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12,346 results for “derivatives”
An archive of net community production estimates derived from autonomous profiler observations at Ocean Station Papa
<p>This dataset contains an archive of marine net community production estimates for Ocean Station Papa, derived using autonomous profilers, including BGC-Argo floats and sea gliders. The archive contains data from the following original publications:</p> <ol> <li>Haskell, W. Z., Fassbender, A. J., Long, J. S., and Plant, J. N.: Annual Net Community Production of Particulate and Dissolved Organic Carbon From a Decade of Biogeochemical Profiling Float Observations in the Northeast Pacific, Global Biogeochemical Cycles, 34, 1–22, <a href="https://doi.org/10.1029/2020GB006599">https://doi.org/10.1029/2020GB006599</a>, 2020.</li> <li>Huang, Y., Fassbender, A. J., Long, J. S., Johannessen, S., and Bernardi Bif, M.: Partitioning the Export of Distinct Biogenic Carbon Pools in the Northeast Pacific Ocean Using a Biogeochemical Profiling Float, Global Biogeochemical Cycles, 36, <a href="https://doi.org/10.1029/2021gb007178">https://doi.org/10.1029/2021gb007178</a>, 2022.</li> <li>Pelland, N. A., Eriksen, C. C., Emerson, S. R., and Cronin, M. F.: Seaglider Surveys at Ocean Station Papa: Oxygen Kinematics and Upper-Ocean Metabolism, Journal of Geophysical Research: Oceans, 123, 6408–6427, <a href="https://doi.org/10.1029/2018JC014091">https://doi.org/10.1029/2018JC014091</a>, 2018.</li> <li>Plant, J. N., Johnson, K. S., Sakamoto, C. M., Jannasch, H. W., Coletti, L. J., Riser, S. C., and Swift, D. D.: Net community production at Ocean Station Papa observed with nitrate and oxygen sensors on profiling floats, Global Biogeochemical Cycles, 30, 859–879, <a href="https://doi.org/10.1002/2015GB005349">https://doi.org/10.1002/2015GB005349</a>, 2016.</li> <li>Yang, B., Emerson, S. R., and Bushinsky, S. M.: Annual net community production in the subtropical Pacific Ocean from in-situ oxygen measurements on profiling floats, Global Biogeochemical Cycles, 31, 728–744, <a href="https://doi.org/10.1002/2016GB005545">https://doi.org/10.1002/2016GB005545</a>, 2017.</li> </ol> <p> </p> <p><strong>Dataset description:</strong></p> <p>Separate Matlab (.mat) and NetCDF (.nc) files are provided for each original publication dataset. At minimum, each contains time (recorded as absolute days since 01 Jan 2000, 00:00:00), and time-explicit depth-integrated NCP. Additional fields include depth-resolved NCP, and water column depth (Plant et al., 2016; Pelland et al., 2018).</p> <p>Note that the Haskell et al. (2020) dataset (haskell20.mat, haskell20.nc) contains climatological NCP estimates. Accordingly, the time field represents the Year-day only. </p> <p>All NCP units are recorded in units of mmol O2/m2/d (depth-integrated) or mmol O2/m3/d (depth-resolved).</p> <p>Additional information on each dataset is contained within the data files. Additional processing information is contained in Izett et al. (under review).</p> <p> </p> <p><strong>The data were compiled in: </strong></p> <p>Izett, R. W., Fennel, K., Stoer, A. C., and Nicholson, D. P. Reviews and syntheses: Expanding the global coverage of gross primary production and net community production measurements using BGC-Argo floats, <em>Submitted to Biogeosciences. 2023</em>.</p> <p> </p> <p><strong>Please cite as:</strong></p> <p>Izett, R., Haskell, W., Huang, Y., Pelland, N., Plant, J., and Yang, B. 2023. An archive of net community production estimates derived from autonomous profiler observations at Ocean Station Papa. Database. Zenodo. doi: 10.5281/zenodo.7667521. Accessed on <em>DATE</em>. </p>
Derived data supporting the analysis of surface albedo changes from Mars 2020 observations: Probabilistic distribution of the Amplitude Spectral Densities of Supercam microphone recordings and Monte-Carlo dust devil simulations.
<p>These files contain derived data used in the analysis submitted for publication in Journal of Geophysical Research: Planets, entitled "Dust Lifting Through Surface Albedo Changes at Jezero Crater, Mars" by Vicente-Retortillo et al. The article was initially submitted on November 14, 2022, and the revised version on March 1, 2023.</p> <p>Files include the derived data and information needed to generate Figures 4 (Microphone_Data.mat and Plot_ASD_from_Microphone_Data) and 6 (remaining files) of the article.</p>
Data from: Enhanced climate tolerance for trees derived from microbial communities
<p>Changing climates are pushing species outside of their evolved tolerances; populations must acclimate or adapt to the new conditions or migrate to avoid extinction. However, because plants associate with diverse microbial communities that shape their phenotype, shifts in microbial associations may provide an alternative source of novel climate tolerance. Here we show that tree seedlings inoculated with microbial communities sourced from drier, warmer, or colder sites displayed higher survival when facing drought, heat, or cold stress, respectively. Microbially mediated drought tolerance was associated with increased diversity of arbuscular mycorrhizal fungi, while cold tolerance was related to reduced diversity of non-adapted taxa. Understanding microbially mediated climate tolerance may enhance our ability to predict and manage the adaptability of forest ecosystems to changing climates.</p>
Dataset: A Systematic Study on the Redox Potentials of Phenazine- Derivatives in Aqueous Media: A Combined Computational and Experimental Work
<p>Dataset for the results shown in the publication "A Systematic Study on the Redox Potentials of Phenazine-Derivatives in Aqueous Media: A Combined Computational and Experimental Work"</p>
CMIP6 derived ensemble of global vapor pressure deficit, potential evapotranspiration, and reference evapotranspiration
<p>Climate change induced trends in long-term aridity—via changes to atmospheric water demand for have the potential to impact surface water availability across the globe by altering efficiency by which precipitation is converted to runoff. Quantification of aridity requires estimates of evaporative demand, often using vapor pressure deficit, potential evapotranspiration, and/or reference evapotranspiration, but no comprehensive estimate of these climate variables exists to date from the Coupled Model Intercomparison Project 6 (CMIP6). Here we present global monthly estimates of the Penman-Monteith short grass reference evapotranspiration, its advective and radiation components, Priestley-Taylor potential evapotranspiration, and vapor pressure deficit from 16 CMIP6 general circulation models (GCM) for the historical period and four future emission scenarios ranging from low to high projected emissions. The purpose of this dataset is to offer structured and well-documented estimates of historical and future projected evaporative demand derived from the state-of-the-science CMIP6 climate models for use in hydrologic and ecological analyses. We produce a single file for all monthly values of each variable for individual GCM/emission scenario combination gridded at the given GCMs native resolution. Produced alongside all of the files are descriptions of each of the variables and generated python scripts that contain the functions used to estimate vapor pressure deficit, potential evapotranspiration, and reference evapotranspiration.</p>
Temporal Synchrony in Satellite-Derived Ocean Parameters in the Inner Sea of Chiloé, Northern Patagonia, Chile
<p>GENERAL INFORMATION</p> <p>Title of Dataset: Replication data for: Long-term synchrony in satellite-derived ocean parameters in northern Patagonia, Chile.</p> <p>- General Bathymetry of the Ocean (GEBCO),northern Patagonia.</p> <p>- Daily Chlorophyll-a (Chla, mg m-3), Fluorescence Line Height (nFLH; W m-2 μm-1 sr-1) and surface reflectance at 645nm (Rrs 645). MODIS Level2.</p> <p>- Daily river discharge (m3/s) from Puelo and Futaleufú stations. Dirección General de Aguas (DGA, Chile).</p> <p>- Climatic indices: ENSO Multivariate (MEI v2) and Southern Annular Mode (SAM).</p> <p> </p>
VIIRS-derived annual mean chlorophyll-a in China large lakes from 2012 to 2021
<p>This dataset included annual mean Chl-a in China's large lakes (>50 km<sup>2</sup>) derived from VIIRS-SNPP imagery from 2012 to 2021. The dataset is stored as the Geo-Tiff data.</p> <p>To generate this dataset, we develop a practical deep neural network (DNN) model . The DNN model performed satisfactory performance on Chl-a retrievals (MR = 0.86, MAPE = 32%, Bias = 5%) over the three magnitudes (0.1–300 μg L<sup>−1</sup>) spanning clear/deep to turbid/shallow waters, with significant improvements compared with the existing algorithms and other machine learning approaches. </p> <p>The dataset is related to a under-review manuscript and we will release it when the paper is published.</p>
CBRA: The first multi-annual (2016-2021) and high-resolution (2.5 m) building rooftop area dataset in China derived with Super-resolution Segmentation from Sentinel-2 imagery
<p>Large-scale and up-to-date maps of building rooftop area (BRA) are crucial for addressing policy decisions and sustainable development. In addition, as a fine-grained indicator of human activities, BRA could contribute to urban planning and energy modeling to provide benefits to human well-being. However, existing large-scale BRA datasets, such as those from Microsoft and Google, do not include China, hence there are no full-coverage maps of BRA in China. To this end, we produce the multi-annual China building rooftop area dataset (CBRA) with 2.5 m resolution from 2016-2021 Sentinel-2 images. The CBRA is the first full-coverage and multi-annual BRA data in China. The CBRA achieves good performance with the F1 score of 62.55% (+10.61% compared with the previous BRA data in China) based on 250,000 testing samples in urban areas, and the recall of 78.94% based on 30,000 testing samples in rural areas. </p> <p>The CBRA is organized as GeoTIFF (.tif) raster file format with a single band and GCS_WGS_1984 coordinate system. The pixel values are 0 and 255, with 0 representing the background and 255 representing the building rooftop area. Furthermore, to facilitate the use of the data, the CBRA is split into 215 tiles of spatial grid, named “CBRA_year_E/W**N/S**.tif”, where “year” is the sampling year, the “E/W**N/S**” is the latitude and longitude coordinates found in the upper left corner of the tile data.</p> <p> </p> <p>Version 2.0: In version 1.0, there were empty raster images (because they didn't contain buildings). In version 2.0, these raster images were removed.</p>
Data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'
<p>Additional data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'</p>
Dataset used in "Comment on "Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam" by Kim-Anh Nguyen, Yuei-An Liou, Ha-Phuong Tran, Phi-Phung Hoang and Thanh-Hung Nguyen"
<p>The Excel file provides all the data included in Tab.4 of Nguyen et al. 2020 plus reflectances extracted from the Landsat 8 OLI image acquired on 14 February 2017 and downloaded from the USGS Earth Explorer website. Observations on the number of pixels falling of water, land and mixed water/land surfaces are provided as well as water percentage cover estimated using regular spaced points. </p> <p>The dataset includes vector files (kml format) of the grids corresponding to the selected L8 pixels as well as the regularly spaced points generated within the selected pixels. These files can be imported in QGIS, Google Earth Pro and other free GIS software.</p>
Taste Peptides and their derivatives
<p>Food Ai Researcher</p>
Polygenic risk scores validated in patient-derived cells stratify for mitochondrial subtypes of Parkinson's disease
<p><strong>Background</strong> Parkinson’s disease (PD) is the fastest growing neurodegenerative disorder, with affected individuals expected to double during the next 20 years. This raises the urgent need to better understand the genetic architecture and downstream cellular alterations underlying PD pathogenesis, in order to identify more focused therapeutic targets. While only ∼10% of PD cases can be clearly attributed to monogenic causes, there is mounting evidence that additional genetic factors could play a role in idiopathic PD (iPD). In particular, common variants with low to moderate effect size in multiple genes regulating key neuroprotective activities may act as risk factors for PD. In light of the well-established involvement of mitochondrial dysfunction in PD, we hypothesized that a fraction of iPD cases may harbour a pathogenic combination of common variants in nuclear-encoded mitochondrial genes, ultimately resulting in neurodegeneration.</p> <p><strong>Methods</strong> to capture this mitochondria-related “missing heritability”, we leveraged on existing data from previous genome-wide association studies (GWAS) – i.e., the large PD GWAS from Nalls and colleagues. We then used computational approaches based on mitochondria-specific polygenic risk scores (mitoPRSs) for imputing the genotype data obtained from different iPD case-control datasets worldwide, including the Luxembourg Parkinson’s Study (412 iPD patients and 576 healthy controls) and the COURAGE-PD cohorts (7270 iPD cases and 6819 healthy controls).</p> <p><strong>Results</strong> applying this approach to gene sets controlling mitochondrial pathways potentially relevant for neurodegeneration in PD, we demonstrated that common variants in genes regulating <em>Oxidative Phosphorylation (OXPHOS</em>-PRS<em>)</em> were significantly associated with a higher PD risk both in the Luxembourg Parkinson’s Study (odds ratio, OR=1.31[1.14-1.50], <em>p</em>=5.4e-04) and in COURAGE-PD (OR=1.23[1.18-1.27], <em>p</em>=1.5e-29). Functional analyses in primary skin fibroblasts and in the corresponding induced pluripotent stem cells-derived neuronal progenitor cells from Luxembourg Parkinson’s Study iPD patients stratified according to the <em>OXPHOS</em>-PRS, revealed significant differences in mitochondrial respiration between high and low risk groups (<em>p</em> < 0.05). Finally, we also demonstrated that iPD patients with high <em>OXPHOS</em>-PRS have a significantly earlier age at disease onset compared to low-risk patients.</p> <p><strong>Conclusions</strong> our findings suggest that OXPHOS-PRS may represent a promising strategy to stratify iPD patients into pathogenic subgroups – in which the underlying neurodegeneration is due to a genetically defined mitochondrial burden – potentially eligible for future, more tailored mitochondrially targeted treatments.</p>
Data set used in "Effect of turbulence and viscosity models on wall shear stress derived biomarkers for aorta simulations"
<p>Data set used in "Effect of turbulence and viscosity models on wall shear stress derived biomarkers for aorta simulations"</p> <p>Includes the data for 20 heartbeats. Divided into external and internal walls regions. </p>
Landsat-derived rangeland condition indicators in East Africa from 2000 to 2022
<p>Tracking environmental change is important to ensure efficient and sustainable natural resources management. East Africa is dominated by arid and semi-arid rangeland systems, where extensive grazing of livestock represents the primary livelihood for most of the human population. Despite several mapping efforts, East Africa lacks accurate and reliable high-resolution rangeland health maps necessary for management, policy, and research purposes. Earth Observations offer the opportunity to assess spatiotemporal dynamics in rangeland health conditions at much higher spatial and temporal coverage than conventional approaches that rely on in-situ methods, while complimenting their certainty. Using machine learning-based classification and linear unmixing, this paper produced Landsat-based time series at 30 m spatial resolution for mapping of land cover classes (LCC) and vegetation fractional cover (VFC, including photosynthetic vegetation PV, non-photosynthetic vegetation NPV, and bare ground BG), two major data assets to derive metrics for rangeland health in East Africa. Due to scarcity of in-situ measurements in a large, remote and highly heterogeneous landscape, an algorithm was developed to combine very high-resolution WorldView-2 and -3 satellite imagery at < 2 m resolutions with a limited set of ground observations to generate reference labels across the study region. The LCC analysis yielded an overall accuracy of 0.856 using our validation dataset, with Kappa of 0.832; VFC, yielded R<sup>2</sup> = 0.801, <em>p</em> < 2.2e-16, normalized root mean squared error (nRMSE) = 0.123. Our products represent the first multi-decadal high-resolution dataset specifically designed for mapping and monitoring rangelands health in East Africa including Kenya, Ethiopia and Somalia, covering a total area of 745,840 km<sup>2</sup>, dominated by arid and semi-arid extensive rangeland systems. These data can be valuable to a wide range of development, humanitarian, and ecological conservation efforts and are available at https://doi.org/10.5281/zenodo.7106166 and Google Earth Engine (GEE; details in data availability section).</p>
Canopy top height models at 10m GSD from airborne LIDAR (derived from LVIS and small-footprint ALS)
<p>Rasterized canopy top height models (CTHM) at 10m ground sampling distance (GSD) derived from airborne LIDAR.</p><p>The CTHMs were created to be comparable to GEDI canopy top heights (within 25m footprints) using two sources:</p><p>1) NASA's LVIS airborne LIDAR campaigns (here we rasterized the RH98).<br>2) High-resolution canopy height models derived from small-footprint airborne laser scanning campaigns in Europe (max pooled with a circular 25m footprint corresponding to the GEDI footprint).</p><p>The original LVIS LIDAR data is available here: <a href="https://lvis.gsfc.nasa.gov">https://lvis.gsfc.nasa.gov</a></p><p>Links to the original ALS data are available here: <a href="https://publications.jrc.ec.europa.eu/repository/bitstream/JRC126223/jrc126223_jrc126223_lidaropensourcedata.pdf">https://publications.jrc.ec.europa.eu/repository/bitstream/JRC126223/jrc126223_jrc126223_lidaropensourcedata.pdf</a></p><p>Code to create GEDI-like canopy top heights from high-resolution ALS data is available here: https://github.com/langnico/global-canopy-height-model</p><p>More information is available in the Lang et al. (2022). Please cite our paper if you use these derived data in your own work.</p><p><strong>Reference:</strong></p><p>Lang, N., Jetz, W., Schindler, K., & Wegner, J. D. (2023). A high-resolution canopy height model of the Earth. Nature Ecology & Evolution, 1-12, <a href="https://doi.org/10.1038/s41559-023-02206-6">https://doi.org/10.1038/s41559-023-02206-6</a></p>
Supporting Material for "Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC And Kaguya TC Images"
<p>Supporting Material for "Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC And Kaguya TC Images"</p> <p>Contents of this material</p> <ul> <li>Supplemental Text S1 and Text S2.</li> <li>Figures S1, S2, S2, S4, S5.</li> <li>Tables S1, S2</li> </ul> <p>For any questions email JHF (john.h.fairweaher@gmail.com).</p>
Radiometer network dataset of 10 Hz spectral irradiance and derived variables (LIAISE campaign)
<p><strong>Description</strong></p> <p>Measurements from the spatial network of 15 radiometers deployed at the LIAISE field campaign in 2021.</p> <p>14 July 2021 until 28 July 2021.</p> <p><strong>Dataset Contents</strong></p> <ul> <li><em>rsds: </em>Total shortwave downwelling solar irradiance @ 10 Hz, 1 sec, and 1 minute resolution (Level 2, derived dataset)</li> <li><em>prw: </em>Total column integrated water vapour @ 1 sec resolution (Level 2, derived dataset)</li> <li><em>spectrum: </em>Pre-calibrated solar spectral irradiance measurements @ 10 Hz resolution (Level 1, source dataset)</li> <li><em>raw data:</em> straight from the sensors (Level 0)</li> </ul> <p><strong>Dataset Quality</strong></p> <p>All data is quality controlled and completed with metadata and quality flags. Level 2 data is calibrated against high quality references, and derived from Level 1 data.</p> <p>Methodology, performance, and usage all described in detail in an upcoming pre-print.</p> <p><strong>References and more info</strong></p> <ul> <li><a href="https://egusphere.copernicus.org/preprints/2022/egusphere-2022-726/">Radiometer reference paper (FROST)</a></li> <li>LIAISE <a href="https://liaise.aeris-data.fr/">campaign website</a>, <a href="https://liaise.aeris-data.fr/page-catalogue/?uuid=594dbc5d-986e-4679-b0ec-7d1e29b5cab9">LIAISE database</a></li> <li>Dataset description paper: <a href="https://arxiv.org/abs/2307.06980">pre-print on Arxiv</a></li> <li>Code to produce these data <a href="https://doi.org/10.5281/zenodo.10159129">on Zenodo</a></li> </ul> <p><strong>Version History</strong></p> <p>v1.2: fixed bug of incorrect wavelength labeling, all bands but 900 and 940 nm were affected. This only concerns the 10 Hz spectrum data, rest unchanged.</p> <p>v1.1: added raw (level 0) data, fixed typo in file name for the 10 Hz spectrum zip (L2 -> L1).</p>
Data of soil mineralization rates, carbon and nitrogen pools in a rainfed almond crop and an irrigated mandarin crop derived from Diverfarming project
Data of soil carbon and nitrogen dynamics, auxiliary data and methods metadata from a rainfed almond crop and an irrigated mandarin crop studied in Diverfarming project
Satellite derived floodplains (GFD ) combined with spatially- explicit socio-economic data and DFO impacts
<p>These data is linked to the paper </p> <p><strong>Limited progress in global reduction of vulnerability to flood impacts over the past two decades</strong></p> <p><strong>Inga J. Sauer¹ ², Benedikt Mester¹ ³, Katja Frieler¹, Sandra Zimmermann1, Jacob Schewe¹, and Christian Otto¹</strong></p> <p><strong>¹ Potsdam Institute for Climate Impact Research, Potsdam, Germany </strong></p> <p><strong>² Institute for Environmental Decisions, ETH Zurich, Zurich, Switzerland</strong></p> <p><strong>³ Institute of Environmental Science and Geography, Potsdam University, Potsdam, Germany</strong></p> <p><span>DOI: 10.1038/s43247-024-01401-y</span></p> <p>It combines the satellite observed flooded areas from the <strong>global flood database (GFD) </strong>with socio-economic and infrastructure data and the socio-economic impacts recorded in the <strong>Global Active Archive of Large Flood Events provided by the Dartmouth Flood Observatory (DFO).</strong></p>
Fig 2 in Soluble total antigen derived from Toxoplasma gondii RH strain prevents apoptosis, but induces anti-apoptosis in human monocyte cell line
Fig 2. This schematic overview suggests signaling pathways of apoptosis. Apoptosis is induced through either the extrinsic pathway or intrinsic pathway. Toxoplasma gondii can prevent cell apoptosis via inhibition of cytochrome c release from the mitochondria into the cytosol, inhibition of cas-3, -6, -7, and -9 via blocking the mitochondrial pathway, and blocking cas-8 by external pathways. The parasite may also suppress pro-apoptotic protein (Bax) and induce anti-apoptotic Bcl-2 proteins and is able to activate transcription factors STAT6 and STAT3-miR-17-92-Bim pathway to inhibit apoptosis. Some proteins of T. gondii such as ROP18 plays a role in Fas/ CD95-mediated apoptosis to inhibit this process. Similarly ROP16 phosphorylates STAT3 and STAT6 to inhibit cell death. Original (S. Nemati).
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.