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424 results for “In-situ”
Data from: Influence of in-situ oil sands development on caribou (Rangifer tarandus) movement
In-situ oil sands development (ISD) involves a network of facilities, wells, roads and pipelines to extract and transport subsurface bitumen. This technology is rapidly expanding and there is uncertainty whether ISDs restrict animal movement, leading to increased extinction probabilities for some wide-ranging species. Here we test for effects of simulated future (i.e., 50 years from now) and current ISDs on simulated movements of woodland caribou (Rangifer tarandus), a threatened species across North America. In simulations of future scenarios, we varied the spacing and permeability of ISDs and the presence/absence of protected areas. Permeability was measured as the number of times simulated caribou crossed ISDs with different levels of modelled permeability. We estimated the effects of these factors on caribou step length and annual home range size, key metrics of small and large spatiotemporal scales of movement, respectively. Current caribou crossings of above-ground pipeline features of ISDs were measured using camera traps and compared to expected caribou crossing rates based on present-day caribou movement simulations. Current crossing rates were evaluated within the context of predicted future crossing success rates necessary to maintain caribou step lengths and home ranges. With few exceptions, permeability across ISDs was the main factor affecting caribou movement, more so than spacing between developments or the presence of protected areas. However, minimal permeability (crossing rates of c. 15% to 60%, relative to an undisturbed site was needed to maintain existing home range size and step lengths. The effect of permeability on home range size and step length was non-linear, suggesting that small increases in permeability would provide a disproportionately greater benefit to caribou movement. Our predictions demonstrate that maintaining permeability across ISDs is more important than spacing between leases or including protected areas, and thus provides clear direction for mitigation efforts for features that will exist on the landscape for decades to come.
[Dataset] enhanced functional connectivity properties of human brains during in-situ nature experience
<p>Raw data</p> <p>Artifact-free EEG raw data recorded by Emotiv Epoc (sample rate 128/s, 14 channels).</p>
In-situ, time resolved monitoring of uranium in BFS:OPC grout. Part 1: Corrosion in water vapour.
<p>Uranium encapsulated in grout was exposed to water vapour for extended periods of time. Through synchrotron x-ray powder diffraction and tomography measurements, uranium dioxide was determined the dominant corrosion product over a 50-week time period. The oxide growth rate initiated rapidly, with rates comparable to the U + H<sub>2</sub>O reaction. Over time, the reaction rate decreased and eventually plateaued to a rate similar to the U + H<sub>2</sub>O + O<sub>2</sub> reaction. This behaviour was not attributed to oxygen ingress, but instead the decreasing permeability of the grout, limiting oxidising species access to the metal surface.</p>
Data supporting Satellite in-situ electron density observations of the mid-latitude storm enhanced density on the noon meridional plane in the F region during the 20 November 2003 magnetic storm
<p>This is the data for the submitted paper: Satellite in-situ electron density observations of the mid-latitude storm enhanced density on the noon meridional plane in the F region during the 20 November 2003 magnetic storm. The data contains five files. The file NE_TGWeimer_2003324 is the electron density (NE) data along the CHAMP orbit on Nov 20, 2003. The file TGSED4_Mlat30_2003324 is the NE, HMF2, WI_ExB, VI_ExB and VN at Mlat = 30 on the noon meridional plane (MLT = 12 hr) in the Northern hemisphere on Nov 20, 2003. The temporal resolution is 1-min. The file TGSED4_Mlat60_2003324 is the NE, HMF2, WI_ExB, VI_ExB and VN at Mlat = 60 on the noon meridional plane (MLT = 12 hr) in the Northern hemisphere on Nov 20, 2003. The temporal resolution is 1-min. The file TGSED3_Mlat30_2003324 is the NE at Mlat = 30 as a function of MLT and UT. The temporal resolution is 5-min. The file TGSED3_Mlat60_2003324 is the NE at Mlat = 60 as a function of MLT and UT. The temporal resolution is 5-min.</p>
[Data] Self-Supervised Bayesian Representation Learning of Acoustic Emissions from Laser Powder Bed Fusion Process for In-situ Monitoring
<div> <div> <div> <p>Different Laser Powder Bed Fusion (LPBF) process spaces were deliberately introduced by employing two distinct 316L stainless steel powder distributions (with particle sizes >45 μm and < 45 μm) and processing them with two sets of laser parameters, resulting in the creation of four datasets [D1, D2, D3, and D4]. These datasets encompass LoF pores, conduction mode, and keyhole formations, each associated with three LPBF regimes denoted as D1, D2, D3, and D4. The experiments utilized a Sisma MYSINT 100 commercial LPBF printer and an airborne AE sensor system with a flat frequency response ranging from 0 to 150 kHz. Validation of the ground truths for the three laser regimes across the four datasets, representing distinct process spaces, was accomplished through the confirmation of cross-sectional images. In the course of fabricating a cube using a powder bed and laser, data acquisition from an AE sensor was triggered when the optical intensity reached a threshold of 0.5 V for each scan length. The photodiode trigger gain was adjusted to saturate at 5 V, and the ensuing continuous-time window, where the optical signal remained at 5 V for 12.5 ms, was calculated and segmented to generate the dataset. Irrespective of the specific regime (Lack of Fusion, Conduction, and Keyhole) or the cube being fabricated (with two powder distributions), the signals obtained during this process were then segmented into a 12.5 ms window comprising 5000 data points. To eliminate any noise, an offline application of a low-pass Butterworth filter with a 150 kHz cut-off frequency was employed, aligned with the frequency response specification of the AE sensor. Each dataset has two files against it [raw/groundtruth label].</p> </div> </div> </div>
An adaptive segment anything model for water level measurement with staff gauge images: staff gauge images and in-situ water levels
<p><span>We installed a commercial time-lapse camera on an urban lake in South China to collect the staff gauge images with a interval of 15 minutes. The data samples spanned from May 27th, 0:00 am, to July 6th, 11:00 am, 2023 (UTC+8), including a total of 2691 images. All the collected images were manually read to derive the stages as ground truth. The image and water level data is stored in this dataset.</span></p> <p> </p>
Data products from "GNSS reflectometry from low-cost sensors for continuous in-situ contemporaneous glacier mass balance and flux divergence"
<p>GNSS, GNSS-IR, and mass balance data from "GNSS reflectometry from low-cost sensors for continuous in-situ contemporaneous glacier mass balance and flux divergence". Contains the following folders and files</p> <ul> <li>GNSS <ul> <li><em>Precise point positioning solution (.pos, etc) using the CSRS-PPP tool for each GNSS system</em></li> </ul> </li> <li>GNSS_basefix <ul> <li><em>Precise point positioning solution (.pos) with base station observations using the Emlid Studio desktop application for GNSS systems AB floating and AB fixed</em></li> </ul> </li> <li>GNSSIR<br> <ul> <li><em>Reflector height solutions for site AB floating, AB fixed, and D floating (see Fig. 7). The filename is the day of year 2023.</em></li> </ul> </li> <li>Monitored Ablation Stake<br> <ul> <li><em>Processed daily and seasonal climatic mass balance height changes (see Fig. 5)</em></li> </ul> </li> </ul>
Reproducing nonlinear ground response and pore pressure variations using in-situ soil properties
<p>The zip file named 'Seismic and pore water pressure data.zip' contains all the seismic and pore water pressure data in our study.</p><p>The zip file named 'WLA model.zip' contains the numerical models used in our study.</p>
Code and Training Data for "Cascaded Machine Learning of Soil Moisture and Salinity Prediction in Estuarine Wetlands based on In-situ Internet of Things Monitoring"
Open the record for dataset details and reuse information.
Upgrading and extending the lifecycle of soft robots by in-situ freeform liquid three-dimensional printing
<p>The data is associated with the research article titled '<em>Upgrading and extending the lifecycle of soft robots by in-situ freeform liquid three-dimensional printing</em>', published in <em>Science Robotics</em> journal.</p>
Open data for publication Reconstruction of Ice Surface upon Acetone Adsorption: An in-situ ATR-IR Modulation Excitation Spectroscopy Study
<p>Original data for publication "Reconstruction of Ice Surface upon Acetone Adsorption: An in-situ ATR-IR Modulation Excitation Spectroscopy Study". Original data used for the Figures.</p>
In-situ lake level observations on the western Tibetan Plateau
<p>Lake level has been monitored at six lakes (Lumajiangdong Co, Memar Co, Jieze Caka, Longmu Co, Luotuo Lake, Aksaiqin Lake) on the western TP. HOBO water level loggers (U20-001-01) or Solist water level loggers were installed in the littoral zone of the lakes. To validate lake level changes, two HOBO water-level loggers were installed in different regions of Lumajiangdong Co (Fig. S1). Because water levels were recorded as changes in pressure (less than 0.5 cm water level equivalent), air pressure data were subtracted from the level loggers to obtain pressure changes related to water column variations. The loggers can still work efficiently at the beginning of ice cover. However, there is no data available when the lake ice was thick enough and loggers were frozen up. Daily lake-level changes were used in this study. At Lumajiangdong Co, lake level data are available between October 2016 and September 2021. At Memar Co, lake level data are only available between October 2017 and September 2019 and between October 2020 and September 2021. For Jieze Caka, Longmu Co and Luotuo Lake, there is only one year’s data available. Water depth of the loggers was measured during fieldwork to validate the logger data.</p>
Dataset for "Data-Mining of In-Situ TEM Experiments: Towards Understanding Nanoscale Fracture"
<p>Dataset accompanying the publication "Data-Mining of In-Situ TEM Experiments: Towards Understanding Nanoscale Fracture"</p>
Soil Moisture from SMAP, Sentinel 1 and in-situ observations dataset
<p>Each folder contains the dataset for the entire CONUS over the corresponding time period.</p> <p>For folder contains two classes of GeoTIFF images, namely the NW_Day_XXX_9km_Signals.tif and NW_Day_XXX_1km_Signals.tif, corresponding to data at 9 and 1 km spatial resolution respectively (XXX encodes the specific date e.g. 20180601)</p> <p>Each *9km_Signals.tif image contains 7 bands that correspond to the following variables:</p> <ol> <li> <p>SMAP Tb, Horizontal polarization</p> </li> <li> <p>SMAP Tb, Vertical polarization</p> </li> <li> <p>Soil Moisture (estimation)</p> </li> <li> <p>Clay</p> </li> <li> <p>Bulk Density</p> </li> <li> <p>Latitude</p> </li> <li> <p>Longitude</p> </li> </ol> <p> </p> <p>Each *1km_Signals.tif image contains 12 bands that correspond to the following variables:</p> <ol> <li> <p>Sentinel 1 σ0, Vertical polarization</p> </li> <li> <p>Sentinel 1 σ0, Horizontal polarization</p> </li> <li> <p>SMAP TB, vertical polarization;</p> </li> <li> <p>In-Situ Soil Moisture value</p> </li> <li> <p>Soil Moisture (estimated) at 1km;</p> </li> <li> <p>Vegetation Water Content</p> </li> <li> <p>Surface Temperature</p> </li> <li> <p>Precipitation</p> </li> <li> <p>Land cover map</p> </li> <li> <p>In-Situ location name</p> </li> <li> <p>Latitude</p> </li> <li> <p>Longitude</p> </li> </ol> <p> </p>
Original data for publication: Transient Inactivation Effect on Au/TiO2 Catalyst: Insight by in-situ DRIFT and UV–vis Spectroscopy
<p>Original data for publication: Transient Inactivation Effect on Au/TiO2 Catalyst: Insight by in-situ DRIFT and UV–vis Spectroscopy</p> <p>The original data shown in the Figures of the main manuscript and suporting information are given.</p>
Chemical and Structural In-Situ Characterization of Model Electrocatalysts by Combined Infrared Spectroscopy and Surface X-Ray Diffraction
<p>Raw and treated data</p>
In-situ transilluminated white light imaging data of non-crimp fabric based fibre composite under fatigue loading
<p>In-situ transilluminated white light imaging data published with data in brief: </p> <p>Jespersen, K. M., Glud, J. A., Zangenberg, J., Hosoi, A., Kawada, H., & Mikkelsen, L. P. (2018). Ex-situ X-ray computed tomography, tension clamp and in-situ transilluminated white light imaging data of non-crimp fabric based fibre composite under fatigue loading.<em> Data in Brief.</em></p> <p>as a part of the below journal paper.</p> <p>Jespersen, K. M., Glud, J. A., Zangenberg, J., Hosoi, A., Kawada, H., & Mikkelsen, L. P. (2018). Uncovering the fatigue damage initiation and progression in uni-directional non-crimp fabric reinforced polyester composite. <em>Composites Part A.</em></p> <p>If using the data, please refer to one of the two.</p>
Data for "In-situ strain tuning in hBN-encapsulated graphene electronic devices"
<p>Data for the publication "In-situ strain tuning in hBN-encapsulated graphene electronic devices"</p>
Data sets for the Publication 'Analytical solution of gas flow in rough-walled micro-fracture at in-situ state' in Water Resources Research.
<p>Data sets for the Publication 'Analytical solution of gas flow in rough-walled micro-fracture at in-situ state' in Water Resources Research.</p>
The AF2 predicted structures and MD simulation results for the paper "In-situ structural insights into activity regulation of mammalian pyruvate dehydrogenase complex"
<p>Thank you for your interest in our work. You can discover content that interests you within the respective compressed packages, accompanied by “readme” files.</p>
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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.