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2,371 results for “platform”
Characterising underwater noise and changes in harbour porpoise behaviour during the decommissioning of an oil and gas platform
<p>Many man-made marine structures (MMS) will have to be decommissioned in the coming decades. While studies on the impacts of the construction of MMS on marine mammals exist, no research has been done on the effects of their decommissioning. The complete removal of an oil and gas platform in Scotland in 2021 provided an opportunity to investigate the response of harbour porpoises to decommissioning. Arrays of broadband noise recorders and echolocation detectors were used to describe noise characteristics produced by decommissioning activities and assess porpoise behaviour. During decommissioning, sound pressure levels in the frequency range 100 Hz to 10 kHz were 30-40 dB higher than baseline, with the presence of vessels being the main source of noise. The study detected small-scale (< 2 km) and short-term levels of porpoise displacement during decommissioning, with porpoise occurrence increasing immediately after this. These findings can inform the consenting process of future decommissioning projects.</p>
Fig. 3 in Feeding convergence among ray-finned fishes: Teeth of the herbivorous actinopterygians from the latest Permian of East European Platform, Russia
Fig. 3. Comparison of teeth of actinopterygian fish Isadia spp. from the Late Permian of Sokovka, Russia with their Recent equivalents. A, B. Isadia aristoviensis. C–E. Labeotropheus fuelleborni (C from Streelman et al. 2003; D, E from Abertson and Kocher 2006). F, G. Isadia suchonensis. H, J. Monotocheirodon kontos (from Menezes et al. 2013). I. Bryconamericus lethostigmus (from Hirschmann et al. 2017). K, L. Isadia arefievi. M–O. Eretmodus cyanosticus (M from Rüber et al. 1999; N, O from Boulenger 1915). Not to scale.
Fig. 2 in Feeding convergence among ray-finned fishes: Teeth of the herbivorous actinopterygians from the latest Permian of East European Platform, Russia
Fig. 2. The isolated teeth of actinopterygian fish Isadia from the Sokovka outcrop, Vyazniki, Russia, late Permian (Upper Vyatkian). A–D. Isadia aristoviensis Minikh, 1990, mandibulary teeth. A. ZPAL V.51/1, lingual view. B. ZPAL V.51/2, labial view. C. ZPAL V.51/3, lingual view. D. ZPAL V.51/4, labial view. E–I. Isadia aristoviensis Minikh, 1990, maxillary teeth. E. ZPAL V.51/6, lingual view. F. ZPAL V.51/7, labial view. G. ZPAL V.51/5, lingual view. H. ZPAL V.51/8, lingual view. I. ZPAL V.51/9, labial view. J. Isadia arefievi Minikh, 2015, ZPAL V.51/10, mandibular tooth,?lingual view. K, L. Isadia suchonensis Minikh, 1986, mandibular teeth. K. ZPAL V.51/11, lingual (K1) and lateral (K2) views. L. ZPAL V.51/12, labial view. M. Isadia suchonensis Minikh, 1986, ZPAL V.51/13, maxillary teeth,?labial view. Scale bars 1 mm (A–I), 0.5 mm (J, K, M), 0.2 mm (L).
Fig. 1 in Feeding convergence among ray-finned fishes: Teeth of the herbivorous actinopterygians from the latest Permian of East European Platform, Russia
Fig. 1. Location of the fish-bearing site and details of the exposed section. A. Map of the Eastern Europe with position of Vyazniki (BY, Belarus, LV, Latvia; EST, Estonia; LT, Lithuania). B. The area around the town of Vyazniki with position of Sokovka site (star). C. Photograph of the Sokovka section from 2013 and exposure of the fish-bearing deposits. D. The simplified section from Sokovka site showing the fish-bearing layers. Modified from Newell et al. 2010, Owocki et al. 2012, and Bajdek et al. 2017.
CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research
<p>Sample sensor data and vehicle information of our autonomous research vehicle CoCar NextGen.</p> <p>This repository contains a short sequence of sample data from all sensors (except radar) of our research platform. The data is collected in a ROSBag. Additionally, sensor postions are provided in a URDF file. Finally, basic vehicle parameters are given in a YAML file.</p>
Bilingual Dataset of Multinational Brand Posts and Consumer Replies from Platform X (Turkish and English)
<div> <div> <div> <div> </div> </div> </div> </div> <div> <p>This dataset consists of posts and consumer replies from a curated selection of Fortune 500 companies from 2021 that actively maintained Platform X accounts in both English and Turkish. The sample includes 33 multinational brands spanning various industries: fast-moving consumer goods (FMCG), fast food, technology, automotive, apparel, retail, finance, and logistics.</p> <p>All Platform X messages posted by these brands, along with corresponding consumer responses, were collected over a five-year period, from June 2016 to June 2021. The dataset initially contained a total of 8,101,034 English and 735,459 Turkish messages. Among these, the English dataset includes 2,708,874 brand posts and 5,392,160 consumer replies, while the Turkish dataset comprises 245,422 brand posts and 490,037 consumer replies.</p> <p>All files are in GZIP compressed parquet format.</p> </div>
A phenopushing platform to identify compounds that alleviate acute hypoxic stress by fast-tracking cellular adaptation
<p><span>Severe acute hypoxic stress is a major contributor to the pathology of human diseases, including ischemic disorders. Current treatments focus on managing consequences of hypoxia, with few addressing cellular adaptation to low-oxygen environments. Here, we investigate whether accelerating hypoxia adaptation could provide a strategy to alleviate acute hypoxic stress. We develop a high-content phenotypic screening platform to identify compounds that fast-track adaptation to hypoxic stress. </span><span>Our platform</span><span> captures a high-dimensional phenotypic hypoxia response trajectory consisting of normoxic, acutely stressed, and chronically adapted cell states. Leveraging this trajectory, we identify compounds that phenotypically shift cells from the acutely stressed towards the adapted state, revealing mTOR/PI3K or BET inhibition as strategies to induce this phenotypic shift. Importantly, </span><span>our</span><span> compound hits promote the survival of liver cells exposed to ischemia-like stress, and rescue cardiomyocytes from hypoxic stress. Our “phenopushing” platform offers a general, target-agnostic approach to identify compounds and targets that accelerate cellular adaptation, applicable across various stress conditions.</span></p>
Derived daily timeseries of weather, soil moisture and temperature, flow and nitrogen species (nitrate and nitrite, ammonium) concentrations data for the North Wyke Farm Platform National Biosciences Research Infrastructure, England
<p>For a selection of catchments from the North Wyke Farm Platform in southwest England, where land use conversions have been introduced, daily time series data covering weather conditions (minimum temperature, maximum temperature, total rainfall, wind speed and solar radiation), near-surface soil status (moisture content and temperature), flow and concentrations of key nitrogen species (nitrate and nitrite, ammonium) have been filtered based on attached data quality tags . The datasets run between 2013 and March 2024. For the main climate variables, data gaps were infilled with preceding- and following-on daily data, observations from a nearby weather station or existing national datasets to generate a continuous data series for modelling. For the other data series, annual and seasonal summary statistics on data coverage are provided. Information on significant field events, such as ploughing, drilling and harvest, fertiliser applications and manure spreading were also tabulated.</p>
Usability ratings on the MuLiMi platform expressed by Participants
<p>The database contains usability ratings for the MuLiMi platform for the screening of Dyslexia risk in multilingual children, expressed by the participants (children users). Ratings are expressed through an ad-hoc questionnaire with 12 items on a 1-to-5 point scale. NB ratings for question .1 are to be reversed in order to obtain a scale with increasing scores from the negative to the positive pole, like all other questions.</p>
usability ratings for the MuLiMi platform expressed by Examiners
<p>The database contains usability ratings for the MuLiMi web-platform for the screening of Dyslexia risk in multilingual children, expressed by Examiners on an ad-hoc Usability Questionnaire. Ratings for Questions 2 to 9 are expressed on a scale from 1 to 5, Questions from 10 to 46 are expressed on a scale from 1 to 9. NB ratings to Questions 2, 4, 7, 9 and 38 are to be reversed so as to obtain consistent ratings with increasing numbers correponding to increase from the negative to the positive pole. </p>
Information and results obtained from IoT Platform in Alba Iulia Pilot
<p> </p> <p> The IoT platform allows the geolocation of the container, as well as manage the information of the filling level and traceability of trucks. The eco driving application on board of the truck sends the data from the truck (location, speed, RPM and engine load) t o the IoT platform where it is stored. At the same time sound alarms are emitted when driver excess the ecodriving parameters in the Android application. Besides this, the application receives from the IoT platform the position of the containers that must be collected.</p> <p>In this way the driver can see the position, order of collection of the containers and pathway to collect them, as explained above.<br> The IoT platform receives the information of the labels dispensed from the smart containers. The score of the characterized bags were registered in the platform as explained in the next section. </p> <p>Attached the different data sets generated during the project.</p> <p>For general info, follow the link: https://plasticircle.eu/home/</p>
Information and results obtained from IoT Platform in Valencia Pilot
<p> The IoT platform allows the geolocation of the container, as well as manage the information of the filling level and traceability of trucks. The eco driving application on board of the truck sends the data from the truck (location, speed, RPM and engine load) t o the IoT platform where it is stored. At the same time sound alarms are emitted when driver excess the ecodriving parameters in the Android application. Besides this, the application receives from the IoT platform the position of the containers that must be collected.</p> <p>In this way the driver can see the position, order of collection of the containers and pathway to collect them, as explained above.<br> The IoT platform receives the information of the labels dispensed from the smart containers. The score of the characterized bags were registered in the platform as explained in the next section. </p> <p>Attached the different data sets generated during the project.</p> <p>For general info, follow the link: https://plasticircle.eu/home/</p> <p> </p>
Webinar: Can digital platforms be democratically regulated?
<p>(Originally published on YouTube on October 1, 2021: https://www.youtube.com/watch?v=TZuuAelRjyo)</p> <p>Big Data and Artificial Intelligence are part of a larger digital transformation. Today, the GAFA (Google, Apple, Facebook, Amazon) companies have gained dominance, not only in marketing and communication but also in other fields. Power asymmetries also have geostrategic implications in the rivalry between the United States and China. With data protection regulation, the European Union, Brasil, and other countries are pursuing a regulatory model in the digital realm. I will discuss the opportunities of this regulation for preserving privacy and democratic values in society.</p> <p>Ingrid Schneider is professor of political science in the center “Ethics in Information Technology” at University of Hamburg in Germany. With FGV, she is part of the EU-funded project PRODIGEES (Promoting Research on Digitalisation in Emerging Powers and Europe Towards Sustainable Development) which she will also present in her lecture. In 2022, she will be a guest researcher at FGV in Rio. <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjlRbVhkVFdVa1c5RExpNkNzV2xhWFpna3Awd3xBQ3Jtc0tuT0NtUUpoSWhKWUhWRWZHMVFLZVBtdzdqYUgwaWk2UU5EV2RGODBmbFJRY214cUNZcVFNMXYwQklKRHpUVUdHOWJMQXdwRFNOemc5dUFYUUxXdTdZT1F4ZE1oRzFBZEQ4WGQxVEFZd3FWc3NXNk5mSQ&q=https%3A%2F%2Fblogs.die-gdi.de%2Flongform%2Fprodigees%2F">https://blogs.die-gdi.de/longform/pro...</a></p> <p>Website professor Schneider: <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0VMZlZnQUxRcnN1aWNoNnRDaVVVY2RKVlBUZ3xBQ3Jtc0trYlB2czNMTHozVl9VNEtMSE9pbUtBNy1ESmczcTZMNEluc3hLZ0oyeksyREtnQ2gtYWdFWUZvX3p4RVdXVmlQVThqRkRvOUJOSGdRQmpQTVhDWDRrTUlTTm9BSDdXemlWUXgxRzJkYnN2MUY1SWhUTQ&q=http%3A%2F%2Fuhh.de%2Finf-schneider">http://uhh.de/inf-schneider</a> </p> <p>Speakers: Ingrid Schneider - Prof. Dr. Universität Hamburg | Department of Informatics Ethics in Information Technology </p> <p>Moderator: Bernardo Fajardo - Coordenador da Graduação em Administação FGV EBAPE</p> <p>This was an event organized by FGV EBAPE on 10/01/2021</p>
BioRECO2VER 1st BES platform at the University of Girona
<p>A tour through the world's 1st fully automated bio-electrochemical platform for carbon-neutral production from carbon dioxide and renewable energy. In contrast to prior attempts, this platform uses solely carbon-dioxide as a source. This BioRECO2VER prototype platform is located at the Scientific Parc of the University of Girona, Spain.</p>
LEXIS Platform Architecture Scheme
<p>This image contains current version of the <a href="https://lexis-project.eu/web/lexis-platform/">LEXIS platform architecture</a>, which has been created during the LEXIS project.</p> <p>The architecture is divided in three top-level layers:</p> <ol> <li> <p>The LEXIS Portal Layer, providing easy access to the LEXIS platform for Pilots and possible external users,</p> </li> <li> <p>The LEXIS Services Layer, running on top of the infrastructure layer. It includes federated security Infrastructure (Authentication & Authorization Infrastructure, AAI), data management (Data Distribution Infrastructure, DDI), and orchestration services (Orchestrator),</p> </li> <li> <p>The HPC/Cloud Infrastructure Layer, focusing on the interactions among HPC and Cloud hardware systems to provide the computing power and data storage space to the upper layers. It is implemented as a federation of multiple HPC providers and data centres.</p> </li> </ol> <p>Please refer to the project WP2 (co-design) deliverables at <a href="https://lexis-project.eu/web/outcomes/deliverables/">https://lexis-project.eu/web/outcomes/deliverables/</a> for more information.</p>
A survey of access to the digital collections of 195 UK GLAMs across internal and external platforms - Appendix 1 for A Culture of Copyright: A scoping study on open access to digital cultural heritage collections in the UK
<p>Created for the<a href="https://doi.org/10.5281/zenodo.6242611"> 'A Culture of Copyright: A scoping study on open access to digital cultural heritage collections in the UK' </a>report, this sample replicates and expands the Open galleries, libraries, archives and museums (GLAMs) Survey data extraction and methodology to include a range of GLAMs across the UK and new data points. The initial sample of 350 organisations included Independent Research Organisations (IROs) and Research Centre Institutes (RCIs), GLAMs associated with <a href="https://www.nationalcollection.org.uk/">Towards a National Collection</a> Foundation and Discovery projects, UK GLAMs in the Open GLAM Survey, and other UK GLAMs and related organisations. An initial review was performed to identify and remove organisations outside the scope of inquiry (<em>e.g.</em>, no permanent collections). The final sample included 195 organisations.</p> <p>From the final sample, 24 are IROs (all RCIs were removed). Another 32 are Universities (including GLAMs within universities). This brings the total number of organisations eligible for AHRC funding to 56 (or 28.6%). The remaining 140 include public and private GLAMs at national, regional and local levels (<em>e.g., </em>councils, historic buildings) and research initiatives or data aggregators (<em>e.g.,</em> Portable Antiquities Scheme, Culture Grid, Archaeology Data Service). Organisations are distributed across the UK as follows: Channel Islands (1 total); England (154 total); Isle of Man (1 total); Northern Ireland (5 total); Scotland (28 total); Wales (6 total).</p> <p>A survey of the copyright and open access policies of 63 GLAMs from the UK GLAM Sample is available on Zenodo at: <a href="https://doi.org/10.5281/zenodo.6242559">https://doi.org/10.5281/zenodo.6242559</a></p>
BioTAGME: A comprehensive platform for biological knowledge network analysis
<p><strong>A Knowledge Graph containing logical or physical relationships among biological elements</strong>. <br> This Network was built through BioTAGME, a system that combines TAGME, an entity-annotation framework based on Wikipedia corpus with a network-based inference methodology (i.e., DT-Hybrid).<br> <em>BioTAGME</em> exploits several Biological Ontologies as "ground truth" of significant bio-entities, such as <em>DisGeNET, DrugBank, STRING</em> and many more. <br> We Deployed <em>BioTAGME</em> on <em>PubMed</em>, where the aim was on extracting biological entities and their relations from titles and abstracts.<br> Biological entities are the <em>nodes</em> of our graph, while <em>edges</em> are the relations between them.<br> Edges are of three categories:</p> <ol> <li>Literature edges: interactions derived from publications.</li> <li> STRING: protein-protein associations stored in the STRING database.</li> <li>BioTAGME: interactions predicted by our tool.</li> </ol> <p> </p> <p>The <strong>network</strong> is released (<strong>BiotagmeNetwork.zip</strong>) in a neo4j compatible format. Such archive contains:</p> <ol> <li><strong>Edges.csv and Nodes.csv</strong> that contain the nodes and edges of our network, rispectively.</li> <li><strong>Name_Aliases.csv</strong>: contains the synonyms list of each biological entity.</li> <li><strong>Wiki_Titles.csv</strong>: contains the wikipedia pages title associated with the annotated entities.</li> <li><strong>wid1_wid2_pmid.csv</strong>: contains the associations between pairs of entities and pubmed id</li> <li><strong>BioIDs_WikiIDs.csv</strong>: contains the association between the biological entities annotated by BioTAGME, and the wikipedia pages that are associated. </li> </ol>
Commodity Dataset | Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform
<p>(Commodity data in raster format) Supplementary materials for “Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform” that had been published on Land MDPI (2020). doi:<a href="https://doi.org/10.3390/land9100377">10.3390/land9100377</a> </p> <p>The data included:</p> <p>1) Raster data of commodity maps (TIFF Compressed in ZIP)</p> <p>2) READ ME for the dataset (DOCX)</p> <p>3) Legend for raster data in ArcGIS Format (LYR)</p> <p> </p>
Electrical Low-Frequency 1/fγ Noise Due to Surface Diffusion of Scatterers on an Ultra-low-Noise Graphene Platform
<p>Experimental dataset for article “Electrical Low-Frequency 1/<em>f<sup>γ</sup></em> Noise Due to Surface Diffusion of Scatterers on an Ultra-low-Noise Graphene Platform”, <em>Nano letters</em>, <strong>21</strong>(18), 7637-7643 (2021), <a href="https://doi.org/10.1021/acs.nanolett.1c02325">doi: 10.1021/acs.nanolett.1c02325</a></p>
Data of paper Chemically vapor deposited Eu3+:Y2O3 thin films as a material platform for quantum technologies
<p>Data of the figures of the paper:</p> <p>N. Harada, A. Ferrier, D. Serrano, M. Persechino, E. Briand, R. Bachelet, I. Vickridge, J.-J. Ganem, P. Goldner, and A. Tallaire, <em>Chemically Vapor Deposited Eu 3+:Y 2O 3thin Films as a Material Platform for Quantum Technologies</em>, J. Appl. Phys. <strong>128</strong>, 055304 (2020). doi: <a href="https://doi.org/10.1063/5.0010833">10.1063/5.0010833</a></p> <p> </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.