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224 results for “environmental impacts”
Global analysis of the impact of environmental perturbation on cis-regulation of gene expression: control and variety of treatments, 2hr and 24hr
GEO Series GSE21727. Homo sapiens. 48 samples. Type: Expression profiling by array.
Rv0500A is a transcription factor that links Mycobacterium tuberculosis environmental response with division and impacts host colonization
GEO Series GSE194262. Mycobacterium tuberculosis. 12 samples. Type: Expression profiling by high throughput sequencing.
Environmental Stressors Impact Placentation Through Actions On Trophoblast, Immune, and Endothelial Cell Dynamics
GEO Series GSE178407. Rattus norvegicus. 4 samples. Type: Expression profiling by high throughput sequencing.
GIS Data and Analysis for Cooling Demand and Environmental Impact in The Hague
<p>This dataset contains raw GIS data sourced from the BAG (<i>Basisregistratie Adressen en Gebouwen</i>; Registry of Addresses and Buildings). It provides comprehensive information on buildings, including advanced height data and administrative details. It also contains geographic divisions within The Hague. Additionally, the dataset incorporates energy label data, offering insights into the energy efficiency and performance of these buildings. This combined dataset serves as the backbone of a Master's thesis in Industrial Ecology, analysing residential and office cooling and its environmental impacts in The Hague, Netherlands. The codebase of this analysis can be found in this Github repository: <a href="https://github.com/simonvanlierde/msc-thesis-ie"><strong>https://github.com/simonvanlierde/msc-thesis-ie</strong></a></p><p>The dataset includes a background research spreadsheet containing supporting calculations. It also presents geopackages with results from the cooling demand model (CDM) for various scenarios: Status quo (SQ), 2030, and 2050 scenarios (Low, Medium, and High)</p><h3>Background research data</h3><p>The <i>background_research_data.xlsx</i><strong> </strong>spreadsheet contains comprehensive background research calculations supporting the shaping of input parameters used in the model. It contains several sheets:</p><ul><li><strong>Cooling Technologies</strong>: Details the various cooling technologies examined in the study, summarizing their characteristics and the market penetration mixes used in the analysis.</li><li><strong>LCA Results of Ventilation Systems</strong>: Provides an overview of the ecoinvent processes serving as proxies for the life-cycle impacts of cooling equipment, along with calculations of the weight of cooling systems and contribution tables from the LCA-based assessment.</li><li><strong>Material Scarcity</strong>: A detailed examination of the critical raw material content in the material footprint of ecoinvent processes, representing cooling equipment.</li><li><strong>Heat Plans per Neighbourhood</strong>: Forecasts of future heating solutions for each neighbourhood in The Hague.</li><li><strong>Building Stock</strong>: Analysis of the projected growth trends in residential and office building stocks in The Hague. AC Market: Market analysis covering air conditioner sales in the Netherlands from 2002 to 2022.</li><li><strong>Climate Change</strong>: Computations of climate-related parameters based on KNMI climate scenarios.</li><li><strong>Electricity Mix Analysis</strong>: Analysis of future projections for the Dutch electricity grid and calculations of life-cycle carbon intensities of the grid.</li></ul><h3>Input data</h3><p><strong>Geographic divisions</strong></p><ul><li>The outline of The Hague municipality through the Municipal boundaries (<i>Gemeenten</i>) layer, sourced from the <a href="http://www.pdok.nl/geo-services/-/article/bestuurlijke-gebieden">Administrative boundaries (<i>Bestuurlijke Gemeenten</i>) dataset</a> on the PDOK WFS service.</li><li>District (<i>Wijken</i>) and Neighbourhood (<i>Buurten</i>) layers were downloaded from the PDOK WFS service (from the <a href="https://www.pdok.nl/geo-services/-/article/cbs-wijken-en-buurten#df0df8fa1c3bab1a71a2f09d990abd7e"><i>CBS Wijken en Buurten 2022</i></a><i> </i>data package) and clipped to the outline of The Hague.</li><li>The 4-digit postcodes layer was downloaded from PDOK WFS service (<a href="http://www.pdok.nl/ogc-webservices/-/article/cbs-postcode4"><i>CBS Postcode4 statistieken 2020</i></a>) and clipped to The Hague's outline. The postcodes within The Hague were subsequently stored in a csv file.</li><li>The census block layer was downloaded from the PDOK WFS service (from the <a href="http://www.pdok.nl/introductie/-/article/cbs-vierkantstatistieken-100m"><i>CBS Vierkantstatistieken 100m 2021</i></a> data package) and also clipped to the outline of The Hague.</li><li>These layers have been combined in the <i>GeographicDivisions_TheHague</i> GeoPackage.</li></ul><p><strong>BAG data</strong></p><ul><li>BAG data was acquired through the download of a BAG GeoPackage from the BAG <a href="https://www.pdok.nl/downloads/-/article/basisregistratie-adressen-en-gebouwen-ba-1">ATOM download page</a>.</li><li>In the resulting GeoPackage, the Residences (<i>Verblijfsobject</i>) and Building (<i>Pand</i>) layers were clipped to match The Hague's outline.</li><li>The resulting residence data can be found in the <i>BAG_buildings_TheHague</i> GeoPackage.</li></ul><p><strong>3D BAG </strong></p><ul><li>Due to limitations imposed by the PDOK WFS service, which restricts the number of downloadable buildings to 10,000, it was necessary to acquire 145 individual GeoPackages for tiles covering The Hague from the <a href="http://3dbag.nl/nl/download">3D BAG website</a>.</li><li>These GeoPackages were merged using the <i>ogr2ogr</i> <i>append</i> function from the <a href="http://gdal.org/index.html">GDAL library </a>in bash.</li><li>Roof elevation data was extracted from the <i>LoD 1.2 2D</i> layer from the resulting GeoPackage.</li><li>Ground elevation data was obtained from the <i>Pand</i> layer.</li><li>Both of these layers were clipped to match The Hague's outline.</li><li>Roof and ground elevation data from the <i>LoD 1.2 2D</i> and <i>Pand</i> layers were joined to the <i>Pand</i> layer in the BAG dataset using the <i>BAG ID</i> of each building.</li><li>The resulting data can be found in the <i>BAG_buildings_TheHague</i> GeoPackage.</li></ul><p><strong>Energy labels</strong></p><ul><li>Energy labels were downloaded from the <a href="http://www.ep-online.nl/PublicData">Energy label registry</a> (<i>EP-online</i>) and stored in <i>energy_labels_TheNetherlands</i>.<i>csv</i>.</li></ul><p><strong>UHI effect data</strong></p><ul><li>A bitmap with the UHI effect intensity in The Hague was retrieved from the from the <a href="https://www.atlasnatuurlijkkapitaal.nl/kaarten?config=58bf95bc-67bf-402d-a355-af211ad33949&gm-x=121187.11870218973&gm-y=467370.5793842884&gm-z=3.1666666666666665&gm-b=1544180834512,true,1;1554714019959,true,0.8;&activateOnStart=layermanager&deactivateOnStart=layercollection">Dutch Natural Capital Atlas</a> (<i>Atlas Natuurlijk Kapitaal</i>) and stored in <i>UHI_effect_TheHague.tiff</i>.</li></ul><h3>Output data</h3><ul><li>The residence-level data joined to the building layer is contained in the <i>BAG_buildings_with_residence_data_full</i> GeoPackage.</li><li>The results for each building, according to different scenarios, are compiled in the <strong>buildings_with_CDM_results_[scenario]_full</strong> GeoPackages. The scenarios are abbreviated as follows:<ul><li><strong>SQ</strong>: Status Quo, covering the 2018-2022 reference period.</li><li><strong>2030</strong>: An average scenario projected for the year 2030.</li><li><strong>2050_L</strong>: A low-impact, best-case scenario for 2050.</li><li><strong>2050_M</strong>: A medium-impact, moderate scenario for 2050.</li><li><strong>2050_H</strong>: A high-impact, worst-case scenario for 2050.</li></ul></li></ul><p> </p>
Impact of Environmental Award & Financial Performance on Environmental Disclosure Quality: A Case Study of Listed Companies in Pakistan
Open the record for dataset details and reuse information.
Investigating the Impact of Environmental Factors on the Transcriptomics Profile in Healthy Individuals
ClinicalTrials.gov study NCT06040008. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Impact of Fungal Domestic Environmental Exposure on COPD Patients
ClinicalTrials.gov study NCT02318524. IPD Sharing: NO. Countries: 1. Publications: 0.
Inspiration From Eye-tracking Data: Investigating the Impact of Combining Specific Environmental Features and Power Mobility Training
ClinicalTrials.gov study NCT06928077. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study of Procedural Efficiency in EBUS With Dual Versus Single NEEDLEs: Evaluating the Value of a Second Needle in EBUS as it Pertains to Economic and Environmental Impact
ClinicalTrials.gov study NCT07218042. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Impact of Environmental Factors and Metabolomics on Colorectal Cancer.
ClinicalTrials.gov study NCT06643429. IPD Sharing: NO. Countries: 1. Publications: 0.
Impact of Environmental Exposures on Tumor Risk in Subjects at Risk of Hereditary SDHx Paraganglioma
ClinicalTrials.gov study NCT04481152. IPD Sharing: YES. Countries: 0. Publications: 0.
Using Focus Groups to Assess the Impact of Environmental Health Science Programs for K-12 Educational Community
ClinicalTrials.gov study NCT00428402. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Community-Level Daytime Sleepiness: Social-Environmental Determinants, Consequences, and Impact of Sleep Apnea
ClinicalTrials.gov study NCT04176042. IPD Sharing: NO. Countries: 1. Publications: 0.
De Oorzaak: Citizen Science Project on the Impact of Environmental Noise
ClinicalTrials.gov study NCT06466668. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Feasibility, Safety, Cost-effectiveness, and Environmental Impact of Reprocessed Ablation Catheters in PVI
ClinicalTrials.gov study NCT07389434. IPD Sharing: NO. Countries: 1. Publications: 0.
Decreasing Environmental Impact and Costs of Using Inhalational Anesthetic With a Carbon Dioxide Membrane Filter System
ClinicalTrials.gov study NCT04210570. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact of Enhanced Daily Disinfection on Environmental Contamination in Hospital Rooms
ClinicalTrials.gov study NCT05739955. IPD Sharing: NO. Countries: 1. Publications: 0.
Impact of Environmental Factors on Disease Activity in Spondyloarthritis (SPA): Results of the Prospective Co-Env Cohort
ClinicalTrials.gov study NCT01314547. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impact of Ultraviolet Radiation and Environmental Factors on Human Ocular Biomechanics
ClinicalTrials.gov study NCT06993077. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Impact of Environmental Exposures on Tumor Risk in SDHx-mutation Carriers
ClinicalTrials.gov study NCT06408402. IPD Sharing: YES. Countries: 1. Publications: 0.
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.