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24 results for “BBC”
Raw D and 18O isotope data for a core from the center and moat of the BBC collapse scar: Bonanza Creek Experimental Forest Flood Plains
This data set contains D and 18O data for a core from the center and moat (0 and 6 m) of the BBC collapse scar. Two well-preserved cores from the center of the bog was collected in March 2003 with a gasoline-powered permafrost corer. Cores were stored frozen and sampled using a radial saw. The core was sampled every two cm for macrofossil, diatom analysis and chemistry. Oxygen isotope ratios in aquatic cellulose has been shown to be a reliable tracer of lakewater isotope ratios (Sauer et al., 2001). I predicted that ?D and ?18O signatures in Sphagnum leaves would respond to enrichment and depletion in the bog water over time, providing an independent line of evidence for diatom-inferred hydrologic change. All isotope samples were processed by the Alaska Stable Isotope Facility using a Thermo Finnigan TC EA and Deltaplus XL mass spectrometer (Thermo Electron Corporation, Bremen, Germany) in continuous flow mode. Data were reported relative to standard mean ocean water (SMOW). Instrument precision was 1.2 ? SE for ?D and 0.3 ? SE for ?18O. I separated Sphagnum leaves from the bog and moat cores, and ran whole organic matter samples for ?D and ?18O stable isotopes. To determine the correlation between ?D and ?18O stable isotopes in peat leaves and bog water, I analyzed samples of Sphagnum and adjacent surface water. I collected surface water samples without headspace and refrigerated at 4 ?C until sample analysis. Snow samples were kept frozen until analysis. I refrigerated surface sample Sphagnum leaves from branches directly below the capitulum after harvest until analysis for ?D and ?18O stable isotopes. I identified Sphagnum samples to species. This data set was collected to relate ?D and ?18O to fires, changes in succession, changes in hydrology, and diatom assemblages.
Growing Season D and 18O isotope data for a core from the center and moat of the BBC collapse scar: Bonanza Creek Experimental Forest Flood Plains
This data set contains D and 18O data for a core from the center and moat (0 and 6 m) of the BBC collapse scar. Two well-preserved cores from the center of the bog was collected in March 2003 with a gasoline-powered permafrost corer. Cores were stored frozen and sampled using a radial saw. The core was sampled every two cm for macrofossil, diatom analysis and chemistry. Oxygen isotope ratios in aquatic cellulose has been shown to be a reliable tracer of lakewater isotope ratios (Sauer et al., 2001). I predicted that ?D and ?18O signatures in Sphagnum leaves would respond to enrichment and depletion in the bog water over time, providing an independent line of evidence for diatom-inferred hydrologic change. All isotope samples were processed by the Alaska Stable Isotope Facility using a Thermo Finnigan TC EA and Deltaplus XL mass spectrometer (Thermo Electron Corporation, Bremen, Germany) in continuous flow mode. Data were reported relative to standard mean ocean water (SMOW). Instrument precision was 1.2 ? SE for ?D and 0.3 ? SE for ?18O. I separated Sphagnum leaves from the bog and moat cores, and ran whole organic matter samples for ?D and ?18O stable isotopes. To determine the correlation between ?D and ?18O stable isotopes in peat leaves and bog water, I analyzed samples of Sphagnum and adjacent surface water. I collected surface water samples without headspace and refrigerated at 4 ?C until sample analysis. Snow samples were kept frozen until analysis. I refrigerated surface sample Sphagnum leaves from branches directly below the capitulum after harvest until analysis for ?D and ?18O stable isotopes. I identified Sphagnum samples to species. This data set was collected to relate ?D and ?18O to fires, changes in succession, changes in hydrology, and diatom assemblages.
Average D and 18O isotope data for a core from the center and moat of the BBC collapse scar: Bonanza Creek Experimental Forest Flood Plains
This data set contains D and 18O data for a core from the center and moat (0 and 6 m) of the BBC collapse scar. Two well-preserved cores from the center of the bog was collected in March 2003 with a gasoline-powered permafrost corer. Cores were stored frozen and sampled using a radial saw. The core was sampled every two cm for macrofossil, diatom analysis and chemistry. Oxygen isotope ratios in aquatic cellulose has been shown to be a reliable tracer of lakewater isotope ratios (Sauer et al., 2001). I predicted that ?D and ?18O signatures in Sphagnum leaves would respond to enrichment and depletion in the bog water over time, providing an independent line of evidence for diatom-inferred hydrologic change. All isotope samples were processed by the Alaska Stable Isotope Facility using a Thermo Finnigan TC EA and Deltaplus XL mass spectrometer (Thermo Electron Corporation, Bremen, Germany) in continuous flow mode. Data were reported relative to standard mean ocean water (SMOW). Instrument precision was 1.2 ? SE for ?D and 0.3 ? SE for ?18O. I separated Sphagnum leaves from the bog and moat cores, and ran whole organic matter samples for ?D and ?18O stable isotopes. To determine the correlation between ?D and ?18O stable isotopes in peat leaves and bog water, I analyzed samples of Sphagnum and adjacent surface water. I collected surface water samples without headspace and refrigerated at 4 ?C until sample analysis. Snow samples were kept frozen until analysis. I refrigerated surface sample Sphagnum leaves from branches directly below the capitulum after harvest until analysis for ?D and ?18O stable isotopes. I identified Sphagnum samples to species. This data set was collected to relate ?D and ?18O to fires, changes in succession, changes in hydrology, and diatom assemblages.
Ground cover and biomass projection photos for the BBC collapse scar
We used digital photographs to project the biomass over the growing season. This data set contains ground cover photos of plots from the center of the BBC collapse scar (0m) into the surrounding fire scar (30m) of the Survey Line Fire (burned in June-July 2001) for the growing seasons of 2003 and 2004. Also included are ground cover photos of plots along the biomass transect used to create the projected biomass data. We calculated the percent cover of vegetation for the biomass and intensively monitored transects from digital photographs. Photographs were rectified to 10,000 x 10,000 pixels and a 20 x 20 grid was applied to the photograph. The percentage of each plant type was estimated in each grid cell. The percent cover was regressed against the measured dry biomass to project biomass for the intensively measured transect. We did not project moss biomass and instead assumed it to be the same for both transects. We projected the change in biomass over the growing season from the change in greenness determined from digital photographs. We chose five dates throughout the growing season with pictures of equal color saturation, focus and aspect. From these we estimated the percent photosynthetic biomass by selecting areas of green on the photograph and calculating the percentage of the total pixels made up by these areas. We estimated curves for the change in % green vegetation for 0, 6 m and the mean of the remaining distances along the transect (12, 18, 24, and 30 m), as these regions of the transect exhibited different patterns of greenness across the growing season of 2004. To estimate photosynthetic biomass over the growing season, we corrected the biomass estimates for the study transect to account for the change in green vegetation associated with growth and senescence
CO2, CH4, and H2O flux data and associated environmental variables for the BBC collapse scar for 2004
This data set contains flux measurements for the transect from the center of the BBC collapse scar (0m) into the surrounding fire scar (30m) of the Survey Line Fire (burned in June-July 2001). We measured CO2, H2O and CH4 fluxes every one to two weeks throughout the growing season of 2004. We measured fluxes at permanent plots established from the center of the bog into the surrounding burn at 0, 6, 12, 18, 24, and 30 m on the east and west side of the transect. Flux measurements on either side of the transect were treated as replicates. CO2 and H2O fluxes were measured using a Li-840 infrared gas analyzer (Licor Inc., Lincoln, NB, USA). The IRGA was calibrated before each trip to the field using a span of 400 ppm and a zero of N2 gas. We logged data every 0.5 seconds for 2 min. To account for measurement variability, we conducted two measurements in succession at each location, after flushing the chamber for accumulated CO2 and H2O. For the flux measurements, we built plexiglass chambers with pipe insulation bases with dimensions of 61 x 61 x 30.5 cm, 61 x 61 x 61 cm, or 61 x 61 x 122 cm. The shorter chambers were used in the collapse portion of the transect. Chambers included fans for air circulation, inlet and outlet ports for CO2 measurements, or just outlet ports for CH4 measurements (Carroll and Crill 1997). We placed chambers directly on the soil surface and used pipe insulation and plastic sheeting to make a solid seal during the measurement. To estimate the volume for each chamber measurement, we measured the distance to the soil surface from a 6 cm grid suspended 30 cm above each plot, the surface area was then used to calculate the chamber volume for each measurement. Dark measurements were used to determine CO2 derived from soil and root respiration (ecosystem respiration) using a two-layer cloth shroud with a reflective surface to exclude solar radiation. To estimate net ecosystem exchange (NEE) of CO2, we conducted chamber measurements of plant and soi
Meteorological data for the BBC collapse scar for 2003 and 2004
This data set contains meteorological measurements for a destructively harvested transect 30 m to the east of the permanent transect from the center of the BBC collapse scar (0 m) into the surrounding fire scar (30 m) of the Survey Line Fire (burned in June-July 2001). At the beginning of the 2003 growing season, we installed several meteorological instruments. We measured temperatures using copper-constantan theromocouples (Omega Engineering Inc., Stamford, CT, USA) at 5, 10 20, and 50 cm depth on the east and west side of the boardwalk at 0, 10 (west side only) 20, and 30 m distance along the transect. We measured air temperature using PVC radiation shields at 30, 60, 120, and 240 cm height above the ground surface. We measured soil moisture using EC-20 ECH2O dielectric aquameter probes (Decagon Devices Inc., Pullman, WA, USA) at 16 points along the transect at 30, 28, 26, 24, 18, 16, 14, and 12 m on the east and west side of the boardwalk at 10 cm depth. To measure rain, we installed a TE 525MM tipping bucket rain gauge (Texas Electronics Inc., Dallas, TX, USA) at 2m on the tower. To measure water level, we installed a Druck21 PDCR 1830-8388 submersible pressure transducer (5 psi range, Druck Inc., New Fairfield, CT, USA) inserted 60 cm below the soil surface, down an 11 cm interior diameter PVC well at 30m along the transect. We measured photosynthetically active radiation with Apogee quantum sensors (Apogee Instruments Inc., Logan, UT, USA) at 30, 60, 120, and 240 cm above the soil surface. To monitor changes in thaw depth, we probed the soil at each visit (every one to two weeks throughout the growing season), every 3 m along both the east and west sides of the transect.
Soil data for cores from a transect from the center of the BBC collapse scar into the surrounding burn
This data set contains soil data for cores from a transect from the center of the BBC collapse scar (0 m) into the surrounding burn (30 m). Thirty-five cores were collected soil cores along the transect in March 2003. We drilled cores using a gasoline powered, permafrost corer while soils were frozen. Two to four cores were drilled every 3 m along the transect, yielding a total of 35 cores. We stored cores frozen and cut sample sections using a radial saw. Cores were sampled at the interfaces between different soil layers. We classified soils using the Canadian Soil Classification system (Soil Classification Working Group 1998) identifying fibric, mesic, and humic organic horizions and the A and C mineral horizons. Nine cores were sampled only to the mineral boundary. We measured bulk density, %C and %N for all soil samples. The pH of sample was determined using litmus paper. We oven-dried at 50 - 65 degC and ground all samples before analysis. We analyzed samples for %C and %N using a Carlo Erba EA1108 CHNS analyzer (CE Instruments, Milan, Italy) and a COSTECH ECS 4010 CHNS-O analyzer (Costech Analytical Technologies Inc., Valencia, CA,USA). Sample standard errors were +/- 0.01% for nitrogen, +/- 0.45% for carbon. To indicate fire events in the surrounding ecosystem, charcoal layers in the cores were quantified. We estimated charcoal by emptying dried samples of a known volume and depth (on mean 4.5 cm3) over a 10 cm x 10 cm grid and counting macroscopic charcoal fragments (greater than 0.05 mm in diameter) in each cm grid cell.
Tree ring width data for trees adjacent to the BBC collapse scar
This data set contains ring width data for trees adjacent to the BBC collapse scar. We used dendrochronology to link paleoecological data with modern observations of the response of this system to fire. Tree ring analysis provides a record of the response of the black spruce trees to changing climate and ongoing thermokarst, allowing for speculation about the response of this landscape to future climate change. We harvested twenty-one fire-killed tree cross-sections from the margin of the collapse and in the surrounding burn in the growing season of 2004. We measured ring width (sliding stage, Velmex Inc., Bloomfield, NY, USA, resolution: 0.001mm) for two radial transects of the tree cross-sections. To remove the age-related variation in growth rate, we crossdated trees with Cofecha and standardized ring-widths with the program ARSTAN (Richard Holmes, Laboratory of Tree Ring Research, University of Arizona). We recorded the presence of compression-wood for each tree ring, an indicator of leaning which is interpreted to be related to frost-heaving and permafrost collapse (Camill and Clark, 1998). This data set includes temperature and precipitation data from a composite of climate data from the University Experiment Station (1906-1947) and Fairbanks International Airport (1948-2000) (Wilmking et al., 2004).
Active Layer Depth Data for the BBC collapse scar for 2003 and 2004
This data set contains active layer depth measurements (cm) for a transect from the center of the BBC collapse scar (0 m) into the surrounding fire scar (30 m) of the Survey Line Fire (burned in June-July 2001). Data were collected using a 120m (and during 2004 a 205.5 m) permafrost probe at every visit to the site in 2003 and 2004. Three permafrost depth measurements were made within a 25cm radius at every point along the transect (0, 3, 6, 9, 12, 15, 18, 21, 24, 27, and 30 m on the east and west sides of the boardwalk and at 33 m on the west side only). This data set was collected to monitor the increase in active layer throughout the growing season to relate this to measured fluxes of CO2 and CH4 emissions from soils along the same transect. The data set was also used to monitor permafrost collapse at the margins of the BBC collapse scar.
Biomass, %N, and %C data for the BBC collapse scar for 2003 and 2004
This data set contains biomass measurements for a destructively harvested transect 30 m to the east of the permanent transect from the center of the BBC collapse scar (0m) into the surrounding fire scar (30m) of the Survey Line Fire (burned in June-July 2001). Biomass samples were collected on DOY 231 2004. Two 61 cm x 61 cm plots were harvested on the east and west side of every point along the transect (0, 6, 12, 18, 24, and 30 m). We sorted these above-ground biomass samples into plant type (Sphagnum spp., other mosses, Marchantia spp., Eriophorum vaginatum, Carex spp., Grasses, Betula spp., Salix spp., Potentilla palustris, Ledum groenlandicum, Vaccinium uliginosum, Vaccinium vitis-idaea, Chamaedaphne calyculata, other vascular plants, dead mosses, dead Carex spp., dead Graminoid, dead Potentilla palustris, dead Salix spp., and other litter). Photosynthetic green tissues were separated from the above-ground biomass samples. Samples were dried at 60degC to measure the dry mass. Samples were also analyzed for %C and %N. We oven-dried at 50 - 65degC and ground all samples before analysis. We analyzed samples for %C and %N using a Carlo Erba EA1108 CHNS analyzer (CE Instruments, Milan, Italy) and a COSTECH ECS 4010 CHNS-O analyzer (Costech Analytical Technologies Inc., Valencia, CA, USA). Sample standard errors were +/- 0.01% for nitrogen, +/- 0.45% for carbon. For the biomass transect samples, we analyzed for %C and %N when the samples were more than 10% of the plot biomass allowing for representative sampling of carbon and nitrogen from the dominant plant types. This data set was collected to monitor the change in biomass across the transect to relate this to disturbance, topography, soils, soil moisture and measured fluxes of CO2 and CH4 emissions.
News headlines of BBC articles published by @BBCBreaking twitter account
<p>The dataset consists of a list of news articles headlines retrieved from tweets published by @BBCBreaking profile in specific years (2012, 2015, 2017, 2019 and 2022).</p> <p>The dataset is in <code>.csv</code> format and is organised as follows:</p> <ul> <li>Columns: <ul> <li>ID (tweet ID)</li> <li>created_at (tweet publication's date)</li> <li>url (url of the news article attached to the tweet)</li> <li>Titles (news headline)</li> </ul> </li> <li>Rows: Each row contains a single news article headline sorted by date of publication (created_at). Total number of entries: 7213.</li> </ul> <p>For more details about data collection refer to <a href="https://github.com/caiocmello/news-mood">Github</a>.</p>
RadioNews-BBC
<p>This dataset is released as part of the paper "Exploring Pre-Trained Neural Representations for Audio Topic Segmentation" and it includes embeddings extracted from non-overlapping 1-second audio portions from various news shows from BBC radio channels. Each audio file has been anonymised by labelling it with a randomised label. We release 7 type of embeddings coming from different pre-trained architectures and, where applicable, for 3 of these embedding type we further release 7 sub-folders containing the actual audio embeddings for each file. These sub-folders contain the embeddings obtained with different pooling strategies described in the original paper: as openL3, Wav2Vec2 and CREPE are trained to output multiple embeddings for each 1-second frame the pooling strategies reduce those multiple embeddings to one per frame. The pooling strategy can have a huge impact on final model performance.<br> Finally, we release the ground truth for each audio file as a pickle file containing a python dictionary, where the keys are the same identifiers used to name the embeddings (without the .npy extension). The ground truth were produced by manual annotators and they represent whether each 1-second frame is a topic boundary (i.e. a topic shift happens in or at the end of the frame) or not, where 1 corresponds to topic boundary and 0 to in-topic frames (i.e. non-boundary).</p> <p>Below we describe in more details the structure of our dataset:</p> <p>- RadioNewsUniform1: Parent directory containing all the other directories and files. Uniform 1 indicates the initial segmentation methodology, consisting of non-overlapping 1-second chunks of audio.</p> <p>The parent directory includes the following subdirectories:</p> <p>- - openl3: a folder of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative openl3 embeddings.</p> <p>- - x-vectors: a folder of numpy arrays, one for each audio source file, including the relative x-vector embeddings.</p> <p>- - ecapa: a folder of numpy arrays, one for each audio source file, including the relative ecapa embeddings.</p> <p>- - wav2vec: a folder of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative wav2vec2 embeddings.</p> <p>- - crepe: a folder of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative CREPE embeddings.</p> <p>- - prosodic: a folder of numpy arrays, one for each audio source file, including the relative prosodic embeddings.</p> <p>- - mfcc: a folder of numpy arrays, one for each audio source file, including the relative MFCC embeddings.</p> <p>- - labs_dict.pkl: a pickled file (Protocol version 5) containing the topic segmentation ground truth. It consists of a dictionary where each key is the identifier assigned to the original audio file- and the value associated is a list of 0 and 1s of length equal to the corresponding embedding containing the same name. The elements in each list indicate whether the corresponding embedding constitutes a topic boundary (1) or not (0) and it is therefore used to train and test a topic segmentation model. For example, in the Non-news dataset the key "24260" contains the ground truth for all the numpy array files containing the identifier "24260" in the same dataset (e.g. openl3/_mean_/24260.npy, prosodic/24260.npy, etc.).</p> <p>This work is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/3.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</p>
BBC Maida Vale Impulse Response Dataset
<p>This repository presents a dataset of spatial impulse responses measured from the BBC Maida Vale Studios.</p><p>The measurements were undertaken in Summer/Autumn 2021 by researchers from the University of York, led by Prof Gavin Kearney and Prof Helena Daffern and team members of BBC R&D. </p><p>The measured studio live rooms presented here are studios MV4 and MV5.</p><p>The dataset for each room includes:</p><p>- Higher Order Ambisonic (3rd Order) spatial impulse responses for 3DOF/6DOF rendering.</p><p>- Reference KEMAR binaural measurements</p><p>- ISO-3382 measurements.</p><p>- Readme files for each room. </p><p> </p><p><strong>Important notes: </strong></p><p>- If you use this dataset, please cite the following paper in your work:</p><p>Kearney, G., Daffern, H., Cairns, P., Hunt, A., Lee, B., Cooper, J., Tsagkarakis, P., Rudzki, T. and Johnston, D., 2022, September. Measuring the Acoustical Properties of the BBC Maida Vale Recording Studios for Virtual Reality. In <i>Acoustics</i> (Vol. 4, No. 3, pp. 783-799). MDPI.</p><p>- Source orientations have been measured in the four cardinal directions (N, E, S, W) and impulse responses can be combined to simulate sources with first order directivity patterns. See paper above for further details. </p><p>- For 3DOF/6DOF measurements, Ambix config files are also included for quick audition of the IRs using an appropriate convolver (e.g. MCFX convolver http://www.matthiaskronlachner.com/?p=1910). </p><p>- The ISO measurements should not be used for auralisation.</p><p>- Measurements taken from the same source-receiver position should ideally not be used directly. If you wish to simulate the same source/receiver position for natural reverberation foldback, then the direct sound portion should be removed as the frequency reponse of this component will be imbalanced, and should be replaced with direct monitoring of a close miked source via your soundcard. </p><p>If you have any questions about the dataset, please contact gavin.kearney@york.ac.uk</p><p> </p><p> </p>
Accessibility Reviews Related to BBC Mobile Accessibility Guidelines
<p>This dataset comprises accessibility user reviews from the Android App Store, categorized according to the accessibility principles, topics, and guidelines outlined in the <a href="https://www.bbc.co.uk/accessibility/forproducts/guides/mobile/" target="_blank" rel="noopener">BBC Mobile Accessibility Guidelines</a>.</p>
Blood Pressure in Blacks and Calcium (BBC) and Vitamin D Study
ClinicalTrials.gov study NCT03070483. IPD Sharing: NO. Countries: 1. Publications: 1.
Exploración Dinámica de Contenido: Dataset de Artículos de BBC News con Metadatos Temporales e Imágenes
<p>El conjunto de datos "Exploración Dinámica de Contenido: Dataset de Artículos de BBC News con Metadatos Temporales e Imágenes" ha sido recopilado mediante técnicas de web scraping, ofreciendo una visión detallada y estructurada de las noticias más recientes presentadas por BBC News, un destacado medio de comunicación a nivel mundial.</p><p>Este conjunto proporciona la capacidad de realizar un análisis profundo de patrones informativos, identificación de tendencias emergentes y análisis temporal de eventos noticiosos.</p><p>La organización estructurada y la abundancia de metadatos presentes facilitan la aplicación de técnicas analíticas avanzadas, asegurando que el conjunto esté siempre actualizado gracias a la técnica de web scraping implementada. Además, la inclusión de enlaces adicionales dentro de las noticias permite una exploración más profunda y exhaustiva de temas relacionados.</p><p>Este dataset se destaca no solo como un recurso valioso para comprender la actualidad a través de la lente de BBC News, sino también como una plataforma sólida para la implementación de técnicas avanzadas de análisis de datos y la extracción de conocimientos significativos.</p><p>Este conjunto de datos creado se compone de cuatro columnas distintas que son: Title, Link, Date e Image.</p>
The Excalibur - BBC Merlin
a 3D replica of the Sword in the TV show Merlin by the BBC. the sword can be moved out of the rock. the wording are engraved in the model. the metals are textured with noise texture and they can't be seen here in the preview, you'll need to download it to see the full textureing. it's game ready and lowpoly. this is only for personal use and should not be used commercially. Source: Objaverse 1.0 / Sketchfab
NonNews-BBC
<p>This dataset is released as part of the paper "Exploring Pre-Trained Neural Representations for Audio Topic Segmentation" and it includes embeddings extracted from non-overlapping 1-second audio portions from various magazine-style shows (i.e. non news) from BBC radio channels. Each audio file has been anonymised by labelling it with a randomised label. We release 7 type of embeddings coming from different pre-trained architectures and, where applicable, for 3 of these embedding type we further release 7 sub-folders containing the actual audio embeddings for each file. These sub-folders contain the embeddings obtained with different pooling strategies described in the original paper: as openL3, Wav2Vec2 and CREPE are trained to output multiple embeddings for each 1-second frame the pooling strategies reduce those multiple embeddings to one per frame. The pooling strategy can have a huge impact on final model performance.<br> Finally, we release the ground truth for each audio file as a pickle file containing a python dictionary, where the keys are the same identifiers used to name the embeddings (without the .npy extension). The ground truth were produced by manual annotators and they represent whether each 1-second frame is a topic boundary (i.e. a topic shift happens in or at the end of the frame) or not, where 1 corresponds to topic boundary and 0 to in-topic frames (i.e. non-boundary).</p> <p>Below we describe in more details the structure of our dataset, by describing the content of each sub-folder and file:</p> <p>- NonNewsUniform1: The parent directory containing all the other subdirectories and files. Uniform 1 refers to the initial segmentation method being that of dividing the original audio file in non-overlapping 1-second chunks.</p> <p>-- openL3: a folder of of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative openl3 embeddings.</p> <p>-- x-vectors: a folder of numpy arrays, one for each audio source file, including the relative x-vector embeddings.</p> <p>-- ecapa: a folder of numpy arrays, one for each audio source file, including the relative x-vector embeddings.</p> <p>-- Wav2Vec: a folder of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative wav2vec2 embeddings.</p> <p>-- CREPE: a folder of folders, one for each pooling strategy, each containing numpy arrays, one for each audio source file, including the relative CREPE embeddings.</p> <p>-- prosodic: a folder of numpy arrays, one for each audio source file, including the relative prosodic embeddings.</p> <p>-- mfcc: a folder of numpy arrays, one for each audio source file, including the relative MFCC embeddings.</p> <p>-- labs_dict.pkl: a pickled file (Protocol version 5) containing the topic segmentation ground truth. It consists of a dictionary where each key is the identifier assigned to the original audio file- and the value associated is a list of 0 and 1s of length equal to the corresponding embedding containing the same name. The elements in each list indicate whether the corresponding embedding constitutes a topic boundary (1) or not (0) and it is therefore used to train and test a topic segmentation model. For example, in the Non-news dataset the key "vuci12" contains the ground truth for all the numpy array files containing the identifier "vuci12" in the same dataset (e.g. openl3/_mean_/vuci12.npy, prosodic/vuci12.npy, etc.).</p> <p>This work is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/3.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</p>
BBC ONE - British Bifurcation Coronary Study
ClinicalTrials.gov study NCT00351260. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Enhancing the BBC's news and sports coverage with an ontology-driven information architecture
<p>In Tim Berners Lee’s original proposal for the Web (retrieved from http://info.cern.ch/Proposal.html) he gave us the basic ingredients to build the web of documents as we experience it today. Due to its simplicity, the Web became a victim of its own success as we were soon overwhelmed. At this point information architects were employed to group together documents into manageable piles using a variety of techniques to group sets of documents. The problem with this approach is that if we start out focusing on documents, our sites turn out document-centric and this is not how users think about the world. People are interested in things not documents. This leads us to move away from a document-orientated approach to Web development to a thing-focused one, and with this move comes the need for new tools and approaches to information architecture. This includes the use of domain-driven design to understand the things and relationships in a problem space and the use of open linked data sources to populate these models. This will be illustrated with case studies from the BBC’s Wildlife Finder and the World Cup project.<br> In summary, Semantic Web-like thinking changes the way we build Web sites. Firstly it focuses us on real-world things and the relationships between them, secondly it introduces a culture of building with open vocabularies to add context and links that create richer, more useful and more findable digital products..</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.