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36 results for “London, UK”
Prevalence, severity, and risk factors of disability among adults living with HIV accessing routine outpatient HIV care in London, United Kingdom (UK): A cross-sectional self-report study
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FIGURE 3. Phobaeticus chani female holotype, body length 357 in The types of Phasmida in the Natural History Museum, London, UK
FIGURE 3. Phobaeticus chani female holotype, body length 357 mm.
FIGURE 4 in The types of Phasmida in the Natural History Museum, London, UK
FIGURE 4. Phyllium telnovi male holotype.
urbisphere_gb-london_UR-7: Gridded total road lengths by type for London, UK
<h2>Files in this Archive </h2> <ul> <li>London_road_lengths_by_type.zip <ul> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> <li>Total road lengths by road type (all lanes and traffic flow directions) in 500-m grid-boxes covering Greater London, UK</li> </ul> </li> <li>code.zip <ul> <li>Python3</li> <li>Process input road data in 500-m grid-boxes covering Greater London, UK </li> </ul> </li> <li>urbisphere_gb-london_UR-7.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support urbisphere–London modelling activities, including the generation of a travel route database for private vehicle transport on roads.</p> <h3>Linked with</h3> <ul> <li>McGrory et al. 2024. urbisphere_gb-london_UR-3: Transport database derived from UK road networks, OSM data, and TfL public transport timetables, for modelling in London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889780</li> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-6: Gridded building information for London, UK
<h2>Files in this archive </h2> <ul> <li>London_sample_region_building_info.zip <ul> <li>Gridded building volume and population information in 500-m processing grids for a sample region in central London</li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>auxiliary_data.zip <ul> <li>Auxiliary data for processing (*.csv)</li> </ul> </li> <li>code.zip <ul> <li>Process building data in 500-m grid-boxes covering London (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-6.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities for London, UK.</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-5: Gridded land-cover fractions for London, UK
<h2>Files in this archive </h2> <ul> <li>London_landcover.zip <ul> <li>Land-cover fractions in 500-m grid boxes covering Greater London, UK</li> <li>Polygons, ESRI shapefiles (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>code.zip <ul> <li>Code to process land cover (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-5.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities, including simulations with the Surface Urban Energy and Water Balance Scheme (<a href="https://suews.readthedocs.io/en/latest/">SUEWS</a>).</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10889756</li> </ul>
urbisphere_gb-london_UR-1: Processing and modelling grid of 500-m horizontal resolution for London, UK
<h2>Files in this archive </h2> <ul> <li>London_500m_grid.zip <ul> <li>Grid with ~500 m horizontal resolution, covering Greater London, UK </li> <li>Polygons, ESRI shapefile format (*.shp, *.shx, *.cpg, *.dbf, *.prj)</li> </ul> </li> <li>code.zip <ul> <li>Code to produce the dataset (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-1.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>This dataset includes a grid with ~500 m horizontal resolution covering Greater London, UK. It is used to support <em>urbisphere</em>–London, APex and ASSURE modelling activities and analyses of socio-economic data. </p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024a. urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024b. urbisphere_presentations_UR-2: Connecting physical and socio-economic spaces for urban agent-based modelling, EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889885</li> <li>McGrory et al. 2024. urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation]. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul>
urbisphere_gb-london_UR-2: Activities profiles derived from UK Time Use Survey data for modelling
<h2>Files in this archive </h2> <ul> <li>UK_TUS2014-15_activity_profiles_190324.zip <ul> <li>Activity profile dataset derived from the UK Time Use Survey (2014/15; *.csv) </li> </ul> </li> <li>auxiliary_data.zip <ul> <li>Auxiliary datasets created for processing</li> </ul> </li> <li>AppliancePowerManufacturer.zip <ul> <li>Information used to assigned values</li> </ul> </li> <li>code.zip <ul> <li>Code to produce the dataset</li> <li>Python3.9 Jupyter notebook</li> </ul> </li> <li>urbisphere_gb-london_UR-2.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>People’s activities change through the day and between days. Information about human behaviour and the changing locations where activities occur are used in neighbourhood scale agent-based models of anthropogenic heat fluxes and building scale energy modelling to give realistic occupancy and activity-based energy-use timings.</p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024a: urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024b: urbisphere_presentations_UR-2: Connecting physical and socio-economic spaces for urban agent-based modelling, EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889885</li> <li>McGrory et al. 2024: urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation]. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul>
urbisphere_gb-london_UR-3: Transport database derived from UK road networks, OSM, and TfL public transport timetables, for modelling in London, UK
<h2><strong>Files included in this archive</strong></h2> <p><strong>Documentation</strong></p> <ul> <li> urbisphere_London_transport_database.pdf</li> </ul> <p><strong>JSON Database files</strong> (JSON: <a href="https://www.loc.gov/preservation/digital/formats/fdd/fdd000381.shtml">https://www.loc.gov/preservation/digital/formats/fdd/fdd000381.shtml</a> (<em>last accessed: 30/3/2024</em>))</p> <ul> <li>driving_transport.json <ul> <li>Database of driving routes</li> </ul> </li> <li>cycling_transport.json <ul> <li>Database of cycling routes</li> </ul> </li> <li>walking_transport.json <ul> <li>Database of walking routes</li> </ul> </li> <li>public_transport.json <ul> <li>Database of public transport routes</li> </ul> </li> </ul> <p><strong>Python 3.9 Code</strong></p> <ul> <li>London_travel_dictionaries.py <ul> <li>to create databases</li> </ul> </li> <li>assign_speed_limits.py <ul> <li> to assign OSM speed limits to each road in GLA</li> </ul> </li> <li>reduce_sub_services.py <ul> <li> to group transport routes within the TfL timetables</li> </ul> </li> </ul> <h2>Data purpose</h2> <p>This dataset contains transport routes for walking, driving, cycling, and public transport (train, tube, and bus) within the Greater London (GLA), which can be used for simulations of human behaviour and movement, for example using agent-based models (e.g. Capel-Timms et al. 2021, McGrory et al. 2024b).</p> <h3><em>Associated publications</em></h3> <ul> <li>Hertwig et al. 2024b: urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> <li>Hertwig et al. 2024c: urbisphere_gb-london_UR-7: Gridded total road lengths by type for London, UK. urbisphere–London Data Release and Technical Documentation [Dataset].. Zenodo. https://doi.org/10.5281/zenodo.10889841</li> <li>McGrory et al. 2024a: urbisphere_presentations_UR-3: Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): An agent-based model for heat and exposure to other anthropogenic emissions. EMS Annual Meeting 2023 [Presentation].. Zenodo. https://doi.org/10.5281/zenodo.10889900</li> </ul> <div> <div> </div> <div> <p> </p> </div> </div>
Multi-scale harmonisation Across Physical and Socio-Economic Characteristics of a City region (MAPSECC): London, UK
<p>A new methodology and comprehensive database (<strong>M</strong>ulti-scale harmonisation <strong>A</strong>cross <strong>P</strong>hysical and <strong>S</strong>ocio-<strong>E</strong>conomic<strong> C</strong>haracteristics of a<strong> C</strong>ity region, <strong>MAPSECC</strong>) is developed that connects physical characteristics of a city (building morphology and materials, land-surface cover) with socio-economic aspects (building function, microenvironments of activity, urban transport infrastructure, residential and workplace populations, human activities), and is demonstrated for London, UK (<strong>MAPSECC: London</strong>). The database fulfils input requirements for dynamic and multi-scale urban modelling approaches. Dataset components combine and harmonise information from primary sources (often government agencies) through novel downscaling and aggregation methods to give a traceable, repeatable methodology. Further details about the processing and methodology can be found here:</p> <ul> <li><span>Hertwig, D., McGrory, M., Paskin, M., Liu, Y., Piano, S.L., Llanwarne, H., Smith, S.T. and Grimmond, S. (2025), Connecting Physical and Socio-Economic Spaces for Multi-Scale Urban Modelling: A Dataset for London. Geoscience Data Journal 12, e289. </span><a href="https://doi.org/10.1002/gdj3.289">https://doi.org/10.1002/gdj3.289 </a></li> </ul> <p><strong><em>Cite the article above together with the dataset DOI in any publications using MAPSECC: London data.</em></strong></p> <h3>Files in this archive</h3> <ul> <li>Documentation <ul> <li>MAPSECC_London_documentation.pdf</li> </ul> </li> <li>Processing grid <ul> <li>Main dataset: London_500m_grid.zip</li> <li>Code: London_500m_grid_code.zip</li> </ul> </li> <li>Land-cover fractions <ul> <li>Main dataset: London_landcover.zip</li> <li>Auxiliary data: London_landcover_auxiliary.zip</li> <li>Code: London_landcover_code.zip</li> </ul> </li> <li>Building typologies (with population statistics) <ul> <li>Main dataset: Building_typologies.zip</li> <li>Auxiliary data: Building_typologies_auxiliary.zip</li> <li>Code: Building_typologies_code.zip</li> </ul> </li> <li>Building material parameters <ul> <li>Main dataset: Materials_layer_info.zip, Materials_layer_processed.zip, Materials_parameters.zip</li> <li>Code: Materials_code.zip</li> </ul> </li> <li>Human activity profiles <ul> <li>Main dataset: UK_TUS2014-15_activity_profiles.zip</li> <li>Auxiliary data: Activity_profiles_auxiliary.zip</li> <li>Code: Activity_profiles_code.zip</li> </ul> </li> <li>Transport database <ul> <li>Main dataset: London_transport_database.zip</li> <li>Code: London_transport_code.zip</li> </ul> </li> <li>Road lengths by type <ul> <li>Main dataset: London_roads_by_type.zip</li> <li>Auxiliary data: London_roads_auxiliary.zip</li> <li>Code: London_roads_code.zip</li> </ul> </li> <li>Spatial attractors <ul> <li>Main dataset: London_attractors.zip</li> <li>Auxiliary data: London_attractors_auxiliary.zip</li> <li>Code: London_attractors_code.zip</li> </ul> </li> <li>Disclaimer notice <ul> <li>disclaimer_note.txt</li> </ul> </li> </ul>
Cross-Sectional Survey on the Use of Tobacco Products - London (UK)
ClinicalTrials.gov study NCT03527030. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
APPENDIX Individuals included in the genetic and/or skull morphology analyses are presented with source and locality information (reference to sites in Fig. 1 are given in parentheses when available). Voucher numbers are provided for individuals that were collected: AMNH — American Museum of Natural History, New York, NY, USA, BMNH — Natural History Museum, London, UK, FMNH — Field Museum, Chicago, IL, USA, HZM — Harrison Zoological Museum, Kent, UK, MCZ — Museum of Comparative Zoology, Harvard, MA, USA, MZB — Muzeum Zoologicum Bogoriense, Bogor, Indonesia, RMNH — National Museum of Natural History Naturalis, Leiden, Netherlands, SEN — Senckenberg Museum, Frankfurt, Germany, TK — tissue collection and TTU — specimen numbers; Texas Tech. University, Lubbock, TX, USA, and USNM — Smithsonian Institute, Washington D.C., USA. All specimens from peninsular Malaysia with THK or MBCRU field numbers were collected by A. Zubaid, and the specimens or duplicate wing punches were deposited at UKM (Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia). The original taxonomy of type specimens (type) are listed. Haplotypes (Hap) are given for individuals of H. bicolor (=H. bicolor-131) and H. kunzi (=H. bicolor-142). GenBank accession numbers are given for one representative of each unique haplotype in A new species in the Hipposideros bicolor group (Chiroptera: Hipposideridae) from Peninsular Malaysia
APPENDIX Individuals included in the genetic and/or skull morphology analyses are presented with source and locality information (reference to sites in Fig. 1 are given in parentheses when available). Voucher numbers are provided for individuals that were collected: AMNH — American Museum of Natural History, New York, NY, USA, BMNH — Natural History Museum, London, UK, FMNH — Field Museum, Chicago, IL, USA, HZM — Harrison Zoological Museum, Kent, UK, MCZ — Museum of Comparative Zoology, Harvard, MA, USA, MZB — Muzeum Zoologicum Bogoriense, Bogor, Indonesia, RMNH — National Museum of Natural History Naturalis, Leiden, Netherlands, SEN — Senckenberg Museum, Frankfurt, Germany, TK — tissue collection and TTU — specimen numbers; Texas Tech. University, Lubbock, TX, USA, and USNM — Smithsonian Institute, Washington D.C., USA. All specimens from peninsular Malaysia with THK or MBCRU field numbers were collected by A. Zubaid, and the specimens or duplicate wing punches were deposited at UKM (Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia). The original taxonomy of type specimens (type) are listed. Haplotypes (Hap) are given for individuals of H. bicolor (=H. bicolor-131) and H. kunzi (=H. bicolor-142). GenBank accession numbers are given for one representative of each unique haplotype
The Impact of Community Health Workers on the Uptake of Preventative Care Services in London, UK
ClinicalTrials.gov study NCT06144580. IPD Sharing: NO. Countries: 0. Publications: 0.
Statue of Horatio Nelson, Greenwich, London, UK
Location: https://goo.gl/maps/2wGVo Source: Objaverse 1.0 / Sketchfab
UK-London - Honor Oak Park - Ceilometer - Mixed Layer Height - 2021
<p><strong>Site: </strong>UK- London - Honor Oak Park </p> <p><strong>Data:</strong> Ceilometer - Mixed Layer Height - 2021</p> <p><strong>Year</strong>: 2021</p> <p><strong>Day of Year</strong> 1-139</p> <p><strong>Files format:</strong> netCDF</p> <p><strong>Data processing:</strong></p> <ul> <li>1) Calibrated</li> <li>2) MLH determined - CABAM (Kotthaus and Grimmond 2018; QJRMS)</li> </ul> <p><strong>Metadata documentation:</strong> </p> <ul> <li><a href="https://muhd.readthedocs.io/en/latest/">Multi-City Urban Hydrometeorology Database — MUHD -Multi-city Urban Hydroclimate Data - Meta data for observations 2021-07-23 documentation</a></li> <li>Instrumentation: <a href="https://muhd.readthedocs.io/en/latest/instrument_types/Ceilometer/instIds/CL31.html">3.7.1. CL31 — MUHD 2021-07-20 documentation</a></li> <li>Site :<a href="https://muhd.readthedocs.io/en/latest/networks/LUMA/sites/HOP.html">2.6.12. HOP — MUHD 2021-07-20 documentation</a></li> <li>10.5281/zenodo.5126614</li> </ul>
London, UK - DSM - DEM - CDSM - LC
<p>London</p> <p>1 m resolution DSM digital surface model</p> <p>1 m resolution DEM digital elevation model</p> <p>4 m resolution CDSM canopy DSM</p> <p>LC - land cover</p> <p> </p>
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OpenNeuro
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