Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
570
datasets available to search
ShareScore release 0.9.0
Dataset results
570 results for “threats”
Dynamic_Passive_Threat
Open the record for dataset details and reuse information.
Dataset: The Role of News Consumption on Influencers' Facebook Pages in Threat Perception and Political Conservatism During Times of COVID-19: A Comparative Study between the USA, Spain, and Egypt
<p>Este archivo ofrece los datos en bruto de una encuesta examina el impacto del consumo de noticias en las páginas de Facebook de los influencers en la motivación del conservadurismo político durante amenazas como el terrorismo o las pandemias. Muestra: N=1309, jóvenes de entre 18 y 35 años en Estados Unidos, España y Egipto. Trabajo de campo realizado entre el 10 de agosto de 2021 y el 5 de septiembre de 2021.</p> <p><span>Dataset correspondiente al proyecto El rol de la ciudadanía en la comunicación política digital CI-COMPOL (PID2020-119492GB-I00) financiado por MCIN/AEI/10.13039/501100011033/. IP: Andreu Casero-Ripollés, Departamento de Ciencias de la Comunicación, Universitat Jaume I de Castellón</span></p>
Deliverable T2.2 soil threats and soil ecosystem services of interest in SERENA.xlsx
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales. </p> <p>In T2.2 we discussed the definitions of soil threats (ST) and soil-based ecosystem services (SES) to be further analysed in SERENA. In this process we kept information from the literature review and the results of the national prioritisation of ST and SES. This dataset description is an Excel with sheets of literature search and national prioritisation from the participating countries. Please read metadata at the fist sheet. Furthermore, the last sheet shows the results of our discussion on definitions that we had to clarify before the prioritisation. </p>
Review of existing modelling studies focusing on specific soil-based ecosystem services (SES) and threats (ST) including climate change, management and land use change scenarios.
<p><span>We </span><span>reviewed existing modelling studies focusing on soil ecosystem services (SES) and soil threats (ST) including climate change, land use change and management scenarios. A publication has been submitted and is currently being reviewed. The title of the manuscript is: </span><span>Assessing and mapping soil ecosystem services and soil threats changes in agroecosystems through scenario-based approaches – a systematic review. </span></p> <p><span>Work was split between various authors. All Co-authors were working on either one or more SES or one ST. Excel sheets were prepared by INRA and BFW to ensure the comparability of results that members extracted from the papers found. Literature search was done in Scopus and Web of Science. The final list of related publications is reported here. <br></span></p>
Dataset. Responses to digital disinformation as part of hybrid threats: an evidence-based analysis on the effects of disinformation and the effectiveness of fact-checking/debunking
<p>Dataset from the meta-analysis carried out in the article Responses to digital disinformation as part of hybrid threats: a systematic review on the effects of disinformation and the effectiveness of fact-checking / debunking using the EU-HYBNET Meta-Analysis Survey Instrument for Evaluating the Effects of Disinformation and the Effectiveness of counter-responses</p>
The commitment to global sea level rise over the next 500 years: exploring the threat of the Antarctic Ice Sheet to coastal infrastructure
<p>Within Australia alone, more than A$226 billion of coastal infrastructure is vulnerable to the anticipated rise in sea level by the end of the century. The IPCC Fifth Assessment Report concludes that the likely increase in global mean sea level during the 21st century ranges from 26-55 centimetres (under the low-end RCP2.6 climate scenario) to 45-82 centimetres (under the high-end RCP8.5 climate scenario). However, these projections do not take into account the potential for collapse of the marine-based sectors of the Antarctic Ice Sheet.</p> <p>Recent evidence has indicated that the IPCC projections may be under-estimates, with sea level increases of up to 2.5 metres possible by the end of the 21st century. Modelling studies have also demonstrated the potential for the Antarctic Ice Sheet to undergo irreversible collapse during the coming centuries, leading to dramatic increases in global sea level on time scales relevant to critical coastal infrastructure such as refineries and airports. The most extreme prediction is that Antarctica could contribute 15.65±2.00 metres to global sea level by the year 2500.</p> <p>Here, we combine climate modelling and ice sheet modelling to explore the evolution of the Antarctic Ice Sheet over the next 500 years under a range of climate scenarios. We run the models many times to take into account gaps in our understanding of ice sheet dynamics. This allows us to generate robust projections of the Antarctic contribution to global sea level from the present to the year 2500, complete with quantified confidence intervals. We conclude that the sea level contribution during the 21st century will be modest, consistent with the IPCC Fifth Assessment Report, but that melting of the Antarctic Ice Sheet will accelerate thereafter. By the year 2500, we predict that the Antarctic contribution to global sea level will be at least 5 metres.</p>
Effects of intolerance of uncertainty on subjective and psychophysiological measures during threat acquisition and delayed threat extinction
<p>This dataset includes measurements of intolerance of uncertainty (Intolerance of Uncertainty Scale [Freeston et al., 1994]), trait anxiety (State-Trait Anxiety Inventory [Spielberger et al., 1983]), skin conductance response (SCR), fear potentiated startle (FPS) and fear ratings (RAT) acquired in a differential fear conditioning paradigm with habituation and threat acquisition training on one day and extinction training, mood induction (by presenting negative vs. neutral slides), re-extinction training, reinstatement and reinstatement-test 24h later. Overall, 66 participants (female = 44, aged between 18 and 40 years, M = 25.76, SD = 5.82) took part in the study. Several participants had to be excluded due to technical issues (n = 3), non-responding (SCR: n = 2; auditory startle blink: n = 1) and no SCRs to the CSs (n = 1). Visual CSs were two shapes resembling snowflakes. The US consisted of a train of three 2 ms electrotactile square-waves (inter stimulus interval, ISI: 50 ms) and was delivered 7.9 s after each CS+ onset (100% reinforcement rate) during threat acquisition training and three times during reinstatement. The duration of the ITIs ranged from 10 to 13 s (M = 11.5). For SCR measurements, a 1 Hz lowpass filter and a gain of 5 or 10 μΩ were applied. SCR data were scored by using the semi-automatic scoring system Autonomate (Green et al., 2014), down sampled to 10 Hz and scored as the first response within 0.9 to 4 s after CS onset as SCR from trough to peak with a maximum rise time of 5 s. SCRs were square root transformed to reduce skew and z-scored within individuals across trials for day 1 and day 2 separately. To elicit the auditory startle blink, a 95 dB white noise burst was presented simultaneously on both ears. Startle probes were administered 6 or 8 s after the ITI-onset and 6 or 7 s after CS-onset. A gain of 5000 at 1000 Hz and a band-pass filter (28–500 Hz) were applied. Data were rectified and integrated online (averaged over 20 samples) and scored semi-automatically by using a custom-made computer program (EDA View, developed by Prof. Dr. Matthias Gamer, University of Würzburg) as trough to peak 20–120 ms after startle probe onset. For analyses, FPS data was z-scored within individuals across trials for day 1 and day 2 separately. To acquire fear ratings, participants rated throughout the experiment, how much stress, fear, and tension they experienced, when they last saw the CSs. Answers had to be logged in via button press within 7 s on a visual analog scale (VAS) ranging from zero (answer = none) to 100 (answer = maximum). Unlogged ratings were considered as missing values.</p>
Scanning the horizon for invasive plant threats using a data-driven approach
<p>This repository holds the data and code for the manuscript "Scanning the horizon for invasive plant threats using a data-driven approach". </p> <p><strong>Contents</strong></p> <ul> <li>code: descriptions below</li> <li>data: descriptions below</li> <li>intermediate-data: datasets produced by processing original data (see code) or produced through horizon scan process (descriptions below)</li> <li>fl-plants-horizon-scan.Rproj: RStudio project for running R scripts</li> </ul> <p> </p> <table> <thead> <tr> <th scope="col">code</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>gcw_processing.R</td> <td>R script to format data downloaded from the Global Compendium of Weeds</td> </tr> <tr> <td>native_introduced_ranges.R</td> <td>R script to create map of native and introduced ranges of taxa on the final list</td> </tr> <tr> <td>random_draws_plant_families.R</td> <td>R script to evaluate over- and underrepresentation of plant families in initial and final list</td> </tr> <tr> <td>review_process_comparison.R</td> <td>R script to evaluate differences in scores before and after peer-review and consensus-building</td> </tr> <tr> <td>scores_certainty_pathways.R</td> <td>R script to create figures of scores, certainty, and pathways for final list</td> </tr> <tr> <td>risk_scores_analys.R</td> <td>R script to evaluate final risk scores</td> </tr> <tr> <td>pathways_process.R</td> <td>R script to process pathways to introduction data</td> </tr> <tr> <td>taxa_list_processing.R</td> <td>R script to create list used for rapid risk assessments from an initial list</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">data</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>cab_list_full.csv</td> <td>list of potential invasive species to Florida generated by CABI Horizon Scan Tool on November 15, 2019</td> </tr> <tr> <td>GCW_full_list_020420.csv</td> <td>Global Compendium of Weeds downloaded on February 4, 2020</td> </tr> <tr> <td>PlantAtlasDataExport-20191211-194219.csv</td> <td>Atlas of Florida plants downloaded December 11, 2019</td> </tr> <tr> <td>Taxon_x_List_GloNAF_vanKleunenetal2018Ecology_121119.csv</td> <td>GloNAF 1.2 database downloaded December 11, 2019</td> </tr> <tr> <td>the-plant-list</td> <td>The Plant List Database downloaded August 3, 2021</td> </tr> </tbody> </table> <p> </p> <table> <thead> <tr> <th scope="col">intermediate-data</th> <th scope="col">description</th> </tr> </thead> <tbody> <tr> <td>federal_noxious_weed_list.csv</td> <td>manually formatted version of the USDA Federal Noxious Weed List downloaded March 16, 2020</td> </tr> <tr> <td>first_round_assessments_050120.csv</td> <td>rapid risk assessments for horizon scan pre-peer-review</td> </tr> <tr> <td>fl_prohibited_plants.csv</td> <td>manually compiled list of prohibited plants in Florida based on the Florida Noxious Weed List, Florida Prohibited Plants list, and Florida Invasive Species Council (all downloaded March 9, 2020)</td> </tr> <tr> <td>horizon_scan_plants_full_reviews_080321.csv</td> <td>rapid risk assessments for horizon scan post-peer-review and consensus-building</td> </tr> </tbody> </table> <p> </p>
DNS Threats Dataset
<p>The dataset contains Normal, DGA and Tunneling domain names: i. the total number of normal domains are conformed by the Alexa top one million domains, 3,161 normal domains provided by the Bambenek Consulting feed, and another 177,017 normal domains; ii. the DGA domains were obtained from the repositories of DGA domains of Andrey Abakumov and John Bambenek, corresponding to 51 different malware families; iii. the DNS Tunneling consist of 8000 tunnel domains generated using a set of well known DNS tunneling tools under laboratory conditions: iodine, dnscat2 and dnsExfiltrator.</p> <p>The dataset is described in the paper:<br> Palau, F., Catania, C., Guerra, J., García, S. J., & Rigaki, M. (2019). Detecting DNS threats: A deep learning model to rule them all. In XX Simposio Argentino de Inteligencia Artificial (ASAI 2019)-JAIIO 48 (Salta).</p>
Evidence for Early Mesozoic diversification of Hypsimetopidae Nicholls, 1943 (Isopoda), with the description of a new genus from Andhra Pradesh and notes on threats to Indian cave environments
<p>Datafiles and scripts for https://doi.org/10.1093/jcbiol/ruac052</p> <p>Evidence for Early Mesozoic diversification of Hypsimetopidae Nicholls, 1943 (Isopoda), with the description of a new genus from Andhra Pradesh and notes on threats to Indian cave environments</p> <p>George D. F. Wilson1,2 and Shabuddin Shaik 3</p> <p>1 Saugatuck Natural History Laboratory, Saugatuck, MI, USA; gdfw@snhlab.com</p> <p>3 Department of Life Science, Central University of Karnataka, Kadaganchi, 585 367, India; shabu.biologist@gmail.com</p> <p>2 Corresponding author: George D. F. Wilson, P. O. Box 714, Saugatuck, Michigan 49453, USA. e-mail: gdfw@snhlab.com </p> <p>File List:</p> <p>Phreatoi20220525.nex <br> Mesquite data file that contains all data from the DELTA taxonomic database that were used for data presentation, organization, analysis, as well as trees resulting from all analyses. For Mesquite version 3.70; Maddison WP, Maddison DR. 2021. Mesquite: a modular system for evolutionary analysis. Version 3.6 University of British Columbia & Oregon State University., http://www.mesquiteproject.org/ <br> <br> The DELTA database is still being edited and changed so it is not included here<br> For DELTA, see website https://www.delta-intkey.com/<br> publications:<br> Dallwitz MJ. 1980. A general system for coding taxonomic descriptions. TAXON 29: 41-46.<br> Dallwitz MJ, Paine TA, Zurcher EJ. 2000. User's guide to the DELTA system: a general system for processing taxonomic descriptions. CSIRO: Canberra.</p> <p> <br> Phreatoi20220525.tnt - the TNT data file generated by Mesquite<br> Analyses were performed using TNT-64bit, version 1.5, Goloboff PA, Catalano SA. 2016. TNT version 1.5, including a full implementation of phylogenetic morphometrics. Cladistics 32: 221-238.<br> Note: TNT counts zero as a number so the first tree, taxon or k paramter is 0, the second is 1, the third is 2 and so on </p> <p>TNT Scripts were written or modified for this project by George D. F. Wilson. They were run using the console in Ubuntu 20.04 but should work using the console version of TNT in other operating systems available from http://www.lillo.org.ar/phylogeny/tnt/. I recommend using the console because it allows you do to multiple analysis with one script. </p> <p>Each script has a banner that explains what is being done. If this fails to appear the first time, enter n and restart the script</p> <p>These are easily modified in a text editor to change the analysis<br> -- tnt.run : standard run of tnt. <br> -- tnt-jacK.run : symmetric jackknife analysis with concavity parameter, select file, concavity and prob parameter <br> -- piwe_rangeK.run : A range of concavity parameters are selected at the beginning and run sequentially<br> -- setk_trans.run : Modified from setk.run by Salvador Arias, Instituto Miguel Lillo, San Miguel de Tucuman, Argentina<br> -- aquickie_bt1000.run : Modified from the standard script distributed with TNT with more iterations of jackknifing<br> <br> If you are new to using TNT, see the information available on http://www.lillo.org.ar/phylogeny/tnt/ as well as these articles:<br> Goloboff PA. 1993. Estimating character weights during tree search. Cladistics 9: 83-91.<br> Goloboff PA. 1997. Self-Weighted Optimization: Tree Searches and Character State Reconstructions under Implied Transformation Costs. Cladistics 13: 225-245.<br> Goloboff PA, Carpenter JM, Arias JS, Esquivel DRM. 2008. Weighting against homoplasy improves phylogenetic analysis of morphological data sets. Cladistics 24: 758-773.<br> Goloboff PA, Catalano SA. 2016. TNT version 1.5, including a full implementation of phylogenetic morphometrics. Cladistics 32: 221-238.<br> Goloboff PA, Farris JS. 2001. Methods for Quick Consensus Estimation. Cladistics 17: S26-S34.<br> Goloboff PA, Farris JS, Källersjö M, Oxelman B, Ramírez MJ, Szumik CA. 2003. Improvements to resampling measures of group support. Cladistics 19: 324-332.<br> Goloboff PA, Farris JS, Nixon KC. 2008. TNT, a free program for phylogenetic analysis. Cladistics 24: 774-786.</p>
Dataset and Source Code for the Paper: A Framework for Developing Strategic Cyber Threat Intelligence from Advanced Persistent Threat Analysis Reports Using Graph-Based Algorithms
<p>Here are the data set and source code related to the paper: "A Framework for Developing Strategic Cyber Threat Intelligence from Advanced Persistent Threat Analysis Reports Using Graph-Based Algorithms"</p> <p>1- aptnotes-downloader.zip : contains source code that downloads all APT reports listed in https://github.com/aptnotes/data and https://github.com/CyberMonitor/APT_CyberCriminal_Campagin_Collections</p> <p>2- apt-groups.zip : contains all APT group names gathered from https://docs.google.com/spreadsheets/d/1H9_xaxQHpWaa4O_Son4Gx0YOIzlcBWMsdvePFX68EKU/edit?gid=1864660085#gid=1864660085 and https://malpedia.caad.fkie.fraunhofer.de/actors and https://malpedia.caad.fkie.fraunhofer.de/actors</p> <p>3- apt-reports.zip : contains all deduplicated APT reports gathered from https://github.com/aptnotes/data and https://github.com/CyberMonitor/APT_CyberCriminal_Campagin_Collections</p> <p>4- countries.zip : contains country name list.</p> <p>5- ttps.zip : contains all MITRE techniques gathered from https://attack.mitre.org/resources/attack-data-and-tools/</p> <p>6- malware-families.zip : contains all malware family names gathered from https://malpedia.caad.fkie.fraunhofer.de/families</p> <p>7- ioc-searcher-app.zip : contains source code that extracts IoCs from APT reports. Extracted IoC files are provided in report-analyser.zip. Original code repo can be found at https://github.com/malicialab/iocsearcher</p> <p>8- extracted-iocs.zip : contains extracted IoCs by ioc-searcher-app.zip</p> <p>9- report-analyser.zip : contains source code that searchs APT reports, malware families, countries and TTPs. I case of a match, it updates files in extracted-iocs.zip.</p> <p>10- cti-transformation-app.zip : contains source code that transforms files in extracted-iocs.zip to CTI triples and saves into Neo4j graph database.</p> <p>11- graph-db-backup.zip : contains volume folder of Neo4j Docker container. When it is mounted to a Docker container, all CTI database becomes reachable from Neo4j web interface. Here is how to run a Neo4j Docker container that mounts folder in the zip:</p> <p>docker run -d --publish=7474:7474 --publish=7687:7687 --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/data:/data --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/plugins:/plugins --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/logs:/logs --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/conf:/conf --env 'NEO4J_PLUGINS=["apoc","graph-data-science"]' --env NEO4J_apoc_export_file_enabled=true --env NEO4J_apoc_import_file_enabled=true --env NEO4J_apoc_import_file_use__neo4j__config=true --env=NEO4J_AUTH=none neo4j:5.13.0</p> <h4><strong>web interface: http://localhost:7474</strong></h4> <h4><strong>username: neo4j</strong></h4> <h4><strong>password: neo4j</strong></h4> <p> </p>
STOP-IT Cyber Threat Sharing Service (CTSS)
<p>The Cyber Threat Sharing Service collects sources of existing threats from relevant feeds, and structuring the information using standards to facilitate the exchange of the security threats identified (e.g. MITRE, OASIS). Personalized alerts and relevant information can be provided according to the subscription parameters the CI has requested. This service ensures the mitigation of threats to CI; enhances the coordination within CI establishing exchange methods to prevent, reduce, mitigate and recover from existing threats; and allows the coordination between similar centres in the world to deal with CI threats in a global approach.</p>
Dataset for Advanced Persistent Threat (APT) Attacks on Power Substation Networks via GOOSE Protocol Exploitation
<p>This dataset captures network traffic from a simulated Advanced Persistent Threat (APT) campaign targeting a power substation's communication network. The attacker maintains a prolonged presence within the network, conducting low-profile scans using Nmap to stealthily discover the network configuration. The focus is on the communication between the Remote Terminal Unit (RTU), the Programmable Logic Controller (PLC), and the Bay Protection Unit, all of which utilize the Generic Object Oriented Substation Event (GOOSE) protocol for critical operations.</p>
SAPPAN: Advanced Threat Data
<p>The data were acquired from a simulated environment consisting of two Windows clients, a Windows server, a Linux host, and a Linux router whose connection diagram can be found in the <a href="https://zenodo.org/record/5547862/files/infrastructure.png">infrastructure.png</a> file. One attack scenario was performed in this environment, and data relevant to this attack are uploaded as this dataset.</p> <p>The advanced attack scenario follows our previous experiment (see <a href="https://zenodo.org/record/4159878">SAPPAN: Combined Network and Host Data</a>), where the initial compromise of a host from outside has already been carried out. The scenario starts by running the code on Workstation1 and extracting the data, followed by a lateral movement to Workstation2, where the data is also extracted. The scenario ends with the deactivation of all implants. A detailed description of the scenario can be found in the <a href="https://zenodo.org/record/5547862/files/test_protocol.xlsx">test_protocol.xlsx</a> file.</p> <p>The scenario is inspired by the first scenario described in <a href="https://attackevals.mitre-engenuity.org/enterprise/apt29/operational-flow">APT29 Evaluation: Operational Flow</a> and <a href="https://github.com/mitre-attack/attack-arsenal/tree/master/adversary_emulation/APT29/Emulation_Plan/Day%201">APT29 Day 1 (Steps 1 through 10)</a>. However, in order to better showcase analyses relevant to the SAPPAN project, we have chosen a different C2 framework (POshC2 instead of Pupy RAT) and performed certain steps concerning code execution, downloading and exfiltrating data differently.</p> <p>The dataset consists of the following data:</p> <ul> <li><a href="https://zenodo.org/record/5547862/files/infrastructure.png">infrastructure.png</a> - Schema of the artificial infrastructure</li> <li><a href="https://zenodo.org/record/5547862/files/test_protocol.xlsx">test-protocol.xlsx</a> - Detailed protocol of the captured attack</li> <li><a href="https://zenodo.org/record/5547862/files/network_traffic_capture.pcap">network_traffic_capture.pcap</a> - Full packet capture (PCAP format) of all network traffic passing through firewall host</li> <li><a href="https://zenodo.org/record/5547862/files/RDR-data.zip">RDR-data.zip</a> - Raw event data (JSON format) from all Windows host with the following attributes: <ul> <li>time - the time when the sensor recorded the event</li> <li>event_type - the type of the event</li> <li>host - info about the host machine (name and OS version)</li> <li>event - event type-specific payload</li> </ul> </li> </ul>
Corticolimbic Response to Threat and Recollected Ages of Exposure to Childhood Maltreatment
<p>Data files indicating regional BOLD fMRI response of young adults to negative (angry or fearful) faces versus neutral faces in Hariri amygdala activation face matching task.</p> <p>MACE_scores_BOLD_fMRI_amyg_hipp.csv - Contains overall BOLD fMRI response to negative minus neutral faces in bilateral amygdala, hippocampus, fusiform gyrus, inferior frontal gyrus pars triangularis, ventromedial prefrontal cortex, dorsomedial prefrontal cortex and anterior cingulate cortex as well as Maltreatment and Abuse Chronology of Exposure scores for severity of exposure to 10 types of childhood maltreatment across each age of childhood and parameters for age, sex, parental education and childhood financial sufficiency.</p> <p>Early_vs_late_maltreatment_BOLD_fMRI_amyg_hipp_pfc_fusiform_for_mixed_model.xlsx - Data in long format indicating for each participant baseline adjusted BOLD fMRI response to negative minus neutral faces at each TR interval for amygdala, hippocampus, fusiform gyrus, inferior frontal gyrus pars triangularis, ventromedial prefrontal cortex, dorsomedial prefrontal cortex and anterior cingulate cortex with participants classified as having experienced no maltreatment, only early childhood maltreatment on only late childhood maltreatment based on type / time predictors for each region.</p> <p>Early_vs_late_maltreatment_regional_fMRI_response_negative_vs_neutral_faces.xlsx - Individual participant baseline adjusted data for response to negative faces and neutral faces at each TR interval for amygdala, hippocampus, fusiform gyrus, inferior frontal gyrus pars triangularis, ventromedial prefrontal cortex, dorsomedial prefrontal cortex and anterior cingulate cortex with each participant classified as having experienced no maltreatment, only early childhood maltreatment or only late childhood maltreatment based on region specific definitions.</p> <p>Early_vs_late_maltreatment_time_course_BOLD_fMRI_regional_response.xlsx - Group means and sem for baseline adjusted BOLD fMRI response to negative minus neutral faces at each TR interval for amygdala, hippocampus, fusiform gyrus, inferior frontal gyrus pars triangularis, ventromedial prefrontal cortex, dorsomedial prefrontal cortex and anterior cingulate cortex based on region specific groupings classifications as having experienced no maltreatment, only early childhood maltreatment on only late childhood maltreatment.</p> <p>Early_vs_late_maltreatment_time_course_regional_response_negative_vs_neutral_faces.xlsx - Group means and sem for baseline adjusted BOLD fMRI response to negative faces and neutral faces at each TR interval for amygdala, hippocampus, fusiform gyrus, inferior frontal gyrus pars triangularis, ventromedial prefrontal cortex, dorsomedial prefrontal cortex and anterior cingulate cortex based on region specific groupings classifications as having experienced no maltreatment, only early childhood maltreatment on only late childhood maltreatment.</p> <p> </p>
Climate change threats to the global functional diversity of freshwater fish
<p>This dataset provides supplementary information for the paper entitled "Climate change threats to the global functional diversity of freshwater fish".</p> <p> </p> <p><strong>Fish trait data</strong></p> <p>fish_traits_removed.csv<br> - species with missing trait values were removed<br> - species coverage: 3,792</p> <p>fish_traits_imputed.csv<br> - missing trait values were imputed<br> - species coverage: 11,425</p> <p>Traits<br> - HLrel = relative head length<br> - BDrel = relative body depth<br> - Troph = trophic level<br> - K = relative growth rate</p> <p><br> <strong>Geospatial data</strong></p> <p>Files<br> Data under the assumption of no dispersal<br> - SR.tif: species richness<br> - FRic.tif: functional richness<br> - FEve.tif: functional evenness<br> - FDiv.tif: functional divergence<br> - FRic_loss.tif: functional richness loss<br> - FEve_loss.tif: functional evenness loss<br> - FDiv_loss.tif: functional divergence loss</p> <p>Data under the assumption of maximal dispersal<br> - SR_dispersal.tif: species richness<br> - FRic_dispersal.tif: functional richness<br> - FEve_dispersal.tif: functional evenness<br> - FDiv_dispersal.tif: functional divergence<br> - FRic_loss_dispersal.tif: functional richness loss<br> - FEve_loss_dispersal.tif: functional evenness loss<br> - FDiv_loss_dispersal.tif: functional divergence loss</p> <p>Layers<br> - imp_*: missing trait values were imputed<br> - rem_*: species with missing trait values were removed<br> - *_hist: historical reference scenario<br> - *_1p5: warming level of 1.5°C<br> - *_2p0: warming level of 2.0°C<br> - *_3p2: warming level of 3.2°C<br> - *_4p5: warming level of 4.5°C</p> <p>Spatial resolution: 0.08333333, 0.08333333 (x, y)<br> Spatial extent: -180, 180, -60, 85 (xmin, xmax, ymin, ymax)<br> Coordinate reference system: WGS84</p>
Relyea, R. A. 2000. Trait-mediated indirect effects in larval anurans: Reversing competition with the threat of predation. Ecology 81:2278-2289.
Ecologists recently have been focusing on the role that trait-mediated indirect effects can have on community structure and composition. To date, this work has primarily focused on the effects of predator-induced behavioral plasticity on communities. However, predator-induced morphological plasticity, which has been documented in many taxa, might also lead to trait-mediated indirect effects. Here, I examined how predators altered the behavior and morphology of larval wood frogs (Rana sylvatica) and leopard frogs (R. pipiens) and how these phenotypic changes altered the outcome of competition between the two species. Competition in the absence of caged predators was asymmetric; when reared separately, leopard frogs grew more than wood frogs, but when competing (without predators), wood frogs grew faster than leopard frogs. The presence of caged predators reversed the outcome of competition between the two anuran prey. In the presence of larval dragonflies (Anax spp.) or caged mudminnows (Umbra limi), leopard frogs grew faster than wood frogs while total tadpole biomass production remained unchanged. Thus, there was a predator-mediated indirect effect. Because predators alter both the behavior and morphology of larval anurans and both of these traits are known to affect resource consumption and growth, both are potential mechanisms to explain the change in competitive outcome. Changes in behavior were not related to changes in growth, but changes in morphology (specifically mouth width and tail length) were related to changes in growth. When competitors were added (without predators), wood frogs increased their mouth width by 10% and their tail length by 3%, while leopard frogs increased their mouth width by 5% and did not change their tail length. The greater increase in mouth width for wood frogs should increase their forage intake, since tadpoles feed by scraping periphyton; the importance of a 3% longer tail in competitive ability is unknown. The presence of the p
Fig. 3 in Genetic diversity and population structure of Brycon nattereri (Characiformes: Bryconidae): a Neotropical fish under threat of extinction
Fig. 3. Haplotype network based on partial sequencing of the D-loop region (mtDNA) of 92 individuals of Brycon nattereri from the Laranjinha River. Circle sizes are pro- portional to haplotype frequency.
3D Point Cloud of a railway slope - MOMIT (Multi-scale observation and monitoring of railway infrastructure threats) EU project - H2020-EU.3.4.8.3. - Grant agreement ID: 777630
<p>3D point cloud of a railway trench in Lavancia-Épercy (France). The 3D point cloud has been generated from pictures obtained by means of a UAV (DJI Matrice 600 Pro) and processed using Agisoft Metashape. The 3D point cloud is composed of 110,356,682<strong> </strong> million points containing XYZ and RGB information.</p> <p>The original file is in .bin format and is compressed in zip format.</p> <p> </p>
Phylogenetic and Spatial Distribution of Evolutionary Isolation and Threat in Turtles and Crocodilians (Non-Avian Archosauromorphs)
The origin of turtles and crocodiles and their easily recognized body forms dates to the Triassic. Despite their long-term success, extant species diversity is low, and endangerment is extremely high compared to other terrestrial vertebrate groups, with ~ 65% of ~25 crocodilian and ~360 turtle species now threatened by exploitation and habitat loss. Here, we combine available molecular and morphological evidence with machine learning algorithms to present a phylogenetically-informed, comprehensive assessment of diversification, threat status, and evolutionary distinctiveness of all extant species. In contrast to other terrestrial vertebrates and their own diversity in the fossil record, extant turtles and crocodilians have not experienced any mass extinctions or shifts in diversification rate, or any significant jumps in rates of body-size evolution over time. We predict threat for 114 as-yet unassessed or data-deficient species and identify a concentration of threatened crocodile and turtle species in South and Southeast Asia, western Africa, and the eastern Amazon. We find that unlike other terrestrial vertebrate groups, extinction risk increases with evolutionary distinctiveness: a disproportionate amount of phylogenetic diversity is concentrated in evolutionarily isolated, at-risk taxa, particularly those with small geographic ranges. Our findings highlight the important role of geographic determinants of extinction risk, particularly those resulting from anthropogenic habitat-disturbance, which affect species across body sizes and ecologies.
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.