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11,506 results for “Dynamics”
Code, data and scripts to study wave dynamics in asymmetric material
<p>Supplementary data for [1] Vladislav A. Yastrebov. "Wave propagation through an elastically-asymmetric architected material", 2021, https://arxiv.org/abs/1712.06294v2</p> <p>See "Readme.md" and indivual "Readme.md" files in folders: "data", "src", "fig"</p>
Data for "The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada".
<p>Epidemiological and mobility data analysed in the paper "The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada".</p>
Dynamics of macrophage polarization in Salmonella infection : Raw data
<p>Experimental raw data of the paper "Dynamics of macrophage polarization support <em>Salmonella</em> persistence in a whole living organism", Leiba et al.</p>
Data from: Structure and dynamics of secondary and mature rainforests: insights from South Asian long-term monitoring plots
<p><strong>1) DESCRIPTION </strong></p> <p>The dataset contains annual woody stems (shrubs and trees) census data collected from two long-term ecological monitoring plots spanning one hectare each in the Anamalai Hills of the Southern Western Ghats, India. These two plots represent one situated in a mature forest located within relatively undisturbed rainforest of the Anamalai Tiger Reserve (ATR) and one in secondary forest on the Valparai Plateau, respectively. Both plots have been censused and measured from 2017 to 2022 following the standardized protocol (RAINFOR-GEM, Marthews et al. 2014).</p> <p><br><strong>2) CONTACTS</strong></p> <p>CONTACT #1<br>1. Name: Akhil Murali<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 82812 97441<br>4. Email address: akhil@ncf-india.org<br>5. ORCID: 0000-0001-6149-6458</p> <p>CONTACT #2<br>1. Name: Srinivasan Kasinathan<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: srini@ncf-india.org<br>5. ORCID: 0000-0001-7323-6653 </p> <p>CONTACT #3<br>1. Name: Kshama Bhat<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: kshama@ncf-india.org<br>5. ORCID: 000-0002-6190-2687</p> <p>CONTACT #4 <br>1. Name: Jayashree Ratnam <br>2. Work Address: National Centre for Biological Sciences, TIFR, Bellary Road, Bengaluru 560065, Karnataka, India<br>3. Work Phone: +91 80 23666001 <br>4. Email address: jratnam@ncbs.res.in <br>5. ORCID: 0000-0002-6568-8374</p> <p>CONTACT #5<br>1. Name: Mahesh Sankaran <br>2. Work Address: National Centre for Biological Sciences, TIFR, Bellary Road, Bengaluru 560065, Karnataka, India<br>3. Work Phone: +91 80 23666001<br>4. Email address: mahesh@ncbs.res.in <br>5. ORCID: 0000-0002-1661-6542</p> <p>CONTACT #6<br>1. Name: Divya Mudappa<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org<br>5. ORCID: 0000-0001-9708-4826</p> <p>CONTACT #7<br>1. Name: T. R. Shankar Raman<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org<br>5. ORCID: 0000-0002-1347-3953</p> <p>CONTACT #8<br>1. Name: Anand M Osuri <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: aosuri@ncf-india.org <br>5. ORCID: 0000-0001-9909-5633</p> <p><br><strong>3) GEOGRAPHIC COVERAGE and SITE DESCRIPTION</strong></p> <p>a) Site type: : Tropical Forest<br>b) Geography: : Anamalai Tiger Reserve, Southern Western Ghats.<br>c) Habit: : Mid elevation Wet evergreen Forest<br>d) Site History: : </p> <p>i) MANAMBOLI- The Mature Forest plot (10.357748° N, 76.889747° E; 825 m asl) is situated within a relatively undisturbed 200-hectare mid-elevation tropical wet evergreen rainforest tract at the core of the Anamalai Tiger Reserve (ATR). This area has been protected from logging and other significant disturbances since its establishment as a protected area in 1979.</p> <p>ii) CANDURA- The Secondary Forest plot (10.30855411° N, 76.83391853° E; 875 m asl) is situated within a 124-hectare rainforest remnant on the Valparai Plateau: the Candura rainforest remnant. The Candura site experienced episodic selective logging in the 1990s and early 2000s, with the last logging episode occurring in 2004. In the early 2000s, the understorey of the remnant was cleared for Vanilla (Vanilla planifolia) cultivation in the central and southern parts (abandoned in 2007), robusta coffee (Coffea canephora) in the northwestern corner (abandoned in the early 2000s), and pepper in 21 hectares in the northeastern part (established in 2015, abandoned in 2021).</p> <p>Climate: Humid tropical with about 2400 mm rainfall annually, falling mainly during the southwest monsoon.</p> <p><br><strong>4) TEMPORAL COVERAGE</strong></p> <p>a) Begins: 2017-11-30 (Year, Month, Day)<br>b) Ends: 2022-11-12 (Year, Month, Day)</p> <p><br>5) SAMPLING DESIGN AND METHODS </p> <p>a) Plot Design: Each 1 ha plot of 100 m × 100 m, sub-divided into 100 continuous sub-plots of 10 m × 10 m, was surveyed and mapped to maximum accuracy using a theodolite in the field, with grid corners permanently staked. <br>b) Data collection period and frequency: After the plot establishment in NOvember -- December 2017, the plots were recensused each year (around November). <br>c) Research Methods: All woody plant individuals with girth at breast height (GBH, at 1.3 m) ≥10 cm were tagged with numbered aluminum tags and spatially mapped. Plant species were identified using standard floral keys. Stem GBH was measured for all single stemmed individuals. For trees with buttresses, the GBH point of measurement (POM) was taken at 50 cm above the buttresses or at the height where the stem is regular. New saplings that recruited into the ≥10 cm GBH class were identified, mapped, tagged, and added to the monitoring. Stems that appeared to be dead were recorded at each monitoring and those that showed no signs of recovery in subsequent visits were recorded as mortality.</p> <p><br><strong>6) FILES INCLUDED</strong></p> <p>The dataset includes the following 9 files, whose details and contents are explained below. (Wherever used in the various files, NA implies not available.)</p> <p>01_README.txt<br>Metadata (this file) including information on the dataset explaining associated files and their contents.</p> <p>02_Candura_annual_census.csv <br>This contains the Annual census data with the following column headings: <br>site: Site name (Can = Candura)<br>cno: Census Number (1 = 2017, 2 = 2018..., 6 = 2022)<br>ymd: Date in DD-MM-YYYY format (Day Month Year)<br>gno: Grid Number<br>tno: Unique tag number for the plant<br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes<br>lx: X coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ly: Y coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ht1: Point of measurement at 1.3 m above the ground or 50 cm above the top of the highest buttress or stilt root (POM1)<br>c1: Alive status of the stem at the POM1 (coded according Marthews et al. 2014, page: 97)<br>g1: Stem girth at POM1 (in centimetre)<br>ht2: 20 cm above the ht1 or point of measurement 2 (POM2) recording girth at which the dendroband is attached<br>c2: Alive status of the stem at the POM2 (coded acording Marthews et al. 2014, page: 97)<br>g2: Girth at POM2 (in centimetre)<br>dyn: whether the dendroband is attached to the tree or not (y-Yes, n-No)<br>da: alive status of stem (d-dead,a-alive)<br>remarks: remarks or notes</p> <p>03_Manamboly_annual_census.csv<br>This contains Annual census data with the following column headings: <br>site: Site name (Man = Manamboli)<br>cno: Census Number (1 = 2017, 2 = 2018..., 6 = 2022)<br>ymd: Date in DD-MM-YYYY format (Day Month Year)<br>gno: Grid Number<br>tno: Unique tag number for the plant<br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes<br>lx: X coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ly: Y coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ht1: Point of measurement at 1.3 m above the ground or 50 cm above the top of the highest buttress or stilt root (POM1)<br>c1: Alive status of the stem at the POM1 (coded according Marthews et al. 2014, page: 97)<br>g1: Stem girth at POM1 (in centimetre)<br>ht2: 20 cm above the ht1 or point of measurement 2 (POM2) recording girth at which the dendroband is attached<br>c2: Alive status of the stem at the POM2 (coded acording Marthews et al. 2014, page: 97)<br>g2: Girth at POM2 (in centimetre)<br>dyn: whether the dendroband is attached to the tree or not (y-Yes, n-No)<br>da: alive status of stem (d-dead,a-alive)<br>remarks: remarks or notes</p> <p>04_Candura_vernier.csv<br>This file has the girth measurement of trees with lianas where digital vernier calipers were used to measure stem diameter since it was not possible to measure stem girth using measuring tape.<br>site: Site name (Can = Candura)<br>cno: Census Number<br>ymd: Date in DD-MM-YYYY format (Day Month Year)<br>gno: Grid Number<br>tno: Unique tag number for the plant<br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes<br>vern1_d1 First measure of diameter at POM1 (in millimetre) <br>vern2_d1 Second measure of diameter at POM1 (in millimetre) <br>vern3_d1 Third measure of diameter at POM1 (in millimetre) <br>calc_g1: Girth at POM1 (in centimetre; calculated using the averaged value as diameter from the three measurements)<br>vern1_d2 First measure of diameter at POM2 (in millimetre) <br>vern2_d2 Second measure of diameter at POM2 (in millimetre) <br>vern3_d2 Third measure of diameter at POM2 (in millimetre) <br>calc_g2 Girth at POM2 (in centimetre; calculated using the averaged value as diameter from the three measurements)<br>Remarks Remarks and notes</p> <p>05_Manamboli_vernier.csv<br>This file has the girth measurement of trees with lianas where digital vernier calipers were used to measure stem diameter since it was not possible to measure stem girth using measuring tape.<br>site: Site name (Man = Manamboli)<br>cno: Census Number<br>ymd: Date in DD-MM-YYYY format (Day Month Year)<br>gno: Grid Number<br>tno: Unique tag number for the plant<br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes<br>vern1_d1 First measure of diameter at POM1 (in millimetre) <br>vern2_d1 Second measure of diameter at POM1 (in millimetre) <br>vern3_d1 Third measure of diameter at POM1 (in millimetre) <br>calc_g1: Girth at POM1 (in centimetre; calculated using the averaged value as diameter from the three measurements)<br>vern1_d2 First measure of diameter at POM2 (in millimetre) <br>vern2_d2 Second measure of diameter at POM2 (in millimetre) <br>vern3_d2 Third measure of diameter at POM2 (in millimetre) <br>calc_g2 Girth at POM2 (in centimetre; calculated using the averaged value as diameter from the three measurements)<br>Remarks Remarks and notes</p> <p>06_Candura_Height_data.csv<br>This contains data on the heights of individual trees in plot as measured in 2018.<br>site: Site name (Can = Candura)<br>ymd: Date in YYYY/MM/DD format (Year Month Day)<br>gno: Grid Number: <br>tno: unique tag number: <br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes: <br>lx: X coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ly: Y coordinate of tree in the 10 m × 10 m subplot (in metres)<br>height: Height of tree in metres<br>remarks: Remarks: and notes</p> <p>07_Manamboli_Height_data.csv<br>This contains data on the heights of individual trees in plot as measured in 2018.<br>site: Site name (Man = Manamboli)<br>ymd: Date in YYYY-MM-DD format (Year Month Day)<br>gno: Grid Number: <br>tno: unique tag number: <br>pno: Pole Number (unique alphabetic code for each stem of multi-stemmed individuals)<br>sps: Species name as codes: <br>lx: X coordinate of tree in the 10 m × 10 m subplot (in metres)<br>ly: Y coordinate of tree in the 10 m × 10 m subplot (in metres)<br>height: Height of tree in metres<br>remarks: Remarks: and notes</p> <p>08_Species_name_match.csv<br>This file provides the combined list of species codes updated taxonomy and successional guild. Scientific names were updated to current taxonomy using the species name matching tool of the Global Biodiversity Information Facility, GBIF (www.gbif.org).<br>sps: Species codes<br>query : Scientific name of the plant at the time of data collection: <br>scientificName: : with auther citation: <br>key: GBIF key<br>rank: Taxonomic rank or level of identification (GENUS, SPECIES)<br>kingdom: Taxonomic Kingdom (plants) provided by GBIF name matching tool: <br>phylum: Taxonomic Phylum provided by GBIF name matching tool<br>class: Taxonomic Class provided by GBIF name matching tool<br>order: Taxonomic Order provided by GBIF name matching tool<br>family: Taxonomic Family provided by GBIF name matching tool<br>genus: Taxonomic Genus provided by GBIF name matching tool<br>botanical_name: Updated scientific name of the species provided by GBIF name matching tool<br>habt_new: Successional guild of the species (Mature = mature forest species; Secondary = secondary successional species; Int - Introduced species)</p> <p>09_R_scrpt_for_manuscript.R<br>Text file with code in the R statistical and programming environment (www.r-project.org).</p> <p><br><strong>Reference</strong><br>Marthews TR, Riutta T, Oliveras Menor I, Urrutia R, Moore S, Metcalfe D, Malhi Y, Phillips O, Huaraca Huasco W, Ruiz Jaén M, Girardin C, Butt N, Cain R and colleagues from the RAINFOR and GEM networks (2014). Measuring Tropical Forest Carbon Allocation and Cycling: A RAINFOR-GEM Field Manual for Intensive Census Plots (v3.0). Manual, Global Ecosystems Monitoring network, http: //gem.tropicalforests.ox.ac.uk/.</p> <p> </p>
Data for manuscript: Functional Protein Dynamics in a Crystal
<p>The data is provided as a part of the manuscript "<strong>Functional Protein Dynamics in a Crystal</strong>". This repository includes an archive with folders:<br> <br> <strong>md_data</strong></p> <ul> <li>contains various simulation systems (crystal supercell, apo and ligand-bound solution) built from the crystal structure of the PDZ domain (PDB ID: 5E11) and carried out using three force fields: Amber ff14SB, CHARMM36m, Amber ff94. <em>The details of the simulations are provided in the Methods and Supplementary methods sections of the manuscript. </em></li> </ul> <p><strong>fig_data</strong></p> <ul> <li>contains the data sets underlying Figures 1-5 of the manuscript's main text. </li> </ul> <p> </p>
Wrapper Impact Workloads and BSC Slurm Simulator Output of Dynamic Traces from CEA Curie
<p>This dataset contains the workloads, with the workflow added to them, and the results of the simulations of the dynamic trace utilizing <a href="https://www.cs.huji.ac.il/labs/parallel/workload/l_cea_curie/index.html">Curie's workload</a> carried out using <a href="https://ieeexplore.ieee.org/abstract/document/8641556">BSC's SLURM Simulator</a>.</p> <p>It is organized in two folders: workloads and results. In the first, we find a folder per target fair share value that the user that we track its usage. Within, we have a file with the name indicating if the workflow is wrapped or not, the type, vertical or horizontal, and the instant of submission. This file is in <a href="https://www.cs.huji.ac.il/labs/parallel/workload/swf.html">SWF</a> format. Under the results folder, we have the same organizaion: each .trace is the raw file produced by the simulator. </p> <p>The workload log from the CEA Curie system was graciously provided by Joseph Emeras (<a href="mailto:Joseph.Emeras@imag.fr">Joseph.Emeras@imag.fr</a>).</p>
Raw data from the manuscript "Full-aperture extended-depth oblique plane microscopy through dynamic remote focusing"
<p>The repository contains all the raw data from the manuscript titled "Full-aperture extended-depth oblique plane microscopy through dynamic remote focusing" (https://doi.org/10.1117/1.JBO.29.3.036502).<br> The data consists in 3D stacks acquired with the method described in the manuscript. Since raw images are acquired along a diagonal plane, and are stretched in one direction, the dataset also includes a Python script to perform an affine transform projecting the stack on cartesian coordinates.</p> <p>Samples imaged include sub-resolution microbeads in agarose gel, a fixed slice of mouse kidney (fluocells prepared slide #3, invitrogen), and 3 to 5 days post fertilization Tg(kdrl:eGFP)s843 Zebrafish.</p>
Data for: Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network
<p>The data is supplementary to the publication "Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network", DOI: <a title="DOI URL" href="https://doi.org/10.1021/acs.jpclett.4c00406">10.1021/acs.jpclett.4c00406</a></p> <p>Key words: Thermal volume expansion, Interphase dynamics, Temperature-modulated optical refractometry, Nanoparticles, Optical Remanence, Hysteresis, Refractive index</p> <p>The data sets contain measured and processed data on the interphase dynamics of a nanoparticle modified epoxy resin collected via Temperature-modulated optical refractometry (TMOR).</p> <p>Material details:</p> <ul> <li>Cycloaliphatic epoxy resin + Anhydride curing agent + 1-methylimidazole</li> <li>Core-shell rubber nanoparticles, 100 nm, dispersed in a cycloaliphatic epoxy carrier resin</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629.</li> </ul>
The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states
<p>This repository contains three figures mentioned in "The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states" <em>(DOI to follow on publication)</em>.</p> <p>We show the contours of the X-ray surface brightness distribution (solid green lines) and the distribution of galaxies belonging to the red sequence (solid gray lines). Black crosses symbolize the positions of the X-ray peaks, black "X" marks represent the positions of the X-ray centroids, and open red circles denote the positions of the BCGs. The blue circle corresponds to the R200 of each cluster.</p>
Reproduction package for the paper "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"
<p>Research Data Management package for "Bottling the Champagne: Dynamics and Radiation Trapping of Wind-Driven Bubbles around Massive Stars"</p> <p>Authors: Sam Geen & Alex de Koter</p> <p>Status: Accepted by MNRAS<br> This package aims to provide a full data reproduction pipeline. Please see Readme.md for more information.</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>
An experimental data set on the thermal and fluid dynamic performance of double skin facades (DSFs) subjected to various controlled boundary conditions through the use of a climate simulator facility
<p>Double skin facades (DSFs) are building envelope systems defined by complex phenomena and non-linear-processes that make characterizing their performance a non-trivial task. In an effort to enable the scientific community to access experimental data for further analysis or model validation purposes, we release together with the open-access paper entitled “<strong><em>Laboratory testbed and methods for flexible characterization of the thermal and fluid dynamic behavior of double skin facades” (</em></strong><a href="https://doi.org/10.1016/j.buildenv.2021.108700"><strong><em>https://doi.org/10.1016/j.buildenv.2021.108700</em></strong></a><strong><em>)</em></strong>, a set of experimental data collected during tests carried out with the use of the newly developed testbed. The data contains the results of a series of tests where various configurations of a full-scale DSF mock-up that have been subjected to different boundary conditions replicated in a climate simulator. The database contains a guide in the form of the file ‘Guide.pdf’, which explains how to read data, presents a schematic drawing of sensor layout, and provides more information on sensors’ positions. Further information on the original aims of the experiments, methods, and other data can be found in the article mentioned above, which becomes an essential tool to understand how to read and interpret the experimental data fully. The following collection of experimental data are provided:</p> <ul> <li>32 steady-state measurements where the following factors were changed: ventilation mode (indoor and outdoor air curtain), solar irradiance (0, 400, 600, and 800 Wm<sup>-2</sup>), outdoor chamber temperature (10, 20, 30, and 40 ℃), cavity depth (20, 30, 40 and 60 cm) and venetian blinds position (no blinds, closed blinds, θ=45 º, and open blinds) [file names: ‘Taguchi_4Lx4F_L16_I-I.csv’ and ‘Taguchi 4Lx4F_L16_O-O.csv’],</li> <li>Dynamic profile measurements corresponding to a typical hot summer day [Dynamic_profile_measurements.csv] and</li> <li>Calibration data [Callibration.csv].</li> </ul> <p>Any inquires on the experimental data<em> can be sent </em>to: aleksandar.jankovic@ntnu.no</p>
Super-resolving ocean dynamics from space with computer vision algorithms: training datasets
<p>We provide here the datasets used for the development of the dilated Adaptive Residual Network for the super-resolution of ocean Absolute Dynamic Topography described in <em>Buongiorno Nardelli et al.</em> (2022). The model is designed to combine satellite altimetry and thermal observations and provides super-resolved dynamic topography. The training/test datasets have been built starting from the data originally prepared for an Observing System Simulation Experiment carried out in the framework of the European Space Agency CIRCOL project [<em>Ciani et al.</em>, 2021]. They consist of one year of synthetic daily Absolute Dynamic Topography (ADT), surface geostrophic currents and sea surface temperature data obtained from Copernicus Marine Service Mediterranean Forecasting System (MFS) (Product ID: MEDSEA-ANALYSIS- FORECAST-PHY-006-013) [<em>Clementi et al. 2021</em>]. Synthetic Altimeter-derived ADT maps were obtained by first sampling the model output along the actual tracks of a synthetic constellation composed of 4 Radar Altimeters: Jason-3, Sentinel-3A, SARAL/Altika, and Cryosat-2 missions (this step is achieved by running the SWOT simulator software [<em>Gaultier et al.</em>, 2016]) and successively applying the DUACS (<em>Data Unification and Altimeter Combination System)</em> mapping method. The original input images cover the entire Mediterranean domain at 1/24° spatial resolution, leading to an individual image size of 380x1000 pixels. Here, we have randomly chosen 40 dates (~11% of the total) to be kept aside as fully independent test data, and successively re-sampled the original images extracting much smaller tiles (76x100), which are used as input to the network training. The tiles are extracted by going through a double loop on latitude and longitude, imposing a spatial overlap of 50%. Full details on data pre-processing (e.g.normalization strategies) are given in the paper:</p> <ul> <li>Buongiorno Nardelli, B.; Cavaliere, D.; Charles, E.; Ciani, D. Super-Resolving Ocean Dynamics from Space with Computer Vision Algorithms. <em>Remote Sens.</em>, <strong>2022</strong>, 14, 1159. https://doi.org/10.3390/rs14051159</li> </ul>
Impact of the dynamics of the catalytic arginine on nitrite and chlorite binding by dimeric chlorite dismutase
<ul> <li><strong>Data type</strong>: spectroscopic measurements (UV-visible, ECD, EPR), DSC measurements, X-ray crystallography datasets, kinetic measurements, Molecular Dynamics simulations and data analysis.</li> <li>Files are in <strong>spc, par, DTA, DSC, dsx, csv, mtz </strong>formats</li> <li>Information on <strong>origin of the data</strong>: <ul> <li>EPR spectroscopic measurements in <strong>spc</strong>,<strong> par</strong>,<strong> DTA </strong>and<strong> DSC</strong> formats</li> <li>EPR spectroscopic simulation and analyses in <strong>m </strong>and<strong> mat</strong> format</li> <li>UV-vis spectroscopic measurements in <strong>csv</strong> format</li> <li>ECD measurements in <strong>dsx</strong> format</li> <li>Enzyme activity data in <strong>csv</strong> format</li> <li>DSC measurements in <strong>csv </strong>format</li> <li>X-ray data in <strong>mtz</strong> format</li> <li>MD simulations data are in<strong> xlsx</strong> format</li> </ul> </li> <li>The data are <strong>generated</strong> by: <ul> <li>UV−vis spectra were recorded using a Cary 60 UV−vis spectrophotometer (Agilent).</li> <li>Electronic circular dichroism spectroscopy was performed using Chirascan (Applied Photophysics, Leatherhead, U.K.).</li> <li>X-Band CW-EPR experiments were performed on A) a Bruker ESP300E spectrometer equipped with a liquid helium cryostat (Oxford Inc.); B) a Bruker ELEXSYS E580 X-band spectrometer equipped with an Oxford ESR 900 continuous-flow helium cryostat and a Bruker ER 4122 SHQ resonator.</li> <li>Enzyme activity was measured polarographically following the release of O2 by using a Clark-type oxygen electrode (Oxygraph Plus; Hansatech Instruments, Norfolk, U.K.).</li> <li>Differential scanning calorimetry experiments were performed on a Micro-Cal PEAQ-DSC Automated instrument (Malvern Panalytical Ltd., Malvern, U.K.) equipped with an autosampler for 96-well plates and controlled by the MicroCal PEAQ-DSC software.</li> <li>Crystallization experiments were performed using the sitting drop vapor diffusion method in SWISSCI MRC three-well crystallization plates (Molecular Dimensions, Newmarket, U.K.). Crystallization drops were set up using a mosquito crystallization robot (TTP Labtech). Commercially available crystallization screens were used for further screening. Crystallization plates were stored in a Formulatrix RI-1000 imaging device at 22 °C. Data were collected at 100 K using an Eiger2 XE 16 M detector at the beamline i04 at the Diamond Light Source (DLS, Didcot, United Kingdom). Further data was collected at 100 K at beamline ID30A-3 using a Eiger X 4 M detector, at beamline ID-23-1 using a Pilatus 6 M detector and at beamline ID23-2 using a PILATUS3 X 2 M detector at the of European Synchrotron Radiation Facility (ESRF, Grenoble, France). Data sets were processed with XDS, and symmetry equivalent reflections merged with XDSCONV.</li> <li>Molecular dynamics simulations were performed using the GROMOS11 molecular simulation package and GROMOS force field 54A8. Analyses of the coordinate trajectories was done with Gromos++ programs hbond, rdf and mdf. Coordinates at specific time point were generated using Gromos++ program frameout and analysed using PyMOL Molecular Graphics System.</li> <li> <ul> <li>Files in <strong>PARACAT_WP3_20211216_01_EPR </strong>folder includes EPR spectroscopic measurements and computer simulations/analyses, original data are in <strong>spc</strong>/<strong>par </strong>or<strong> DTA/DSC</strong> formats; files in <strong>m</strong> format were used to process the data.</li> <li>Files in <strong>PARACAT_WP3_20211216_02_UV-vis </strong>folder includes UV-Vis spectroscopic measurements of pH-titration in <strong>csv</strong> format.</li> <li>Files in <strong>PARACAT_WP3_20211216_03_ECD </strong>folder includes ECD measurements of the far UV (180–260 nm) and visible (260–500 nm) area, as well as unfolding curves in <strong>dsx</strong> format.</li> <li>Files in <strong>PARACAT_WP3_20211216_04_activity </strong>folder includes Clark electrode/activity measurements in<strong> csv</strong> format.</li> <li>Files in <strong>PARACAT_WP3_20211216_05_DSC </strong>folder includes DSC measurements in <strong>csv </strong>format.</li> <li>Files in <strong>PARACAT_WP3_20211216_06_Xray </strong>folder includes pre-processed (from the beamline pipeline) data sets in <strong>mtz</strong> format.</li> <li>Files in <strong>PARACAT_WP3_20211216_MD-Simulations </strong>folder includes pre-processed molecular dynamics data in<strong> xlsx</strong> format.</li> </ul> </li> </ul> </li> </ul> <p>NB. See the “READ ME” text file in each subfolder for more detailed information on files organization.</p> <ul> <li><strong>Information on</strong>: <ul> <li>Abbreviations:<strong> Cld</strong>, chlorite dismutase; <strong><em>C</em>Cld</strong>, chlorite dismutase from Cyanothece sp. PCC7425; <strong>CW</strong>, continuous wave; <strong><em>D</em></strong>, tetragonal zero-field splitting; <strong>DSC</strong>, differential circular calorimetry; <strong><em>E</em></strong>, rhombic zero-field splitting; <strong>ECD</strong>, electronic circular dichroism; <strong>EPR</strong>, electron paramagnetic resonance; <strong>HS</strong>, high-spin; <strong>LS</strong>, lowspin; <strong><em>Nd</em>Cld</strong>, chlorite dismutase from “Candidatus Nitrospira defluvii”; <strong>WT</strong>, wild type; <strong>ZFS</strong>, zero-field splitting.</li> </ul> </li> </ul> <p> </p> <ul> <li>Units of measurement: <ul> <li>Concentration: <strong>mM</strong> (millimolar), <strong>µM</strong> (micromolar), <strong>mg/mL</strong> (milligrams per milliliter), <strong>w/v %</strong> (weigth/volume) <strong>v/v %</strong> (volume/volume)</li> <li>Absorptivity: <strong>M<sup>-1</sup></strong> <strong>cm<sup>-1</sup></strong></li> <li>Volume: <strong>mL</strong> (milliliters), <strong>µL </strong>(microliters), <strong>nL</strong> (nanoliters)</li> <li>Wavelength:<strong> nm</strong> (nanometers)</li> <li>Temperature:<strong> °C</strong> (Celsius degrees), <strong>K</strong> (Kelvin degrees)</li> <li>Time:<strong> min</strong> (minutes), <strong>h</strong> (hours), <strong>ns</strong> (nanoseconds)</li> <li>Ellipticity: millidegrees</li> <li>Frequency: <strong>GHz</strong> (gigahertz), <strong>kHz</strong> (kilohertz)</li> <li>Power: <strong>mW</strong> (milliwatt)</li> <li>Pressure: <strong>atm</strong> (atmosphere)</li> </ul> </li> </ul>
Experimental data for the motor learning study performed: "Towards functional robotic training: Motor learning of dynamic tasks is enhanced by haptic rendering but hampered by robotic assistance"
<p>The dataset contains the kinematic data and the questionnaire responses for a robot-assisted motor learning study performed in the Motor Learning and Neurorehabilitation Laboratory at the University of Bern. The details of the study are described in [doi: ]. The kinematic data for each participant is stored as a data frame inside a “pickle” (serialized python object) file. The questionnaire responses and population metrics are stored as “CSV” files. The variables inside the files are explained in “DataframeVariableDescription.rtf”. For questions, please contact oezhan.oezen@artorg.unibe.ch or L.MarchalCrespo@tudelft.nl.</p>
DNA methylation dynamics during stress-response in woodland strawberry (Fragaria vesca)
<p><strong>Genome sequence and annotation of Fragaria vesca cv. Reine des Vallées</strong></p> <p>In order to generate a reference genome for Fragaria vesca cv. Reine des Vallées, we used MinIon long-read sequencing data to substitute the <em>F. vesca</em> genome v.4.0.a2 genome. The detailed method used to obtain these results were the following:</p> <p><em>Genome sequencing and assembly NIL Fb2</em></p> <p>Genomic DNA from strawberry plants was extracted by a Hexadecyltrimethylammonium bromide (Cetrimonium bromide, CTAB) modified protocol (Healey, Furtado, Cooper, & Henry, 2014) and purified with Agencourt AMPure XP beads (cat# A63880). Long-read sequencing was performed for the genome assembly; Genomic DNA by Ligation (Oxford Nanopore, cat# SQK-LSK109) library was prepared as described by the manufacturer and sequenced on a MinION for 72 h (Oxford Nanopore).</p> <p><em>Reference genome polishing</em></p> <p>Reads obtained from nanopore were filtered with Filtlong v0.2.1 (<a href="https://github.com/rrwick/Filtlong">https://github.com/rrwick/Filtlong</a>) using --min_mean_q 80 and --min_length 200. Cleaned reads were then aligned to the most recent version of the <em>F. vesca</em> genome v4.0.a2, downloaded from the Genome Database for Rosaceae (GDR) (<a href="https://www.rosaceae.org/species/fragaria_vesca/genome_v4.0.a2">https://www.rosaceae.org/species/fragaria_vesca/genome_v4.0.a2</a>), using minimap2 v2.21 (H. Li, 2018) with parameters -aLx map-ont --MD -Y. The generated BAM file was then sorted and indexed with samtools v1.11 (H. Li et al., 2009). We used mosdepth v0.3.1 (Pedersen & Quinlan, 2018) to verify that coverage on chromosomic scaffolds was over 50 X. Sniffles v1.0.12a (Sedlazeck et al., 2018) with parameters -s 10 -r 1000 -q 20 --genotype -l 30 -d 1000 was used to detect structural variations larger than 30 bp. The VCF files obtained from Sniffles was sorted and filtered with BCFtools v1.14 (Danecek et al., 2021) to keep only structural variants (SV) with smaller than 200,00 bp (we observed that larger SV were most of the time false positive caused by misalignments in regions with gaps or Ns), supported by 10 or more reads and with allelic frequencies above 0.8 (we were interested in homozygous changes). The complete filtering command used is “bcftools view -q 0.8 -Oz -i '(SVTYPE = "DUP" || SVTYPE = "INS" || SVTYPE = "DEL" || SVTYPE = "TRA" || SVTYPE = "INV" || SVTYPE = "INVDUP") && %FILTER = "PASS" && FMT/DV>9 && SVLEN>29 && SVLEN<200000' “</p> <p>From the VCF listing all the structural variants that we detected in our <em>F. vesca </em>accession, we generated a substituted genome version based on the reference <em>F. vesca</em> genome v.4.0.a2. The reference genome was first indexed with samtools faidx v1.11(Danecek et al., 2021) and a sequence dictionary was generated with Picard CreateSequenceDictionary v2.25.6 (<a href="https://broadinstitute.github.io/picard">https://broadinstitute.github.io/picard</a>). The VCF containing the SV produced from our Nanopore sequencing was also indexed with gatk (Van der Auwera GA & O'Connor BD, 2020) IndexFeatureFile v4.2.0.0 (<a href="https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile">https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile</a>). FastaAlternateReferenceMaker v4.2.0.0 (<a href="https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker">https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker</a>) was then run with the reference genome and the VCF file to generate a substituted genome representative of our <em>Fragaria</em> accession.</p> <p>As substituting our genome with the detected structural variants changes genomic coordinates, we also corrected the public GFF genome annotation of <em>F. vesca</em> (Y, Pi, Gao, Liu, & Kang, 2019) using liftoff v1.6.1 (Shumate & Salzberg, 2021). Liftoff also detects and annotates duplications within the substituted genome.</p> <p>Transposable elements annotation was carried out using the EDTA transposable element annotation pipeline v. 1.9.6 (S. Ou et al., 2019) on the substituted genome using default parameters<em>.</em></p> <p><strong>Differentially methylated regions</strong></p> <p>The file Stress_vs_control_DMRs.zip file contains the DMRs that were called using the reads submitted to ENA (ERP135585) and obtained as follows:</p> <p>First, bedGraph files from wgbs pipeline were pre-filtered for a minimum coverage of 5 reads using awk command. These output files were then used as input for the EpiDiverse/dmr bioinformatics analysis pipeline for non-model plant species to define DMRs (Nunn <em>et al</em>., 2021) with default parameters (minimum coverage threshold 5; maximum q-value 0.05; minimum differential methylation level 10%; 10 as minimum number of Cs; Minimum distance (bp) between Cs that are not to be considered as part of the same DMR is 146 bp). The pipeline uses metilene v.0.2.6.1 (<a href="https://www.bioinf.uni-leipzig.de/Software/metilene/">https://www.bioinf.uni-leipzig.de/Software/metilene/</a>) for pairwise comparison between groups and R-packages ggplot2 v.3.3.5 and gplots v.3.1.1, for visualization results (Fig. S1). Based on our <em>F. vesca</em> genome transcript annotation and methylation data (overlapped regions with DNA methylation cytosines and DMRs), we detected the methylated genes, promoters, 3’ UTRs, 5’UTR and transposable elements in strawberry. Global DNA methylation and DMR plots were performed with R-package ggplot2. Gene analyses by methylation patterns and analysis of per-family TE DNA methylation profiles were performed with deepTools v.3.5.0 (Ramírez <em>et al</em>., 2014). DMRs comparison between treatments were done by the Venn diagram v.1.7.0 R-package.</p> <p>We produced several genome browsers tracks with DMRs that we integrated in our local instance of JBrowse available at the following url: <a href="https://jbrowse.agroscope.info/jbrowse/?data=fragaria_sub">https://jbrowse.agroscope.info/jbrowse/?data=fragaria_sub</a></p>
Nonlinear two-level dynamics of quantum time crystals
<p>Dataset for the manuscript titled "AC Josephson effect between two superfluid time crystals" by the same authors.</p>
Modelling pan-Arctic peatland carbon dynamics under alternative warming scenarios
<p>The purpose of this study is to simulate peatland carbon dynamics in the future climate conditions for four major future warming scenarios. The study examines whether less pronounced warming could further enhance the peatland carbon sink capacity and buffer the effects of climate change. It will also determine which trajectory peatland carbon balance will follow, what the main drivers are and which one will dominate in the future.</p> <p>In this study, LPJGUESS Peatland has been employed across the pan-Arctic and we carried out four sets of simulations. The data files contain the information about carbon accumulation, NEE, NPP and ice fraction.</p>
Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics
<p>Full-resolution representative data sufficient to repeat analyses for the work of: AE Wolf, MA Heinrich, IB Breinyn, TJ Zajdel, and DJ Cohen in "Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics".</p> <p>Please see the _README2.0.0.txt file for explanations on contents in this Zenodo repository.</p> <p>Relevant codes used in our analyses are available on Github (github.com/CohenLabPrinceton/ElectrotaxisSupracellularMemory).</p>
Atomistic trajectories from ab-initio molecular dynamics simulations of wetted TiO2 nanoparticle
<p>This repository contains atomistic trajectories from ab-initio molecular dynamics simulations of water and TiO2 nanoparticle described in the paper:</p> <p>E. G. Brandt, L. Agosta and A.P.Lyubartsev, " Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations", Nanoscale, 8, 13385-13398 (2016) DOI: 10.1039/c6nr02791a</p> <p>The trajectories are saved in the .xtc format, and initial structures with specification of atom types are given in the .pdb format.</p> <p>The name of each file contains brief information about the simulated system:</p> <p>TiO2 : composition of the nanoparticle<br> n24 : number of TiO2 units in the nanoparticle<br> anatase/brookite/rutile : type of crystall structure<br> - a number 0 - 30 : number of water molecules in the simulation<br> 2fs - the time step</p> <p>For more details, see the referred paper</p>
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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
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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
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