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1,630 results for “Stepping”
The loss of the 'pelvic step' in human evolution
<p>Human bipedalism entails relatively short strides compared with facultatively bipedal primates. Unique non-sagittal-plane motions associated with bipedalism may account for part of this discrepancy. Pelvic rotation anteriorly translates the hip, contributing to bipedal stride length (i.e. the 'pelvic step'). Facultative bipedalism in non-human primates entails much larger pelvic rotation than in humans, suggesting that a larger pelvic step may contribute to their relatively longer strides. We collected data on the pelvic step in bipedal chimpanzees and over a wide speed range of human walking. At matched dimensionless speeds, humans have 26.7% shorter dimensionless strides, and a pelvic step 5.4 times smaller than bipedal chimpanzees. Differences in pelvic rotation explain 31.8% of the difference in dimensionless stride length between the two species. We suggest that relative stride lengths and the pelvic step have been significantly reduced throughout the course of hominin evolution.</p>
Step-by-step simulation of the ROUTR algorithm on a road-network graph.
<p>This video simulates, step-by-step, the application of the ROUTR algorithm on a small road-network graph.</p>
FIGURE 8. Fulcaldea and Huarpea. A in Touch me carefully: a step towards understanding morphological diversity in the South American spiny sunflowers (Compositae, Barnadesioideae)
FIGURE 8. Fulcaldea and Huarpea. A: Fulcaldea. B–E: Huarpea. A: Fulcaldea stuessyi. Inflorescence with a white arrow showing swollen style below the branching point. B: Huarpea andina. Habit. C: Capitulum showing five ray flowers and a disc flower. D: Lateral view from the capitula. E: Dissected capitula showing three ray flowers (white) and a disc flower (yellow). Photos by Ivan Abreu (A) and Darwinion Institute (B–E).
FIGURE 7. Doniophyton and Duseniella. A–B in Touch me carefully: a step towards understanding morphological diversity in the South American spiny sunflowers (Compositae, Barnadesioideae)
FIGURE 7. Doniophyton and Duseniella. A–B: Doniophyton. C–D: Duseniella. A: Doniophyton anomalum. B: Doniophyton weddellii. C–D: Duseniella patagonica. Photos by Darwinion Institute.
FIGURE 2 in Touch me carefully: a step towards understanding morphological diversity in the South American spiny sunflowers (Compositae, Barnadesioideae)
FIGURE 2. Synapomorphies of Barnadesioideae. A–C: Diversity of spines. D: Barnadesioid trichomes. A–B: Dasyphyllum vagans. A: Spines in pairs, curved, and convergent. B: Spines in pairs, straight, and convergent. C: Barnadesia parviflora. Spines in fascicles, straight, and divergent. D: SEM photograph of Barnadesioid trichomes.
FIGURE 5. Chuquiraga. A–B in Touch me carefully: a step towards understanding morphological diversity in the South American spiny sunflowers (Compositae, Barnadesioideae)
FIGURE 5. Chuquiraga. A–B: Chuquiraga aurea. A: "Cushion" Habit. B: Capitulum. C–D: Chuquiraga longiflora. D: Capitulum. D: Tubular corolla. E: Chuquiraga jussieui. Capitulum. F: Chuquiraga weberbaueri. Shrub Habit. Photos by Darwinion Institute (A–D), Paola Ferreira (E), Gari Ccana-Ccapatinta (F).
Dataset - Radially resolved dynamic inflow pitch step experiment in wind tunnel
<p>The relevant turbine data of MoWiTO 1.8 and the preprocessed data presented in the following accepted paper are uploaded:</p> <p><br> Berger, F., Onnen, D., Schepers, J. G., and Kühn, M.: Experimental analysis of radially resolved dynamic inflow effects due to pitch steps, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2021-70, accepted, 2021.</p> <p> </p> <p>The dataset describes a pitch step experiment with a model wind turbine in a wind tunnel between a high rotor load and a low rotor load. Measurements of turbine loads, near wake flow and radius resolved induction measurements are available.</p>
Data and supplementary information for "A multiple time step algorithm for trajectory surface hopping simulations"
<p>This repository contains the supplementary information as well as the data necessary to reproduce the content of the article "A multiple time step algorithm for trajectory surface hopping simulations".</p>
FIGURE. DnaSP DNA polymorphism analysis - Nucleotide variability (Pi) comparison between Strobilanthes lupulina and S. glandulata. The window length and step size were set to 600bp and 200bp respectively. The most varying regions and the commonly used barcoding regions are listed against the base-pair differences found. in Strobilanthes glandulata (Acanthaceae), a new species from Sri Lanka based on the morphological and molecular evidences
FIGURE. DnaSP DNA polymorphism analysis - Nucleotide variability (Pi) comparison between Strobilanthes lupulina and S. glandulata. The window length and step size were set to 600bp and 200bp respectively. The most varying regions and the commonly used barcoding regions are listed against the base-pair differences found.
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & McMichael, S. (2018). The Ames Stereo Pipeline: NASA's open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537– 548. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
Tidal channel meanders serve as stepping-stones to facilitate cordgrass landward spread by creating invasion windows
<p>Understanding the mechanisms by which geomorphic structures affect habitat invasibility by mediating various abiotic and biotic factors is essential for predicting whether these geomorphic structures may provide spatial windows of opportunity to facilitate range-expansion of invasive species in salt marshes. Many studies have linked geomorphic landscape features such as tidal channels to invasion by exotic plants, but the role of tidal channel meanders (i.e., convex and concave sides) in regulating the <em>Spartina</em> invasion remains unclear. Here, we examined the combined effects of tidal channel meander-mediated hydrodynamic variables, soil abiotic stresses and propagule pressure on the colonization of <em>Spartina</em> in the Yellow River Delta, China, by conducting field observations and experiments. The results showed that lower hydrodynamic disturbance, bed shear stress, and higher propagule pressure triggered by eddies due to the convex structure of channel meanders facilitated <em>Spartina</em> seedling establishment and growth, whereas the concave side considerably inhibited the <em>Spartina</em> invasion. Lower soil abiotic stresses also significantly promoted the invasibility of the channel meanders by <em>Spartina</em>. Based on these findings, we propose a conceptual framework to illustrate the effects of the meandering geomorphology of tidal channels on the mechanisms that might allow the landward spread of <em>Spartina</em> and related processes. Our results demonstrate that the meandering geomorphic structures of tidal channels could act as stepping-stones to significantly facilitate the landward invasion of <em>Spartina</em> along tidal channels. This implies that geomorphic characteristics of tidal channels should be integrated into invasive species control and salt marsh management strategies.</p>
FIGURE 1. Garcinia stipulata T in Second-step lectotypification of Garcinia stipulata (Clusiaceae) and its recollection from Darjeeling-Sikkim Himalaya, India
FIGURE 1. Garcinia stipulata T. Anderson (A) Male inflorescence twig. (B) Sepal. (C) Petal. (D) Annular mass of stamens. (E) Pistillode after removing stamens. (F) Anther. (G) Female twig with fruit. (H) Female flower bud. (I) Female flower showing sepals, ovary and peltate stigma without petals.
Gneiss dome exhumation aided by extrusion along a step-form detachment in the Eastern Pamir
<p>Supplementary data for submission "Gneiss dome exhumation aided by extrusion along a step-form detachment in the Eastern Pamir" to G-cubed. </p>
Dataset: Bed Stability of Step-Pool Channels with Macrorough Sidewalls
<p>The data set includes the cumulative sediment outflow data and the digital elevation model (DEM) data of flume experiments conducted at the Laboratory of Hydraulics, Hydrology, and Glaciology (VAW) at ETH Zurich.</p>
Joshi et al 2023: Dynamic synchronization between hippocampal representations and stepping
<p>Data and code accompanying Joshi et al 2023, 'Dynamic synchronization between hippocampal representations and stepping'. Please contact Abhilasha Joshi (abhilasha.joshi@ucsf.edu) with any questions.</p>
All analysis steps of SLR1 & SLR2
<p>All analysis steps of SLR_1 and SLR_2 related to teachers´digital competence in the context of China.</p>
A Three-step Process to Isolate Large Quantities of Bioactive Sesquiterpene Lactones from Cichorium intybus L. Roots and Semi-synthesis of Chicory STLs Standards
<p>Supplementary Information:</p> <p>NMR spectra of DHLc, Lc, DHLc-Me-oxalate, Lc-Me-oxalate, DHLc-oxalate, Lc-oxalate, DHLc-glycoside; Figure S1: HPLC profiles (254 and 320 nm) of a water/methanol 50/50 and pure water extracts and different content in 3-CQA; Figure S2: Base peak chromatogram (BPC, All − MS) of a water chicory extract obtained in the positive mode; diagnostic fragment ions in the positive mode for DHLc-gly, DHLc-ox, DHLc, Lc-ox, Lc.</p>
Data for the publication by Mouchi et al "A step towards measuring connectivity in the deep-sea: elemental fingerprints of mollusk larval shells discriminate hydrothermal vent sites"
<p>This is the elemental data collected by fsLA-ICP-MS-MS on 600 individual larval shells of the hydrothermal-vent limpet Shinkailepas tollmanni from 14 sites in the Southwest Pacific Ocean.</p> <p>The first column indicates the sample ID corresponding to onship sample during the scientific cruise CHUBACARC (Hourdez & Jollivet, 2019).</p> <p>The second column indicates the S. tollmanni sample ID from the publication of Mouchi et al.</p> <p>Columns 3 to 15 correspond to elemental abundances measured.</p> <p>Column 16 to 18 correspond to the region, area and hydrothermal sites, respectively, for each larval shell.</p> <p> </p> <p>Hourdez, S., Jollivet, D., 2019. CHUBACARC cruise, <em>L’Atalante R/V</em>. doi: 10.17600/18001111.</p>
Supercurrent, Multiple Andreev Reflections and Shapiro Steps in InAs Nanosheet Josephson Junctions
<p>This file contains the raw data and processing codes of the paper 'Supercurrent, Multiple Andreev Reflections and Shapiro Steps in InAs Nanosheet Josephson Junctions'.</p> <p> High-quality free-standing InAs nanosheets are emerging layered semiconductor materials with potentials in designing planar Josephson junction devices for novel physics studies due to their unique properties including strong spin-orbit couplings, large Landé g-factors and the two dimensional nature. Here, we report an experimental study of proximity induced superconductivity in planar Josephson junction devices made from free-standing InAs nanosheets. The nanosheets are grown by molecular beam epitaxy and the Josephson junction devices are fabricated by directly contacting the nanosheets with superconductor Al electrodes. The fabricated devices are explored by low-temperature carrier transport measurements. The measurements show that the devices exhibit a gate-tunable supercurrent, multiple Andreev reflections, and a good quality superconductor-semiconductor interface. The superconducting characteristics of the Josephson junctions are investigated at different magnetic fields and temperatures, and are analyzed based on the Bardeen-Cooper-Schrieffer (BCS) theory. The measurements of ac Josephson effect are also conducted under microwave radiations with different radiation powers and frequencies, and integer Shapiro steps are observed. Our work demonstrates that InAs nanosheet based hybrid devices are desired systems for investigating forefront physics, such as the two-dimensional topological superconductivity.</p>
Effect of combined subsurface structures and steps on hyporheic exchange
<p>HYPORHEIC FLOW: each file contains the values of downwelling velocity (column 2, in m/s) at each point of the streambed (column 1, in m). The hyporheic exchange flow was calculated through the integration of all downwelling fluxes 197 over the streambed boundary (see section 2.3 of the main manuscript).</p> <p>RTD: in each file, each row corresponds to one upwelling location of the streambed (x, in m) and contains the values of tracer flux (in mol/m^2/s) over time (in seconds). The RTD is obtained through the integration of the flux along the streambed (see section 2.3 of the main manuscript).</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.