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Fig. 2 in Taxonomic notes on the less studied long-horned-beetle fauna (Coleoptera: Cerambycidae) endemic in the Philippines. Part 1.
Fig. 2. Acronia marifelipeae Barševskis, 2016
Fig. 1 in Two new species of long-horned beetles (Coleoptera: Cerambycidae) from the Philippines
Fig. 1. Chydaeopsis torrejosae sp. nov. [holotype]
Fig. 2. Chydaeopsis luzonica Heller, 1923 in Two new species of long-horned beetles (Coleoptera: Cerambycidae) from the Philippines
Fig. 2. Chydaeopsis luzonica Heller, 1923 [holotype] (Berzak 2023)
Figure 3 in The first record of alpine long-eared bat Plecotus macrobullaris in Serbia
Figure 3. Photographs of skull in dorsal (A), ventral (B), and lateral (C) view.
Tif Image Stack - Example of a long sequence that was split into two tif files
<p>These two tif files were recorded during a single time-series capture. </p> <p>20240723_uro3g_t000000.tif - This image stack contains 3984 frames (time slices)</p> <p>20240723_uro3g_t000001.tif - This image stack contains 324 frames (time slices).</p> <p>The total number of frames/time slices should be 4308. (3984 + 324)</p> <p> </p> <p> </p> <p> </p>
Fig. 5 in First record of the Cat Ba Tiger Gecko, Goniurosaurus catbaensis, from Ha Long Bay, Quang Ninh Province, Vietnam: microhabitat selection, potential distribution, and evidence of threats
Fig. 5. Predicted habitat suitability for Goniurosaurus catbaensis in Vietnam.
Fig. 5 in Revision of the genus Thinophilus Wahlberg (Diptera: Dolichopodidae) from Singapore and adjacent regions: A long term study with a prudent reconciliation of a genetic to a classic morphological approach
Fig. 5. Thinophilus apicatus sp. nov. Phenology during a 2-year survey (MIP).
Fig. 2 in Revision of the genus Thinophilus Wahlberg (Diptera: Dolichopodidae) from Singapore and adjacent regions: A long term study with a prudent reconciliation of a genetic to a classic morphological approach
Fig. 2. Thinophilus apicatus sp. nov., male habitus.
Fig. 1 in Bartonella, Blechomonas and Trypanosoma in fleas from the long-tailed ground squirrel (Spermophilus undulatus) in northwestern China
Fig. 1. Map of northwestern China showing sampling sites and coordinates.
Low-amplitude long-period variable (OSARGs) candidates in Gaia DR3 LPV catalogue
<p>The low-amplitude long-period variable (LA-LPV) candidates in Gaia DR3 LPV catalogue. The selection is described in <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240606678Z/abstract">Zhang et al. 2024</a>. The heliocentric distances is in column "luminosity_dist" in unit of kpc. Other astrometric measurements are from Gaia DR3 and has the save column name as Gaia DR3. </p>
Replication data for: "Revisiting the 'East African Paradox': CMIP6 models also struggle to reproduce strong observed Long Rain drying trends."
<h3><strong>Intro</strong></h3> <p>This repository contains replication data for Schwarzwald, Kevin and Richard Seager (2024), "'Revisiting the “East African Paradox': CMIP6 models also struggle to reproduce strong observed MAM long rain drying trends." (under revision at Journal of Climate). This includes the data necessary to replicate all main text figures and most figures in Supplementary Materials. Additional figures in Supplementary Materials require raw precipitation time series, detailed below. This repository also includes a copy of the code necessary to replicate the entire study; the latest version of the code, in addition to instructions on how to use it, is kept at <a href="https://github.com/ks905383/gha_trends">this GitHub archive</a>. </p> <h3><strong>Structure</strong></h3> <p>The repository is structured as follows: </p> <ul> <li><code>code</code>: Static / stable version of reproduction code for Schwarzwald and Seager (2024) that uses and creates these data (see <a href="https://github.com/ks905383/gha_trends">here</a> for more detailed instructions)</li> <li><code>figures</code>: Static / stable versions of main and supplemental figures for Schwarzwald and Seager (2024).</li> <li><code>climate_raw</code>: "raw" (often pre-processed) climate data files; only some files are included, see below for more details</li> <li><code>climate_proc</code>: Processed climate data files upon which the analysis is based, used by main and supplemental figure code</li> <li><code>aux_data</code>: Certain auxiliary data files (fonts, critical values) and intermediate files for long code processes. Created and used by the replication code. </li> </ul> <h3><strong>Notes on raw climate data</strong></h3> <p>Due to space limitations (and a desire to not create yet another cloud copy of CMIP6 data), this repository only contains processed CMIP6 data: the calculated linear trends of rainfall, sea surface temperatures, and 500 hPa geopotential height used in the analysis of Schwarzwald and Seager (2024). The raw data used to create these files can be downloaded from the <a href="https://aims2.llnl.gov/search/cmip6/">ESGF</a>, and consists of every available CMIP6 monthly rainfall, sea surface temperature (SST), and geopotential height file on the archive at the time of processing for the experiments detailed in the manuscript. For precipitation, only a bounding box (-3 S to 12.5 N, 32 E to 55 E) around East Africa was downloaded, and saved with the file suffix "_HoAfrica" (see replication code README for more details). One example precipitation file (one ensemble member of ACCESS-CM2 historical precipitation) is included in this repository for reference. </p> <p>Similarly, this repository only contains processed NMME data: calculated linear trends of rainfall used in the analysis of Schwarzwald and Seager (2024). The raw data used to create these files can be downloaded from the <a href="https://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/">IRI Data Library</a> and consists of every available monthly rainfall hindcast / forecast file from the NMME archive for the models used (see manuscript Table S1). As above, only a bounding box around East Africa was downloaded, and files were standardized to a partial CMIP* file format (one file per variable, with CMIP file and variable name conventions, but with forecast lead time as an additional dimension). Preprocessing is a bit more extensive than for CMIP6 models: first, hindcasts and forecasts were concatenated into a single file (since hindcasts are saved in the archive only up to the time when the model was operationalized), and then reindexed such that the "time" variable refers to the time <em>for which the forecast is made</em>, and not the time <em>at</em> which the forecast is made. One example precipitation file (CanCM4i rainfall hindcasts/forecasts) is included in this repository for reference. </p> <p>This repository does, however, contain preprocessed copies of the "raw" gridded observational rainfall data products used (in addition to the processed trends), since harmonizing and standardizing the data into a format easily compatible with the CMIP6 data was a nontrivial amount of work that would be tedious to replicate. For the ten gridded observational data products used, monthly rainfall was brought into the CMIP* file format (one file per variable, with CMIP file and variable name conventions), with one notable exception: all observational rainfall is saved in units of mm/day. </p> <p>Reanalysis and gridded ocean observations can be downloaded from each product's respective repositories. As before, the code assumes the data have been preprocessed into something akin to the CMIP* file format. </p> <h3><strong>Notes on processed climate data</strong></h3> <p>Note that the repository includes a file (<code>aux_data/pr_doyavg_CHIRPS_historical_seasstats_dunning_19810101-20141231_HoAfrica.nc</code>) containing CHIRPS seasonal characteristics in East Africa, created as part of Schwarzwald et al., 2023, <em>Climate Dynamics</em>. This file is primarily used to set the boundaries of the study region, see the manuscript for details of how it was calculated. </p> <h3><strong>Licensing, citing, questions</strong></h3> <p>These data are offered under a CC 4.0 license, which allows redistribution and reuse as long as they are correctly cited; note that for much of these data (especially for "raw" data), this requires citations to the original creators. </p> <p>For questions, please feel free to reach out to corresponding author Kevin Schwarzwald. </p>
FIGURE 3 in Radiotagging a long-distance migratory characid fish: reproduction after surgery, tag losses, and effects in weight
FIGURE 3 | Fecundity (oocytes by gram of body weight) compared among treatments.
Investigation of satellite vertical sensitivity on long-term retrieved lower tropospheric ozone trends
<p>Regional time-series (monthly mean) of lower tropospheric column ozone (LTCO3; 0-6 km or surface to 450 hPa) between 2008 and 2017 from three satellite products and an Earth System Model (UKESM1.0 - https://ukesm.ac.uk/). The regions of focus are North America, Europe and East Asia based on the HTAP-2 land mask (https://htap.org/). The three satellite products are from the Ozone Monitoring Instrument (OMI) (RAL Space - https://www.ralspace.stfc.ac.uk/Pages/Remote-Sensing.aspx), the Infrared Atmospheric Sounding Interferometer (IASI) FORLI (Fast Optimal Retrievals on Layers for IASI) scheme (https://iasi.aeris-data.fr/cos_iasi_b_arch/) and the IASI SOFRID (SOftware for Fast Retrievals of IASI Data) scheme (https://iasi-sofrid.sedoo.fr/). These data have been used to investigate long-term trends and investigation of satellite long-term discrepancies in retrieved LTCO3. The pre-print of the relevant manuscript can be found at https://doi.org/10.5194/egusphere-2023-3109. </p>
Transcriptional stochasticity reveals multiple mechanisms of long non-coding RNA regulation at the Xist – Tsix locus
<p>Data and codes for Figure reprodicbility, image processing and demo.</p>
Source population and time spent in captivity affect survival and reproduction of long-distance translocated northern bobwhites
<p>Northern bobwhites (<em>Colinus virginianus</em>) have become a species of great conservation priority because of widespread and ongoing population declines. Long-distance translocations are becoming increasingly used to access a source population with densities high enough to support translocation. Two key uncertainties exist regarding the efficacy of long-distance translocations: choosing a source population with adaptations that will be successful in a novel environment and mitigating the stress response common during the translocation process. We translocated bobwhites from the South Texas Plains and the Floridian Coastal Plain to a recipient site in the Floridian Coastal Plain in 2021 and 2022 to compare the survival and productivity of bobwhites translocated from two different source populations. We also evaluated how varying holding times during the translocation process influenced the success of the translocated individuals. Breeding season survival, nest propensity, and fecundity were greater for Florida resident and Florida translocated bobwhites relative to Texas translocated bobwhites. We observed high rates of mortality during the transport and holding processes, but holding time did not affect breeding season survival of Texas translocated bobwhites. Both nest success and fecundity of Texas translocated bobwhites were negatively affected by holding time. Bobwhites translocated long distances may have the adaptive capacity to be successful in novel environments, but the consequences of translocation stress can be detrimental. Future translocation planning should consider choosing source populations from similar ecoregions to simultaneously decrease translocation distances and potential stress from translocation.</p>
Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport
<p>This repository contains supporting data for *Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport,* submitted to Geophysical Research Letters.</p> <p>Delft3D Config for Q1000Qs100Hs15.docx → contains configuration file info for running the Delft3d simulation Q1000Qs100Hs15.</p> <p>Matlab 2022b was used to load Delft3D output files and process the data.</p> <p>WaveDelta_Depth&DepositThick.mat Contains:</p> <p>Depth → timesteps x 322 x 142. Timesteps are variable for each simulation.</p> <p>MSEDRiverSum → 4 x 322 x 142. Mass of sediments from riverine source at four intermediate timesteps. </p> <p>MSEDWaveSum → 4 x 322 x 142. Mass of sediments from longshore transport (LSTUp) source at four intermediate timesteps.</p> <p>VolRiverSum → 322 x 142. Final Volume of sediments from riverine source.</p> <p>VolWaveSum → 322 x 142. Final Volume of sediments from longshore transport (LSTUp) source.</p> <p>XCOR & YCOR are the X and Y grid coordinate locations for maps (322 x 142).</p> <p>Shift2&4km are used for cases highly skewed downdrift to correct for 0 location at the river mouth.</p> <p>Cerc_formula.mlx Computes CERC longshore transport for the simulation conditions.</p> <p>J.mlx calculates river mouth balance (J) values (Nienhuis et al. (2016)) presented in Figure S4. </p> <p>Additional 114 Figures are provided in Data_Visualization_Figures.rar to show Depth and thickness; subaqueous morphodynamics and depth and sediment transport (quiver).</p>
Long-Term Physiological Adaptations Induced by Short-Interval High-Intensity Exercises
Open the record for dataset details and reuse information.
Inlists for "Rethinking Thorne-Żytkow Object Formation: The Fate of X-ray Binary LMC X-4 and Implications for Ultra-long Gamma-ray Bursts"
<div> <div> <div> <p>We use the MESA Isochrones and Stellar Tracks (MIST) package (Dotter 2016; Choi et al. 2016) with MESA v7503 (Paxton et al. 2011, 2013, 2015) and mesasdk x86_64-linux-20141212 revision 245. </p> </div> </div> </div>
Shapefiles showing the locations of long-term climate change refugia and hotspots identified in the FutureMARES report "D6.3, Climate ready strategies for nature-based solutions"
<p>Shapefiles created for the report "D6.3, Climate ready strategies for nature-based solutions", a deliverable report from the Horizon Europe project FutureMARES</p> <p>These shapefiles summarise long-term patterns that emerge from the spatial-meta analysis of physical-biogeochemical and species distribution modelling data, providing an overview of the distribution of climate change refugia and climate change hotspots across six European case study areas between 2026 - 2069, and across the five scenarios considered in the FutureMARES project (Global Sustainability RCP2.6, National Enterprise RCP8.5, World Market RCP8.5, Status Quo RCP2.6 and Status Quo RCP8.5). </p> <p>Filenames refer to the case study area and scenario each set of shapefiles belong to. Details of the modelling datasets used in each of these analyses, the meta-analysis method and shapefile creation can be found in the relevant chapter in the report "D6.3, Climate ready strategies for nature-based solutions".</p>
Long term lake mesocosm warming experiment: dataset of nitrous oxide concentrations, emissions and ancillary variables
<p>Dataset of nitrous oxide concentrations, emissions and ancillary variables collected at theLong term lake mesocosm warming experiment in Lemming, Denmark. </p>
ScienceDex guides
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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.