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29,896 results for “activity”
Data associated with the following publication: "Giant thermoelectric response of confined electrolytes with thermally activated charge carrier generation"
<p>Data associated with the following publication: "Giant thermoelectric response of confined electrolytes with thermally activated charge carrier generation" (DOI: <a title="" href="https://doi.org/10.48328/tudatalib-1376">https://doi.org/10.48328/tudatalib-1376</a>)</p>
Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (VIDIMU)
<p>Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most publicly available datasets on human body movements cannot be used to study both problems in an out-of-the-lab movement acquisition setting. The objective of the VIDIMU dataset is to pave the way towards affordable patient tracking solutions for remote daily life activities recognition and kinematic analysis. </p> <p>The VIDIMU dataset includes 54 healthy young adults that were recorded on video and 16 of them were simultaneously recorded using custom IMUs. For each subject, 13 activities were registered using a low-resolution video camera and five Inertial Measurement Units (IMUs). Inertial sensors were placed in the lower or the upper limbs of the subject, respectively for activities that involve movement with the lower or the upper body. Video recordings were postprocessed using the state-of-the-art pose estimator <em>BodyTrack</em> (similar to OpenPose, and included in NVIDIA Maxine-AR-SDK) to provide a sequence of 3D joint positions for each movement. Raw IMU recordings were post-processed to compute joint angles by inverse kinematics with <em>OpenSim</em>. For recordings including simultaneous acquisition of video and IMU data types, these signals were used for data file synchronization. Collected data can be further used in applications related to human activity recognition and biomechanics related experiments in simulated home-like settings.</p> <p> </p> <p> </p>
Inactive to active transition of human Thymidine Kinase 1 revealed by Molecular Dynamics simulations
<p>The trajectories and input files for the manuscript <em>Inactive to active transition of human Thymidine</em></p> <p><em>Kinase 1 revealed by Molecular Dynamics simulations</em> (<a href="https://doi.org/10.1021/acs.jcim.1c01157">https://doi.org/10.1021/acs.jcim.1c01157</a>) </p> <p>ABSTRACT</p> <p>Despite its importance for the nucleoside (and nucleoside prodrug) metabolism, the structure<br> of the active conformation of human Thymidine Kinase 1 (hTK1) remains elusive. We perform<br> microsecond molecular dynamics simulations of the inactive enzyme form bound to a<br> bisubstrate inhibitor that was shown experimentally to activate another TK1-like kinase,<br> Thermotoga maritima TK (TmTK). Our results are in excellent agreement with the<br> experimental findings for the TmTK closed-to-open state transition. We show that the inhibitor<br> induces an increase of the enzyme radius of gyration due to the expansion on one of the dimer<br> interfaces; the structural changes observed, including the active site pocket volume increase,<br> decrease in monomer-monomer buried surface area and of the number of hydrogen bonds (as<br> compared to the inactive enzyme control simulation), show that the catalytically competent<br> (open) conformation of hTK1 can be assumed in the presence of an activating ligand.</p>
Dataset Activation of Lactate Receptor HCAR1 Down-modulates Neuronal Activity in Rodent and Human Brain Tissue
<p>This dataset is related to the study: </p> <p>Briquet M, Rocher AB, Alessandri M, Rosenberg N, de Castro Abrantes H, Wellbourne-Wood J, Schmuziger C, Ginet V, Puyal J, Pralong E, Daniel RT, Offermanns S, Chatton JY. Activation of lactate receptor HCAR1 down-modulates neuronal activity in rodent and human brain tissue. J Cereb Blood Flow Metab. 2022 Mar 3:271678X221080324. doi: 10.1177/0271678X221080324. Epub ahead of print. PMID: 35240875.</p>
S95 | PFASANEXCH | PFAS List from the NORMAN PFAS Analytical Exchange Activity
<p>This is the collection associated with list S95 PFASANEXCH on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>This is a list from the <a href="https://www.norman-network.net/sites/default/files/files/QA-QC%20Issues/2021%20NORMAN%20network%20PFAS%20Analytical%20Exchange%20Final%20Report%2014022022.pdf">PFAS Analytical Exchange Activity</a>, part of NORMAN Joint Programme of Activities (JPA) 2021 coordinated by UK Environment Agency. This activity aimed to gain an understanding of the current analytical capability of PFAS as Limit of Detection (LOD) in participating international laboratories.</p>
CROSSBOW HLU2-UC1-TC1 measurements: Substation measurements gathered during curtailment activation
<p>The data comprises the measurements read at the Konjsko substation before, during and after a curtailment in Pometeno Brno plant.</p> <p>The measurements gathered from the SCADA are:</p> <ul> <li>P, Q and V of the 110, 220 and 400 Kv buses at the substation</li> </ul> <p>P, Q and V of the line connecting the substation with the plant</p>
The stellar parameters and the quantities of the residual emissions of the detected active stars in the LAMOST-K2 survey
<p>The full Table 1 in <em>Investigation of stellar magnetic activity using variational autoencoder based on low-resolution spectroscopic survey</em> (Xiang, Gu & Cao, 2022, MNRAS, 514, 4781; <a href="https://arxiv.org/abs/2206.07257">arXiv:2206.07257</a>). The columns are LAMOST obsid, K2 ID, Teff, logg, [Fe/H], EW_res_Halpha, EW_res_Ca II 8498, EW_res_Ca II 8542, EW_res_Ca II 8662, log F_Halpha, log F_Ca, log R'_Halpha, log R'_Ca. The chromospheric emissions were detected and measured with the spectral subtraction technique, which removes the inactive template spectra (photospheric contribution) from the observed stellar spectra. In this work, we used the variational autoencoder neural networks to efficiently generate the proper template spectra in a data-driven manner. More details can be found in the associated paper (<a href="https://arxiv.org/abs/2206.07257">https://arxiv.org/abs/2206.07257</a>). The demo code can be found on GitHub (<a href="https://github.com/xylib/vae-for-spectroscopic-survey">https://github.com/xylib/vae-for-spectroscopic-survey</a>).</p>
Prediction of synaptic activity
<p>This folder contains supplementary material for the paper <a href="https://doi.org/10.1007/s12021-022-09609-z">An Algorithm Based on a Cable‑Nernst Planck Model Predicting Synaptic Activity throughout the Dendritic Arbor with Micron Specificity</a>:</p> <ul> <li>Experimental data: <ul> <li>fluorescence data</li> <li>morphometric data</li> </ul> </li> <li>A notebook to simulate calcium dynamics in the dentritic arbor using <a href="https://joss.theoj.org/papers/10.21105/joss.04012">sinaps</a> software, and the algorithm to predict synaptic activity in fluorescence data</li> <li>Simulation results</li> </ul> <p> </p>
Parker Solar Probe Filtered Ion Scale Wave Activity for Encounters 8 to 16
<p>The following datasets are the result of filtering algorithm applied to a wave analysis of Parker Solar Probe data from Encounters 8 to 16. The wave analysis was conducted by Kristoff Paulson using a Short-Time Fourier Transform (STFT) approach based on polarization techniques derived by Means, 1972 (DOI: <a href="http://doi.org/10.1029/JA077i028p05551">10.1029/JA077i028p055511135</a>). Included is a jupyter notebook containing the filtering algorithm, the results of the filtering, and a demonstration of how to best open the files. The dataset for each encounter contains 9 columns that correspond with:</p> <ol> <li>Date in CDF epoch</li> <li>Left-handed (LH) Integrated Wave Power (nT^2) where integration is over frequency space (0-32 Hz) of filtered activity</li> <li>Right-handed (RH) Integrated Wave Power (nT^2)</li> <li>LH median ellipticity where median is over frequency space</li> <li>RH median ellipticity</li> <li>LH median coherency</li> <li>RH median coherency</li> <li>LH median wave normal angle (deg)</li> <li>RH median wave normal angle (deg)</li> </ol> <p>In all cases, ellipticity is measured in the Parker Solar Probe spacecraft frame. Ellipticity measures the ellipticity of the polarization ellipse and takes on values between -1 and 1. Values of 1 correspond with RH circular polarization and -1 with LH circular polarization. Coherency takes on values between 0 and 1. It measures how interrelated fluctuations are where 0 represents noise and 1 represents coherent fluctuations. The wave normal angle is the angle between the wave vector, k, and the local mean magnetic field, B. Since there are inherent ambiguities in the direction of the wave vector for single spacecraft measurements, the wave normal angle is calculated such that it takes on angles from 0 to 90 degrees. The filtering algorithm selects activity in which coherency is above 0.8, absolute value of ellipticity is above 0.5, and wave normal angle is below 45 degrees such that coherent, circularly polarized, near parallel propagating wave activity on ion scales is selected. <strong>If wave power for a given time has value of 0.0, then no fluctuations in the magnetic field data passed the required filters at that time.</strong></p> <p>:</p>
Data Repository: Land surface modelling activities at Weierbach catchment.
<p>The data in this repository comes from the modelling activities with the Community Land Model version 5.0 (CLM5) carried out at the Weierbach catchment, Luxembourg. The repository contains:</p> <ol> <li>A list of matric potentials of <em>Fagus sylvatica </em>at which it experiences a specific loss of conductivity (i.e., 12%, 50%, 88%) obtained from published data [File: additional_PHT_Fagus_sylvatica_Europe.csv].</li> <li>The hourly atmospheric forcing used during the simulations with CLM 5.0 in a NetCDF format [File: atmospheric_forcing.zip].</li> <li>All model results per experiment [model_results.zip].</li> <li>The R scripts for processing the model results for obtaining the information required for each figure [Files: manuscript_figure_#.R].</li> <li>A daily summary of the tree water deficit calculated per PFT, individual tree species, and the whole ecosystem [File: twd.csv].</li> <li>A daily summary of tree transpiration scaled at the catchment level per PFT, individual tree species, and the whole ecosystem [File: et_mm_wei.csv]. This daily summary is based on the hourly data available on: Klaus, J., Fabiani, G., Schoppach, R., Chun, K. P., Iffly, J. F., Penna, D., & Juilleret, J. (2024). Detailed sap flow monitoring data at Weierbach catchment, Luxembourg (Version v01) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.11381618" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11381618</a></li> </ol>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Wave 1 Questionnaires: Czech Republic
<p>This dataset was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538. Work Package 7 of this project aims to test the processes in youth’s construction of active EU citizenship on various social and psychological levels. The main file contains quantitative data from the first wave of the longitudinal survey on adolescents and young adults (age 15-26). Data collection was carried out in the Czech Republic (regions Prague, South Moravian, Moravian-Silesian, Pardubicky, Vysocina) from October to December 2016. The supplementary files contain national translations of the questionnaire for the younger (15-19) and the older (20-26) subgroups.</p>
Participatory activities good practices in the field of cultural heritage (REACH project)
<p>The REACH repository of good practices comprises over a hundred and twenty records of European and extra European participatory activities in the field of cultural heritage, with an emphasis on small-scale, localised examples, but including also larger collaborative projects and global or distributed online initiatives. Located in over twenty different countries, the activities showcased here cover a wide variety of topics and themes, from urban, rural and institutional heritage to indigenous and minority heritage; from preservation, and management to use and re-use of cultural heritage. This easy-to-use collection of good practices offers professionals, practitioners, researchers and citizens useful information about activities which could be transferred, adapted or replicated in new contexts.</p>
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 250 m monthly for period 2014-2019 based on COPERNICUS land products
<p>Long-term monthly Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) median value at 250 m based on the time-series of <a href="https://land.copernicus.eu/global/products/fapar">COPERNICUS FAPAR</a>. Derived using the data.table package and quantile function in R. Processing steps are available <a href="https://gitlab.com/openlandmap/global-layers/tree/master/input_layers/Copernicus_vito"><strong>here</strong></a>. Antartica is not included.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>veg = theme: vegetation,</li> <li>fapar = Fraction of Absorbed Photosynthetically Active Radiation,</li> <li>proba.v.oct = determination method: PROBA-V products, month October,</li> <li>d = median value,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>2014..2019 = time reference: from 2014 to 2019,</li> <li>v1.0 = version number: 1.0,</li> </ul>
Docked structures from "Optimizing active learning for free energy calculations"
<p>This archive contains the docked TYK2 structures used in the paper "Optimizing active learning for free energy calculations" (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ailsci.2022.100050" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.ailsci.2022.100050</span></span></a>). AM1-BCC charges are stored in the field "AM1Cache" in the SD file. The charges can be extracted using the code sample below. </p> <p> </p> <pre><code>from rdkit import Chem import base64 import pickle suppl = Chem.SDMolSupplier("10k_most_similar_tyk2_charged.sdf", removeHs=False) for mol in suppl: am1 = mol.GetProp("AM1Cache") am1_charges = pickle.loads(base64.b64decode(mol.GetProp("AM1Cache"))) assert len(am1_charges) == mol.GetNumAtoms(), "Charge cache has different number of charges than mol atoms"</code></pre>
Identifying Coronal Mass Ejection Active Region Sources: An automated approach - Catalogue results
<p>Catalogue of Coronal Mass Ejection (CME) active region sources. Includes a database version and a simplified .csv version. For full details, refer to the source code at <a href="https://github.com/JulioHC00/cmesrc">https://github.com/JulioHC00/cmesrc</a>. We include a README file for each describing each column.</p> <p>We also include the raw data used to generate the catalogue so that results may be reproduced following the steps detailed in <a href="https://github.com/JulioHC00/cmesrc">https://github.com/JulioHC00/cmesrc</a>. This is a collection of data from other works and we provide it only to allow the results to be reproduced</p> <p>Below, we detail the data sources for the raw_data folders</p> <p>==============================<br><strong>RAW DATA SOURCES</strong><br>==============================</p> <p><strong>DIMMINGS FOLDER</strong></p> <p>Data is from Solar Demon, .csv was provided by Emil Kraaikamp through private communication.</p> <blockquote> <p>Solar Demon – an approach to detecting flares, dimmings, and EUV waves on SDO/AIA images<br>Emil Kraaikamp, Cis Verbeeck<br>J. Space Weather Space Clim. 5 A18 (2015)<br>DOI: 10.1051/swsc/2015019</p> </blockquote> <p><strong>HARPNUM_TO_NOAA FOLDER</strong></p> <p>Obtained from http://jsoc.stanford.edu/doc/data/hmi/harpnum_to_noaa/all_harps_with_noaa_ars.txt</p> <p><strong>LASCO FOLDER</strong></p> <p>This CME catalog is generated and maintained at the CDAW Data Center by NASA and The Catholic University of America in cooperation with the Naval Research Laboratory. SOHO is a project of international cooperation between ESA and NASA.</p> <p>Downloaded from https://cdaw.gsfc.nasa.gov/CME_list/</p> <p><strong>MVTS FOLDER</strong></p> <p>Data from</p> <blockquote> <p>Angryk, R.A., Martens, P.C., Aydin, B. et al. Multivariate time series dataset for space weather data analytics. Sci Data 7, 227 (2020). https://doi.org/10.1038/s41597-020-0548-x</p> </blockquote> <p>Available at the Harvard Dataverse</p> <blockquote> <p>Angryk, Rafal; Martens, Petrus; Aydin, Berkay; Kempton, Dustin; Mahajan, Sushant; Basodi, Sunitha; Ahmadzadeh, Azim; Xumin Cai; Filali Boubrahimi, Soukaina; Hamdi, Shah Muhammad; Schuh, Micheal; Georgoulis, Manolis, 2020, "SWAN-SF", https://doi.org/10.7910/DVN/EBCFKM, Harvard Dataverse, V1</p> </blockquote> <p>The DT_SWAN folder contains the same data but with extra columns obtained directly from the Joint Science Operations Center (JSOC) through the python package drms.</p>
Metagenome-Assembled Genomes Abundance & Activity Tables. Environmental Parameters Associated with the dataset.
<p>Lake Mendota, WI, USA, is a temperate lake subject to annual temperature and oxygen fluctuations. Each summer, the water column becomes anoxic (no-oxygen). In 2020, we sampled the lake at weekly intervals, at different depths (5, 10, 15, 20 and 23.5m). For each time+depth sample, we collected metagenomes, viromes and metatranscriptomes. Environmental data profiles were collected on-site for each sampling day. </p> <p>Following standard metagenomic binning best practices, we obtained 431 metagenomes-assembled-genomes (MAGs).</p> <p>This record comprises the microbial abundance and expression table for these MAGs, and the environmental profiles collected each day.</p>
Dataset for: The antibacterial activity of peptide dendrimers and polymyxin B increases sharply above pH 7.4
<p>The upload contains additional primary data associated with the publication, including raw data in the original file format whenever possible.</p> <p>Data content: HRMS, HPLC-MS, pH titration, CD, MD, TEM</p> <p> </p>
Student activity data
<p>This dataset includes anonymized records of student activities in a peer review activity performed through Synergy platform. This data comes from an educational technology course delivered in an European university. There were 30 participants from different departments (Computer science, Math, Physics, Preschool and Elementary Education) In this course, the main course assignment was a learning design project in which students worked in groups. The activity lasted 3 weeks and for each project 2-3 reviewers were assigned.</p>
Hydrological, physicochemical and metabolic activity data for streams in the Japanese Alps
<p>A series of files with hydrological, physicochemical and metabolic activity data from a study investigating the environmental dynamics of six stream systems in the Japanese Alps.</p>
Effect of Textural Properties and Presence of Co-cation on NH3-SCR Activity of Cu-Exchanged ZSM-5
<p><strong>Description of the dataset: </strong></p> <ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements, computer simulation and analysis</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>m</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectroscopic simulation and analyses with filename extension <strong>m</strong>.</li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If t</strong> <ul> <li>Files in <strong>PARACAT_WP3_20210721_01_CW_Experimental</strong> folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt. formats.</li> <li>Files in <strong>PARACAT_WP3_20210721_02_CW_Simulations</strong> folder includes computer simulations/analyses of the EPR measurements; data are in m and txt formats.</li> </ul> </li> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>EPR</strong> – Electron Paramagnetic Resonance, <strong>CW</strong> – Continuous Wave EPR, <strong>exp </strong>– experimental data, <strong>hyd </strong>– cw-EPR spectra related to hydrated state, <strong>dehyd </strong>– cw-EPR spectra related to the dehydrated state, <strong>sim </strong>– simulation data. <strong>Sys </strong>– copper species used for constructing the spin-Hamiltonian in EPR simulations.</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
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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.