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5,875 results for “lively”
Black Lives, British Justice: Black people in London Criminal Justice Records 1720-1841
<p>This dataset brings together all 698 known references to ‘Black’ or possibly Black African heritage people or groups in records of London criminal justice (1720-1841). Each entry includes references to primary sources mentioning the person(s), including in the <em>Old Bailey Proceedings</em>, <em>Ordinary’s Accounts</em>, and <em>Middlesex Criminal Registers</em>. Individuals are trial witnesses, victims, defendants, and people mentioned in passing during testimony. For each entry, a confidence level is offered by the authors, as a person’s ethnicity cannot always be determined with certainty. Evidence for making that judgment is provided. This dataset is useful for anyone interested in Black history in Britain, Black people and justice, or Black London during the age of enslavement.</p> <p>Significant background material is available on the Old Bailey Online website, which provides additional context for these records. The authors also recommend the following works:</p> <p> * Kathleen Chater. <em>Untold Histories: Black People in England and Wales during the Period of the British Slave Trade, c. 1660-1807</em> (Manchester, 2011).<br> * Norma Myers, <em>Reconstructing the Black Past</em> (Frank Cass, 1996).<br> * Marika Sherwood. ‘Blacks in the Gordon Riots’, <em>History Today</em>, vol. 47 (1997), 24-28.</p> <p><br> Each record includes details on the name of the Black individual(s), as well as information on up to three sources in which he/she/they have been identified, and an indication by the authors on the likelihood the person is actually Black.</p> <p>Each entry has 17 columns of data, all of which are described in full in the ReadMe.txt file.</p>
Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes - Supplementary Tables
<p>This repository contains the Supplementary Tables for Suriyalaksh et al. Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes.</p> <p>The list of table files can be found in <a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/Supplementary%20table%20guide.pdf">Supplementary Tables guide.pdf</a></p> <p>Tables S1, S2 and S3 corresponding to physical gene-gene interaction data are in a separate repository doi:10.5281/zenodo.4382337</p> <p>Details about some of the Supplementary tables:</p> <p>TableS4_inferred_networks.csv - list of inferred GRNs for specified input combinations (set of input regulators, length of the time sequence, NI tool and prior used).</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS5_consensus_network_member.xlsx">TableS5_consensus_network_member.xlsx</a> - list of groups of topologically similar GRNs (from Table S4)</p> <p>Table S6: edge lists (source,target) for each one of the three consensus networks selected according to the GS validation metrics: middle PFE/AUFE, max AUFE, max PFE.<br> TableS6a_max_AUFE_GRN.txt - max AUFE; largest network - this is the one we used in the main analysis and discussion<br> TableS6b_max_PFE_GRN.xt - max PFE<br> TableS6c_middle_AUFE_PFE_GRN.txt - middle PFE/AUFE</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS7_qRTPCR_ddCt_network_accuracy.csv">TableS7_qRTPCR_ddCt_network_accuracy.csv</a> - gene expression count differences for RNAi knockdown GRN validation experiments. </p> <p>Table S8: Group membership for each one of the nodes in each one of the selected networks according to the SBM that best describes the observed network topology. Each column shows the group membership for each level in a SBM block hierarchy. Our analysis is in the second most coarse-grained level (level 1).</p> <p>TableS8a_max_AUFE_SBM.csv<br> TableS8b_max_PFE_SBM.csv<br> TableS8c_middle_AUFE_PFE_SBM.csv</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS9_glp_gs_datasets.pdf">TableS9_glp_gs_datasets.pdf</a> - list of datasets used for defining functional clusters.</p> <p>TableS14a_glp_l1_vs_fem_l1_lifespan_assay.xlsx - Day13 survival of fem-3(q20)ts vs day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L1</p> <p>TableS14b_glp_l1_vs_glp_l4_lifespan_assay.xlsx - Day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L4 vs day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L1</p> <p>TableS15a_glp1_in_vivo_fluorescence_data.xlsx - in vivo fluorescent reporter data of glp-1(e2144)ts;rrf-3(pk1426)</p> <p>TableS15b_fem3_in_vivo_fluorescence_data.xlsx - in vivo fluorescent reporter data of fem-3(q20)ts</p> <p>TableS17_input_regulators_annotated.csv - list input regulators used as input for Network Inference Tools annotated by source type (2nd column): GenAge, known transcription factors (TF) and gene with high variability in the gene expression time series (HV). The third column lists whether that regulator has an orthologue in human (y) according to WormBase (v 278).</p> <p>TableS20_epistasis_lifespan_data.xlsx - Epistasis lifespan data of glp-1(e2144)ts</p> <p>All the image (TIF) files represent representative images in the following genetic backgrounds (below) that have been treated </p> <p>with empty vector (EV) or RNAi against the gene highlighted in the title of the image. See methods section for details. </p> <p><strong>femliu1: </strong></p> <p><em>fem-3(q20)ts.; dhs-3p::dhs-3::gfp</em></p> <p><strong>femsod3:</strong></p> <p><em>fem-3(q20)ts.; sod-3p::gfp</em></p> <p><strong>glp1lgg1:</strong></p> <p><em>glp-1(e2144); lgg-1p:lgg-1:gfp</em></p>
Sample version 2.0 ITS_LIVE Sentinel-1 image pair product of ice velocity in Greenland
<p>21 samples of version 2.0 ITS_LIVE Sentinel-1 image pair product of ice velocity in three test regions of Greenland Ice Sheet</p> <p>Sensor: Sentinel-1A/B</p> <p>Processor: <a href="https://github.com/isce-framework/isce2">ISCE</a> v2.4.1 (topsApp -> <a href="https://github.com/leiyangleon/Geogrid">Geogrid</a> v1.4.0 -> <a href="https://github.com/nasa-jpl/autoRIFT">autoRIFT</a> v1.4.0)</p> <p>Project: NASA MEaSUREs project <a href="https://its-live.jpl.nasa.gov">ITS_LIVE</a></p> <p>Region 1 (69.13N, 50.88W; Jakobshavn Isbræ Glacier): 7 ascending image pairs</p> <p>Region 2 (77.61N, 42.79W; central north of interior Greenland): 3 ascending image pairs</p> <p>Region 3 (72.48N, 35.87W; central south of interior Greenland): 10 descending image pairs and 1 ascending image pair</p> <p>This serves as a supplementary dataset for the companion journal article submitted to Earth System Science Data (to appear soon).</p> <p> </p> <p>Acknowledgement:</p> <p>This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (<a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov/</a>) and through Alex Gardner’s participation in the NASA NISAR Science Team</p>
Supplementary Information to: "Living on the edge: Response of rudist bivalves (Hippuritida) to hot and highly seasonal climate in the low-latitude Saiwan site, Oman"
<p>This dataset contains supplementary information required to understand and reproduce the study detailed in our manuscript titled "<em>Living on the edge: Response of rudist bivalves (Hippuritida) to hot and highly seasonal climate in the low-latitude Saiwan site, Oman</em>" which was submitted for publication to Palaeogeography, Palaeoclimatology, Palaeoecology.</p>
LivWell: a sub-national database on the Living conditions of Women and their Well-being for 52 countries
<p>LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level.</p> <p>For a full description, please refer to the article describing the database here: (link to come)</p> <p>The companion repository <em>livwelldata </em>allows to easily use the database in R. The R package can be downloaded following the instructions on the following git repository: https://gitlab.pik-potsdam.de/belmin/livwelldata. The version of the database in the package is the same as in this repository.</p>
"I have been born, raised, and lived my whole life here"
<p>This dataset completes an article on the story of Einar, a Faroese man who always lived within a 500-meters radius on the island of Suðuroy, who never felt “stuck” or “immobile” in the literal sense of the word. Studies have shown that staying is a process, as much as mobility; yet while mobility studies mainly show that imagination is an incentive to move, we argue that imagination may also actively support staying. Combining sociocultural psychology with mobility studies, we propose to explore the entanglement of symbolic mobility (a form of imagination) and various forms of geographical (im)mobility. Based on ethnographic fieldwork and hours of conversation, we present the case study of Einar's life on his island. We follow the sociogenetic development of the island, and the expansion and contraction of the imaginative horizon over time. On this background, we then retrace the life of Einar and show how, within this transforming context, his imagination developed thanks to resources he could use from the mobility of technologies, ideas, and other people. Interestingly, at different bifurcation points, his symbolic mobility almost led him to move away but, at another point, helped him to refuse geographical mobility. Hence, he was always symbolically mobile while staying. We finally propose directions for generalising from this case study, and implications for cultural psychology and for mobility and migration studies.</p>
Multidimensional pain profiling in people living with obesity and attending weight management services: a protocol for a longitudinal cohort study
<p><strong>Please note: The final dataset will not be available until data collection has been completed in the Autumn of 2024.<br> This dataset currently contains the following:</strong></p> <p>1. Details of the study, including authorship, ethical approval, funding, registration details, an abstract for the protocol of the study and details of data being collected (both in Microsoft Word and open access .txt formats)</p> <p>2. Outline of the data in the process of collection (Microsoft Excel)</p> <p>3. Ethical approval letters from relevant Research Ethics Committees (PDF)<br> <br> </p> <p> </p> <p><strong>Project Title: </strong>Multidimensional pain profiling in people living with obesity and attending weight management services: a longitudinal cohort study</p> <p> </p> <p><strong>Authors:</strong> Keith M. Smart<sup>1,2</sup>, Natasha Hinwood<sup>1</sup>, Colin G. Dunlevy<sup>3</sup>, Catherine Doody<sup>1</sup>, Catherine Blake<sup>1</sup>, Brona Fullen<sup>1</sup>, Jean O’Connell<sup>3</sup>, Carel W. Le Roux<sup>4</sup>, Clare Gilsenan<sup>5</sup>, Francis M. Finucane<sup>6,7</sup>, Gráinne O’Donoghue<sup>1</sup>.</p> <p> </p> <p><strong>Corresponding author</strong>: Natasha Hinwood</p> <p><strong>Address:</strong> UCD School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland</p> <p><strong>Email:</strong> <a href="mailto:natasha.hinwood@ucdconnect.ie">natasha.hinwood@ucdconnect.ie</a></p> <p><strong>Phone:</strong> +353 1 716 6511</p> <p> </p> <p>Full name, department, institution, city, and country of all co-authors.</p> <p><sup>1</sup>UCD School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland</p> <p><sup>2</sup>Physiotherapy Department, St. Vincent’s University Hospital, Dublin, Ireland</p> <p><sup>3</sup>Weight Management Service, St Columcille’s Hospital, Dublin, Ireland</p> <p><sup>4</sup>Diabetes Complications Research Centre, University College Dublin, Dublin, Ireland</p> <p><sup>5</sup>Physiotherapy Department, Beaumont Hospital, Dublin, Ireland</p> <p><sup>6</sup> School of Medicine, College of Nursing and Health Sciences, University of Galway</p> <p><sup>7</sup>Bariatric Medicine Service, Centre for Diabetes, Endocrinology and Metabolism, Galway University Hospitals</p> <p> </p> <p><strong>ORCID</strong></p> <p>1. Keith M. Smart: 0000-0002-1598-5215</p> <p>2. Natasha Hinwood: 0000-0001-9382-716X</p> <p>3. Colin G. Dunlevy:</p> <p>4. Catherine Doody:</p> <p>5. Catherine Blake: 0000-0002-0600-629X</p> <p>6. Brona Fullen: 0000-0003-4408--2063</p> <p>7. Carel W. Le Roux: 0000-0001-5521-5445</p> <p>8. Jean O’Connell: 0000-0001-7241-8025</p> <p>9. Clare Gilsenan:</p> <p>10. Francis M. Finucane: 0000-0002-5374-7090</p> <p>11. Gráinne O’Donoghue: 0000-0002-9126-2094</p> <p> </p> <p> </p> <p><strong>Project abstract (Protocol): </strong></p> <p><em>Introduction</em>:</p> <p>Pain is prevalent in people living with overweight and obesity. Obesity is associated with increased self-reported pain intensity and pain-related disability, reductions in physical functioning and poorer psychological well-being. People living with obesity tend to respond less well to pain treatments or management compared to people living without obesity. Mechanisms linking obesity and pain are complex and may variously include contributions from and interactions between physiological, behavioural, psychological, socio-cultural, biomechanical, and genetic factors. Our aim is to study the multidimensional pain profiles of people living with obesity, over time, in an attempt to better understand the relationship between obesity and pain.<br> </p> <p><em>Methods and analysis: </em></p> <p>This longitudinal observational cohort study will recruit (n=216) people living with obesity and who are newly attending three weight management services in Ireland. Participants will complete questionnaires that assess their multidimensional biopsychosocial pain experience at baseline and at 3, 6, 12 and 18-months post-recruitment. Quantitative analyses will characterise the multidimensional pain experiences and trajectories of the cohort as a whole and in defined sub-groups.<br> </p> <p><em>Ethics and dissemination: </em></p> <p>The study protocol has been approved by the Ethics and Medical Research Committee of St Vincent’s Healthcare Group, Dublin, Ireland (Reference No.: RS21-059) and the University College Dublin Human Research Ethics Committee (Reference No.: LS-E-22-41-Hinwood-Smart). Findings will be disseminated through peer-reviewed journals, conference presentations, public and patient advocacy groups, and social media.</p>
Document Liveness Challenge (DLC-2021) - part 1 (or, cg)
<p>Dataset DLC-2021 consists of 1424 video clips captured in a wide range of real-world conditions and focused on ID document forensics tasks. Each clip was shot vertically and was at least 5 seconds long. Frames extracted at 10 frames per second and for the 50 first extracted frames document position is manually annotated.<br> The novelty of the dataset is that it contains shots from video with color laminated mock ID documents, color unlaminated copies, grayscale unlaminated copies, and screen recaptures of the documents. The proposed dataset complies with the GDPR because it contains images of synthetic IDs with generated owner photos and artificial personal information.</p> <p>Part 1 contains videos, frames and markup for “original” laminated documents from MIDV-2020 collection and unlaminated gray copies. <br> Part 2 contains videos, frames and markup for documents recaptured from device screen<br> Part 3 contains videos, frames and markup for unlaminated color copies.</p> <p><strong>Share and Cite</strong></p> <p><em>MDPI and ACS Style</em></p> <p>Polevoy, D.V.; Sigareva, I.V.; Ershova, D.M.; Arlazarov, V.V.; Nikolaev, D.P.; Ming, Z.; Luqman, M.M.; Burie, J.-C. Document Liveness Challenge Dataset (DLC-2021). <em>J. Imaging</em> <strong>2022</strong>, <em>8</em>, 181. https://doi.org/10.3390/jimaging8070181</p> <p><em>AMA Style</em></p> <p>Polevoy DV, Sigareva IV, Ershova DM, Arlazarov VV, Nikolaev DP, Ming Z, Luqman MM, Burie J-C. Document Liveness Challenge Dataset (DLC-2021). <em>Journal of Imaging</em>. 2022; 8(7):181. https://doi.org/10.3390/jimaging8070181</p> <p><em>Chicago/Turabian Style</em></p> <p>Polevoy, Dmitry V., Irina V. Sigareva, Daria M. Ershova, Vladimir V. Arlazarov, Dmitry P. Nikolaev, Zuheng Ming, Muhammad M. Luqman, and Jean-Christophe Burie. 2022. "Document Liveness Challenge Dataset (DLC-2021)" <em>Journal of Imaging</em> 8, no. 7: 181. https://doi.org/10.3390/jimaging8070181</p>
Data from: CoAct Citizen Science chatbot explores social support networks in mental health based on lived experiences
<p>A data set on lived experiences in the context of social support in mental health, created within a Citizen Social Science project. </p> <p><br> Societies around the world increasingly encounter wicked and complex problems, such as those related to mental health, environmental justice, and youth employment. <strong>CoAct as a EU-funded global effort</strong> addresses these problems by deploying Citizen Social Science. </p> <p> </p> <p><strong>Citizen Social Science</strong> is understood here as participatory research co-designed and directly driven by citizen groups sharing a social concern. This methodology wants to give citizen groups an equal ‘seat at the table’ through <strong>active participation in research</strong>, from the design to the interpretation of the results and their transformation into concrete actions. Citizens thus act as <strong>co-researchers</strong> and are recognised as in-the-field competent experts. </p> <p> </p> <p>In Barcelona, a group of <strong>32 co-researchers</strong> work together with the OpenSystems group, Universitat de Barcelona, the Catalan Federation of Mental Health (Federació Salut Mental Catalunya), and with the help of many others on a better understanding of informal <strong>social support networks in mental health</strong> in the project <em>CoActuem per la Salut Mental</em> (lit. “We act together for mental health”). The co-researchers, who are either persons with a personal history of mental health problems or are family members of the latter, contributed their <strong>personal experiences related to social support</strong> in the form of <strong>222 micro-stories</strong>, each shorter than 400 characters, and most accompanied by an illustration by Pau Badia.</p> <p> </p> <p>Those micro-stories form the heart of the first co-created Citizen Science chatbot, the code of which is open on <a href="https://github.com/Chaotique/CoActuem_per_la_Salut_Mental_Chatbot.git">https://github.com/Chaotique/CoActuem_per_la_Salut_Mental_Chatbot.git</a> . The <strong>Telegram chatbot</strong> sends them to participants <strong>on a daily basis over the course of a year</strong> and asks them either, whether they and/ or their close surrounding lived this experience, too (stories of type C), or, how they would or would have reacted in the presented situation (stories of type T). The answers of each participant can be contrasted with the individual participants’ answer to a 32-questions <strong>socio-demographic survey</strong>. Further, the timing of the messages is included to allow for a broader analysis. </p> <p> </p> <p>The chatbot is still running, hence this data set will still be updated. For further information on the project <strong>CoAct</strong>, see <a href="https://coactproject.eu/">https://coactproject.eu/</a>. For further details on the co-creation process and purpose of the chatbot <strong>CoActuem per la Salut Mental</strong>, take a look on <a href="https://coactuem.ub.edu/">https://coactuem.ub.edu/</a>. Please direct your questions regarding the data set to <strong>coactuem[at]ub.edu</strong>.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>The CoAct project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 873048. We especially thank the co-researchers for the passion and time invested.</p>
Data from: Maximizing the potential for living cell banks to contribute to global conservation priorities
<p><strong>Summary</strong></p> <p>This dataset accompanies the publication "<strong>Maximizing the potential for living cell banks to contribute to global conservation priorities</strong>" published in Zoo Biology. This study analyzed the representation of amphibian, bird, mammal and reptile species within the San Diego Zoo Wildlife Alliance (SDZWA) Frozen Zoo® living cell collection (as of April 2019) and implemented a qualitative framework for the prioritization of species for future sampling. We used global conservation assessment schemes (including the IUCN Red List of Threatened Species<sup>TM</sup>, CITES, the Alliance for Zero Extinction, the EDGE of Existence, and Climate Change Vulnerability), and opportunities for sample acquisition from the global zoo and aquarium community, to identify priority species for future cryobanking efforts.</p> <p>Two datasets accompany this publication. The first provides a complete list of all “<em>Threatened</em>” species not currently represented within the San Diego Zoo Wildlife Alliance (SDZWA) Frozen Zoo®, their representation under various conservation assessment schemes, and their presence in the global zoo and aquarium community, as represented by Species360 members (<strong>Supporting Information Data S1</strong>). The second provides a list of the 2,351 amphibian and bird species not currently represented in the SDZWA Frozen Zoo® or listed as “<em>Threatened</em>” under the IUCN Red List, but assessed by Foden <em>et al.</em> (2013) as highly vulnerable to climate change. This dataset also shows their presence in the global zoo and aquarium community, as represented by Species360 members (<strong>Supporting Information Data S2</strong>).</p> <p>Data provided by SDZWA are only available upon request. Data for each conservation assessment scheme were collected from each source individually (all freely available), and are accurate to April 2019. Zoo species holdings data were provided upon request by Species360 (https://www.species360.org/), which operates the real-time database ZIMS (Zoological Information Management System). ZIMS is the largest real-time database of comprehensive and standardized information spanning more than 1,200 zoological collections globally, and provides the number of institutions currently managing each species and their current population sizes. </p> <p> </p> <p><strong>Description of the Datasets</strong></p> <p> </p> <p><strong>Supporting Information Data S1 (accurate to April 2019):</strong> A complete list of all “<em>Threatened</em>” species not currently represented within the San Diego Zoo Wildlife Alliance (SDZWA) Frozen Zoo®, their representation under various conservation assessment schemes, and their presence in the global zoo and aquarium community, as represented by Species360 members. Provided in .csv format, variables include:</p> <ul> <li><strong>Class: </strong>The taxonomic class of the species</li> <li><strong>IUCN Name: </strong>The taxonomic name of the species (genus and epithet) according to the IUCN Red List</li> <li><strong>IUCN Status: </strong>The IUCN Red List status of the species (VU, EN, or CR)</li> <li><strong>ZIMS:</strong> The presence (1) or absence (0) of the species from Species360 member zoos and aquariums</li> <li><strong>AZE:</strong> The listing of the species on the Alliance for Zero Extinction assessment (listed = 1, not listed = 0)</li> <li><strong>AZA:</strong> The presence of an active <em>ex situ</em> management programme for the species in the Association of Zoos and Aquariums (active programme = 1, no programme = 0)</li> <li><strong>EAZA: </strong>The presence of an active <em>ex situ</em> management programme for the species in the European Association of Zoos and Aquaria (active programme = 1, no programme = 0)</li> <li><strong>CITES:</strong> The listing of the species on of the three CITES appendices (listed = 1, not listed = 0)</li> <li><strong>CC Vulnerability: </strong>The listing of the species as being highly vulnerable to climate change by Foden <em>et al</em>. 2013 (vulnerable = 1, not vulnerable = 0)</li> <li><strong>EDGE: </strong>The listing of the species on the Evolutionary Distinctiveness and Global Endangerment assessment (listed = 1, not listed = 0)</li> </ul> <p> </p> <p><strong>Supporting Information Data S2 (accurate to April 2019):</strong> A list of the 2,351 amphibian and bird species not currently represented in the SDZWA Frozen Zoo® or listed as “<em>Threatened</em>” under the IUCN Red List, but assessed by Foden <em>et al.</em> (2013) as highly vulnerable to climate change. This dataset also shows their presence in the global zoo and aquarium community, as represented by Species360 members. Provided in .csv format, variables include:</p> <ul> <li><strong>Class: </strong>The taxonomic class of the species</li> <li><strong>IUCN Name: </strong>The taxonomic name of the species (genus and epithet) according to the IUCN Red List</li> <li><strong>CC Vulnerability:</strong> The listing of the species as being highly vulnerable to climate change by Foden <em>et al</em>. 2013 (all species are vulnerable = H)</li> <li><strong>IUCN Status: </strong>The IUCN Red List status of the species (excluding VU, EN, or CR)</li> <li><strong>ZIMS:</strong> The presence (1) or absence (0) of the species from Species360 member zoos and aquariums</li> </ul> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We sincerely thank the San Diego Zoo Wildlife Alliance and Species360 member institutions for their support and data input. This research was funded by the Irish Fulbright Commission 2018/2019 to A.M., the Irish Research Council Laureate Awards 2017/2018 IRCLA/2017/60 to Y.M.B. D.A.C. and J.S. were funded by Species360, the University of Southern Denmark and the Species360 Conservation Science Alliance sponsors: the World Association of Zoos and Aquariums (WAZA), Mandai Wildlife Reserve, and Copenhagen Zoo. </p> <p> </p> <p><strong>Disclaimer</strong></p> <p>Despite our best efforts at screening the data for errors and inconsistencies, some information could be erroneous. Similarly, data collected from the various conservation assessment schemes, and those contained within ZIMS, could contain errors or reporting failures. For example, ZIMS data are are based on submitted records from individual institutions, and are not subject to editorial verification, potentially permitting errors or failure to update species holdings etc. Despite this, ZIMS represents the only global database of zoo collection composition records, and as a result, is used by the IUCN, Convention on International Trade in Endangered Species (CITES), the Wildlife Trade Monitoring Network (TRAFFIC), United States Fish and Wildlife Service (USFWS) and Department for Environment, Food and Rural Affairs (DEFRA). </p> <p> </p> <p><strong>Credit</strong></p> <p>If you use this dataset, please cite the corresponding publication:</p> <p>Mooney, A., Ryder, O. A., Houck, M. L., Staerk, J., Conde, D. A., & Buckley, Y. M. (2023). Maximizing the potential for living cell banks to contribute to global conservation priorities. <em>Zoo Biology</em>, 1– 12. <a href="https://doi.org/10.1002/zoo.21787">https://doi.org/10.1002/zoo.21787</a></p>
Internet of Laboratories - Live Demonstration
<p>A video recording of a live demonstration of an experiment that has been performed during the JRC workshop "Supporting a glocal energy transition: from local energy communities to global simulation networks". It is the result of a long-term collaboration with our research partners: RWTH Aachen and the members of the ENET RT-lab in the ENSIEL consortium (Politecnico di Torino, Università di Genova, Politecnico di Bari and Università di Napoli Federico II).</p>
Confocal and STED Live F-actin dataset
<p>Paired confocal and STED images of F-actin nanostructures in living neurons using the far-red fluorogenic dye SiR-Actin. This dataset was used to train and test the TA-GAN model for confocal-to-STED super-resolution of axonal and dendritic F-actin in living neurons (<a href="https://doi.org/10.1101/2021.07.19.452964">Resolution Enhancement with a Task-Assisted GAN to Guide Optical Nanoscopy Image Analysis and Acquisition</a>).</p> <p>All images : 20 nm/pixel.</p> <p>Folders:<br> - train : 753 pairs of confocal/STED images (varying sizes)<br> - valid : 47 pairs of confocal/STED images (varying sizes)<br> - test_initial & test_final : 84 confocal/STED pairs acquired before (initial) and 84 acquired after (final) control sequences where 15 confocal images of the full FOV (500 x 500 pixels = 10μm x 10μm) were acquired at 1 frame/minute. In addition to the confocal image, a sub-region (100 x 100 pixels = 2μm x 2μm) was selected outside the central ROI (300 x 300 pixels = 6μm x 6μm) and acquired with the STED modality at every time step; the signal decrease due to photobleaching effects can therefore be more prononced in the border region outside the central ROI.<br> - test_series : contains 149 series of images acquired with TA-GAN assistance using the change-based Dice coefficient threshold or the variability-based threshold. </p> <p>The test_series folder contains folders with names corresponding to "[date of acquisition]_cs[coverslip number]_ROI[selected region number]". Each folder contains three subfolders : input, full_STED, and initial_final_confocal. <br> - Input : this folder contains three-channel images for each of the 15 frames in the series. The first channel is the full FOV confocal image (10μm x 10μm), the second channel is the STED sub-region (2μm x 2μm) with zero-padding to match the shape of the FOV, and the third channel is a decision map of 0s and 1s, with the 1s indicating the position in the FOV of the STED sub-region.<br> - full_STED : this folder contains all the STED FOVs (10μm x 10μm) acquired when triggered by the TA-GAN assistance. The number of full_STED FOVs varies from 0 to 15 per region, with a mean of 2.8 STED images per series. The full FOV STED images acquired before (initialSTED.tif) and after (finalSTED.tif) the series of 15 frames are also included.<br> - initial_final_confocal : The full FOV confocal images acquired before (initialConfocal.tif) and after (finalConfocal.tif) the series of 15 frames.</p>
ROADMAP Technical Abstract Video: The Living Labs
<p>The Living Labs are one of the pillars of the ROADMAP project, which is focused on the responsible use and reduction of antimicrobials in livestock production. In this video, you will have the chance to get to know better how a Living Lab works, its importance in the process of getting awareness of AMU (antimicrobial use) and how tools are given to farmers in order to implement good practices, recommendations and acknowledging other ways of improving animal health and welfare.</p> <p>Watch the video here: https://youtu.be/afXe1eHX2lM</p>
Dataset for "Blue-shift photoconversion of near-infrared fluorescent proteins for labeling and tracking in living cells and organisms"
<p>Dataset that supports the observation, characterization and application of the blue-shift photoconversion of the near infrared proteins, miRFPs, reported in the manuscript: "Blue-shift photoconversion of near-infrared fluorescent proteins for labeling and tracking in living cells and organisms". The data references to the specific figures and graphs in the manuscript.</p>
South Portugal Live Fuel Moisture Content (LFMC) dataset
<p>This dataset contains a collection of biweekly LFMC field samples collected between April 2022 and July 2023 over the Alentejo region, South Portugal.<br><br>Metadata:</p> <p>Coordinate Reference System: ETRS_1989_Portugal_TM06 - EPSG 3763<br>File Format: ESRI shapefile<br>Column Fields:</p> <ul> <li>FID - Internal ID</li> <li>Ponto - control point for backup purposes.</li> <li>LFMC - Live fuel moisture content (LFMC) in percentage.</li> <li>DATE - Sample date. AREA - in-situ field name.</li> <li>POINT_X - Longitude.</li> <li>POINT_Y - Latitude.</li> <li>POINT_Z - Altitude.</li> </ul> <p>Fundings:</p> <p>Filippe Santos was supported by the Portuguese Foundation for Science and Technology, I.P (Grant 2022.11960.BD).<br>This research was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Refs. PCIF/MPG/0175/2019), ICT project (Refs. UIDB/04683/2020 and UIDP/04683/2020).</p>
Intimate Partner Violence and Mental Health in Migrant Women Living in Spain
<p>This dataset contains data from a convenience sample in a cross-sectional study of intimate partner violence (IPV) and mental health in migrant women living in the Valencian Community of Spain. IPV was assessed using the Revised Composite Abuse Scale Short Form (CASR-SF), the Revised Scale of Economic Abuse (SEA2) and the Cyber Aggression in Relationship Scale (CARS). Mental health was assessed using the PHQ-9 for symptoms of depression and the GAD-7 for symptoms of anxiety.</p>
University of Kansas Field Station: Forest demography, 1980 – 2015. On ten study plots established on three management units all live trees with a dbh > 7.5 cm (3 in) were identified to species, measured, and tagged. Trees were initially measured in 1980/1981 and re-measured in three successive time periods: 1993/95; 2002/03; and 2014/15. Trees will be measured again in 2025/26.
In 1980 researchers at the University of Kansas initiated a long-term experiment monitoring the composition of oak-hickory forest communities at the University’s field station near Lawrence, Kansas. The purpose of the study was to determine how forest species composition varied temporally across distinct habitats that varied in topography, elevation, sun exposure, management history and successional stage. Ten permanent sites were sampled approximately each decade with data collection periods of 1980/81, 1993/95, 2002/03, and 2014/15. Trees with a minimum diameter at breast height (dbh) of ≥ 7.5 cm were tagged, identified to species and measured. Trees will be measured again in 2025/26.
Aboveground Live Biomass (2008), Andrews Experimental Forest
The biomass raster was developed by equations in (Seidl, et al 2012). Lidar variables used to create the raster include 95th percentile height, bare earth elevation, and the standard deviation of height in a 35m moving window. Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data from HJ Andrews and the Willamette National Forest (NF) on August 10th and 11th 2008. Total area for this AOI is 17,705 acres. The total area of delivered LiDAR including 100 m buffer is 19,493 acres.
Tree regeneration after fire: Delta 1994 burn surveys, live spruce seedling diameters
Data for this study were collected in 2001 and 2002 by Jill Johnstone (University of Alaska Fairbanks) and Eric Kasischke (University of Maryland). Sites were located within the perimeter of the 1994 burn southeast of Delta Junction Alaska, USA, bordering the Alaska Highway to the North and the Gerstle River to the West. Sites were selected from satellite classifications prepared by Eric Kasischke to represent different levels of burn severity and post-fire vegetation canopy greenness (NDVI). Site selection was constrained by road access, and only areas where all trees had been killed by the fire were selected. At each site, a central point was located in an area of visually homogeneous vegetation. Five parallel transects, each 50 m long, were laid out as follows: 1) the first transect started at the central point and followed a randomly-selected compass direction, 2) two additional transects were established parallel to the first, but at a random distance from the central transect up to 25 m distant. Vegetation was sampled in a 2-m wide belt centered on each transect, and soil samples were made at intervals along the transect line. Vegetation measurements included: a) basal diameters of all pre-fire trees greater than 1.3 m in height, b) counts of all post-fire tree seedlings, and c) basal diameters of tree seedlings and willows, measured in a randomly chosen 5x2 m portion of each transect. General notes were made on visual percent cover of different vegetation growth forms at the site. Destructive measurements of tree seedlings and willows made in 2001 were used to develop allometric equations to predict dry biomass from basal diameter. Measurements of soil organic layer depth were made at 5 m intervals with the use of a spade to excavate small chunks of sod. At one randomly-selected sample point per transect, a 10x10 cm sample of the organic layer was collected for bulk density measurements. Bulk density samples were dried in a 60degC oven for 48 hours and then w
Tree regeneration after fire: Delta 1994 burn surveys, live aspen seedling diameters
Data for this study were collected in 2001 and 2002 by Jill Johnstone (University of Alaska Fairbanks) and Eric Kasischke (University of Maryland). Sites were located within the perimeter of the 1994 burn southeast of Delta Junction Alaska, USA, bordering the Alaska Highway to the North and the Gerstle River to the West. Sites were selected from satellite classifications prepared by Eric Kasischke to represent different levels of burn severity and post-fire vegetation canopy greenness (NDVI). Site selection was constrained by road access, and only areas where all trees had been killed by the fire were selected. At each site, a central point was located in an area of visually homogeneous vegetation. Five parallel transects, each 50 m long, were laid out as follows: 1) the first transect started at the central point and followed a randomly-selected compass direction, 2) two additional transects were established parallel to the first, but at a random distance from the central transect up to 25 m distant. Vegetation was sampled in a 2-m wide belt centered on each transect, and soil samples were made at intervals along the transect line. Vegetation measurements included: a) basal diameters of all pre-fire trees greater than 1.3 m in height, b) counts of all post-fire tree seedlings, and c) basal diameters of tree seedlings and willows, measured in a randomly chosen 5x2 m portion of each transect. General notes were made on visual percent cover of different vegetation growth forms at the site. Destructive measurements of tree seedlings and willows made in 2001 were used to develop allometric equations to predict dry biomass from basal diameter. Measurements of soil organic layer depth were made at 5 m intervals with the use of a spade to excavate small chunks of sod. At one randomly-selected sample point per transect, a 10x10 cm sample of the organic layer was collected for bulk density measurements. Bulk density samples were dried in a 60degC oven for 48 hours and then w
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.