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3,030 results for “green”
Joseph R. Green (g2214)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Joseph R. Green<br><u>musiXplora-ID</u>: g2214<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/g2214">https://musixplora.de/mxp/g2214</a><br><u>Gender</u>: m<br><u>First Mentioned</u>: 1916<br><u>Sectors</u>: Instrumentenbau<br><u>Professions (Historical)</u>: Patentinhaber<br><u>Other Places of Activity</u>: Wakefield<br><br><br><u>Patentrecht:</u><br><table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>ErfinderInnen</td><td>Erfinder</td><td>Patentschrift. Keyed Zither. Anmeldedatum</td><td><a href="https://musixplora.de/mxp/5080477">5080477</a></td></tr></tbody></table><br><u>Begriffe:</u><br><table><tbody><tr></tr><tr><td>Related</td><td></td><td>Zither</td><td>2001457</td></tr></tbody></table><br><u>Titel/Medien:</u><br><table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Patent US 1299704</td><td>Patentschrift. Keyed Zither. Anmeldedatum</td><td><a href="https://musixplora.de/mxp/5080477">5080477</a></td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Survey data on behaviours and attitudes towards green food consumption of participants of the SmartFood Urban Living Lab in Warsaw, Poland
<p>In this dataset, we present raw data of a survey on behaviours and attitudes towards green food consumption, conducted between June 2023 and April 2024 among a group of 21 households from Warsaw, participating in a SmartFood Urban Living Lab (ULL). The dataset is complemented with results collected from two control groups. The SmartFood Urban Living Lab was an intervention aimed at providing residents of urban blocks of flats with a novel technology for growing their own food. The ULL served as an experimental ground for testing and refining innovations such as hydroponic cabins, rainwater management systems, solar energy systems, and insect farming units. Residents actively participated in the lab, providing valuable insights into the practical challenges and benefits of urban farming, which helped refine and adapt the technologies for broader application. After each month of the intervention, a survey was conducted to check participants' behaviours and attitudes towards green food consumption</p>
A FIELD STUDY ON THERMAL INSULATION PERFORMANCE OF GREEN ROOF FOR BUILDINGS IN HOT DRY CLIMATE OF ZARIA, NIGERIA
<p>Although the practice of employing the use of green roof for thermal insulation is gaining a wideranging acceptance across the globe, its use in Nigeria and the sub Saharan Africa has remained unpopular. Study has shown that, although a vast literature on different approaches in the application of green roof system exists, there is substantial misrepresentation of inferences regarding its applications in Nigeria. The purpose of the study therefore, is to assess the thermal performance of green roof in facilitating thermal insulation for building interiors of hot dry climate in Nigeria. The study is carried out through an empirical field observation in the premises of Ahmadu Bello University Zaria, Nigeria. Two miniature live models were built and covered with galvanised iron roofing sheets on timber trusses; one of which was covered with green roof, while the other was left bare. This is with the view to determine the rate of thermal insulation a green roof system can offer over the bare roof in the building interiors of the study area. Using the experimental approach in green roof investigation, a data logging system was installed in the two thermal zones and readings of the temperature profile was taken. The results showed that; a reduction of 2.08°C in indoor air temperature was obtained on the diurnal ranges, while 19.78% of temperature fluctuation was achieved. Generally, the result showed that higher temperature ranges were recorded in the bare roofed case than the green roof. The maximum, mean and minimum record for the bare roof was 45.20°C, 32.03°C and 21.10°C respectively; while the recorded values for the green roof were 41.90°C, 29.95°C, and 21.00°C respectively. This implies that, the presence of vegetation on the green roofed case has offered a degree of thermal insulation required to achieve better passive cooling in order to attain thermal comfort in the interiors of the study area.</p>
RAKSILA 3D. Laser scanning survey of the street fronts and green areas in Raksila, Oulu (FINLAND)
<p>The video shows the preliminary results of the laser scanner survey of Raksila district in Oulu, Finland. Raksila is an important historical trace in the development of the urban planning of the city of Oulu. The district of Raksila is mainly a well-preserved residential Neighborhood characterized by a strong typicality.The general plan consists of a regular structure and a system of street fronts on the road are ordered and in an homogeneous profile. Despite this, Raksila still has no detailed and updated guidelines capable of managing all different types of interventions allowed (renovation, restoration, repair actions, possible modifications). For this reason, a laser scanner survey and detailed documentation have been created, through which all the elements and characteristics of the place have been defined and collected in sort of atlas and inventory reports. This new documentation is going to constitute the base for the definition of new guidelines, a practical support and analysis for future interventions that can be carried out in total respect of this heritage. This topic is inserted as case study for developing the Research Project n. 746215 entitled "Preserving Wooden Heritage". The project is financed by the European Commission with an Individual Marie S. Curie Fellowship assigned to PostDoctoral Researcher Sara Porzilli, who is working at the University of Oulu - Finland.</p>
Open Access levels of Dutch universities' output 2016-2017 (articles & reviews): green, gold, hybrid and bronze - May 2018
<p>Using Web of Science and Unpaywall data, we here provide an update of Open Access (OA) levels of Dutch universities, for 2016 and 2017.</p> <p>Our previous analysis (<a href="http://doi.org/10.5281/zenodo.1133759">10.5281/zenodo.1133759</a> and <a href="http://doi.org/10.7287/peerj.preprints.3520v1">10.7287/peerj.preprints.3520v1</a>) looked at OA classification as included in Web of Science (gold and green OA, based on Unpaywall data), and supplemented that with a breakdown of gold OA into pure gold, hybrid and bronze, taken from Unpaywall data (formerly OADOI) directly. Here, we improve on this by running all DOIs retrieved from WoS through Unpaywall data (using their web interface that allows batch checking of up to 10,000 DOIs at a time). Unlike WoS, Unpaywall data itself includes author-submitted versions in their green OA classification, resulting in more complete green OA levels. </p> <p>In addition, since our initial analysis of December 2017, Unpaywall data has considerably expanded its coverage of institutional repositories (IRs) (see <a href="https://unpaywall.org/sources">https://unpaywall.org/sources</a>). This now includes coverage of the IRs from all Dutch universities. </p> <p>Taken together, the current data show higher levels of green open access, including author-submitted versions, compared to our previous analysis. </p> <p>In this update, we include output (articles and reviews) from 2016 and 2017 for all 14 universities in the Netherlands. </p> <p>The following categories are distinguished (description taken from Piwowar at al., 2018, doi: <a href="https://doi.org/10.7717/peerj.4375">10.7717/peerj.4375</a>)</p> <ul> <li><strong>Pure gold</strong>: Published in an open-access journal (as defined by the DOAJ)</li> <li><strong>Hybrid</strong>: Free under an open license in a toll-access journal</li> <li><strong>Bronze</strong>: Free to read on the publisher page, but without a license</li> <li><strong>Green: </strong>Available from an institutional or disciplinary repository (including PubMedCentral)</li> </ul> <p>Data for Dutch universities were collected from Web of Science using the organization-enhanced field. Only articles and reviews were included. DOIs were extracted from the Web of Science export, run through the Unpaywall data <a href="https://unpaywall.org/products/simple-query-tool">Simple Query Tool</a>. From the resulting data from Unpaywall, OA classification was done using a simple formula in Excel (to be replaced by an R script in a future update). The Excel template used is included in this dataset, as is the OADOI API output for each Dutch university's article subset, and the lists of DOIs derived from Web of Science. The dataset also includes summarized data and three charts generated from these data, showing levels of different types of OA for 2016, 2017 and the two years compared. </p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p>
Herbarium specimen image of Nothocalais cuspidata (Pursh) Greene, part of the collection of Botanic Garden and Botanical Museum Berlin
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Agoseris apargioides (Less.) Greene, part of the collection of Botanic Garden and Botanical Museum Berlin
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Phyla lanceolata (Michx.) Greene, part of the collection of Meise Botanic Garden
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Dateset on 'Disentangling associations of human wellbeing with green infrastructure, degree of urbanity, and social factors around an Asian megacity'
<p>The data was collected a part of the baseline survey on household socio-economics among the Bengalurian along the rural-urban interface. </p>
Data for "A promiscuous mechanism to phase separate eukaryotic carbon fixation in the green lineage"
<p>This repository contains all raw data associated with the manuscript:</p> <p>"<em><strong>A promiscuous mechanism to phase separate eukaryotic carbon fixation in the green lineage</strong></em>"</p> <p> </p> <p>The files are organised according to their appearance as figures in the manuscript.</p> <p>Within each of the zipped figure folders is a <strong>_readme.txt</strong> file that contains information about the raw data provided for each figure.</p>
Perceptions of green facades among residents of buildings with and without a greened envelope – Data from a household survey in Leipzig, Germany
<p>The data set stems from a survey of residents in two neighborhoods of Leipzig, Germany, and was implemented in April and May of 2022. The primary aim of the study was to better understand resident perceptions of green facades, including their (perceived) benefits as well as concerns. Additionally, residents were asked for a number of other perceptions, including heat stress, noise and air pollution. The sample includes both residents of buildings with and without an existing green facade.</p> <p>All variables included in this data publication are described in the codebook. The original German language wording of the survey questions can be found in the questionnaire enclosed with the data set. We include responses to all questions from the survey that were close-ended or had a numerical response. Open-ended questions were excluded from this publication for data privacy reasons. </p>
SERENA EJP Soil: Green House Gas Regulation Application Emilia-Romagna, Italy (Summer)
<p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p>
Data, Analytical Code, and Model Outputs From: "Green is the New Black: Outcomes of Post-Fire Tree Planting Across the Interior West, USA"
<p>This archive includes data (locations of tree plantings, one-year survival records, remotely sensed canopy cover change), statistical code, and model outputs from Rodman et al. (2024). For more information on specific information, processing methods, and data formats, see "README.md" or "README.html" files associated with this archive</p>
SERENA EJP Soil Green house gas aplication Moravia region, Czechia
<p>The present dataset corresponds to a map of Net Ecosystem Productivity (NEP) for Moravia region in Czechia classified as wheat by the Eurocrop 2028 spatial product (d’Andrimont et al. 2021). The map is the result of applying the NEP cookbook developed in SERENA/EJP-Soil to the area of interest (AOI) input data. NEP is expressed for a single 8-day period in early summer as it is the date with the highest value. The NEP value is a 2010-2014 average for the particular 8-day period. The data description document of the cookbook (hereafter “GHG cookbook”) itself corresponds to other document of the SERENA project.</p>
Divergent evolution between sister species of European green lizards
<p>Annotation and variant calling files (VCFs, heffas) for <em>L. viridis </em>and<em> L. bilineata.</em> The variants have been called with <em>L. viridis</em> genome as reference.</p>
An Open-Source Automatic Survey of Green Roofs in London using Segmentation of Aerial Imagery: Dataset
<p>This archive contains code and data to go with the paper <em>*An Open-Source Automatic Survey of Green Roofs in London using Segmentation of Aerial Imagery*</em>.</p> <p> </p> <p>This archive contains geospatial data, as well as the code used to generate the geospatial data.</p> <p>The geospatial data consists of georeferenced polygons identifying areas which are covered by green roofs in London (GBR) generated from 2019 aerial imagery.</p> <p>The data is described in detail in the manuscript <em>*An Open-Source Automatic Survey of Green Roofs in London using Segmentation of Aerial Imagery*</em>. See abstract below.</p> <p> </p> <p>GeoJSON format:</p> <p>GeoJSON is a format for encoding geospatial data, see https://geojson.org/.</p> <p>GeoJSON can be read using GIS programs including ArcGIS, QGIS, OGR.</p> <p> </p> <p>Contents:</p> <p>`geospatial_data/buffered_polygons_2021.zip` a zip archive containing a geojson file. It is the estimated locations of green roofs in London in 2021 and is the main result, which can be opened in any GIS program after being unzipped.</p> <p>`geospatial_data/buffered_polygons_2019.zip` a zip archive containing a geojson file. It is the estimated locations of green roofs in London in 2019 and is a secondary result, which can be opened in any GIS program after being unzipped. The predictions were made with the same model as the 2021 results.</p> <p>`geospatial_data/labelled_area.zip` a zip archive containing a geojson file. Identifies the area which was hand-labelled.</p> <p>`geospatial_data/manual_2021.zip` a zip archive containing a geojson file. Manually labelled green roof from 2021 imagery.</p> <p>`geospatial_data/manual_2019.zip` a zip archive containing a geojson file. Manually labelled green roof from 2019 imagery.</p> <p>`segmentation_code` contains the code used to produce the segmentation from the aerial imagery.</p> <p>`analysis_code` contains the code used to produce the plots and tables for the paper.</p> <p> </p> <p>Imagery availability:</p> <p>Unfortunately the aerial imagery and building footprint data cannot be shared directly, as you will require the proper license. Both can be found at [Digimap](https://digimap.edina.ac.uk) provided your institution has the license.</p> <p> </p> <p>Abstract:</p> <p>Green roofs can mitigate heat, increase biodiversity, and attenuate storm water, giving some of the benefits of natural vegetation in an urban context where ground space is scarce. To guide the design of more sustainable and climate resilient buildings and neighbourhoods, there is a need to assess the existing status of green roof coverage and explore the potential for future implementation. Therefore, accurate information on the prevalence and characteristics of existing green roofs is needed, but this information is currently lacking. Segmentation algorithms have been used widely to identify buildings and land cover in aerial imagery. Using a machine-learning algorithm based on U-Net to segment aerial imagery, we surveyed the area and coverage of green roofs in London, producing a geospatial dataset \cite[]{simpson_charles_2022_6861929}. We estimate that there was 0.23 km^2 of green roof in the Central Activities Zone (CAZ) of London, (1.07 km^2) in Inner London, and (1.89 km^2) in Greater London in the year 2021. This corresponds to 2.0% of the total building footprint area in the CAZ, and 1.3% in Inner London. There is a relatively higher concentration of green roofs in the City of London, covering 3.9% of the total building footprint area. Test set accuracy was 0.99, with an f-score of 0.58. When tested against imagery and labels from a different year (2019), the model performed just as well as a model trained on the imagery and labels from that year, showing that the model generalised well between different imagery. We improve on previous studies by including more negative examples in the training data, and by requiring coincidence between vector building footprints and green roof patches. We experimented with different data augmentation methods, and found a small improvement in performance when applying random elastic deformations, colour shifts, gamma adjustments, and rotations to the imagery. The survey covers 1558 km^2 of Greater London, making this the largest open automatic survey of green roofs in any city. The geospatial dataset is at the single-building level, providing a higher level of detail over the larger area compared to what was already available. This dataset will enable future work exploring the potential of green roofs in London and on urban climate modelling.</p>
Data on public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland
<p>A public participatory GIS -survey dataset detailing public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland.</p>
Dataset for Green Transition Policies, Stakeholders and Practices in Albania
<p>This dataset contributed to deliverable 4.2 Regional Mapping Report and shows the Albanian mapping. This report is the second deliverable of WP4 – Measuring and assessing impacts and costs of a just green transition in the WB, of the GreenFORCE project. It was jointly authored by the WB project partners, as well as 2 subcontracted parties from the region.</p> <p>The EU Economic and Investment Plan for the WB includes a green agenda for the WB, with pillars to be pursued for transitioning towards a carbon-neutral economy. Such a shift will surely challenge the economies and societies in the WB. The social and policy context is yet fragile to allow for the development and mass distribution of green transition technologies, while human resources are not prepared and/or are insufficient to produce and implement innovation. Yet, the green transition also paves the way towards new development and resilience opportunities. The research will inform on the readiness/potential of societal actors (industry, academia, policymakers, civic society) to embrace the pathways to transformation, and will propose a framework for continuous monitoring of impacts and costs. The key findings and lessons learnt derived within WP4 will be transferred into the scientific papers and policy briefs (WP 2 & 3) and published under the dissemination events (WP5).</p> <p>Regional mapping is a key task for the research, contributing to initial data gathering and the refinement of the research proposal, and to the sub-question on the identification of sectors and territories affected by the transitions and current progress of transition practices. This is a participatory mapping, engaging local stakeholders and communities to reveal local knowledge. Each WB partner will produce the respective country report, and Co-PLAN will work on the final regional report.</p> <p>This deliverable is the final regional report. It will also include the mapping frame used to conduct the mapping process. The WB partners will do the mapping for their own countries. The PC will subcontract data gathering for the remaining countries. The mapping is done for actors, practices and policies in place, territories upon the level of relevance and potential for engaging in green transition; and sectors. All partners will design the mapping frame, using also knowledge from other mapping processes. The frame will contain the type of information to be collected, the standardisation of data entry, and the tailored instruments to be deployed for accessing information.</p>
Dataset for Green Transition Policies, Stakeholders and Practices in Bosnia and Herzegovina
<p>This dataset contributed to deliverable 4.2 Regional Mapping Report and shows the mapping in Bosnia and Herzegovina. This report is the second deliverable of WP4 – Measuring and assessing impacts and costs of a just green transition in the WB, of the GreenFORCE project. It was jointly authored by the WB project partners, as well as 2 subcontracted parties from the region.</p> <p>The EU Economic and Investment Plan for the WB includes a green agenda for the WB, with pillars to be pursued for transitioning towards a carbon-neutral economy. Such a shift will surely challenge the economies and societies in the WB. The social and policy context is yet fragile to allow for the development and mass distribution of green transition technologies, while human resources are not prepared and/or are insufficient to produce and implement innovation. Yet, the green transition also paves the way towards new development and resilience opportunities. The research will inform on the readiness/potential of societal actors (industry, academia, policymakers, civic society) to embrace the pathways to transformation, and will propose a framework for continuous monitoring of impacts and costs. The key findings and lessons learnt derived within WP4 will be transferred into the scientific papers and policy briefs (WP 2 & 3) and published under the dissemination events (WP5).</p> <p>Regional mapping is a key task for the research, contributing to initial data gathering and the refinement of the research proposal, and to the sub-question on the identification of sectors and territories affected by the transitions and current progress of transition practices. This is a participatory mapping, engaging local stakeholders and communities to reveal local knowledge. Each WB partner will produce the respective country report, and Co-PLAN will work on the final regional report.</p> <p>This deliverable is the final regional report. It will also include the mapping frame used to conduct the mapping process. The WB partners will do the mapping for their own countries. GreenFORCE will subcontract data gathering for the remaining countries. The mapping is done for actors, practices and policies in place, territories upon the level of relevance and potential for engaging in green transition; and sectors. All partners will design the mapping frame, using also knowledge from other mapping processes. The frame will contain the type of information to be collected, the standardisation of data entry, and the tailored instruments to be deployed for accessing information.</p> <p> </p>
Dataset for Green Transition Policies, Stakeholders and Practices in Montenegro
<p>This dataset contributed to deliverable 4.2 Regional Mapping Report and shows the Montenegrin mapping. This report is the second deliverable of WP4 – Measuring and assessing impacts and costs of a just green transition in the WB, of the GreenFORCE project. It was jointly authored by the WB project partners, as well as 2 subcontracted parties from the region.</p> <p>The EU Economic and Investment Plan for the WB includes a green agenda for the WB, with pillars to be pursued for transitioning towards a carbon-neutral economy. Such a shift will surely challenge the economies and societies in the WB. The social and policy context is yet fragile to allow for the development and mass distribution of green transition technologies, while human resources are not prepared and/or are insufficient to produce and implement innovation. Yet, the green transition also paves the way towards new development and resilience opportunities. The research will inform on the readiness/potential of societal actors (industry, academia, policymakers, civic society) to embrace the pathways to transformation, and will propose a framework for continuous monitoring of impacts and costs. The key findings and lessons learnt derived within WP4 will be transferred into the scientific papers and policy briefs (WP 2 & 3) and published under the dissemination events (WP5).</p> <p>Regional mapping is a key task for the research, contributing to initial data gathering and the refinement of the research proposal, and to the sub-question on the identification of sectors and territories affected by the transitions and current progress of transition practices. This is a participatory mapping, engaging local stakeholders and communities to reveal local knowledge. Each WB partner will produce the respective country report, and Co-PLAN will work on the final regional report.</p> <p>This deliverable is the final regional report. It will also include the mapping frame used to conduct the mapping process. The WB partners will do the mapping for their own countries. The PC will subcontract data gathering for the remaining countries. The mapping is done for actors, practices and policies in place, territories upon the level of relevance and potential for engaging in green transition; and sectors. All partners will design the mapping frame, using also knowledge from other mapping processes. The frame will contain the type of information to be collected, the standardisation of data entry, and the tailored instruments to be deployed for accessing information.</p>
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.