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1,899 results for “Running”
Data for "Does the Preferred Walk-Run Transition Speed on Steep Inclines Minimize Energetic Cost, Heart Rate or Neither?"
<p>Abstract</p> <p>Humans prefer to walk at slow speeds and to run at fast speeds. In between, there is a speed at which people choose to transition between gaits, the Preferred Transition Speed (PTS). At slow speeds, it is energetically cheaper to walk and at faster speeds, it is cheaper to run. Thus, there is an intermediate speed, the Energetically Optimal Transition Speed (EOTS). Our goals were to determine: 1) how PTS and EOTS compare across a wide range of inclines and 2) if the EOTS can be predicted by the heart rate optimal transition speed (HROTS). Ten healthy, high-caliber, male trail/mountain runners participated. On day 1, subjects completed 0&[deg] and 15&[deg] trials and on day 2, 5&[deg] and 10&[deg]. We calculated PTS as the average of the walk-to-run transition speed (WRTS) and the run-to-walk transition speed (RWTS) determined with an incremental protocol. We calculated EOTS and HROTS from energetic cost and heart rate data for walking and running near the expected EOTS for each incline. The intersection of the walking and running linear regression equations defined EOTS and HROTS. We found that PTS, EOTS, and HROTS all were slower on steeper inclines. PTS was slower than EOTS at 0&[deg], 5&[deg], and 10&[deg], but the two converged at 15&[deg]. Across all inclines, PTS and EOTS were only moderately correlated. Although EOTS correlated with HROTS, EOTS was not predicted accurately by heart rate on an individual basis.</p> <p>Methods</p> <p>Subjects walked and ran on a classic Quinton 18-60 motorized treadmill with a rigid steel deck (Quinton Instrument Company, Bothell, WA).</p> <p><strong>Determination of PTS: </strong>The average of the walk-to-run transition speed (WRTS) and run-to-walk transition speed (RWTS) defined the PTS as per Hreljac et. al. (2007). We first determined the WRTS in the walk-first group and then their RWTS and <em>vice versa</em> for the run-first group. Based on pilot experiments, we selected starting speeds such that there was no doubt which gait would be preferred at the initial speed. Once the speed of the treadmill was correctly set, subjects mounted the treadmill and chose their gait <em>ad libitum</em>. After we determined the preferred gait at the particular speed, the subject straddled the treadmill belt while we changed the speed by 0.1 m/s (increased during WRTS trials, decreased during RWTS trials). The process repeated until a gait transition occurred and was sustained for 30 seconds.</p> <p><strong>Determination of EOTS and HROTS: </strong>For the energetics and heart rate trials, we set the initial speed based on pilot experiments that indicated it would be near the EOTS. Subjects in the walk-first group walked at the incline-specific initial speed for 5 min, rested for ∼5 min and then ran at that speed for 5 min. Subjects in the run-first group did the opposite. During the rest periods, we re-weighed the subject and they drank just enough water to compensate for the weight loss due mostly to sweating. Thus, each subject maintained a nearly constant weight throughout all the trials.</p> <p>To measure metabolic rate during walking and running, we used an open-circuit, expired gas analysis system (TrueOne 2400; ParvoMedics, Sandy, UT). Subjects wore a mouthpiece with a one-way breathing valve and a nose clip allowing us to collect their expired air. The ParvoMedics software calculated the STPD rates of oxygen consumption (V□O<sub>2</sub>) and carbon dioxide production (V□CO<sub>2</sub>) and we averaged the last 2 minutes of each 5-minute trial. We then calculated metabolic power using the equation of Péronnet and Massicotte (1991) equation, as clarified by Kipp et al. (2018). We only included trials with respiratory exchange ratios (RER) <1.0 to ensure that metabolic energy was predominantly being provided from oxidative pathways. We used an R7 Polar iWL (Polar Electro Oy, Kempele, Finland) to measure heart rate in beats per minute (bpm) and averaged the values for the last 2 min of each trial.</p> <p>Immediately after both gait trials were completed for the initial speed, we calculated and compared the metabolic power required for walking and running. If walking was the more economical gait, we increased the treadmill speed by 0.1 m/s, and the process repeated. If running was the more economical gait, we decreased the treadmill speed by 0.1 m/s, and the process repeated. Each subject performed three speeds, both walking and running at each incline. However, some subjects needed to complete walking and running trials at a fourth speed so that we could obtain energetics data for one speed faster and one speed slower than their EOTS.</p> <p>For the three speeds at which the differences between metabolic rates between walking and running were least, we calculated linear regression equations for both metabolic power and heart rate as functions of speed for both walking and running for each subject and incline. The speeds at which the two equations intersected defined the EOTS and HROTS for each subject.</p> <p>Overall, we analyzed ten subjects at four different inclines, i.e. 40 determinations of EOTS and HROTS. Of those 80 linear regression analyses, the walking vs. running regressions intersected at a speed < 3 m/sec for all but two subjects (one subject for EOTS at 15° and a different subject for HROTS at 10°). Essentially, those individuals’ regression lines were nearly parallel. We chose to exclude those two conditions from further statistical analysis and aggregate data compilation.</p> <p>Usage Notes</p> <p>There are two missing values, as noted in the methods: HROTS for subject 5 at 10 degrees and EOTS for subject 4 at 15 degrees.</p>
Supplemental IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": AMPOP_April2016
<p>Full output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the April 2016 event, with IPWM driven by AMPERE convection maps and Ovation Prime precipitation (AMPOP_April2016). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/AMPOP_April2016_output.</p>
Supplemental IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": SDOP_May2014
<p>Full output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the May 2014 event, with IPWM driven by SuperDARN convection maps and Ovation Prime precipitation (SDOP_May2014). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/SDOP_May2014_output.</p>
Supplemental IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": SDOP_April2016
<p>Full output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the April 2016 event, with IPWM driven by SuperDARN convection maps and Ovation Prime precipitation (SDOP_April2016). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/SDOP_April2016_output.</p>
Supplemental IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": AMPOP_May2014
<p>Full output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the May 2014 event, with IPWM driven by AMPERE convection maps and Ovation Prime precipitation (AMPOP_May2014). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/AMPOP_May2014_output.</p>
Data from: Running in circles in phylomorphospace: host environment constrains morphological diversification in parasitic wasps
Understanding phenotypic diversification and the conditions that spur morphological novelty or constraint is a major theme in evolutionary biology. Unequal morphological diversity between sister clades can result from either differences in the rate of morphological change or in the ability of clades to explore novel phenotype ranges. We combine an existing phylogenetic framework with new phylogenomic data and geometric morphometrics to explore the relative roles of rate versus mode of morphological evolution for a hyperdiverse group: cryptine ichneumonid wasps. Data from genomic ultraconserved elements (UCEs) confirm that cryptines are divided into two large clades: one specialized in the use of hosts that are deeply concealed under hard substrates, and another with a much more diversified host range. Using a phylomorphospace approach, we show that both clades have experienced similar rates of morphological evolution. Nonetheless, the more specialized group is much more restricted in morphospace occupation, indicating that it repeatedly evolved morphological change through the same morphospace regions. This is in agreement with our prediction that host use imposes constraints in the morphospace available to lineages, and reinforces an important distinction between evolutionary stasis as opposed to a scenario of continual morphological change restricted to a certain range of morphotypes.
Data from: Adiposity is related to cerebrovascular and brain volumetry outcomes in the RUN DMC Study
Objective: Adiposity predictors, body mass index (BMI), waist circumference (WC), and blood leptin and total adiponectin levels were associated with components of cerebral small vessel disease (CSVD) and brain volumetry in 503 adults with CSVD age ≥50 years and enrolled in the Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort (RUN DMC). Methods: RUN DMC participants were followed for 9 years (2006-2015). BMI, WC, brain imaging and dementia diagnoses were evaluated at baseline and follow-up. Adipokines were measured at baseline. Brain imaging outcomes included CSVD components, white matter hyperintensities, lacunes and microbleeds; and gray and white matter, hippocampal, total brain, and intracranial volumes. Results: Cross-sectionally among men at baseline, higher BMI, WC and leptin were associated with lower gray matter and total brain volumes, and higher BMI and WC were associated with lower hippocampal volume. At follow-up 9 years later, higher BMI was cross-sectionally associated with lower gray matter volume, and an obese WC (>102cm) was protective for >1 lacune or >1 microbleed in men. In women, increasing BMI and overweight or obesity (BMI >25 kg/m2 or WC >88 cm) were associated with >1 lacune. Longitudinally, over 9 years, a baseline obese WC was associated with decreasing hippocampal volume particularly in men, and increasing WMH volume in women and men. Conclusions: Anthropometric and metabolic adiposity predictors were differentially associated with CSVD component and brain volumetry outcomes by sex. Higher adiposity is associated with a vascular-neurodegenerative spectrum among adults at-risk for vascular forms of cognitive impairment and dementias.
Model inputs and results from FastScape landscape evolution model runs for southern Africa
<p>These are the input files and results for the models presented in the revised version of the paper "Constraining plateau uplift in southern Africa by combining thermochronology, sediment flux, topography, and landscape evolution modeling" submitted to JGR:Solid Earth in October 2020 and revised in May 2017. The corresponding code needed to run the inputs can be found here: http://doi.org/10.5281/zenodo.4150333. The readme.txt file contained here explains the included data and results, as well as simple instructions for how to run the models.</p>
A French solider running down the hill
This is the recreation of the french running down the hill because they thought William of Normandy was dead. But he wasn't so yeah! Source: Objaverse 1.0 / Sketchfab
Hero 01 (Run)
There is one vertion this character is in 3d free stuff but this vertion has some animation, So that why I selling this one instant give free There is Idle, attack 1, attack 2, Walk, Run and Skill Source: Objaverse 1.0 / Sketchfab
C1 CAGE preview sequence run 150519_M00528_0125_000000000-ACUAB
<p>Sequence data (Illumina MiSeq run 150519_M00528_0125_000000000-ACUAB) for the public preview of the C1 CAGE technology.</p>
JISSN Downhill Running Data
<p>Data for study entitled: The Effects of a Multi-Ingredient Supplement on Markers of Muscle Damage and Inflammation Following Downhill Running in Females.</p>
Example run of the Biognosys iRT standard for liquid chromatography - mass spectrometry
<p>Depending on the composition of QC samples the LC performance can be monitored using peptides that elute over the entire gradient, and the dynamic range can be monitored if peptides are present in varying concentrations. Depicted here is the Biognosys iRT standard which consists of eleven peptides with varying chromatographic retention.</p>
Example data to run the STABLE algorithm
<p>Datasets from ERA5 (1 degree resolution) and NCAR (2.5 degree resolution) from both hemispheres to run the SubTropical Atmospheric ridge and BLocking Events (STABLE) algorithm. See the STABLE GitHub repository (https://github.com/mikaslima/STABLE) for details.</p>
Instructions for ContinuousFlex software installation and Tutorial for running MDSPACE and MDTOMO with test datasets
<p>Instructions for ContinuousFlex software installation and Tutorial for running MSPACE and MDTOMO methods of ContinuousFlex, together with test datasets. The ContinuousFlex installation instructions also include the instructions for installing Scipion, Xmipp, ChimeraX, and VMD (required for using ContinuousFlex). This distribution was prepared for the practical session of AlgoSB 2023 thematic school (Novembre 20 - 24, 2023, Cargese, France) on hybrid methods MDSPACE and MDTOMO for obtaining continuous conformational landscapes from cryo electron microscopy and cryo electron tomography data. Instructions for the software installation are in Instructions-Installation-ContinuousFlex.txt. The tutorial for the practical session is in MDSPACE_Tutorial_v4.docx and MDSPACE_Tutorial_v4.pdf.</p>
CUT&RUN_X
<p>CUT&RUN data of human cancer cell line.</p>
Example of Workflow Run RO-Crate Output in Sapporo
<p>This is an archive of the contents under <a href="https://github.com/sapporo-wes/sapporo-service/tree/main/tests/ro-crate/ro-crate_dir">https://github.com/sapporo-wes/sapporo-service/tree/main/tests/ro-crate/ro-crate_dir</a> as of <a href="https://github.com/sapporo-wes/sapporo-service/releases/tag/1.5.1">version 1.5.1 of GitHub - sapporo-wes/sapporo-service</a>. For more details, please refer to <a href="https://github.com/sapporo-wes/sapporo-service/blob/main/tests/ro-crate/README.md">https://github.com/sapporo-wes/sapporo-service/blob/main/tests/ro-crate/README.md</a>.</p>
Running a Red Light: An Investigation into Why Software Engineers (Occasionally) Ignore Coverage Checks --- Appendix
<p>This online appendix contains the anonymised responses to our survey, which we have analysed in our report. In addition, it also includes the mapping of axial coding codes to larger groups, and (if not self-evident) a further explanation of these groups.</p>
Implemented Algorithm built and loaded succ. run 1.
Open the record for dataset details and reuse information.
Hitler Running Mii
On the web, we have lot of 3D model for Hitler... but there models are too heavy, non-animable and aren't free ! If you want to do videos with this model, it's free, not too heavy and it's easy to animate ! Source: Objaverse 1.0 / Sketchfab
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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.