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Figure 11 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 11. The body mass dynamics by month of first-year individuals of N. noctula during 2013 in Kharkiv. F – ♀♀, M – ♂♂ (black dot – mean value, line – median value, whiskers – min and max values, open dot – outlier).
Figure 4 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 4. Spatial distributions of records of E. serotinus in Kharkiv. (a) The records in periods from 1 August to 2 December; (b) the records in winter, 1 January to 29 March and from 3 December to 31 December.
Figure 3 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 3. Spatial distributions of four bat species records throughout the year in Kharkiv. NNOC: N. noctula; PKUH: P. kuhlii; VMUR: V. murinus; PAUR: P.auritus.
Figure 10 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 10. The body mass dynamics by month of adult individuals of N. noctula during 2013 in Kharkiv. F – ♀♀, M – ♂♂ (black dot – mean value, line – median value, whiskers – min and max values, open dot – outlier).
Figure 9 in Year-round monitoring of bat records in an urban area: Kharkiv (NE Ukraine), 2013, as a case study
Figure 9. Comparative ratios of the causes of death or significant injury during 2013 in Kharkiv: dir. people – directly killed or injured by people; cas. people – indirectly/casually killed or injured by people; attenuation – death after exhaustion; oil – death after fouling by oil products; cat – killed or injured by a cat; window trap – death as a result of becoming trapped in a window; un – uncertain.
Figure. Food preferences of Chinese mole shrew (Anourosorex squamipes) from an urban area. a, b, c, d. Mean relative consumption along six trials for each food set are shown in a, b, c, d, respectively. (see materials and methods for details on the calculation of relative consumption). in Natural animal food preference of Chinese mole shrew (Anourosorex squamipes) from an urban area: a laboratory study
Figure. Food preferences of Chinese mole shrew (Anourosorex squamipes) from an urban area. a, b, c, d. Mean relative consumption along six trials for each food set are shown in a, b, c, d, respectively. (see materials and methods for details on the calculation of relative consumption).
CHILDHOOD OBESITY IN URBAN AND RURAL INDIA: A SYSTEMATIC REVIEW AND META-ANALYSES OF PREVALENCE STUDIES
<p><strong><span>Background:</span></strong><span> Childhood obesity has become a pressing global public health issue, particularly in low- and middle-income countries like India. This systematic review aims to investigate the prevalence of childhood obesity and its associated risk factors in urban and rural regions of India.</span></p> <p><strong><span>Methods:</span></strong><span> A comprehensive systematic search was conducted in PubMed, Embase, and Scopus databases to identify relevant English-language studies published within the past decade. Inclusion criteria included studies conducted in India, focusing on children and adolescents aged 0-18, and reporting either the prevalence of childhood obesity or related risk factors. Ten studies, comprising both cross-sectional and quantitative research designs, met these criteria.</span></p> <p><strong><span>Results:</span></strong><span> The findings reveal a significant disparity in childhood obesity prevalence between urban and rural areas of India. Urban regions exhibit notably higher rates, with a pooled prevalence estimated at 9.0% (95% CI: 2.0 to 17), compared to 4.0% (95% CI: 4.0 to 5.0) in rural areas. Risk factors associated with childhood obesity in urban settings include unhealthy dietary habits, limited physical activity, higher income levels, parental education, and attendance at private schools. In rural areas, gender, age, and household size emerged as potential risk factors.</span></p> <p><strong><span>Discussion:</span></strong><span> These findings underscore the urgent need for geographically tailored interventions to address the urban-rural disparities in childhood obesity. Lifestyle-oriented strategies promoting healthier dietary patterns and increased physical activity are essential. Gender-inclusive programs targeting both boys and girls are crucial. Future research should consider regional and cultural diversity to design more effective public health responses.</span></p> <p><strong><span>Conclusion:</span></strong><span> This systematic review provides valuable insights into the prevalence and risk factors of childhood obesity in India. It highlights the necessity for customized interventions and lifestyle adjustments to combat this escalating public health challenge and reduce disparities in health outcomes.</span></p>
Experimental and numerical study of the effect of model geometric distortion on laboratory modelling of urban flooding
<p>The supporting datasets includes: </p> <p>(1) All the figures in the manuscript in .fig format (in case possible)</p> <p>- Figures in main text</p> <p>- Figure in Support Information</p> <p>(2) Datasets for generating the main outcomes of the manuscript</p> <p>- two files that explain detailed data content in three structure</p> <p>- 3 sub-repositories which contains the results for the three models</p> <p>- one repository contains the data for Figure 8</p> <p> </p>
Fig. 3 in Lymnaeid snails in the city of Salzburg - A malacological and ecological study in the urban area
Fig. 3: Global Marginality Coefficient (GMC; a) and Global Tolerance Coefficient (GTC; b) modeled for the different environmental parameters (Abbreviations: see Table 1).
Fig. 1 in Lymnaeid snails in the city of Salzburg - A malacological and ecological study in the urban area
Fig. 1: Geographic map of the city of Salzburg with all sample locations investigated for the possible colonization by pond snails.
Fig. 2 in Lymnaeid snails in the city of Salzburg - A malacological and ecological study in the urban area
Fig. 2: Urban distribution maps computed for Radix labiata (a) and R. balthica (b). The first gastropod species could be collected at 68% of all sample locations, whereas the second one was restricted to 62% of the studied sites.
Analyzing Satellite-Derived 3D Building Inventories and Quantifying Urban Growth towards Active Faults: A Case Study of Bishkek, Kyrgyzstan
<p>#############################################################################################################<br> Datasets supporting the publication:<br> Analyzing satellite-derived 3D building inventories and quantifying urban growth towards active faults:<br> a case study of Bishkek, Kyrgyzstan.<br> <a href="https://doi.org/10.3390/rs14225790">https://doi.org/10.3390/rs14225790</a></p> <p>-Please refer to the publication for details on the production of each dataset.<br> -Datasets are ordered following the publication figures.<br> -Please cite the publication and this dataset repository when using the data.<br> #############################################################################################################</p> <p>------------------------<br> Structure:<br> File ID<br> -[fields:] description<br> ------------------------</p> <p>KH9_1979_builtup.shp<br> -KH9 1979 built-up area classification</p> <p>S2_2021_builtup.tif<br> -Sentinel-2 2021 built-up area classification.</p> <p>S2_2021_corine_land_cover_class.tif<br> -Sentinel-2 2021 land cover classification in Corine 2018 land-cover classes.</p> <p>S2_KH9_DN_change_aggregated.shp<br> -Proportional DN change aggregated to a 1 km^2 grid for areas ≥50% built-up.</p> <p>building_characteristics.shp<br> -build_count: building count in 500 m square grid cell.<br> -mean_area: mean building size (m^2) in 500 m square grid cell.<br> -median_area: median building size(m^2) in 500 m square grid cell.<br> -cell_coverage: %building coverage of 500 m square grid cell.</p> <p>pleiades_buildings_all.shp<br> -All building detections from Pleiades data. Confidence values are output from the deep learning model.</p> <p>pleiades_buildings_heights.shp<br> -Building detections from the Pleiades data that were allocated heights (m).<br> -Zmean, Zmedian,... refer to heights (m)</p> <p>wv2_buildings_all.shp<br> -All building detections from WorldView-2 data. Confidence values are output from the deep learning model.</p> <p>wv2_buildings_heights.shp<br> -Building detections from the WorldView-2 data that were allocated heights (m).<br> -Zmean, Zmedian,... refer to heights (m)</p> <p>trained_rcnn.zip<br> -ArcGIS Pro deep learning model (DLPK) used to extract building footprints.</p>
Fig. 1 in Nest Entry Shape Change May Cause Nest Abandonment In Urban Cavity-Nesting Species: A Case Study Of The Tree Sparrow Passer Montanus
Fig. 1. Location of the study area (left) and examples of Tree Sparrow nests at the study sites (right). Site 1: Agricultural Practical Training Center, Chonnam National University,
Data from: Assessing the contributions of intraspecific and environmental sources of infection in urban wildlife: Salmonella enterica and white ibis as a case study
Open the record for dataset details and reuse information.
Stocks of paracetamol products stored in urban New Zealand households: A cross-sectional study
<p><b>Background</b></p> <p>Intentional self-harm is a common cause of hospital presentations in New Zealand and across the world, and self-poisoning is the most common method of self-harm. Paracetamol (acetaminophen) is frequently used in impulsive intentional overdoses, where ease of access may determine the choice of substance.</p> <p><b>Objective</b></p> <p>This cross-sectional study aimed to determine how much paracetamol is present and therefore accessible in urban New Zealand households, and sources from where it has been obtained. This information is not currently available through any other means, but could inform New Zealand drug policy on access to paracetamol.</p> <p><b>Methods</b></p> <p>Random cluster-sampling of households was performed in major urban areas of two cities in New Zealand, and the paracetamol-containing products, quantities, and sources were recorded. Population estimates of proportions of various types of paracetamol products were calculated.</p> <p><b>Results</b></p> <p>A total of 174 of the 201 study households (86.6%) had at least one paracetamol product. Study households had mostly prescription products (78.2% of total mass), and a median of 24.0 g paracetamol present per household (inter-quartile range 6.0-54.0 g). Prescribed paracetamol was the main source of large stock. Based on the study findings, 53% of New Zealand households had 30 g or more paracetamol present, and 36% had 30 g or more of prescribed paracetamol, specifically.</p> <p><b>Conclusions</b></p> <p>This study highlights the importance of assessing whether and how much paracetamol is truly needed when prescribing and dispensing it. Convenience of appropriate access to therapeutic paracetamol needs to be balanced with preventing unnecessary accumulation of paracetamol stocks in households and inappropriate access to it. Prescribers and pharmacists need to be aware of the risks of such accumulation and assess the therapeutic needs of their patients. Public initiatives should be rolled out at regular intervals to encourage people to return unused or expired medicines to pharmacies for safe disposal.</p>
Datasets of studying Isoprene oxidation in urban and suburban areas
<p>Observational dataset including functionalized isoprene oxidation products, VOCs, trace gases, MET and organic aerosol composition measured at SORPES, Nanjing (118.9E,32.1N) and ECUST, Shanghai (121.5E,30.9N) during summer of 2018. The measurement period is July 13th- August 9th and June 21th-June 26th, respectively. The isoprene functionalized oxidation products were measured by NO3- CI-API-TOF, VOCs were measured by PTR-TOF-MS and ogrganic aerosol composition was measured by TOF-ACSM.</p>
Enhancement of cloud-to-ground lightning activity caused by the urban effect: a case study in the Beijing metropolitan area
<p>The dataset here includes land-surface temperature, wind field, precipitation, UV aerosol index, and lightning information analyzed in the paper "<strong>Enhancement of cloud-to-ground lightning activity </strong><strong>caused by the urban effect: a case study in</strong> <strong>the Beijing metropolitan area</strong>".</p>
Data: Exploring the Drivers and Dynamics of Urban Waters: A Case Study of Wuhan from 1980 to 2060
<p>The dataset comprises three main folders: "lulc," "factors," and "results."</p> <p><span>1. </span><strong><span>lulc (Land Use/Land Cover)</span></strong>: This folder contains raster data spanning from 1980 to 2020, representing land use and land cover dynamics. The data is stored in TIFF format, with values ranging from 1 to 6 denoting different land cover classes: farmland (1), woodland (2), grassland (3), waters (4), settlements (5), and unused land (6).</p> <p><span>2. </span><strong><span>factors</span></strong>: This folder includes various driving factors influencing water dynamics. It encompasses eleven raster datasets, including Digital Elevation Models (DEM), annual precipitation data, and other relevant variables. The temporal coverage of these factors spans from 1980 to 2020. Additionally, demographic factors such as population data and economic indicators like GDP are available, covering the period from the 1990s to 2020. All datasets are stored in TIFF format with a spatial resolution of 30 meters.</p> <p><span>3. </span><strong><span>results</span></strong>: This folder contains the outcomes of the analysis conducted using the PLUS (Patch Landscape and Urban Growth Model) framework. The results include outputs from the Landscape Ecological Assessment Protocol (LEAP) and the Cellular Automata for Regional Simulation (CARS) modeling. These results offer insights into the spatial and temporal patterns of water dynamics in the study area.</p> <p>The data structure follows a systematic organization to facilitate access and analysis. Each folder contains raster datasets stored in TIFF format, ensuring compatibility and ease of use with common GIS software. The temporal consistency of the datasets allows for longitudinal analysis of water dynamics, while the inclusion of various driving factors provides a comprehensive understanding of the underlying processes. Overall, this dataset offers valuable insights into land-water interactions and their implications for urban planning and water resource management strategies.</p>
SESMG model scenarios of the study "Indicators for the optimization of sustainable urban energy systems based on energy system modeling"
<p>This folder contains the model scenarios belonging to the publication "<strong>Indicators for the optimization of sustainable urban energy systems based on energy system modeling</strong>" (<a href="https://doi.org/10.1186/s13705-021-00323-3">https://doi.org/10.1186/s13705-021-00323-3</a>).</p> <p>The individual scenarios can be executed and evaluated with the <strong>Spreadsheet Energy System Model Generator (<a href="https://github.com/chrklemm/SESMG">SESMG</a>)</strong> <a href="https://doi.org/10.5281/zenodo.5412027">v0.0.4</a>, respectively <a href="https://doi.org/10.5281/zenodo.5520513">v0.2.0</a>.</p> <p>The file names are to be understood as follows:</p> <p><em>"scenario name"_"(dispatch) optimization criterion"_"scenario concretization"_"further scenario concretization"_"associated program version"</em>.xlsx.</p> <p>For example, the title name "<em>Scenario3_C_4MW_Biogas_SESMGv0.0.4.xlsx</em>" contains the following information:<br> - This file belongs to scenario 3 (see main publication for details).<br> - Dispatch optimized according to energy costs C (see main publication for details).<br> - The scenario contains 4 MW biogas CHP capacity (see main publication for details)<br> - The scenario is to be executed with SESMG version v0.0.4.</p> <p>Another example. The title name "<em>optimization_C_80PercentDemand_70PercentEmissions_SESMGv0.1.1.xlsx</em>" contains the following information:<br> - This file belongs to the optimization scenario (see main publication for details).<br> - The primary optimization criterion is energy costs C (see main publication for details).<br> - Energy demand was capped at 80 percent and emissions at 70 percent of baseline (see main publication for details)<br> - The scenario is to be executed with SESMG version v0.1.1.<br> </p> <p><strong>Acknowledgements:</strong></p> <p>The authors would like to thank Prof. Dr. Peter Vennemann (Münster University of Applied Sciences) for the constructive discussion regarding this article. This research has been conducted within the R2Q project, funded by the German Federal Ministry of Education and Research (BMBF) - grant number 033W102A and the junior research group energy sufficiency funded by the German Federal Ministry of Education and Research (BMBF) as part of its Social-Ecological Research funding priority, funding number 01UU2004A. </p>
Dataset used in the study "Residential buildings real estate values linked to summer surface thermal anomaly patterns and urban features: the Florence (Italy) case study."
<p>This dataset repository includes eight raster layers (Reference System EPSG:3035 - ETRS89-extended / LAEA Europe), used in the study "Residential buildings real estate values linked to summer surface thermal anomaly patterns and urban features: the Florence (Italy) case study", and obtained by the adaptation of analyses carried out by previous studies (Morabito et al., 2021; Guerri et al., 2021; 2022).</p> <p>Further information regarding the source, study period, and horizontal resolution is available in the attached text file. </p> <p> </p> <p><strong><em>References</em></strong></p> <p>Guerri, G., Crisci, A., Congedo, L., Munafò, M., Morabito, M., <strong>2022</strong>. A functional seasonal thermal hot-spot classification: Focus on industrial sites. Science of The Total Environment 806, 151383.<a href="http://https://doi.org/10.1016/j.scitotenv.2021.151383"> https://doi.org/10.1016/j.scitotenv.2021.151383</a>.</p> <p>Guerri, G., Crisci, A., Messeri, A., Congedo, L., Munafò, M., Morabito, M., <strong>2021</strong>. Thermal Summer Diurnal Hot-Spot Analysis: The Role of Local Urban Features Layers. Remote Sensing 13, 538. <a href="https://doi.org/10.3390/rs13030538">https://doi.org/10.3390/rs13030538</a>.</p> <p>Morabito, M., Crisci, A., Guerri, G., Messeri, A., Congedo, L., Munafò, M., <strong>2021</strong>. Surface Urban Heat Islands in Italian Metropolitan Cities: Tree Cover and Impervious Surface Influences. Science of The Total Environment 751, 142334. <a href="https://doi.org/10.1016/j.scitotenv.2020.142334">https://doi.org/10.1016/j.scitotenv.2020.142334</a>.</p>
ScienceDex guides
Understand access before you commit
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.