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21,983 results for “UNITE”
Fig. 1 in Redescription of Strophopoda aprica Van Duzee and the Description of Two New Genera and Five New Species from the Southwestern United States and Northern Mexico (Heteroptera: Miridae)
Fig. 1. Habitus views of Calidroides, Chlamyopsallus, Pseudopsallus, and Strophopoda spp.
Chang'e-5 Mare Unit and Crater Catalogue
<p><strong>This page archives data used in the following article:<br>Qiao, L., Xu, L., Yang, Y., Xie, M., Chen, J., Fang, K., & Ling, Z. (2021). Cratering Records in the Chang’e-5 Mare Unit: Filling the "Age Gap" of the Lunar Crater Chronology and Preparation for its Re-calibration. <em>Geophysical Research Letters</em>, 48, e2021GL095132. <a href="https://doi.org/10.1029/2021GL095132" target="_blank" rel="noopener">https://doi.org/10.1029/2021GL095132</a></strong></p> <p><strong>They include files of the Chang'e-5 mare unit and crater catalogue:</strong></p> <p><strong>Chang'e-5_Mare.7z: ArcGIS shapefile for the mare unit;</strong></p> <p><strong>Chang'e-5_Crater.7z: ArcGIS shapefile for the crater catalogue;</strong></p> <p><strong>Chang'e-5_Crater.txt: text file for the crater catalogue.</strong></p>
Covid19Dynamics/2ndSurges: Ascertaining the initiation of COVID-19 second surges in Europe and the Northeast United States
<p>First release of data used in ascertaining the initiation of COVID-19 second surges in Europe and the Northeast United States</p>
Simultaneous single-unit recording from the basal amygdala and dorsal hippocampus
<p>Animals seeking survival needs must be able to assess different locations of threats in their habitat. However, the neural integration of spatial and risk information essential for guiding goal-directed behavior remains poorly understood. Thus, we investigated simultaneous activities of fear-responsive basal amygdala (BA) and place-responsive dorsal hippocampus (dHPC) neurons as rats left the safe nest to search for food in an exposed space and encountered a simulated 'predator.' In this realistic situation, BA cells increased their firing rates and dHPC place cells decreased their spatial stability near the threat. Importantly, only those dHPC cells synchronized with the predator-responsive BA cells remapped significantly as a function of escalating risk location. Moreover, optogenetic stimulation of BA neurons was sufficient to cause spatial avoidance behavior and disrupt place fields. These results suggest a dynamic interaction of BA's fear signaling cells and dHPC's spatial coding cells as animals traverse safe-danger areas of their environment.</p>
LFP and single-unit data published in Olafsdottir, Carpenter and Barry (2016) Nature Neuroscience 19: 792-794
<p><strong>OVERVIEW</strong></p> <p>All data are recorded using tetrodes - eight in MEC (deep layers) and eight in hippocampus - and the DACQ system from Axona Ltd</p> <p>For all recording files (except R2142), tetrodes 1-8 are in MEC (for R2142 it's the other way around)</p> <p>Filenames indicate the recording date, animal ID and whether the animal was running on the Z-track ('track1'), resting ('sleepPOST'), or foraging in the open field ('Training') - e.g. 20151201_R2337_track1 indicates that this file is from animal R2337 running on the Z-track on 1st December 2015</p> <p>Rest recordings were recorded immediately after animals were exposed to the track; foraging was carried out in a 1m square arena</p> <p>All files ending with .cut have spike sorted data - e.g. 20151127_R2337_track1_11.cut, contains the spike sorted data for tetrode 11; files ending with .pos contain position data (sampled at 50Hz); files ending with .egf contain LFP data (sampled at 4.8kHz); files ending with .set contain the header information; files ending with a number contain tetrode data - e.g. '20151127_R2337_track1.1' contains tetrode data from tetrode 1; and some folder have .clu files (the output of KlustaKwik), but these should be ignored as they are superseded by the .cut files</p> <p><br> <strong>RAT SPECIFIC NOTES</strong></p> <p>R2142</p> <p>>>2014-08-06</p> <p>Screening, Track1 and SleepPost present</p> <p> </p> <p>R2192</p> <p>>>2104-09-17</p> <p>Track1 and SleepPost sessions present</p> <p>>>2014-10-01</p> <p>Note this animal has a typo in the file name for the track session, indicating the wrong date - i.e. 20140110 should be 20141001, as this recording was made on 1st October 2014 NOT 10th January 2014. Note that this digit switch applies to all files for that session (i.e. track) but not to the other files from that day (i.e. sleepPost)</p> <p> </p> <p>R2217</p> <p>>>2014-12-13</p> <p>Screening, Track1 and SleepPost present</p> <p>>>2014-12-18</p> <p>Screening, Track1 and SleepPost present</p> <p><br> R2335</p> <p>>>2015-10-26</p> <p>Screening, Track1 and SleepPost present<br> </p> <p>R2336</p> <p>>>2015-11-01</p> <p>Track1 and SleepPost present</p> <p>>>2015-11-04</p> <p>Track1 and SleepPost present</p> <p> </p> <p>R2337</p> <p>>>2015-11-27</p> <p>Track1 and SleepPost present</p> <p>>>2015-12-01</p> <p>Track1 and SleepPost present</p>
Auxetic vibration behaviours of periodic tetrahedral units with a shared edge
A very low frequency mode supported within an auxetic structure is presented. We propose a constrained periodic framework with corner-to-corner and edge-to-edge sharing of tetrahedra and develop a kinematic model incorporating two types of linear springs to calculate the momentum term under infinitesimal transformations. The modal analysis shows that the microstructure with its two degrees of freedom has both low and high frequency modes under auxetic transformations. The low frequency mode approaches zero frequency when the corresponding spring constant tends to zero. With regard to coupled eigenmodes, the stress–strain relationship of the uniaxial forced vibration covers a wide range. When excited, a very slow motion is clearly observed along with a structural expansion for almost zero values of the elastic modulus.
Problem instances for scheduling personnel for the build-up of unit load devices at an air cargo terminal with limited space
<p>We randomly generated problem instances for the problem of scheduling the build-up of unit load devices at an air cargo terminal under space and personnel constraints (ULDSP in the following) which are used in the working paper "Emde, S., Abedinnia, H., Lange, A., and Glock, C. (2018): Scheduling personnel for the build-up of unit load devices at an air cargo terminal with limited space. Working paper TU Darmstadt".</p> <p>In total there are 60 problem instances which are divided in three datasets (small, medium, large) each of which contains 20 problem instances.</p>
Formation of ultra-depleted mantle peridotites and their relationship with boninitic melts: an example from the Kamuikotan Unit, Hokkaido, Japan
<p>Additional Supporting Information</p> <p>table_S1.xlsx: Compilation of the ultra-depleted peridotites<br> table_S1.xlsx: Locations and mineral major and trace elements compositions of the Takadomari and Horokanai ultra-depleted peridotites<br> table_S3.xlsx: Mineral and melt trace elements compositions obtained by our melting models</p> <p>QGIS<br> Geological map of the studied area</p>
Dataset for "Provide Developer-Approved Descriptive Names for Unit Tests"
<p>Dataset for "Provide Developer-Approved Descriptive Names for Unit Tests"</p> <p>Author: Jianwei Wu, James Clause</p> <p>Please contact at wjwcis@udel.edu for any questions.</p>
Accelerate the Parameterization of Unified Microphysics Across Scales (PUMAS) on the graphics processing unit (GPU) with directive-based methods
<p>Code used to produce results of paper titled "Accelerate the Parameterization of Unified Microphysics Across Scales (PUMAS) on the graphics processing unit (GPU) with directive-based methods" by Sun et al.</p> <p>Includes:</p> <p>- Source code of CAM to perform a CPU or GPU simulation</p> <p>- Source code of PUMAS stand-alone kernel for GPU porting (OpenACC and OpenMP offload), an example batch script for build/run on Casper (NCAR's cluster) and the input dataset</p> <p>- Dataset to reproduce the figures in the paper</p> <p> </p> <p>Contact details: Jian Sun (sunjian@ucar.edu)</p>
Administrative Units
<p>Intra-state water conflicts have increased substantially over the past few decades particularly in developing regions, and partly attributed to water scarcity. However, empirical studies linking water scarcity and violent conflicts are sparse, while existing quantitative studies have used mostly climate variables (precipitation and temperature) to understand this link. Most studies that have used climate variables concluded that they were not strong predictors of water conflicts. The aim of this study was to identify water scarcity hotspots and to understand the links between water scarcity and violent conflicts across the Sahel and Lake Chad Basin (LCB) over the period 2000-2021. To achieve this, we combine outputs from a global hydrological model and demographic data to develop six water scarcity metrics. The developed metrics show varying levels of water scarcity across the study region. The Falkenmark index across all capital cities (Ouagadougou-Burkina Faso, Ndjamena-Chad, Bamako-Mali, and Niamey-Niger), and Maradi-Niger and Jigawa & Kano states in Nigeria was less than 100 m<sup>3</sup>/capital/year, indicating acute water scarcity in those areas. Findings further indicated that green water scarcity (GWS) and the Falkenmark index were closely linked with water conflicts compared to the other metrics. Our findings suggest that water conflicts cannot be explained by hydroclimatic factors alone without incorporating other socioeconomic variables like demographic information. Results from this study may be used by stakeholders to tackle endemic water scarcity and to predict and mitigate water conflicts in the region.</p>
PHOTO.CAT Unit video | Short version
<p>Using Project Ô deliverables as a reference as well as a series of meetings held with the partners who developed each of the technologies, the PHOTO.CAT Unit video was published in July 2022. The production of this video included pre-production (script-writing, creating storyboards), production (designing and animating infographics, motion graphics, translating the script to Croatian, recording voice-over), and post-production (compiling, video and audio editing, subtitling, visual effects and rendering).</p> <p>--</p> <p>Project Ô has developed the PHOTO.CAT unit to treat water used in textile production. It will remove dyes from used water and it can help increase the amount of water that can be reused in a textile production factory. By using PHOTO.CAT and nanofiltration technologies, textile producers have control over the levels of sodium sulphate in the water that is reused in the dyeing process.</p>
Figure 24 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 24. Pronota of Aneflomorpha. a) A. subpubescens. b) A. aculeata, holotype.
Figure 20 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 20. Basal antennomeres of Aneflomorpha. a) A. delongi. b) A. linsleyae.
Figure 29 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 29. Elytral apex in Aneflomorpha. a) A. fisheri. b) A. rectilinea.
Figure 22 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 22. Basal antennomeres of Aneflomorpha. a) A. subpubescens. b) A. delongi.
Figure 31 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 31. Basal antennomeres in Aneflomorpha. a) A. cazieri. b) A. rectilinea.
Figure 28 in Revision of Aneflomorpha Casey and Neaneflus Linsley (Coleoptera: Cerambycidae) of the United States with an illustrated key to species
Figure 28. Coloration in Aneflomorpha. a) A. gilana. b) A. luteicornis.
Hyperspectral imaging of exciton confinement within a moiré unit cell with a subnanometer electron probe
<p>Data and processing notebooks for article titled "Hyperspectral imaging of exciton confinement within a moiré unit cell with a subnanometer electron probe" published in Science in Decembner 2022.</p> <p>The `ADF Image.dm4` is the simultaneously acquired annular dark field (ADF-) scanning transmission electron microscopy (STEM) image. This was used to determine the structural reconstruction of the WSe2 / WS2 heterostructure.</p> <p>The `EELS Spectrum Image.dm4` is a spectrum image (one spectra per probe position). This was used to determine the extent of the localization of the exciton peak I.</p> <p>The two `ipynb` jupyter notebooks were used to do the analysis shown in the paper. The output is embedded in the notebooks. Also, each notebook was run and then exported as a static HTML file to retain the code and output together in a generally readable format.</p> <p>Contact Peter Ercius (percius@lbl.gov) regarding the code or data.</p>
Quantification of Error Sources with Inertial Measurement Units in Sports - Data and Matlab Scripts
<p>Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filer. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to quantify each of the sources of error of an IMU separately. An optoelectronic system was used as a golden standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different trials, varying both in type of movement and in movement intensity. The error of the definition of the body frames (10.9-18.1 deg RMSD), the STA (3.6-9.4 deg RMSD) and the error of the orientation filter (2.8- 13.1 deg RMSD) were all quantified separately. The data and code to process the data can be found in this publication.</p> <p> </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.