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.
380
datasets available to search
ShareScore release 0.9.0
Dataset results
380 results for “Pressure Data”
Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, pressure, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, fluorescent dissolved organic matter, and turbidity at discrete depths in Falling Creek Reservoir, Virginia, USA in 2018-2025
We monitored water quality in Falling Creek Reservoir (Vinton, Virginia, USA; 37.30325 -79.8373) with high-frequency (10-minute) sensors in 2018-2025. All variables were measured at the deepest site of the reservoir adjacent to the dam. Falling Creek Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. This data product consists of one dataset compiled of depth profiles of water temperature on 1-m intervals from 0.1 to 9 m depth; dissolved oxygen at 5 m and 9 m depth; pressure at 9 m depth; and temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, fluorescent dissolved organic matter, turbidity, and pressure at ~1.6 m depth. The dataset is accompanied by a sensor maintenance log and quality assurance/quality control analysis scripts.
Data and code from Artificial light at night increases top-down pressure on caterpillars: experimental evidence from a light-naive forest - 2021-2022
This dataset has been prepared in support of a paper to be published in Proceedings of the Royal Society B: Biological Sciences. It includes both data files and R scripts used for the analysis in this publication: Deitch, J.F. and S.A. Kaiser. 2023. Artificial light at night increases top-down pressure on caterpillars: experimental evidence from a light-naive forest. Proceedings of the Royal Society B: Biological Sciences. (https://doi.org/10.1098/rspb.2023.0153) Artificial light at night (ALAN) is a globally widespread and expanding form of anthropogenic change that impacts arthropod biodiversity. ALAN alters interspecific interactions between arthropods, including predation and parasitism. Despite their ecological importance as prey and hosts, the impact of ALAN on larval arthropod stages, such as caterpillars, is poorly understood. We examined the hypothesis that ALAN increases top-down pressure on caterpillars from arthropod predators and parasitoids. We experimentally illuminated study plots with moderate levels (10-15 lux) of LED lighting at light-naive Hubbard Brook Experimental Forest, New Hampshire. We measured and compared between experimental and control plots: 1) predation on clay caterpillars and 2) abundance of arthropod predators and parasitoids. We found that predation rates on clay caterpillars and abundance of arthropod predators and parasitoids were significantly higher on ALAN treatment plots relative to control plots. These results suggest that moderate levels of ALAN increases top-down pressure on caterpillars. We did not test mechanisms, but sampling data indicates that increased abundance of predators near lights may play a role. This study highlights the importance of examining the effects of ALAN on both adult and larval life stages and suggests potential consequences of ALAN on arthropod populations and communities. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubba
New Zealand Hikurangi Margin temperature and pressure loggers - data sets.
<p>Description of data</p> <p>In 2019, 14 RBR data loggers were purchased as a supplement to an existing NSF grant, and were tested, calibrated, and deployed on the Hikurangi Subduction Zone margin as part of the Evan Solomon (UW) deployment of flow meters at this site. The purpose of the Solomon pore fluid analysis program was to determine the impact of Slow Slip Tectonic Events on near-surface fluid flow for this active margin. The purpose of the supplemental RBR loggers, attached directly to fluid flow meters, was to add the key components of pressure and temperature to this data set and specifically to identify any sediment slope failures and turbidity flows that occur during the two year deployment period.</p> <p>By May 6, 2021, all of the Solomon flow meters have been recovered with the attached UW supplemental RBR loggers. The loggers were be subjected to a final ice bath calibration test prior to data-download in New Zealand and all T/P data will be returned to UW via internet. The physical data loggers were then be returned to UW via air freight.</p> <p>The data in these Zenodo data archive files include all of the pre-cruise and post-cruise calibrations fro the RBR T/P loggers, the raw and calibrated data, and the locations of the stations. Also included are some infrastructure information including a multi-channel seismic profile showing that locations on the Hikurangi margin with known fault zones, and a published catalogue of earthquakes that occurred during the logger deployment period.</p> <p> </p>
PetrocShelley/Measured-solid-state-and-sub-cooled-liquid-vapour-pressures-of-nitroaromatics-using-KEMS-Data-Set: Measured-solid-state-and-sub-cooled-liquid-vapour-pressures-of-nitroaromatics-using-KEMS-Data-Set
<p>All data files for the Measured solid state and sub-cooled liquid vapour pressures of nitroaromatics using Knudsen effusion mass spectrometry by Shelley et al.</p>
Raw data for: Pressure and inertia sensing drifters for glacial hydrology flow path measurements
<p>Raw data for paper</p> <p>Title: Pressure and inertia sensing drifters for glacial hydrology flow path measurements</p> <p>Authors: A.Alexander, M.Kruusmaa, J.A. Tuhtan, A.J. Hodson, T.V. Schuler, A. Kääb</p> <p>Journal: The Cryosphere</p> <p>Year, 2020</p>
Mammals under pressure: presence data for assessing extinction of endemic, threatened, and mammals subject to use, in Colombia
<p>This is the first dataset that provides a complete compilation of mammal records based on camera traps, human observations, and specimens deposited in biological collections in Colombia. We compiled a dataset with unpublished information, including 97,943 records corresponding to 136 species, of which 38 are endemic, 92 are identified as species subject to use by humans in the literature, and 33 are categorized either as Data Deficient or threatened according to international or unofficial national assessments. The information comes from 31 out of 32 departments of Colombia and constitutes relevant input for future distribution and conservation assessments. Most records (n=96,417, 98.44%) come from non-invasive sampling methods such as camera traps. However, we highlight the contribution of museum specimens (n= 1,332), especially for small and medium-sized species, many of them with restricted distributions in the country. This dataset constitutes a joint collaborative and interinstitutional effort that serves as the basis for cooperative work to comprehensively assess the current conservation status of all mammal species in Colombia.</p>
OpenFOAM cases of the paper "CFD modeling of pressure drop through an OCP server for data center applications"
<p>This dataset contains the<em> underling data</em> for the paper "<em>CFD modeling of pressure drop through an OCP server for data center applications</em>” in Energies Journal.</p> <p>Numerical simulations are performed using open-source CFD code OpenFOAM. Features of the numerical model described in the paper can be summarized as:</p> <ul> <li> A hexahedra (hex) and split-hex mesh was created using <em>snappyHexMesh</em> utility from the STL (Stereolithography) model of the server</li> <li><em>Allrun</em> script runs steady-state simulations for different inlet flow rates given in the <em>flowrates</em> file.</li> <li><em>k-omegaSST</em> turbulence closure model is used</li> <li>Convective and diffusive fluxes are computed using second-order accurate numerical schemes.</li> <li>Resultant matrices are solved using <em>GAMG</em> and <em>smoothSolver</em> methods.</li> </ul> <p>New libraries are developed for the detection of whether the solution reaches state-state and for the calculation of average pressures at the inlet and outlet of the server. These libraries need to be download via the following link and compiled before the cases run: </p> <p><a href="https://github.com/DSTECHNO/OCPFoam">https://github.com/DSTECHNO/OCPFoam</a></p> <p><strong>active_Server.tar.gz:</strong> OpenFOAM files and scripts for the steady-state simulation of turbulent flow flow over Leopard V3.1 model of OCP server neglecting fan blades.</p> <p><strong>inactive_Server.tar.gz:</strong> OpenFOAM files and scripts for the steady-state simulation of turbulent flow over Leopard V3.1 model of OCP server considering fan blades.</p> <p><strong>Results_active_Server.tar.gz:</strong> Simulation results for active server.</p> <p><strong>Results_inactiveServer.tar.gz: </strong>Simulation results for inactive server.</p>
Keystroke timing and pressure data captured during touchscreen typing by early Parkinson's disease patients and healthy controls
<p><strong>DATASET</strong></p> <p>The present dataset comprises keystroke timing and pressure data that correspond to short text excerpts typed by early Parkinson’s disease (PD) patients (n=18) and healthy controls (n=15) on a common touchscreen-equipped smartphone (LG Nexus 5X with a screen of 5.2 inches in diagonal and a resolution of 1080 × 1920 pixels, running native Android 7.0). Subjects were asked to transcribe up to 11 short text excerpts, with the initial one being 200 characters-long and common for all subjects, while the rest were 40-115 characters-long, pseudorandomly drawn from the fairy tale 'The Little Prince'. Data were recorded using a custom Android Operating System input method (keyboard), developed for the purposes of the study. Additional details on exepriment design, material and methods can be found in the related research article mentioned below. </p> <p>Data consist of sequences of raw press and release timestamps (in milliseconds), as well as of values of normalized pressure (0.000-1.000) applied to initiate keystrokes, corresponding to the consecutive keys tapped during the transcription of each text excerpt. Data included in the 'Data' folder are organised in sub-folders per subject. Each sub-folder contains a number of .txt files with each one corresponding to a text excerpt typed by the particular subject. Files are named using the format S##_TEX##.txt, with S## denoting the subject's coded ID and TEX## the serial number of the transcribed text excerpt. For all subjects, file S##_TEX01.txt corresponds to the initial and common 200 characters-long text excerpt. Each file contains the sequences of raw key press/release timestamps (Tp#, Tp#) and normalized pressure (NP#), applied to initiate each keystroke, in the following format:</p> <p>{<br> Press, Tp1, Release, Tr1, NP1<br> Press, Tp2, Release, Tr2, NP2<br> .<br> .<br> . <br> Press, Tpn, Release, Trn, NPn<br> }</p> <p>where 1,2,...,n denote the serial index of the key tapped during typing.</p> <p><em>Note:</em> Out of 33 subjects, 32 managed to transcribe 8 to 11 text excerpts, while the remaining one (Subject ID: 16) typed only 5. Ten subjects (Subject IDs: 6, 14, 16, 17, 25, 27, 29, 31, 32, 33) did not manage to type the initial 200 characters-long excerpt in its entirety.</p> <p>The dataset also includes a record, in Microsoft Excel format (Demographics_Clinical_Characteristics.xlsx), of the demographic and clinical characteristics (with respect to PD) of subjects. Entries of the Excel file are linked to subjects' sub-folders and individual keystroke data text files via the coded ID of the subject.</p> <p>Demographic characteristics included:</p> <p>Age; Gender; Education level; Years of smartphone usage; Dominant hand<sup>1</sup></p> <p>Clinical characteristics included:</p> <p>Group (PD, Control); Years from diagnosis; Hoehn-Yahr disease stage; Most affected side<sup>2</sup>; Levodopa Equivalent Daily Dose; UPDRS_III<sup>3</sup> total score; UPDRS_III Item 21 Tremor-Right hand; UPDRS_III Item 21 Tremor-Left hand; UPDRS_III Item 22 Rigidity-Right hand; UPDRS_III Item 22 Rigidity-Left hand; UPDRS_III Item 23 Finger taps-Right hand; UPDRS_III Item 23 Finger taps-Left hand; UPDRS_III Item 31 Body bradykinesia/ Hypokinesia</p> <p><sup>1</sup>Dominant hand: (Relating to handedness) the operant hand generally used for performing fine motor-skills tasks.<br> <sup>2</sup>Most affected body side by Parkinson's disease<br> <sup>3</sup>UPDRS_III: Unified Parkinson's Disease Rating Scale Part III (Motor section)</p> <p> </p> <p><strong>RELATED RESEARCH</strong></p> <p>This dataset was originally used and described in the OPEN ACCESS publication: </p> <p>[1] Iakovakis, D., Hadjidimitriou, S., Charisis, V., Bostantzopoulou, S., Katsarou, Z., & Hadjileontiadis, L. J. (2018). Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson’s disease. Scientific reports, 8(1), 7663. <a href="http://doi.org/10.1038/s41598-018-25999-0">https://doi.org/10.1038/s41598-018-25999-0</a> </p> <p>All documents and papers that report on research that uses this dataset will acknowledge this by citing the above publication.</p> <p> </p> <p><strong>ETHICS & FUNDING</strong></p> <p>The study during which the present dataset was collected was approved by the Aristotle University of Thessaloniki Bioethics Committee of Medical School (approval no. 359/3.4.17), Thessaloniki, Greece. Informed consent, including permission for third-party access to pseudo-anonymised data, was obtained from all subjects prior to their engagement with the study. The work has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 690494 - i-PROGNOSIS: Intelligent Parkinson early detection guiding novel supportive interventions (<a href="http://www.i-prognosis.eu">i-prognosis.eu</a>).</p> <p> </p> <p><strong>CORRESPONDANCE</strong></p> <p>Any inquiries regarding this dataset should be adressed to:</p> <p>Mr. Dimitrios Iakovakis (Electrical & Computer Engineer, PhD candidate)</p> <p>Signal Processing & Biomedical Technology Unit<br> Department of Electrical & Computer Engineering<br> Aristotle University of Thessaloniki<br> University Campus, Building D, 6th floor<br> Thessaloniki, Greece, GR54124</p> <p>Tel: +30 2310 996319<br> Fax: +30 2310 996312<br> E-mail: dimiiako12@gmail.com</p> <p> </p> <p><strong>LICENSE</strong></p> <p>This is an open access dataset, licensed under Creative Commons Attribution 4.0 International (<a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a>).</p> <p> </p> <p><strong>WARRANTY</strong></p> <p>This dataset comes without any warranty. Administrators of this dataset can not be held accountable for any damage (physical, financial or otherwise) caused by the use of this dataset. </p>
REXUS 25 HEDGEHOG pressure data
<p>Pressure data from REXUS 25 sounding rocket from HEDGEHOG experiment.</p> <p>Data was simultaneously saved with 2 Honeywell HSCDANN001BA2A3 pressure sensors.<br> Basic information: range 0 to 1 bar, accuracy 1 mbar, frequency 10 Hz<br> More information: <a href="https://sensing.honeywell.com/HSCDANN001BA2A3-amplified-board-mount-pressure-sensors">https://sensing.honeywell.com/HSCDANN001BA2A3-amplified-board-mount-pressure-sensors</a></p> <p>About REXUS: <a href="http://rexusbexus.net/">http://rexusbexus.net/</a><br> About HEDGEHOG experiment: <a href="https://www.facebook.com/HEDGEHOG.REXUS.Project/">https://www.facebook.com/HEDGEHOG.REXUS.Project/</a></p>
Data files for the manuscript "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes"
<p>This depository contains the data of all DEM simulations used in the manuscript titled "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes" submitted to Soft Matter in July 2024.</p> <p>The data in the excel file are the measurements obtained after the coarse graining procedure.</p>
Raw data for the Article "Cyclopentadienone Iron Complex-Catalyzed Hydrogenation of Ketones: An Operando Spectrometric Study Using Pressurized Sample Infusion-Electrospray Ionization-Mass Spectrometry"
<p>This data set contains the raw data (NMR, LC-MS, ESI-MS, HRMS, Elemental Analysis) for the article "Cyclopentadienone Iron Complex-Catalyzed Hydrogenation of Ketones: An <em>Operando</em> Spectrometric Study Using Pressurized Sample Infusion-Electrospray Ionization-Mass Spectrometry" published in <em>Organometallics</em>, DOI:</p> <p><a href="https://doi.org/10.1021/acs.organomet.2c00341">https://doi.org/10.1021/acs.organomet.2c00341</a></p> <p>The compound names correspond to the ones used in the article and its supporting information.</p>
Daliy weather data (wind, temperatrue, humididty, pressure, precipitation) from Roche Mountonnee , in the northern foothills of the Brooks Range, Alaska, summers 2010-2014.
Daily weather data from mid May to late July 2011 to 2013 from Roche Moutonnee (south of Toolik Field Station and Arctic LTER), in the northern foothills of the Brooks Range, Alaska. Parameters measured include: wind speed, wind directions, temperature, humidity, pressure and precipitation.
Riparian Evapotranspiration (ET) Study (SEON) from the Middle Rio Grande River Bosque, New Mexico (1999-2011 ): Vapor Pressure Deficit (VPD) Data
We hypothesized that flooding and invasions of non-native species would strongly impact ecosystem water use. Our objectives were to measure and compare water use of native (Rio Grande cottonwood, Populus deltoides ssp. wizleni) and non-native (saltcedar, Tamarix chinensis, Russian olive, Eleagnus angustifolia) vegetation and to evaluate how water use is affected by climatic variability resulting in high river flows and flooding as well as drought conditions and deep water tables. Eddy covariance flux towers to measure ET and shallow wells to monitor water tables were instrumented in 1999. Active sites in their second decade of monitoring include a xeroriparian, non-flooding salt cedar woodland within Sevilleta National Wildlife Refuge and a dense, monotypic salt cedar stand at Bosque del Apache NWR, which is subject to flood pulses associated with high river flows.
Data for "First Principle Calculation on Pressure Dependent Yielding in Solute Strengthened Aluminium Alloys"
<p>The dataset contains the DFT results which is the basis for the results and discussions in the related article, "First principle calculations of pressure dependent yielding in solute strengthened aluminium alloys". The details of the DFT calculations are written in the article.</p> <p>The two different file-name conventions are explained below.</p> <p>OUTCAR_Al_R1_HSP<br> OUTCAR_X_HSP_POS</p> <p>Al-files represent the pure aluminium models, showing the dislocation energies at various hydrostatic pressures. X (Cu, Si, Mg) represents the solute specie in the full model showing the configurational energy. R1 is the radius of the relaxed region. HSP represents the superimposed hydrostatic pressure, which is given by (-560+HSP*80) MPa. POS is the atomic index in the OUTCAR files, where the solute is substituted.</p>
Data Sets: Unsteady Land-Sea Breeze Circulations in the Presence of a Synoptic Pressure Forcing
<p>{Mg (m/s): 0, 0.4, 1.2, 2 and α: 0°, and 180°}</p> <p>Consult the details in Allouche et al. (2023): https://doi.org/10.1002/qj.4552. The latter corresponds to the steady state simulations of these transient ones here.<br>All of these simulations have a domain extent (L_x, L_y, L_z=z_i) of (80 km, 5 km, 1.6 km). The numerical mesh (Nx, Ny, Nz) is (384, 24, 64). For plotting, the vertical levels vary for each variable. A variable at 'c_s nodes' is plotted at dz/2, dz, 2*dz, 3*dz, and so forth up to z_i. A variable on 'w nodes' is plotted at 0, dz, 2*dz, 3*dz, and so forth up to z_i. This information is given in the variable table below.</p> <p>These simulations are given in a netcdf format (.nc). One is able to download and reshape these matrices.</p>
Research data for "Cluster Fragments in Amorphous Phosphorus and their Evolution under Pressure"
<p>This dataset supports the paper: "Cluster Fragments in Amorphous Phosphorus and their Evolution under Pressure". The paper is online here: https://doi.org/10.1002/adma.202107515. </p> <p>The following .xyz and .zip files are provided:</p> <ul> <li>"LDA_structure_final.xyz": the atomic structure of the LDA model generated in this work.</li> <li>"slow_melt_quench.zip": the trajectory of the slow melt-quench process in (extended) XYZ format. </li> <li>"compress_decompress.zip": the trajectory of the ambient-pressure compression and the subsequent decompression processes in (extended) XYZ format. </li> <li>"Structure_factor.zip": atomic structures in (extended) XYZ format at different pressures (used to calculate the structure factors). </li> </ul> <p> </p>
Pressure oscillations data as storm precursors
<p>The folders contain the derived data product from REMS pressure that study the storm precursors.</p>
Pressure data used in 'Surface-to-space atmospheric waves from Hunga Tonga-Hunga Ha'apai eruption' (Wright et al., 2022)
<p>Pressure data used in 'Surface-to-space atmospheric waves from Hunga Tonga-Hunga Ha’apai eruption' (Wright et al., 2022). </p> <p> </p> <p><strong>Phase speed estimates by station:</strong></p> <p>Author: <em>Fred Prata, AIRES Pty Ltd</em></p> <p>Description:<em> distances, locations, arrival times and phase speed estimates for the Hunga Tonga Lamb wave from pressure stations used in our study.</em></p> <p> </p> <p> </p> <p><strong>Pressure time series data (19 stations):</strong></p> <p><strong>Lauder (1 station):</strong></p> <p>Author: <em>Dan Smale/NIWA, State Highway 85, Omaku, New Zealand</em></p> <p>Description: <em>Data sourced from a CO2 eddy-covariance instrument operated and maintained by NIWA. Values were provided as an image file of pressure anomaly versus time (NZST) which was digitized at approximately 90 s time resolution and 0.1 hPa.</em></p> <p><strong>Mt Eliza / HRO (1 station):</strong></p> <p>Author: <em>Fred Prata/AIRES Pty Ltd, 116 Humphries Road, Mount Eliza, Vic 3930, Australia</em></p> <p>Description: <em>Data derived from an ecowitt weather station (Easyweather-WIFIA 19E) operated and maintained by AIRES Pty Ltd. The measurements are logged every 5 minutes with a pressure resolution of 0.1 hPa.</em></p> <p><strong>Tonga (1 station):</strong></p> <p>Author:<em> Malo e Leilei Taaniela/Fua'amotu Domestic Airport, Tonga and Shane Cronin/University of Auckland, School of Environment, New Zealand.</em></p> <p>Description: <em>Data derived from a barometer operated by the Tongan meteorological office located at Nukualofa port (met.gov.to). Sampling interval is 1 minute and the pressure resolution is 0.1 hPa</em></p> <p><strong>Weatherlink (3 stations):</strong></p> <p>Author: <em>Fred Prata/AIRES Pty Ltd, 116 Humphries Road, Mount Eliza, Vic 3930, Australia</em></p> <p>Description: <em>Data downloaded from http://weatherlink.com The time resolution is 5 minutes for Davis and Boston and 15 minutes for Travis. The pressure resolution is 0.01 in Hg.</em></p> <p><strong>PurpleAir (13 stations): </strong></p> <p>Author: <em>citizen science project - https://map.purpleair.com/ (free for non-commercial use)</em></p> <p>Description: <em>PNG images of pressure traces from each station: American Samoa, Anchorage, Auckland, Brisbane, Colorado Springs, Concepcion, Glenn Dale, Kahuko, Manhattan Beach, Papeete, Solvang, Sydney, Tokyo. See table, described above, for latitude/longitude of each site.</em></p> <p> </p> <p><strong>Other pressure data used in the paper already archived elsewhere, and associated licensing (11 stations):</strong></p> <p><strong>AIMS (10 stations)</strong>: https://apps.aims.gov.au/metadata/search?term=Weather%20Stations (CC BY 3.0 AU)</p> <p><strong>Wegenernet (1 station)</strong>: https://wegenernet.org/portal/v7.1/2021/1 ("openly available to all and free of charge except for commercial usage")</p> <p> </p> <p> </p> <p><strong>Not included (6 stations):</strong></p> <p>Due to licensing terms, we do not include 6 pressure time series obtained from the Australian Bureau of Meteorology in their raw form, specifically those at <em>Mt Isa Aero, Learmonth Airport, Broome Airport, Alice Springs Airport, Adelaide Airport and Perth Airport</em>. Derived products made from these data are permitted to be shared, and accordingly phase speed estimates from these stations are included in the table described above. A graphical representation of the data from <em>Broome</em> is also included in the scientific paper these data support as Extended Data Figure 1e.</p> <p> </p> <p> </p>
Data from: Unwrapping broken tails: Biological and environmental correlates of predation pressure in limbless reptiles
<p>Studying species interactions in nature often requires elaborate logistics and intense fieldwork. The difficulties in such task might hinder our ability to answer questions on how biotic interactions change with the environment. Fortunately, a workaround to this problem lies within scientific collections. For some animals, the inspection of preserved specimens can reveal the scars of past antagonistic encounters, such as predation attempts. A common defensive behaviour that leaves scars on animals is autotomy, the loss of a body appendage to escape predation. By knowing the collection site of preserved specimens, it is possible to assess the influence of organismal biology and the surrounding environment in the occurrence of autotomy. We produced data on tail loss for 8,189 preserved specimens of 33 snake and 11 amphisbaenian species to investigate biological and environmental correlates of autotomy in reptiles. We applied generalized linear mixed effect models to evaluate whether body size, sex, life-stage, habitat use, activity pattern, biome, tropicality, temperature, and precipitation affect the probability of tail loss in limbless reptiles. We observed autotomy in 23.6% of examined specimens, with 18.7% of amphisbaenian and 33.4% of snake specimens showing tail loss. Probability of tail loss did not differ between snakes and amphisbaenians, but it was higher among large-sized specimens, particularly in adults and females. Chance of tail loss was higher for diurnal and arboreal species, and among specimens collected in warmer regions, but it was unaffected by biome, precipitation, and tropicality. Autotomy in limbless reptiles was affected by size-dependent factors that interplay with ontogeny and sexual dimorphism, although size-independent effects of life-stage and sex also shaped behavioural responses to predators. The increase in probability of tail loss with verticality and diurnality suggests a risk-balance mechanism between species habitat use and activity pattern. Although autotomy is more likely in warmer regions, it seems unrelated to seasonal differences in snakes and amphisbaenians activity. Our findings reveal several processes related to predator-prey interactions involving limbless reptiles, demonstrating the importance of scientific collections to unveil ecological mechanisms at different spatio-temporal scales.</p>
Data set for "The ion-ion recombination coefficient α: comparison of temperature- and pressure-dependent parameterisations for the troposphere and stratosphere"
<p>The uploaded data are related to the publication "The ion–ion recombination coefficient <span class="math-tex">\(\alpha\)</span>: comparison of temperature- and pressure-dependent parameterisations for the troposphere and stratosphere" in Atmospheric Chemistry and Physics (ACP). The data are the same as shown in the figures of the publication. The naming of the uploaded files indicates the figure (e.g., "Fig_2" indicates Figure 2 of the publication). </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.