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753 results for “metrics”
Shallow subsurface water-ice distribution in the lunar south pole: Analysis based on Mini-RF and multi-metrics
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Human Activity and Environmental Metrics for Anomaly Detection
<p>This dataset contains records of human physiological and environmental data, all collected in a consistent environment at the same time intervals, designed to support research in anomaly or attack detection. The measurements simulate conditions under which physiological parameters may fluctuate, potentially indicating anomalous activities or conditions.</p> <p>The dataset includes 4002 entries with the following parameters:</p> <ul> <li>Humidity: Environmental humidity levels measured in percentage.</li> <li>Temperature: Environmental temperature recorded in degrees.</li> <li>Step count: The number of steps taken by an individual.</li> <li>motion_values: A measurement representing physical motion intensity.</li> <li>heart_rate: Heart rate measured in beats per minute.</li> <li>Attack: Binary indicator (1 or 0) denoting an "attack" or anomalous state (1) versus normal state (0).</li> </ul> <p> </p>
Interview Study About Coursework Consultation Sessions with GitLab Metrics in a Software Engineering Course
<p>This data repository is created to share materials used in an interview study about coursework consultation sessions with GitLab Metrics in a software engineering course, and selected quotations with their corresponding themes.</p>
Diurnal oscillations of MRI metrics in human brains
<p>Restricted access dataset used for the study "Diurnal oscillations of MRI metrics in human brains".</p> <p>Contains subject-level data within the following files:</p> <p>whole_brain_data.csv - average of each MRI metric across the relevant atlas for each time point.</p> <p>processed_ROI_data.csv - average of each MRI metric within each atlas ROI for each time point.</p> <p>whole_brain_techvar_data.csv - average of each MRI metric across the relevant atlas for each time point and back-to-back replicate.</p> <p>weights_kg.csv - body weight at each time point.</p> <p>actigraphy_3day.csv - steps registered by the FitBit device each minute for the 3 days of observation.</p> <p>actigraphy_sleep.csv - sleep intervals registered by the FitBit device during the 3 days of observation.</p> <p> </p>
Performance of the Naneos Partector 2 multi-metric nanoparticle detector at low temperature and pressure conditions
<p>Processed and aggregated datasets from the experiments conducted for characterizing the performance of the Naneos Partector 2 (P2 from now on) under low pressure and temperature conditions (i.e., 0.7 -1.0 atm. and ca. 4 to 22 ºC) with polydisperse and monodisperse aerosols. For the experiments conducted with polydisperse aerosols (see "Polydisperse" excel sheet) the dataset contains the geometric mean diameters (GMDs) derived by the SMPS system, the average particle sizes derived by the P2 and its sizing efficiencies, together with the prevailing temperature and pressure within the testing chamber.</p> <p>For the experiments with the monodisperse aerosols (see "Monodisperse excel sheet"), the dataset contains the average detection and sizing efficiencies of the P2 (DE and SE, respectively) their standard deviations (std DE and std SE, respectively) measured for each monodisperse size at given temperature and pressure conditions. </p>
CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.
<p>Dataset from Schiaffino S, Albano D, Cozzi A, Messina C, Arioli R, Bnà C, Bruno A, Carbonaro LA, Carriero A, Carriero S, Danna PSC, D'Ascoli E, De Berardinis C, Della Pepa G, Falaschi Z, Gitto S, Malavazos AE, Mauri G, Monfardini L, Paschè A, Rizzati R, Secchi F, Vanzulli A, Tombini V, Vicentin I, Zagaria D, Sardanelli F, Sconfienza LM. CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19. Radiology. 2021 Aug;300(2):E328-E336. doi: 10.1148/radiol.2021204141. Epub 2021 Mar 16. PMID: 33724065; PMCID: PMC7971428.</p> <p>Abstract</p> <p>Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; <em>P</em> < .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; <em>P</em> = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; <em>P</em> < .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; <em>P</em> = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; <em>P</em> = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; <em>P</em> = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 <em>Online supplemental material is available for this article.</em></p>
tree metrics at OAL-UK
<p>Spatially-distributed dataset containing basic tree metrics retrieved from tree individuals planted on the braes of OAL-UK between the years 2015 and 2016</p>
Exploring metrics for the characterization of the cerebral autoregulation during head-up tilt and propofol general anesthesia.
<p>Bari V, Barbarossa L, Gelpi F, Cairo B, De Maria B, Tonon D, Rossato G, Faes L, Ranucci M, Barbieri R, Porta A. Exploring metrics for the characterization of the cerebral autoregulation during head-up tilt and propofol general anesthesia. Auton Neurosci. 2022 Nov;242:103011. doi: 10.1016/j.autneu.2022.103011. Epub 2022 Jul 8. PMID: 35834916.</p> <p><strong>Abstract</strong></p> <p>Techniques grounded on the simultaneous utilization of Tiecks' second order differential equations and spontaneous variability of mean arterial pressure (MAP) and mean cerebral blood flow velocity (MCBFV), recorded from middle cerebral arteries through a transcranial Doppler device, provide a characterization of cerebral autoregulation (CA) via the autoregulation index (ARI). These methods exploit two metrics for comparing the measured MCBFV series with the version predicted by Tiecks' model: normalized mean square prediction error (NMSPE) and normalized correlation ρ. The aim of this study is to assess the two metrics for ARI computation in 13 healthy subjects (age: 27 ± 8 yrs., 5 males) at rest in supine position (REST) and during 60° head-up tilt (HUT) and in 19 patients (age: 64 ± 8 yrs., all males), scheduled for coronary artery bypass grafting, before (PRE) and after (POST) propofol general anesthesia induction. Analyses were carried out over the original MAP and MCBFV pairs and surrogate unmatched couples built individually via time-shifting procedure. We found that: i) NMSPE and ρ metrics exhibited similar performances in passing individual surrogate test; ii) the two metrics could lead to different ARI estimates; iii) CA was not different during HUT or POST compared to baseline and this conclusion held regardless of the technique and metric for ARI estimation. Results suggest a limited impact of the sympathetic control on CA.</p>
Process Metrics Collected using Commit Guru
<p>This data contains file-level process metrics collected using the commit guru tool.</p>
PROSPR 2 - METRICS Cervical Cancer Restricted Use Dataset
The MultilEvel OpTimization of the CeRvIcal Cancer Screening Process in Diverse Settings & Populations (METRICS) PROSPR II Research Center was designed to elucidate multilevel factors that hamper or facilitate the cervical cancer screening process and reduce disparities. METRICS has three data-contributing sites from diverse healthcare settings - an integrated county tax-supported public safety-net healthcare system; a not-for-profit integrated delivery system primarily represented by two sites; and a mixed-model healthcare system providing coverage to enrolled members in facilities that are owned and operated by the healthcare system and through providers, medical groups, and hospitals that are contracted to provide health care services. Sites collected 10 years of high-quality, comprehensive cervical cancer screening process data at the patient, provider, clinic/facility, and system levels using a rich array of electronic clinical information systems and other data sources. The estimated size of the combined cohort is ~1.1 million screened and unscreened females. This is the public use dataset.
Dataset related to article: " ENTROPY METRICS CORRELATING WITH HIGHER RESIDUAL FUNCTIONING IN PATIENTS WITH CHRONIC DISORDERS OF CONSCIOUSNESS "
<p>the dataset contains data ENTROPY MEASURES</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
GEDI L2A Elevation and Height Metrics Data Global Footprint Level V001
GEDI Version 1 data products were decommissioned on February 15, 2022. Users are advised to use the improved [GEDI02_A Version 2](https://doi.org/10.5067/GEDI/GEDI02_A.002) data product.The Global Ecosystem Dynamics Investigation (GEDI) mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. The GEDI instrument produces high resolution laser ranging observations of the 3-dimensional structure of the Earth. GEDI is attached to the International Space Station and collects data globally between 51.6 degrees N and 51.6 degrees S latitudes at the highest resolution and densest sampling of any light detection and ranging (lidar) instrument in orbit to date.The purpose of the GEDI Level 2A Geolocated Elevation and Height Metrics product (GEDI02_A) is to provide waveform interpretation and extracted products from each GEDI01_B received waveform, including ground elevation, canopy top height, and relative height (RH) metrics. The methodology for generating the GEDI02_A product datasets is adapted from the Land, Vegetation, and Ice Sensor (LVIS) algorithm. The GEDI01_B product is provided in HDF5 format and has a spatial resolution (average footprint) of 25 meters. The GEDI02_A data product contains 156 variables for each of the eight beams, including ground elevation, canopy top height, relative return energy metrics (describing canopy vertical structure, for example), and many other interpreted products from the return waveforms. Additional information for the variables can be found in the GEDI Level 2A Dictionary.Known Issues* Known Issues: Section 7 of the User Guide provides additional information on known issues.* Data acquisition gaps: GEDI data acquisitions were suspended on December 19, 2019 (2019 Day 353) and resumed on January 8, 2020 (2020 Day 8).
GEDI L2B Canopy Cover and Vertical Profile Metrics Data Global Footprint Level V001
GEDI Version 1 data products were decommissioned on February 15, 2022. Users are advised to use the improved GEDI02_B Version 2 (https://doi.org/10.5067/GEDI/GEDI02_B.002) data product.The Global Ecosystem Dynamics Investigation (GEDI) mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. The GEDI instrument produces high resolution laser ranging observations of the 3-dimensional structure of the Earth. GEDI is attached to the International Space Station and collects data globally between 51.6 degrees N and 51.6 degrees S latitudes at the highest resolution and densest sampling of any light detection and ranging (lidar) instrument in orbit to date.The purpose of the GEDI Level 2B Canopy Cover and Vertical Profile Metrics product (GEDI02_B) is to extract biophysical metrics from each GEDI waveform. These metrics are based on the directional gap probability profile derived from the L1B waveform. Metrics provided include canopy cover, Plant Area Index (PAI), Plant Area Volume Density (PAVD), and Foliage Height Diversity (FHD). The GEDI02_B product is provided in HDF-5 format and has a spatial resolution (average footprint) of 25 meters.The GEDI02_B data product contains 96 variables for each of the eight-beam ground transects (or laser footprints located on the land surface). Variables provided include precise latitude, longitude, elevation, height, canopy cover, and vertical profile metrics. Additional information for the variables can be found in the GEDI Level 2B Data Dictionary.Known Issues* Known Issues: Section 7 of the User Guide provides additional information on known issues.* Data acquisition gaps: GEDI data acquisitions were suspended on December 19, 2019 (2019 Day 353) and resumed on January 8, 2020 (2020 Day 8).
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.