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2,271 results for “transporte”
Fig. 1 in Transportation of microplastic during high-flow and low-flow seasons in southeastern Black Sea: A modelling approach
Fig. 1 — Map of the study area and microplastic release point
An Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretization of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation
<p>This repository holds all of the raw data generated by my (Modern) Fortran code for a paper "An Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretization of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation".</p> <p>The (Modern) Fortran code solves the SAAF form of the multi-group neutron transport equation using novel NURBS-based, IGA spatial discretisations.</p>
Southampton Pathology Sample Transport
<p>This dataset concerns pathology samples taken from patients at doctors’ offices (i.e., GPs’ surgeries) in and around the Southampton area. Vans collect these samples and transport them to a pathology laboratory at Southampton General Hospital for analysis. The data detail where and when samples were generated, and the van routes used to transport them. The locations of places in the dataset are representative of the real-world situation, but have been altered so as to be fictitious and do not describe actual activity.</p>
Data for: Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model
<p>This dataset, provided in NetCDF format, supports the research presented in the paper titled "Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model." Please contact Dr. Sun (ltsun@rams.colostate.edu) if you have any questions.</p>
Roles of Upwelling on the Dynamics and Freshwater Transport of a River Plume over the Inner Shelf_original
Open the record for dataset details and reuse information.
Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of a Constraint-Based Continuous Bubnov-Galerkin Isogeometric Analysis Spatial Discretisation of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation with Dual-Weighted Residual Error Measures
<p>This repository holds all of the raw data generated by my (Modern) Fortran code for a paper "Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of a Constraint-Based Continuous Bubnov-Galerkin Isogeometric Analysis Spatial Discretisation of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation with Dual-Weighted Residual Error Measures".</p> <p>The (Modern) Fortran code solves the SAAF form of the multi-group neutron transport equation using novel NURBS-based, IGA spatial discretisations.</p>
CMIP6 HighResMIP HadGEM3-GC3.1 LL, MM and HH datasets for the heat transport in the lower limb of the AMOC
<p>These data include datasets for "Resolving mesoscale eddies is crucial for the heat transport in the lower limb of the AMOC", submitted to <em>Geophysical Research Letters</em>.</p> <p>Each file is prefixed with model resolution (LL, MM and HH) and experiment details (control, SSP5-8.5). Files ending with '_velocities' and '_age_pressure' contain diagnostics projected on the isopycnal surface (sigma2=36.95), depicted in Figures 2 and 3 of the submitted paper. </p>
dataset: Transporting Tenebrio molitor Eggs: The Effect of Temperature, Humidity and Time on the Hatch Rate
Open the record for dataset details and reuse information.
Airborne microbial transport limitation to isolated Antarctic soil habitats
<p>Supplementary Figures 2-4 and 4-6 for Manuscript "Airborne microbial transport limitation to isolated Antarctic soil habitats".</p> <p> </p> <p> </p>
Data supporting Molecular Simulation of Hydrogen Storage and Transport in Cellulose
<p>Data support article accepted for publication in Molecular Simulation. Data includes inputs for crystal relaxation, absorption and diffusion simulations. All processed data required to reproduce plots included and outputs where practicable. Where impractical simulations can be rerun from the inputs provided.</p>
Raw diffraction images of plant vacuolar iron transporter VIT1 (with Zn and Co)
<p>Diffraction images of full-length VIT1 related to PDB codes <a href="https://www.rcsb.org/structure/6IU3">6IU3</a> (Zn-bound) and <a href="https://www.rcsb.org/structure/6IU4">6IU4</a> (Co-bound). All data were collected from loop-harvested (micro)crystals on BL32XU, SPring-8 using EIGER X 9M detector.<br> <br> 6IU3: Helical (20, 45, or 90°/crystal) datasets were collected automatically using ZOO system at a wavelength of 1 Å.<br> 6IU4: Small-wedge (10°/crystal) and helical (120°/crystal) datasets were collected at a wavelength of 1.28 Å.<br> <br> The crystals belonged to space group <em>C</em>222<sub>1</sub> with unit cell parameter a~47, b~290, c~46 Å. All datasets were processed and merged using KAMO pipeline with XDS.</p> <p>Related entries: <a href="https://zenodo.org/record/2532134">metal binding domain</a>, <a href="https://zenodo.org/record/2532138">data for phasing by Hg-SIR</a> <br> </p>
Raw diffraction images of plant vacuolar iron transporter VIT1 (metal binding domain)
<p>Diffraction images of the metal binding domain of VIT1 related to PDB codes <a href="http://www.rcsb.org/structure/6IU5">6IU5</a> (Zn-bound), <a href="http://www.rcsb.org/structure/6IU6">6IU6</a> (Ni-bound), <a href="http://www.rcsb.org/structure/6IU8">6IU8</a> (Co-bound), and <a href="http://www.rcsb.org/structure/6IU9">6IU9</a> (Fe-bound).</p> <p>Helical data (180°/crystal) were collected from loop-harvested crystals on BL41XU, SPring-8 at the peak and low-remote wavelengths of specific metals (Zn: 1.2820/1.3000; Ni: 1.4850/1.5220; Co: 1.6050/1.6480; Fe: 1.74009/1.79148 Å).</p> <p>The crystals belonged to space group <em>P</em>3<sub>1</sub> with unit cell parameter a~85, c~98 Å.</p> <p>Related entries: <a href="https://zenodo.org/record/2532136">full-length with Co/Zn</a>, <a href="https://zenodo.org/record/2532138">full-length data for phasing by Hg-SIR</a></p>
Raw diffraction images of plant vacuolar iron transporter VIT1 (phasing data by Hg-SIR)
<p>Diffraction images of full-length VIT1 for Hg-SIR phasing. All data were collected from loop-harvested crystals on BL32XU, SPring-8 at a wavelength of 1 Å using the EIGER X 9M detector.</p> <p>For Hg-bound VIT1, six helical (71-210°/crystal) datasets were collected. From native (without Hg) crystals, 24 helical (20-90°/crystal) datasets were automatically collected. The crystals belonged to space group <em>C</em>222<sub>1</sub> with unit cell parameter a~47, b~290, c~46 Å.</p> <p>Related entries: <a href="https://zenodo.org/record/2532136">full-length with Co/Zn</a>, <a href="https://zenodo.org/record/2532134">metal binding domain</a><br> </p>
On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil (Data set)
<p>Data used for "On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" by Colombi T, Walder F, Büchi L, Sommer M, Liu K, Six J, van der Heijden M, Charles R and Keller T. (2019). SOIL. 5, 91-105, https://doi.org/10.5194/soil-5-91-2019.</p> <p>.txt file "MetaInformation_On-farm study reveals positive relationship between gas transport capacity and organic carbon content in arable soil" contains all necessary meta-information </p>
Raw diffraction images of prokaryotic peptide transporter PepTSo2
<p>Diffraction images of prokaryotic peptide transporter PepTSo2. In Nagamura et al. (<a href="https://doi.org/10.1107/S2053230X19003546">Acta Cryst. F, 2019</a>), the crystal form A (PDB code: <a href="http://www.rcsb.org/structure/6JKD">6JKD</a>, space group I4, 3.9 Å resolution) and the form B (PDB code: <a href="http://www.rcsb.org/structure/6JKC">6JKC</a>, space group P42<sub>1</sub>2, 3.5 Å resolution) were reported.</p> <p>Small-wedge (5 or 10°/crystal) datasets collected from loop-harvested microcrystals using EIGER X 9M detector at a wavelength of 1 Å on BL32XU, SPring-8.</p> <p>PepT-So2_171220_BL32XU_{1..4}.tar.xz contains directories 01, 07-1, 07-2, 09, 10, 11. PepT-So2_180215_BL32XU.tar.xz contains directories 01, 02, 03, 04, 05, 14. Different directories are from different crystallization conditions. It seems they have different space groups even though they may share the same reduced cells. In the literature for form A data (I4, a=b=115, c=110 Å) from 07-2 and 11 of 171220_BL32XU were used while for form B data (P42<sub>1</sub>2, a=b=119, c=104.3 Å) from 04 and 05 of 180215_BL32XU were used.<br> <br> Note that master.h5 files were modified; see <a href="https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md">https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md</a>.</p>
Data: Influence of Arm Swing on Cost of Transport during Walking
<p>Data and code for De Graaf et al. (2019): Influence of Arm Swing on Cost of Transport during Walking (<a href="https://doi.org/10.1101/426775">https://doi.org/10.1101/426775</a>).</p> <p>The ArmSwingData folder contains two subfolders. One with the raw data and one with the necessary scripts to run the analyses. The analysis can be run from the <strong>Main.m</strong> script located in the top folder. <strong>Start.m</strong> initializes the program, and saves some important variables in <strong>infovar.mat</strong> so most programs can be ran separately, without being called from Main.m. If you change the name of the ArmSwingData folder, make sure to change the name for the directory in this script.</p> <p>Data is ordered in the subfolder ‘Data’. For each participant (PP01, PP02, …, PP12) three folders exist:</p> <ul> <li><strong>Cosmed</strong>: contains excel files with the metabolic (cosmed) data, as well as age/height/weight information of the participant</li> <li><strong>ForcePlate</strong>: contains .afp and .afp2 files with kinetic data for forceplate 1 and 2 respectively. You can find which file corresponds to what condition in the file ‘Main_Forceplate.m’ stored in the software subfolder. Heelstrike information for the forceplate data has already been stored in the variable PP**_HS.mat, but can also be recalculated and checked from within the software. To do this open ‘Main_Forceplate.m’ and uncomment line 23 that runs ‘Forceplate_HeelStrike.m’ .</li> <li><strong>Xsens</strong>: contains .mvnx for all conditions. You can find which file corresponds to what condition in the file ‘Main_Xsens.m’ stored in the software subfolder. Heelstrike information for the xsens data has already been stored in the variable PPXX_HS.mat, but can also be recalculated and checked from within the software. To do this open ‘Main_Xsens.m’ and uncomment line 23 that runs ‘Xsens_HeelStrike.m’ .</li> </ul> <p>All scripts (except for start-up files Main.m and Start.m) are located in the software folder:</p> <ul> <li><strong>=VU 3D Model=</strong>: the somewhat under documented VU 3D model, several functions of which are being used;</li> <li><strong>Cosmed</strong>: All scripts belonging to the cosmed analysis. These can be all run from Main_Cosmed.m</li> <li><strong>ForcePlate</strong>: All scripts belonging to the kinetic analysis. These can be all run from Main_ForcePlate.m</li> <li><strong>Xsens</strong>: All scripts belonging to the kinematic analysis. These can be all run from Main_Xsens.m</li> <li><strong>Plotting</strong>: All scripts necessary for creating the figures featured. These can be all run from Plots.m</li> </ul> <p>All the Main_*.m files can in turn be ran from Main.m. The Main_*.m files also contain brief descriptions of the files. All files first check if the product they create already exist. If so they will not run. If you want to run them anyways, simply inverse the if ~exist statement by removing the tilde, the program will then be executed and the existing product will be overwritten.</p> <p>N.B. For Xsens_Align, checking if it’s product exists takes a long time, so it could be wise to not run this program again after the first time (set run=false at the start of the program, or simply comment the line in Main_Xsens)</p>
Supplemental Videos for: Association of SLC52A3a [p. L267P] and [p. T278M] with riboflavin transportation in esophageal cancer cells
<p>Supplemental data</p> <p>Supplemental Video S1 showing motility of GFP-SLC52A3a-WT containing vesicles in KYSE150 R<sup>+</sup> cells; </p> <p>Supplemental Video S2 showing motility of GFP-SLC52A3a-WT containing vesicles in KYSE150 R<sup>-</sup> cells; </p> <p>Supplemental Video S3 showing motility of GFP-SLC52A3a-L267P containing vesicles in KYSE150 R<sup>+</sup> cells;</p> <p>Supplemental Video S4 showing motility of GFP-SLC52A3a-L267P containing vesicles in KYSE150 R<sup>-</sup> cells;</p> <p>Supplemental Video S5 showing motility of GFP-SLC52A3a-T278M containing vesicles in KYSE150 R<sup>+</sup> cells;</p> <p>Supplemental Video S6 showing motility of GFP-SLC52A3a-T278M containing vesicles in KYSE150 R<sup>-</sup> cells;</p> <p>Supplemental Video S7 showing motility of GFP-SLC52A3a-L267/T278M containing vesicles in KYSE150 R<sup>+</sup> cells;</p> <p>Supplemental Video S8 showing motility of GFP-SLC52A3a-L267/T278M containing vesicles in KYSE150 R<sup>-</sup> cells.</p>
A Ceramide-Regulated Element in the Late Endosomal Protein LAPTM4B Controls Amino Acid Transporter Interaction - buil and Analysis
<p><strong>Title publication: </strong><em>A Ceramide-Regulated Element in the Late Endosomal Protein LAPTM4B Controls Amino Acid Transporter Interaction</em></p> <p><strong><strong>Year publication:</strong></strong><strong> </strong>2018</p> <p><strong>DOI publication: </strong>10.1021/acscentsci.7b00582</p> <p><strong>Description:</strong> All scripts, jupyter notebooks, and data files used to building and analyzing systems in the presented in the paper. Also related experimental data.</p>
Development and Implementation of Sustainable Transportation Resilience Indicators
<p>Communities are complex systems subject to a variety of hazards that can result in significant disruption to critical functions. Community resilience assessment is gaining popularity as a means to help communities better prepare for, respond to, and recover from disruption. Sustainable resilience, a recently developed concept, requires communities to assess system-wide capability to maintain desired performance levels, while simultaneously evaluating impacts to resilience due to changes in hazards and vulnerability over extended periods of time.</p> <p>In an earlier work, the authors developed a classification scheme to aid in identification, selection and application of community sustainable resilience indicators that can be tailored to a community’s needs in operationalizing the assessment process. These indicators were characterized according to whether they aligned with social, economic or environmental systems that are necessary for a community to achieve a sustainable resilience domain of survival, well-being, or full preparedness.</p> <p>Of the critical infrastructure systems that support these systems and domains, transportation is arguably the most important. This is based on the premise that transportation is a means to an end, providing the mobility that enables a community to establish and maintain a social, economic and environmental fabric. Whether it involves an educational, medical, recreational, religious, work or other purpose, absent a safe and reliable transportation system, none of these activities can be satisfactorily pursued. Moreover, in times of crisis, transportation serves as a vital artery for enabling access to and egress from impacted areas.</p> <p>The objective of this project was to establish and demonstrate a method for evaluating a community’s transportation resilience, such that if deficiencies exist, attention can be focused on mitigating those concerns. This approach was designed around the scenario of a river valley community exposed to the threat of a significant flood event, with the expectation that the methodology has the potential to be extended to assess community resilience to other natural and manmade hazards.</p>
Data for Aeolian Ripple Migration and Associated Creep Transport Rates
<p><strong>Overview:</strong></p> <p>The attached spreadsheet, "AeolianRippleMigration_ShermanEtAl2019.csv," summarizes the ripple migration and related data acquired from the wind tunnel and field experiment literature and from the field experiments at Jericoacoara, Ceará, Brazil (2008) and Oceano, California, USA (2015), associated with the article "Aeolian Ripple Migration and Associated Creep Transport Rates" by Douglas J. Sherman, Pei Zhang, Raleigh L. Martin, Jean T. Ellis, Jasper F. Kok, Eugene J. Farrell, and Bailiang Li.</p> <p><strong>Notes for data sources:</strong></p> <p>"a" - indicates that the data from a particular study were included in our final analyses</p> <p>"b" - indicates an estimate of threshold shear velocity (calculated as per Lorenz et al., 2011) with A = 0.1</p> <p>"c" - the value for ripple height in this study is the average of about 200 measurements for ripples in equilibrium or near-equilibrium with the wind field</p> <p>"d" - the data from this study were digitized as depicted in terms of ust/ust_th and u_r/(gd)^0.5 (see "Key to variables" below)</p> <p>"e" - Shear velocity (ust) values are from Martin & Kok, 2017. Median grain diameter (d) and threshold shear velocity (ust_th) values are from Martin & Kok, 2018 (see Table 2: "Date interval")</p> <p><br> <strong>Key to variables [units]:</strong></p> <p>Source - literature origin of previous studies or field location of observations for this study</p> <p>Note - annotation for additional information about study (see above "Notes for data sources")</p> <p>StudyType - classified as "field" or "wind tunnel"</p> <p>Date - date of observation for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>StartTime - start time of observation window (local time) for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>EndTime - end time of observation window (local time) for observations at Jericoacoara and Oceano ( "N/A" for other sites)</p> <p>u_r [mm/s] - calculated ripple migration speed ( "N/A" for Zhu et al, 2011, see "u_r_alt" below)</p> <p>sigma_u_r [mm/s] - uncertainty in ripple migration speed. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p> <p>u_r_alt - dimensionless proxy values for ripple migration speed for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as u_r/(gd)^1/2, where "g" is gravitational acceleration and "d" is median surface grain diameter </p> <p>ust [m/s] - shear velocity ( "N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>d [mm] - median surface grain diameter ("N/A" if not reported for literature studies)</p> <p>ust_th [m/s] - threshold shear velocity ("N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>ust_over_ust_th - dimensionless proxy values for shear velocity for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as ust/ust_th</p> <p>length [m] - ripple wavelength ("N/A" if not reported or measured)</p> <p>height [mm] - ripple amplitude ("N/A" if not reported or measured)</p> <p>sigma_height [mm] - uncertainty in ripple amplitude. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p>
ScienceDex guides
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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.