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1,899 results for “Running”
Replication package for "Long Run Effects of Aid: Forecasts and Evidence from Sierra Leone"
<p>Replication package for "Long Run Effects of Aid: Forecasts and Evidence from Sierra Leone" by K.Casey, R. Glennerster, E. Miguel and M. Voors, in the Economic Journal 2022</p>
Players of the Innovation Ecosystem: A Quantitative Analysis of the Scientific Collaboration of a State-Run Research Institute in Brazil
<p>Análise de colaborações em artigos do Instituto Nacional de Tecnologia. </p>
V6-V10 - Raw Data - Motion-resolved fat fraction mapping with whole-heart free-running multiecho GRE
<p>(PART 2) whole-heart cardiac MRI datasets from healthy volunteers (1.5T)</p> <p>Each folder labelled V6-V10 contains:</p> <p>1) Free-running multiecho GRE (N<sub>TE</sub>=8) raw data file</p> <p>2) ECG-triggered multiecho GRE (N<sub>TE</sub>=5) raw data file</p> <p>3) Matlab file "PhysioInfo.mat" containing the physiological signal information (Pilot Tone raw data, extracted respiratory signal, extracted cardiac signal, extracted cardiac trigger points, and corresponding time stamps).</p> <p>************************************************************************************************************************************************************************************************************************************************************</p> <p>Matlab code to load the raw data, compute the 3D trajectory and read the raw and extracted Pilot Tone signals is available at:</p> <p><a href="https://github.com/QIS-MRI/ReadDataAndTrajectory_FreeRunningFatFractionHeart">https://github.com/QIS-MRI/ReadDataAndTrajectory_FreeRunningFatFractionHeart</a></p> <p>************************************************************************************************************************************************************************************************************************************************************</p> <p>Please cite the following work when using this dataset:</p> <p>Link to publication: <a href="https://onlinelibrary.wiley.com/doi/10.1002/mrm.29680">https://onlinelibrary.wiley.com/doi/10.1002/mrm.29680</a></p> <p>************************************************************************************************************************************************************************************************************************************************************</p> <p>Data was collected and approved for sharing according to the terms of the Ethics authorization CER-VD 2021-00708 (Lausanne, Switzerland).</p>
Data to run analyses present in the paper: Cell specificity of human regulatory annotations and their genetic effects on gene expression
<p>Data for the manuscript:</p> <p>Varshney A., H. VanRenterghem, P. Orchard, A. P. Boyle, M. L. Stitzel, <em>et al.</em>, 2019 Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression. Genetics 211: 549–562. <a href="https://doi.org/10.1534/genetics.118.301525">https://doi.org/10.1534/genetics.118.301525</a></p> <p>The code to generate these data are at GitHub: https://github.com/ParkerLab/regulatoryAnnotations_comparisons</p> <p>Also see processed data available in this previous Zenodo record: https://zenodo.org/record/1413623</p>
BNCI_less_runs_and_channels
<p>BNCI2014001 first four files with less runs and just the following channels: "Fz", "FC3", "FC1", "FCz", "FC2", "FC4", "C5"</p>
Figure 2 in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 2. Depiction of the measurements (a, b, h) taken from figures in the paper by Bates et al. (2009) and the methods to estimate wetted areas and volumes from cylindrical slices. A representative example of the methods (best reconstruction of Tyrannosaurus rex BHI 3033) is shown. The silhouettes were modified from fig. 5 in the paper by Bates et al. (2009). A, cranial view and lateromedial measurements. B, right lateral view and anteroposterior measurements. C, a generic cylindrical slice and the equations to estimate the contribution to the total areas and volumes.
Figure 1 in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 1. Schematic representation of the hunting scenario. Tyrannosaurus rex is wading in mode II, while Edmontosaurus annectens and Struthiomimus sedens are already engaged in mode IV, corresponding to surface swimming.
Figure 3. A in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 3. A comparative plot of maximum speed in water as a function of water depth for the three species studied here.
A comment on Dincecco et al. (2022): Pre-colonial warfare and long-run development in India
<p>We test the reproducibility and replicability of Dincecco et al. (2022),<br> which reports a positive relationship between pre-colonial interstate warfare<br> and long-run development patterns across India. Overall, we confirm that all<br> of the study’s estimates are computationally reproducible using the provided<br> replication package in Stata, but note that the ease of replication could be<br> improved by the provision of code and intermediate datasets for the conflict<br> exposure measure. We test for and find no evidence of data manipulation in<br> the final datasets. Concerning direct replicability, we consider different ways<br> of measuring distance to conflicts and also alternative proxies for both the<br> dependent variable and variables which capture channels by which the main<br> effects operate. We find that some estimates are sensitive to the type of con-<br> flict considered. Other estimates are sensitive to the time period considered,<br> most likely due to time heterogeneity in the number of conflicts recorded.<br> Nevertheless, most estimates are substantially in line with the original study</p>
Downloaded datasets required to run code repository
<p>Downloaded datasets required to run code repository</p>
OpenRTP: Dataset of long-running test suites
<p>OpenRTP is a dataset of long-running test suites for software testing research.</p> <p>OpenRTP curates test suite runs of continuous integration (CI) builds from actively-maintained, open-source projects with rich commit history and publicly accessible CI servers.</p> <p> </p>
Reconstruction of car–running pedestrian accident based on humanoid robot method
<p>This is the appendix of the manuscript titled "Reconstruction of car–running pedestrian accident based on humanoid robot method", which will help the reviewers to better understand the manuscript. It is also the supporting part of this manuscript.</p>
Dense vegetation hinders sediment transport towards saltmarsh interiors - Supporting data and source code (Part II: Main runs)
<p>This is Part II of the supporting data and source code for the paper entitled "Dense vegetation hinders sediment transport towards saltmarsh interiors", submitted to <em>Limnology and Oceanography Letters.</em> It contains all input and output files for every simulations used in the paper.</p> <p>Each zip file corresponds to a model run. </p> <p>TIGER_XX.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 0-100.<br>TIGER_XX_100.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 100-200.<br>TIGER_XX_HYYY.zip: Scenario XX, hydro-morphodynamics only, year YYY.</p> <p>Main scenarios:<br>- 01: Spartina (Figures 1-5, S3-S10)<br>- 02: Salicornia (Figures 1-5, S3-S10)<br>- 83: No vegetation (Figures 1-5, S3, S8-S10)</p> <p>Additional scenarios:<br>- 146: Spartina, low bulk drag coefficient (Figure S3)<br>- 147: Spartina, very low bulk drag coefficient (Figure S3)<br>- 148: Salicornia, low bulk drag coefficient (Figure S3)<br>- 149: Salicornia, very low bulk drag coefficient (Figure S3)<br>- 122: Spartina, low settling velocity (Figure S8)<br>- 123: Spartina, high settling velocity (Figure S8)<br>- 124: Salicornia, low settling velocity (Figure S8)<br>- 125: Salicornia, high settling velocity (Figure S8)<br>- 126: No vegetation, low settling velocity (Figure S8)<br>- 127: No vegetation, high settling velocity (Figure S8)<br>- 128: Spartina, low critical bed erosion shear stress (Figure S8)<br>- 129: Spartina, high critical bed erosion shear stress (Figure S8)<br>- 130: Salicornia, low critical bed erosion shear stress (Figure S8)<br>- 131: Salicornia, high critical bed erosion shear stress (Figure S8)<br>- 132: No vegetation, low critical bed erosion shear stress (Figure S8)<br>- 133: No vegetation, high critical bed erosion shear stress (Figure S8)<br>- 134: Spartina, low Partheniades constant (Figure S8)<br>- 143: Spartina, high Partheniades constant (Figure S8)<br>- 136: Salicornia, low Partheniades constant (Figure S8)<br>- 144: Salicornia, high Partheniades constant (Figure S8)<br>- 138: No vegetation, low Partheniades constant (Figure S8)<br>- 145: No vegetation, high Partheniades constant (Figure S8)<br>- 150: Spartina, low sediment dry bulk density (Figure S8)<br>- 151: Spartina, high sediment dry bulk density (Figure S8)<br>- 152: Salicornia, low sediment dry bulk density (Figure S8)<br>- 153: Salicornia, high sediment dry bulk density (Figure S8)<br>- 154: No vegetation, low sediment dry bulk density (Figure S8)<br>- 155: No vegetation, high sediment dry bulk density (Figure S8)<br>- 76: Spartina, replicate #1 (Figures S9-S10)<br>- 77: Spartina, replicate #2 (Figures S9-S10)<br>- 78: Spartina, replicate #3 (Figures S9-S10)<br>- 88: Spartina, replicate #4 (Figures S9-S10)<br>- 80: Salicornia, replicate #1 (Figures S9-S10)<br>- 81: Salicornia, replicate #2 (Figures S9-S10)<br>- 82: Salicornia, replicate #3 (Figures S9-S10)<br>- 89: Salicornia, replicate #4 (Figures S9-S10)<br>- 85: No vegetation, replicate #1 (Figures S9-S10)<br>- 86: No vegetation, replicate #2 (Figures S9-S10)<br>- 87: No vegetation, replicate #3 (Figures S9-S10)<br>- 90: No vegetation, replicate #4 (Figures S9-S10)</p>
Running a Data Center
<p>This short presentation delivered as part of a consultation event for the Digital Footprints project examines the technical, organizational and legislative aspects and challenges of running a secure data center, based on a decade of working in secure data centers in both the UK and Germany.</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 1 cDNA 1
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (1/5).<br> RUN 1(/2), cDNA 1(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 2 cDNA 2
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (4/5).<br> RUN 2(/2), cDNA 2(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 2 cDNA 1
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (3/5).<br> RUN 2(/2), cDNA 1(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity - Run 1 cDNA 2
<p><strong>Dataset from article</strong> : The coenzyme A precursor pantethine restrains sarcoma growth through promotion of type 1 immunity</p> <p>10X Single-cell RNA-sequencing dataset (2/5).<br> RUN 1(/2), cDNA 2(/2).</p> <p>This repository contains results and necessary files for reproducing the analyses in Miallot et al. (2023). The instructions for reproducing the analysis are given in github (https://github.com/CIML-bioinformatic/PNlab_Sarcoma) and extra files are available in GEO/SRA (GSE221164).</p>
Comparison of Plyometric and Resistance Warmup on Running Performance in Athlets
ClinicalTrials.gov study NCT05045521. IPD Sharing: NO. Countries: 1. Publications: 10.
Comparison the Effects of Deep Water Running and Treadmill Running
ClinicalTrials.gov study NCT04488809. IPD Sharing: NO. Countries: 1. Publications: 14.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.