NY. 9) acropodite of the same. 10) telopodite of Mimuloria castanea (McNeill), Monroe Co., IN. 11) the same of M. d. dilatata Hennen and Shelley, Marshall Co., TN. 12–15, Eurymerodesmina. 12) Eurymerodesmus varius louisianae Chamberlin, Natchitoches Par., LA. 13) acropodite of a second individual from the same locality. 14) the same, Columbia Co., AR. 15) E. v. varius (McNeill), Escambia Co., FL. Figures 8–9 reprinted from Chamberlin (1949) with permission from the Biological Society of Washington. Figures 10–11 reprinted from Hennen and Shelley (2015) with permission of the Center for Systematic Entomology. Figures 12–15 reprinted from Shelley (1990a) with permission of the American Entomological Society.
Fig. 27 in Revision of Leucothoe (Amphipoda, Crustacea) from the Southern Ocean: a cosmopolitanism concept is vanishing
Fig. 27. Distribution of Leucothoe weddellensis sp. nov. Hydrographic fronts as in Fig. 5. TL = type locality.
ScienceDex guides
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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.