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766 results for “Baseline”
BASELINE_dev
<p>BASELINE_dev</p>
BASELINE
<p>Our Baseline system</p>
BASELINE_dev
<p>BASELINE_dev 3</p>
BASELINE_dev
<p>BASELINE_dev 2</p>
BASELINE_dev
<p>BASELINE_dev 8</p>
BASELINE_dev
<p>BASELINE_dev 9</p>
Hackathon - TF-TG literature triage Baseline Files
<p><strong>Files needed to use the baseline system.</strong></p> <p>Instructions to use the baseline system:</p> <ol> <li> <p>Install DeLFT as explained in <a href="https://github.com/kermitt2/delft">https://github.com/kermitt2/delft</a> (<em>If you are not using GPU, it is </em><em>recomended</em><em> to change the requirements.txt to “tensorflow==1.8.0” instead of “tensorflow_gpu==1.8.0”)</em></p> </li> <li> <p>Download the optimized embeddings (Model_FastText.zip) available in this repository and place it inside the main delft folder.</p> </li> <li> <p>Copy the following files available in this repository:</p> <ol> <li> <p>Greekc.zip: Extract the contents to ./delft/data/models/textClassification</p> </li> <li> <p>greekClassifier.py: Copy to ./delft</p> </li> <li> <p>reader.py: Substitute in ./delft/delft/textClassification/reader.py</p> </li> <li> <p>Embedding-registry.json: Substitute in ./delft/embedding-registri.json</p> </li> <li> <p>Fasttext_300_opt.zip: Extract the contents to ./delft/data/db</p> </li> </ol> </li> <li> <p>To make predictions, change the line 96 in greekClassifier to point to the text you want to predict. Each new line should be an abstract. Then run python3 greekClassifier.py classify > path_to_predicted</p> </li> </ol>
Pulse Wave Database (PWDB): Baseline subjects aged 25 to 75
<p><strong>The Pulse Wave Database</strong></p> <p>The <a href="https://peterhcharlton.github.io/pwdb">Pulse Wave Database (PWDB)</a> is a database of simulated arterial pulse waves designed to be representative of a sample of pulse waves measured from healthy adults. It contains pulse waves for 4,374 virtual subjects, aged from 25-75 years old (in 10 year increments). The database contains a baseline set of pulse waves for each of the six age groups, created using cardiovascular properties (such as heart rate and arterial stiffness) which are representative of healthy subjects at each age group. It also contains 728 further virtual subjects at each age group, in which each of the cardiovascular properties are varied within normal ranges. The entire database is available at DOI: <a href="https://doi.org/10.5281/zenodo.2633174">10.5281/zenodo.2633174</a> .</p> <p><strong>This dataset: baseline subjects aged 25 to 75</strong></p> <p>This dataset is a subset of the PWDB. It contains the pulse waves for the six baseline subjects aged 25 to 75 (in 10 year increments). It contains the following waves:</p> <ul> <li>arterial flow velocity (U),</li> <li>luminal area (A),</li> <li>pressure (P), and</li> <li>photoplethysmogram (PPG).</li> </ul> <p>These pulse waves are provided at a range of measurement sites, including:</p> <ul> <li>aorta (ascending and descending)</li> <li>carotid artery</li> <li>brachial artery</li> <li>radial artery</li> <li>finger</li> <li>femoral artery</li> </ul> <p>The data are available in three formats: Matlab, CSV and WaveForm Database (WFDB) format. Further details of the formatting and contents of each file are available at: <a href="https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database">https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database</a></p> <p><strong>Accompanying Publication</strong></p> <p>This is a subset of the PWDB database, which is described in the following publication:</p> <p><a href="https://peterhcharlton.github.io/pwdb/pwdb_article.html">Charlton P.H., Mariscal Harana, J., Vennin, S., Li, Y., Chowienczyk, P. & Alastruey, J., “Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices,”</a> [under review]</p> <p>Please cite this publication when using the database.</p> <p><strong>Further Information</strong></p> <p>Further information on the Pulse Wave Database project can be found at: <a href="https://peterhcharlton.github.io/pwdb/"><em>https://peterhcharlton.github.io/pwdb/</em></a></p> <p><strong>Version History</strong></p> <p><strong>Version 1.0 : </strong>provided for peer review of "Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices"</p>
Baseline soil characteristics
<p>Baseline soil data from Drumbrae, May 2024</p>
Copper Baseline mpi4py and horovod
Open the record for dataset details and reuse information.
D1.3 - Map and report of baseline exposure and vulnerability
<p>This document primarily describes the methodology and summarises the results and conclusions of Task 1.3 – Mapping of coastal cities exposure and vulnerability to climate effects and sea level rise. Itis part of the work included in WP1, whose final objective is to produce a high-level baseline risk map of extreme climate impacts and sea-level rise based on a semi-quantitative assessment of exposure and vulnerability for the ten CCLLs.</p>
SHY Project - Baseline Lifecycle Impacts Dataset
<p>This document has been developed by Julia F. Chozas, Consulting Engineer and Wavepiston A/S.</p> <p>The aim of this document is to present the database compiled as part of Task 6.1 of the SHY project. </p> <p>These data has also been presented in Deliverable 6.1 "Baseline Lifecycle Impacts", which will be publicly available at: https://shyproject.eu/project-results/</p> <p>Any questions can be directly addressed to Julia Fernandez Chozas (info@juliafchozas.com)</p>
Dataset for baseline Raman Spectral fingerprints of zebrafish embryos and larvae
<p>Here, we share the dataset obtained from a baseline characterisation of Raman spectra of zebrafish embryos and larvae throughout early development. Raman spectra were recorded from the iris, forebrain, melanocytes, heart, muscle and swim bladder between 24 and 168 hours post-fertilisation. The dataset contains the raw data and the baseline-corrected spectra used to obtain a Raman characterisation of each tissue or organ, throughout early developmental stages, with chemometrics analysis (Partial least-squares discriminant analysis, PLS-DA). Specific details on the acquisition conditions and data analysis are provided in the associated article: Abreu IO, Teixeira C, Vilarinho R, Rocha ACS, Moreira JA, Oliva-Teles L, Guimarães L, Carvalho AP. 2024. Baseline Raman Spectral Fingerprints of Zebrafish Embryos and Larvae. <em>Biosensors</em>, 14(11), 538 (2024).</p>
Childhood Obesity Study-Baseline Data
<p>This is a study of Obesity in Children, done in 4 primary schools- 2 private and 2 public institutions. </p>
Data from: Number of alleles as a predictor of the relative assignment accuracy of STR and SNP baselines for chum salmon
Short tandem repeat (STR) markers, which exhibit many alleles per locus, are commonly used to assign fish to their populations of origin. Single nucleotide polymorphisms (SNPs), which have many technical advantages over STRs, typically exhibit only two alleles per locus. Simulation studies have indicated that number of independent alleles is a good predictor of accuracy of genetic markers for fishery applications. Extant STR baselines for salmon contain hundreds of alleles, and it has been extrapolated that hundreds of SNP markers need to be developed before SNP baselines will compare to these STR baselines. We compared 15 STRs exhibiting 349 independent alleles to 61 SNP assays exhibiting 66 independent alleles for accuracy in assigning to closely related populations of chum salmon. The SNP baseline yielded slightly higher mean accuracies for proportional assignment and comparable accuracies for individual assignment. Overall the SNP baseline performed considerably better, relative to the microsatellite baseline, than predicted based on the number of independent alleles in each baseline. We suggest that this discrepancy is due to the fact that the simulation studies do not capture the impacts of the different strategies commonly employed for discovering and selecting STR and SNP markers.
Data from: Fuel for the pace of life: baseline blood glucose concentration coevolves with life history traits in songbirds
1. It has been proposed that life histories have coevolved with a suite of physiological and behavioural adaptations, termed pace-of-life syndromes (POLS). Here, we hypothesise that basal concentration of blood glucose (G0), a major source of energy circulating in vertebrate blood, may constitute a key component of POLS. 2. To test this hypothesis, we measured G0 in 30 passerine species and tested its covariation with body mass and other life history traits. Importantly, body mass is a major life history determinant and, when its effect is controlled for, there may be no single fast-slow life history continuum in birds comprising both fecundity and lifespan. Hence, we used individual life history traits, rather than principal component analysis, to characterise life history variation in our analysis. 3. In support of G0 life history coevolution, we found G0 to be negatively correlated with body mass and positively with reproductive investment in a single clutch across 30 passerine species. Higher G0 in females suggests that the energy demands of clutch production and incubation may be an important selection force driving coevolution of G0 with reproductive output. 4. In contrast, G0 was not associated with maximum lifespan, suggesting that high G0 may not constrain evolution of longevity. This implies that long-lived species can evolve physiological adaptations preventing harmful effects of high glucose concentrations, known to cause pathologies and accelerate ageing. 5. In addition, G0, but not basal metabolic rate (BMR), was negatively correlated with migration distance, attesting to evolutionary changes in energy metabolism in long distance migrants. Our results further suggest that the links between body mass, reproduction and G0 are not mediated by BMR and that G0 is associated with fast-slow life history variation more closely than available BMR data. 6. A species life history is determined to a great extent by body mass. When this effect is controlled for, only those traits related to reproduction (but not lifespan) constitute the principal axis of life history variation in birds. Hence, the coevolution of G0 with body mass and reproductive output evidenced in our study indicates that G0 constitutes an important physiological component of POLS.
Comparison of a system using the MROS metacontroller to a benchmark system (Baseline) for a navigation mission
<p>The data from this navigation mission experiment of the paper "MROS: Runtime AdaptationFor Robot Control Architectures" can be found in this repo.</p>
Impact of artificial activity decrease on black carbon aerosol concentration and CO2 at the Mt Waliguan WMO/GAW baseline station during the COVID-19 period
<p>This one is about the data of the article, including BC data, CO2, meteorological data, and boundary layer data. As well as the trajectory and CWT obtained from the Hysplit run. Both BC and CO2 are raw results and can be used to check or repeat the experiment.</p>
Figure 2 in Diversity of Chironomidae (Diptera) breeding in the Great Stour, Kent: baseline results from the Westgate Parks non-biting midge project
Figure 2. (a) Genus percent abundance per site, and (b) genus dominance plot per site in the Great Stour in Kent, UK.
Figure 3 in Diversity of Chironomidae (Diptera) breeding in the Great Stour, Kent: baseline results from the Westgate Parks non-biting midge project
Figure 3. (a) Dendrogram showing the Bray-Curtis dissimilarities among sites, and (b) Principal Components Analysis (PCA) and biplot of Chironomidae genera for sites in the Great Stour in Kent, UK.
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.