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412 results for “SCOPE”
Scoping fieldwork conducted in Yakutsk (2018)
<p>Photos taken during the scoping fieldwork conducted in Yakutsk (June 2018). </p>
WW2 Artillery Spotting Scope
WWII Era Japanese Mounted Artillery Spotting Scope Optics assignment for Game Asset Pipeline course. Source: Objaverse 1.0 / Sketchfab
ASTRAL-SCOPe subset 2.04 in ActivePapers format
<p>This ActivePaper contains the structures in version 2.04 of the ASTRAL SCOPe subset with less than 40% sequence identity. For more information about ASTRAL and SCOPe, see</p> <p> http://scop.berkeley.edu/astral/</p> <p>Each ASTRAL entry describes a domain from a protein structure in the PDB. This ActivePaper contains these domains in the MOSAIC HDF5 format. For more information about MOSAIC, see</p> <p> http://mosaic-data-model.github.io/</p> <p>The structures are arranged by its SCOPe classification. For example, ASTRAL entry d1v0aa1 is found under /data/b/18/1/30/d1v0aa1, because SCOPe classifies it as</p> <p> b: all-beta proteins<br /> b.18: Galactose-binding domain-like<br /> b.18.1: Galactose-binding domain-like<br /> b.18.1.30: CBM11</p> <p>For each entry, the ASTRAL database provides a reference to the PDB entry with chain and residue identifiers plus a sequence. The importlet in /code/import_structures reads this information, downloads the corresponding PDB entry in mmCIF format, extracts the domain, checks that its sequence matches the one given by ASTRAL, and stores the domain in MOSAIC format.</p> <p>For a small number of ASTRAL entries, this process failed for various reasons: mismatch between the ASTRAL reference and the PDB data, mismatch in the sequences, a mistake in the PDB mmCIF file, or unjustified hypotheses in the conversion script. The number of failures was deemed sufficiently small (28 failures out of 13042 entries) for not attempting a time-consuming in-detail analysis of each failure. The list of missing entries (generated automatically during the import process) can be found in this ActivePaper under /documentation/missing-entries.</p>
micro*scope: micro*scope 2024
<p>micro*scope is a community that provides descriptive information about all kinds of microbes. It combines locally assembled content with links to other expert sites on the internet. Information is assembled in collections provided by various contributors.</p><p></p><p>With manual edits, removing some images. </p>
STEMMUS-SCOPE for PLUMBER2: A Physically Consistent Dataset Across the Soil-Plant-Atmosphere Continuum
<p>High-quality and long-term measurements of water, energy, and carbon fluxes between the land and atmosphere are critical for climate monitoring and land surface model (LSM) benchmarking. This dataset presents high-quality and long-term fluxes, and the corresponding above and below-ground hydrological, physiological, photosynthetic and radiative data derived from the STEMMUS-SCOPE model simulations for the PLUMBER2 project at 170 FLUXNET sites. The generated datasets by STEMMUS-SCOPE are in good agreement with quality in-situ measurements. Therefore, we recommend future applications of the datasets, for such as the detection and attribution of historical changes of fluxes and SM and associated extreme events, providing the initial and boundary conditions for atmospheric models, benchmarking various types of models, and monitoring drought risks. The published dataset can contribute to the development of earth system models in better representing land surface processes and land-atmosphere exchanges in forms of energy, water, and carbon.</p>
What harms and what hinders de-implementation of low-value care in emergency medicine practice ? A scoping review
<p><span>Low-value care can harm patients and healthcare systems. </span><span>Despite a decade of global endeavours, low-value care has persisted. Identification of barriers and enablers is essential for effective de-implementation of low-value care. This scoping review is an evidence summary of barriers, enablers and features of effective interventions for de-implementation of low-value care in emergency medicine practice worldwide.</span></p>
H-2020 MOOD Scoping review of Leptospirosis, Influenza A and Chikungunya on the environmental covariates
<p>The dataset contains quantitative data on the environmental covariates associated with influenza A, Chikungunya, and Leptospirosis retrieved from scientific papers through a standardized search on PubMed, Embase, Web of Science, and Scopus. Inclusion criteria were data on the association between disease and covariates, language (English or other EU languages), time frame (30 years), geographical location (Europe), and publication type. Studies without data or with non-original or duplicated data (reviews, editorials, letters, modeling studies with no data), lacking denominators or reference populations, unavailable full-texts, referring to data older than 2000 or gathered outside Europe, were excluded. The final time frame covered a period from 2000 to 2022.</p> <p>The important environmental covariates were extracted with the associated quantitative information, and the related information on the diseases. The covariates were submitted to a revision process to label them according to a labeling system agreed upon among a group of experts within the MOOD (grant agreement No 874850; <a href="https://mood-h2020.eu/" target="_blank" rel="noopener noreferrer">https://mood-h2020.eu/</a>) project consortium.</p>
Telemedicine for diabetes in Norway: Scoping review appendices
<p>Contains appendices:</p> <p>- Appendix 1: Full search strategy</p> <p>- Appendix 2: List of publications that were rejected during the full-text review and exclusion reasons </p>
A scoping review of patient safety research carried out in the Republic of Ireland [dataset]
<p>This is an example search strategy (supplemental materials 1) and the charting form data (supplemental materials 2) from each of the 31 included papers included in the scoping research.</p> <p><strong>Background.</strong> Maintaining the highest levels of patient safety is a priority of healthcare organisations. However, although considerable resources are invested in improving safety, patients still suffer avoidable harm.</p> <p><strong>Aims.</strong> (1) To examine the extent, range, and nature of patient safety research activities carried out in the RoI; (2) make recommendations for future research; and (3) consider how these recommendations align with the Health Service Executive’s (HSE) patient safety strategy.</p> <p><strong>Methods.</strong> A five-stage scoping review methodology was used to synthesise the published research literature on patient safety carried out in the RoI: (1) identify the research question; (2) identify relevant studies; (3) study selection; (4) chart the data; and (5) collate, summarising, and reporting the results. Electronic searches were conducted across five electronic databases.</p> <p><strong>Results.</strong> A total of 31 papers met the inclusion criteria. Of the 24 papers concerned with measuring and monitoring safety, 12 (50%) assessed past harm, 4 (16.7%) the reliability of safety systems, 4 (16.7%) sensitivity to operations, 9 (37.5%) anticipation and preparedness, and 2 (8.3%) integration and learning. Of the six intervention papers, three (50%) were concerned with education and training, two (33.3%) with simplification and standardisation, and one (16.7%) with checklists. One paper was concerned with identifying potential safety interventions.</p> <p><strong>Conclusions.</strong> There is a modest, but growing, body of patient safety research conducted in the RoI. It is hoped that this review will provide direction to researchers, healthcare practitioners, and health service managers, in how to build upon existing research in order to improve patient safety.</p>
Dataset_Scoping review_Changes in quality of cancer care assessed through performance indicators
<p>Data on which the conclusions of the study "<em>Changes in the quality of cancer care as assessed through performance indicators during the first wave of the COVID-19 pandemic in 2020: a Scoping Review</em>" rely, namely: articles included in the Scoping Review and performance indicators extracted and collated.</p>
Training dataset for HeLa "Kyoto" cells under the scope
<p>The Patches folder contains the training patches with csv files of cells 2 steps before the division and 2 steps in time after the division for 5 channels of the Kyoto Hela cells, the Oneat folder contains the json file of the cell categories and the map of XYTHW locations and its corresponding integer labels. The dataset is intended to be used for training oneat networks for these cells in different imaging modalities.</p> <p> </p> <p>Training patches with labels for 5 channels of hela cells: trainX, trainY = 64, 64, tminus = 2, tplus = 2, whole image was normalized using percentile based normalization pre patch making process. Patches made without segmentation image as input so height and width = 1 in yolo training labels.</p> <p>Made by oneat software, pip install oneat for training of such datasets.</p> <p> </p> <p>Original data published by Romain Guiet at https://zenodo.org/record/6139958#.YmAh1NpBxhG</p>
Revealing the Sustainability of Novel Food System Technologies: A systematic scoping review
<p>This repository contains the R- script and data files used to generate visualizations for a systematic scoping review on the sustainability of novel food system technologies. </p>
Scoping survey on the state of play of Open Science at SEA-EU universities
<p>Survey data that sought to collect information about the state of play on Open Research Data Management practices amongst the SEA-EU Alliance.</p>
Randomised trials in maternal and perinatal health in low- and middle-income countries from 2010 to 2019: A systematic scoping review
<p><strong>Objectives: </strong>To identify and map all trials in maternal health conducted in low- and middle-income countries (LMIC) over the 10-year period 2010-2019, to identify geographical and thematic trends, as well as compare to global causes of maternal death and pre-identified priority areas.</p> <p><strong>Design: </strong>Systematic scoping review.</p> <p><strong>Primary and secondary outcome measures: </strong>Extracted data included location, study characteristics and whether trials corresponded to causes of mortality and identified research priority topics.</p> <p><strong>Results: </strong>Our search identified 7,269 articles, 874 of which were included for analysis. Between 2010 and 2019, maternal health trials conducted in LMICs more than doubled (50 to 114). Trials were conducted in 61 countries – 231 trials (26.4%) were conducted in Iran. Only 225 trials (25.7%) were aligned with a cause of maternal mortality. Within these trials, pre-existing medical conditions, embolism, obstructed labour, and sepsis were all under-represented when compared with number of maternal deaths globally. Large numbers of studies were conducted on priority topics such as labour and delivery, obstetric haemorrhage, and antenatal care. Hypertensive disorders of pregnancy, diabetes, and health systems and policy – despite being high-priority topics – had relatively few trials.</p> <p><strong>Conclusion: </strong>Despite trials conducted in LMICs increasing from 2010 to 2019, there were significant gaps in geographical distribution, alignment with causes of maternal mortality, and known research priority topics. The research gaps identified provide guidance and insight for future research conducted in low-resource settings.</p>
Identification of components associated with the operation of Mutual Aid Groups: a scoping review. Matriz.
<p>Base de datos del socping review titulado </p> <p>Identification of components associated with the operation of Mutual Aid Groups: a scoping review</p>
2017 SCOPE Gradients Water Column Data
<p>This dataset contains water column data collected via CTD/rosette profiles taken on the SCOPE Gradients 2 cruise in the Northeast Pacific Ocean, averaged at every Niskin bottle trip. The SCOPE-Gradients program is designed to test conceptual and mathematical models of biogeochemical organization across the transition zone between different ecosystems. </p>
2019 SCOPE Gradients Downcast CTD Data
<p>This dataset contains water column data collected via CTD profiles taken on the SCOPE Gradients 3 (KM1906) oceanographic research cruise in the Northeast Pacific Ocean. These data were collected on the CTD downcast. The SCOPE-Gradients program is designed to test conceptual and mathematical models of biogeochemical organization across the transition zone between different ecosystems.</p>
2021 SCOPE Gradients Downcast CTD Data
<p>This dataset contains water column data collected via CTD profiles taken on the SCOPE Gradients 4 cruise. These data were collected on the CTD downcast. The SCOPE-Gradients program is designed to test conceptual and mathematical models of biogeochemical organization across the transition zone between different ecosystems. This dataset was collected on the R/V Thompson during the Gradients 4 cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu.</p>
2021 SCOPE Gradients, Water Column Data
<p>This dataset contains water column data collected via CTD/rosette profiles taken on the SCOPE Gradients 4 cruise, averaged at every Niskin bottle trip. The SCOPE-Gradients program is designed to test conceptual and mathematical models of biogeochemical organization across the transition zone between different ecosystems. This dataset was collected on the R/V Thompson during the Gradients 4 cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu.</p>
2016 SCOPE Gradients Water Column Data
<p>This dataset contains water column data collected via CTD/rosette profiles taken on the SCOPE Gradients 1 (KOK1606) oceanographic research cruise in the Northeast Pacific Ocean, averaged at every Niskin bottle trip. The SCOPE-Gradients program is designed to test conceptual and mathematical models of biogeochemical organization across the transition zone between different ecosystems. </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.