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2,271 results for “transporte”
Monosaccharide transporter OsMST6 is activated by transcription factor OsERF120 to enhance chilling tolerance in rice seedlings
<p>Chilling stress caused by extreme weather is threatening global rice (<em>Oryza sativa</em> L.) production. Identifying components of the signal transduction pathways underlying chilling tolerance in rice would advance molecular breeding. Here, we report that <em>OsMST6</em>, which<em> </em>encodes<em> </em>a monosaccharide transporter, positively regulates the chilling tolerance of rice seedlings. The <em>mst6</em> mutants showed hypersensitivity to chilling, while the <em>OsMST6</em> overexpression lines were tolerant. During chilling stress, OsMST6 transported more glucose into cells to modulate sugar and ABA signal pathways. We showed that the transcription factor OsERF120 could bind to the DRE/CRT element of the <em>OsMST6</em> promoter and activate the expression of <em>OsMST6</em> to positively regulate chilling tolerance. Genetically, OsERF120 was functionally dependent on OsMST6 when promoting chilling tolerance. In summary, OsERF120 and OsMST6 form a new downstream chilling regulatory pathway in rice in response to chilling stress, providing valuable findings for molecular breeding aimed at achieving global food security.</p> <p><span>The stored data is the analysis results of transcriptome data from ZH11 and <em>mst6-1</em> after 0 hours and 4 hours of chilling treatment. These data form the basis for the transcriptome data visualization in the article.</span></p>
A phosphate transporter in VIPergic neurons of the suprachiasmatic nucleus gates locomotor activity during the light/dark transition in mice
<p>Raw Data for <strong>An atypical phosphoswitch in specific neurons of the suprachiasmatic nucleus gates locomotor activity at the light/dark transition in mice</strong></p> <ol> <li>Multi-electrode array data from PiT2<sup>+/+</sup> and PiT2<sup>-/-</sup> mice</li> <li>Locomotor activity from PiT2<sup>+/+ </sup>and PiT2<sup>-/-</sup> mice in LD 12:12, DD, LD 4:20, LD 20:4 and DD with light pulses</li> <li>Phosphoproteome data</li> </ol>
Exploring the thermal and ionic transport of Cu+ conducting argyrodite Cu7PSe6 (Computational data)
<p>This repository contains computational data for the manuscript titled “Exploring the thermal and ionic transport of Cu+ conducting argyrodite Cu7PSe6”. It consists of outputs and analysis scripts for bonding analysis through LOBSTER, harmonic phonon, and Grüneisen parameters calculations using VASP and phonopy. </p>
Raw data from "AC transport detection of magnetic transitions in small and granular samples"
<p>Raw data supporting the submitted manuscript "AC transport detection of magnetic transitions in small and granular samples". Additional information avaliable upon request.</p>
Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se)
<p>The structural, electrical, and optical properties of a series of six layered oxychalcogenides with general formula Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> where <em>M</em> = Ga, Sc, or In and <em>Ch</em> = S or Se have been investigated. From this set we report the structure and properties of Sr<sub>2</sub>GaO<sub>3</sub>CuSe for the first time, as well as the full structural details of Sr<sub>2</sub>ScO<sub>3</sub>CuSe, which have not previously been available. A systematic study of the suitability of all the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> phases as <em>p</em>-type conductors has been carried out, after doping with both sodium and potassium to a nominal composition of <em>A</em><sub>0.05</sub>Sr<sub>1.95</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em>, (<em>A</em> = Na or K), to increase the hole carrier concentration. Density functional theory calculations were used to determine the electronic band structure and predict the transport properties, while optical properties were determined using UV-vis spectroscopy, and structures confirmed using Rietveld refinement against powder X-ray diffraction data. Room temperature conductivity measurements were carried out on both pristine samples and doped samples, eighteen compositions in total, using four-point probe measurements. We found that the most conductive sample wasK<sub>0.05</sub>Sr<sub>1.95</sub>GaO<sub>3</sub>CuSe, with a measured conductivity of 0.46 Scm<sup>−1</sup>, collected from a sintered pellet. We have also been able to identify a relationship between the conductivity and the geometry of the copper chalcogenide layer within the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> series of compounds. As this geometry can be controlled through the material composition, the identification of this structure-property relationship highlights a route to selection and identification of materials with even higher conductivities.</p> <p> </p> <p>This repository contains the computational research data generated for *Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se).</p> <p> </p> <p>## Folder Architecture</p> <p>The folders contain the structures relaxed with hybrid functionals (HSE06), the band structure and the uniform DOS and AMSET calculations for each system.</p> <p> </p> <p> </p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
Supporting Data for "Thermal Transport Through CTAB- and MTAB-Functionalized Gold Interfaces using Molecular Dynamics Simulations"
<p>This gzipped tar archive contains initial configurations and parameters used for the simulations in the manuscript:</p> <p>"Thermal Transport Through CTAB- and MTAB-Functionalized Gold Interfaces using Molecular Dynamics Simulations", by Sydney A. Shavalier, and J. Daniel Gezelter</p> <p>A note on naming conventions. All simulations have filenames with with two numbers - one that signifies simulation replica (1-5), and another that signified which step of equilibration/RNEMD was being performed. For example, lowmtab111_3opt4 would signify the third simulation replica of a low coverage MTAB system and a (111) gold facet, which was on its fourth equilibration step after optimization.</p> <p>The OpenMD simulation engine utilizes a number of file extensions that are present in this archive:</p> <p><strong>.omd</strong> : A combined MetaData and configuration file that is used to start a simulation <br><strong>.frc</strong> : a force field parameter file<br><strong>.eor</strong> : an 'end of run' or final configuration (same format as .omd)<br><strong>.stat</strong> : status file with instantaneous information about energies, temperatures, etc. These are generally large and have not been included, as they can be regenerated easily from the .omd file.<br><strong>.report </strong>: a post-simulation file containing thermodynamic averages from the .stat file<br><strong>.dump</strong> : a full trajectory file containing positions and velocities sampled at a 'sampleTime' specified in the .omd file. These are generally very large and have not been included, as they can be regenerated from the .omd file.<br><strong>.rnemd</strong> : Contains spatial information about temperatures, densities, etc. for simulations run under reverse non-equilibrium molecular dynamics</p> <p>Other data analyis or utility file extensions:</p> <p><strong> .pack</strong> : Files for creating systems with Packmol<br><strong> .z</strong> : Density \rho(z) for specific selected atom types<br><strong> .r </strong> : Density \rho(r) for specific selected atom types<br><strong> .p2z</strong> : Legendre Polynomial Correlation using z as reference axis<br><strong> .p2r</strong> : Legendre Polynomial Correlation using radial vector as reference axis<br> <strong>.chargez</strong> : Charge density as a function of z-axis<br> <strong>.charger</strong> : Charge density as a function of radius<br> <strong>.agr</strong> : Grace graphing package data<br><strong> .xyz </strong> : XYZ (Cartesian) coordinates for visualization<br> </p> <p>The archive is organized as follows:</p> <p> ./CTAB/111: Simulations of Au(111) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/111/RNEMD<br> ./CTAB/110: Simulations of Au(110) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/110/RNEMD<br> ./CTAB/100: Simulations of Au(100) functionalized with CTAB<br> final systems begin with "highctab"<br> RNEMD simulations are in ./CTAB/100/RNEMD<br> ./MTAB/111: Simulations of Au(111) functionalized with MTAB <br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/111/RNEMD<br> ./MTAB/110: Simulations of Au(110) functionalized with MTAB<br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/110/RNEMD<br> ./MTAB/100: Simulations of Au(100) functionalized with MTAB <br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/100/RNEMD<br> ./MTAB/NP/R10: Simulations of Au Nanoparticles (r = 10 angstroms),<br> functionalized with MTAB<br> final systems begin with "highmtab" or "lowmtab"<br> RNEMD simulations are in ./MTAB/NP/R10/RNEMD</p> <p>Systems that were run with metal polarizability turned on have 'fq' as part of their filenames.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
Dataset: Survey for Identifying User Groups of Active Transport Modes in Urban Centers
<p>This dataset was derived from an online questionnaire conducted between June and July 2022. The survey aimed to identify groups of individuals based on patterns revealed through clustering methods, considering the importance assigned to various indicators associated with the dimensions of comfort, safety and security, and time and distance. <span>CSV file structure details are available at 'csv_structure.xlsx'. </span></p> <p>The questionnaire also included a set of items designed to capture the respondents' sociodemographic context, specifically:</p> <ul> <li>Gender </li> <li>Parental Status</li> <li>Age Group</li> <li>Educational Level</li> <li>Country of Residence </li> <li>Employment Situation </li> </ul>
Simulations of FLEXPART-WRF used for testing TRansport Of water VApor (TROVA) software (Part II)
<p>Necessary data for carrying out the tests using TRansport Of water VApor (TROVA) software for backward in time. The TROVA software, was developed in Python and Fortran for the study of moisture sources and sinks. <span><span><span>In addition, the Python code is provided for the representation of the results.</span></span></span></p>
Grid-Free Evaluation of Phonon-Limited Relaxation Times and Electrical Transport Properties
<p>Data, source codes and figures for the manuscript:</p> <p>"Grid-Free Evaluation of Phonon-Limited Relaxation Times and Electrical Transport Properties"</p>
Dataset for: Anniés et al., "Accessing structural, electronic, transport and mesoscale properties of Li-GICs via a complete DFTB-model with machine-learned repulsion potential"
<p>GPrep training data, GPrep jupyter notebook, .skf files.</p> <p>The GPrep code is available at https://doi.org/10.5281/zenodo.3697913</p>
Data and code for the publication "Tracking microplastics across the streambed interface: Using laser-induced fluorescence to quantitatively analyze microplastic transport in an experimental flume"
<p>This archive contains datasets and codes that were used in the publication "Tracking microplastics across the streambed interface: Using laser-induced fluorescence to quantitatively analyse microplastic transport in an experimental flume".</p>
Needs-based approaches for representing personal transportation decision-making
<p>Data from a Utah State University research study, "Needs-based approaches for representing personal transportation decision-making". This version includes data from the focus group portion of the study. </p>
Data for: Serotonin transporter (SERT) polymorphisms, personality and problem-solving in urban great tits
<p class="CxSpFirst"><span><span><span><span><span><span><span><span><span><span><span>Understanding underlying genetic variation can elucidate how diversity in behavioral phenotypes evolves and is maintained. Genes in the serotonergic signaling pathway, including the serotonin transporter gene (<i>SERT)</i>, are candidates for affecting animal personality, cognition and fitness. In a model species, the great tit (<i>Parus major</i>), we reevaluated previous findings suggesting relationships between <i>SERT</i> polymorphisms, neophobia, exploratory behavior and fitness parameters, and performed a first test of the relationship between single nucleotide polymorphisms (SNPs) in SERT and problem-solving in birds. We found some evidence for associations between <i>SERT </i>SNPs and neophobia, exploratory behavior and laying date. Furthermore, several SNPs were associated with behavioral patterns and success rates during obstacle removal problem-solving tests performed at nest boxes. In females, minor allele homozygotes (AA) for nonsynonymous SNP226 in exon 1 made fewer incorrect attempts and were more likely to problem-solve. In both sexes, there was some evidence that minor allele homozygotes (CC) for SNP84 in exon 9 were more likely to problem-solve. Only one SNP-behavior relationship was statistically significant after correcting for multiple comparisons, but several were associated with substantial effect sizes. Our study provides a foundation for future research on the genetic basis of behavioral and cognitive variation in wild animal populations. </span></span></span></span></span></span></span></span></span></span></span></p>
Dataset for the paper "Toward Understanding the Utilization of Oxygen Reduction Electrocatalysts under High Mass Transport Conditions and High Overpotentials"
<table> <tbody> <tr> <td>The data in this spreadsheet was used to produce the figures in the paper</td> </tr> <tr> <td>Authors:</td> <td>Colleen Jackson, Xiaoqian Lin, Pieter B. J. Levecque, and Anthony R. J. Kucernak</td> </tr> <tr> <td>Title:</td> <td>Toward Understanding the Utilization of Oxygen Reduction 2 Electrocatalysts under High Mass Transport Conditions and High 3 Overpotentials</td> </tr> <tr> <td>Journal:</td> <td>ACS Catalysis</td> </tr> <tr> <td>DOI:</td> <td><a href="https://doi.org/10.1021/acscatal.1c03908">https://doi.org/10.1021/acscatal.1c03908</a></td> </tr> <tr> <td>Please cite the above reference if you wish to use this data</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>DOI of data:</td> <td>10.5281/zenodo.5774052</td> </tr> </tbody> </table>
Dataset and code for "A parameterization of non-hydrostatic pressure transport terms in second- and third-order turbulence equations"
<p>Description of included files:</p> <p> </p> <p><strong>Cloud Layers Unified By Binormals (CLUBB) content</strong></p> <p>The zipped up "clubb_release.tar.gz" folder contains the CLUBB code base used to generate the simulations used in this paper. The ifort compiler was used to produce the simulations used in the paper.</p> <p>The zipped up "clubb_files.tar.gz" folder contains BOMEX, DYCOMS2_RF01, and Wangara 1D simulations for "default" runs (without new pressure transport terms) and "new" runs (with new pressure transport terms). Setup files are also included which give the parameter and flag values for each run. The files contained in clubb_files.tar.gz are:</p> <ol> <li>bomex_setup_dflt.txt</li> <li>bomex_zt_dflt.nc</li> <li>bomex_zm_dflt.nc</li> <li>bomex_sfc_dflt.nc</li> <li>dycoms2_rf01_setup_dflt.txt</li> <li>dycoms2_rf01_zt_dflt.nc</li> <li>dycoms2_rf01_zm_dflt.nc</li> <li>dycoms2_rf01_sfc_dflt.nc</li> <li>wangara_setup_dflt.txt</li> <li>wangara_zt_dflt.nc</li> <li>wangara_zm_dflt.nc</li> <li>wangara_sfc_dflt.nc</li> <li>bomex_setup_new.txt</li> <li>bomex_zt_new.nc</li> <li>bomex_zm_new.nc</li> <li>bomex_sfc_new.nc</li> <li>dycoms2_rf01_setup_new.txt</li> <li>dycoms2_rf01_zt_new.nc</li> <li>dycoms2_rf01_zm_new.nc</li> <li>dycoms2_rf01_sfc_new.nc</li> <li>wangara_setup_new.txt</li> <li>wangara_zt_new.nc</li> <li>wangara_zm_new.nc</li> <li>wangara_sfc_new.nc</li> </ol> <p>The CLUBB code base used for this paper can also be obtained by cloning the repo at https://github.com/larson-group/clubb_release.git. The relevant git branch is "stephens_2022_press_trans_paper" and the relevant git commit hash is 937db014df79318655b4fb6a469a7b77529b2e74. Compiled with ifort, the stephens_2022_press_trans_paper branch will generate the "new" simulations without further modifications. To generate the "dflt" simulations, set C_wp2_pr_dfsn = C_wp3_pr_dfsn = 0 in input/tunable_parameters/tunable_parameters.in, and set l_use_tke_in_wp2_wp3_K_dfsn = .false. in input/tunable_parameters/configurable_model_flags.in.</p> <p> </p> <p><strong>System for Atmospheric Modeling (SAM) content</strong></p> <p>SAM LES files with horizontal average variables:</p> <ol> <li>BOMEX_64x64x75_100m_40m_1s.nc</li> <li>DYCOMS_RF01_96x96x320.nc</li> <li>WANGARA_64x64x80_100m_40m_LES.nc</li> </ol> <p>The SAM code base used for this paper can be obtained by cloning the repo at https://github.com/larson-group/sam_clubb.git. The relevant git commit hash is db3e00a09cb5c0503e1bf3a728603fe690cb9a3e. The gfortran compiler was used to generate the runs used in the paper.</p> <p> </p> <p><strong>Python script</strong></p> <p>The included python script "stephens_2022_press_trans_paper_figures.py" can be used along with the SAM and CLUBB files to generate the plots shown in the paper, with some simple user modifications. This script can also be found in the stephens_2022_press_trans_paper branch of the clubb_release repo, in the "postprocessing" folder.</p>
Dataset of nanoplastic transport in soil via bioturbation by Lumbricus terrestris
<p>The dataset comprises data acquired in laboratory-based process-studies with microcosms on the transport of nanoplastics (polystyrene, 256 nm diameter) in an agricultural soil via bioturbation over the course of 4 weeks. Transport of nanoplastics was monitored through the use of palladium (Pd)-doped nanoplastics (0.24 % w/w) by analyzing soil samples at specific depths (0-2 cm, 2-6 cm, 6-15 cm, 15-29 cm) after defined experimental times (7, 14, 21, 28 days). Microcosms consisted of 30 cm height, 10 cm diameter soil columns which were set up with or without earthworms and with or without nanoplastics spiked to the uppermost 2 cm. Two experimental runs were executed with the first (Exp1) designed to focus on the average transport within the soil profile over time, and the second (Exp2) focussing on the smaller scale distribution of the nanoplastics in the soil (i.e. soil matrix versus drilosphere) while monitoring earthworm burrow development over time using X-ray computed tomography. In the first experiment, earthworms were measured for their nanoplastic content after the experiment.</p> <p>The dataset made available here comprises the details of the microcosm setup for Exp1 and Exp2, details on detected nanoplastic concentrations for the average soil profile (Exp1), drilosphere and soil matrix (Exp2), as well as detected concentrations in earthworm tissue and monitoring of earthworm weight (Exp1). A selection of X-ray CT images is also provided, chosen based on the considered highest relevance. X-ray CT scans of other measurement timepoints are available upon request.</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
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.