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10,553 results for “measurements”
Electrical measurement of coated steels
<p>Electrical measurements of AISI441 coated with Cu-Mn spinel and Crofer 22 APU coated with Co-Mn spinel.</p> <p>Measurement were carried out up to 400 hours, at 750°C and 850°C.</p> <p>At different times were also measured the electrical properties versus temperature to measure the activation energy of conduction.</p>
Datasets for "Evaluating the performance of a Picarro G2207-i analyser for high-precision atmospheric O2 measurements"
<p>These data files contain the data used in the manuscript "Evaluating the performance of a picarro G2207-i analyser for high-precision atmospheric O2 measurements" submitted to Atmospheric Measurement Techniques. </p> <p>WAO_G2207i_O2_calibrated_AM_all : Calibrated O2 measurements from the G2207-i during the no-drying, partial-drying, and full-drying periods at WAO, for both the water-corrected and non-water corrected outputs</p> <p>CRAM_lab_run1_noRT : calibrated O2 measurements for the first run of cylinder gases in the CRAM lab, UEA, without reference tank correction</p> <p>CRAM_lab_run1_wRT : calibrated O2 measurements for the first run of cylinder gases in the CRAM lab, UEA, with reference tank correction applied</p> <p>CRAM_lab_run2_noRT : calibrated O2 measurements for the second run of cylinder gases in the CRAM lab, UEA, without reference tank correction</p> <p>CRAM_lab_run2_wRT : calibrated O2 measurements for the second run of cylinder gases in the CRAM lab, UEA, with reference tank correction applied</p>
Characterizing Measures for the Assessment of Cluster Analysis and Community Detection
<p><strong>Description. </strong>The dataset is constituted of:</p> <ul> <li>`figs.zip`: an archive containing the plot files;</li> <li>`data&results.zip`: an archive containing the necessary data to perform our analysis, as well as result files.</li> </ul> <p>These are the resources used in the following articles:</p> <ol> <li>N. Arınık, V. Labatut and R. Figueiredo, "Characterizing measures for the assessment of cluster analysis and community detection", Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques (MARAMI), 2020. ⟨<a href="https://hal.archives-ouvertes.fr/hal-02993542">hal-02993542</a>⟩</li> <li>N. Arınık, R. Figueiredo, and V. Labatut, “Characterizing and comparing external measures for the assessment of cluster analysis and community detection,” <em>IEEE Access </em>9:20255–20276, 2021. DOI: <a href="http://doi.org/10.1109/access.2021.3054621">10.1109/access.2021.3054621</a> ⟨<a href="https://hal.archives-ouvertes.fr/hal-03124118">hal-03124118</a>⟩</li> </ol> <p><strong>Source code. </strong>The associated source code is available on GitHub: <a href="https://github.com/CompNet/ExtMeasEval">https://github.com/CompNet/ExtMeasEval</a></p> <p><strong>Citation. </strong>If you use these data, please cite the paper [2].</p> <p><br><code>@Article{Arinik2021,</code><br><code> author = {Arınık, Nejat and Figueiredo, Rosa and Labatut, Vincent},</code><br><code> title = {Characterizing and Comparing External Measures for the Assessment of Cluster Analysis and Community Detection},</code><br><code> journal = {IEEE Access},</code><br><code> year = {2021},</code><br><code> volume = {9},</code><br><code> pages = {20255-20276},</code><br><code> doi = {10.1109/access.2021.3054621},</code><br><code>}</code></p>
Number of chamber measurement locations for accurate quantification of landscape-scale greenhouse gas fluxes: Importance of land use, seasonality, and greenhouse gas type
<p>Contains all raw data measured in the Schwingbach Earth Observatory (SEO) from Spring, Summer and Autumn 2020. Data was measured with an on-site LGR laser from the GHG emissions, and with 100cm³ soil cores for the soil characteristics. Details can be found in the corresponding manuscript "Number of chamber measurement locations for accurate quantification of landscape-scale greenhouse gas fluxes: Importance of land use, seasonality, and greenhouse gas type"</p>
Supporting data for the article "Charge-Induced Artifacts in Nonlocal Spin-Transport Measurements: How to Prevent Spurious Voltage Signals"
<p>Supporting data for the article "Charge-Induced Artifacts in Nonlocal Spin-Transport Measurements: How to Prevent Spurious Voltage Signals"</p> <p>If the design files are used to reproduce the current source, we ask to cite the peer-reviewed publication of our work in any publication in which the adjustable virtual ground feature is used for measurements.</p> <p>We provide the following data and design files:</p> <p>1.) Data used to create each figure both in the main manuscript and the supplementary material in the zip-folder "Data presented in figures".<br> The data is provided in two formats:<br> I.) Raw data in freely accessible file formats such as .dat, .txt, or .csv.<br> II.) Graphically processed data (figures as shown in the publication) in the proprietary file format .opju. Used program: OriginPro 2019</p> <p>2.) LTspice models in the zip-folder "LTspice models". The simulations were conducted with LTspice version XVII(x64).</p> <p>3.) Altium Designer files of the current source in the zip-folder "Altium Designer files".</p> <p>4.) Gerber X2 and NC drill files (dimensions in millimeters) for the manufacturing of the PCB that is used in our project in the zip-folder "Fabrication files". See the readme file in the directory for more information on the fabrication process.</p> <p>5.) A bill of materials.</p>
The effect of pseudofrazil particle entrainment on salinity measurements: Data
<p>This experiment was designed to investigate the effect of entraining frazil ice particles found in supercooled ocean water by mimicking their effect through plastic particles of similar material properties as ice. <br> This was done in order to better control the volume concentration of the particles and avoid damage to sensors by icing which is common in supercooled water.<br> In total six experiments were run in which non-spherical round polyamide-12 seeding particles made by Dantec Dynamics A/S with a mean diameter of 50 micro meters were added to natural saltwater tinged with surfactant whilst recording temperature and conductivity with Sea-Bird Electronics sensors. <br> Surfactant was Ecostore-brand eucalyptus laundry liquid (ingredients can be found here: https://ecostore.com/au/eucalyptus-laundry-liquid-409/, last accessed July 2022).<br> Experiments are H1, H2 and HC performed with saltwater taken from Otago Harbour, Dunedin, New Zealand and M1, M2 and MC performed with saltwater taken from the Munida Transect offshore of Otago Peninsula, Dunedin, New Zealand.<br> HC and MC were run in a walk-in freezer with water temperatures around -1 degrees C, all other experiments were performed at ambient room temperatures.<br> The setup consisted of a 30 litre bucket containing 24 litres of seawater filtered to 1 micro meter. Surfactant was added to the water to aid particle dispersion. <br> Subsequently particles were added in increments to a total mass of particles in the bucket of 100 g.<br> Temperature was recorded with a SBE3plus temperature sensor and conductivity with a SBE4C sensor. <br> These were connected to a SBE pump with standard SBE CT ducting. <br> Data were recorded with a SBE31 deck unit connected to a laptop computer.<br> Data were recorded continuously, times at which particles were added or other operations performed are given in the tables <experimentname>info.xlsx<br> Raw data were converted using the sensors' calibration coefficients and corrected for CT offset and cell thermal mass using the SBE data processing software and standard values for sensors configured as in the SBE911+ setup, which is equivalent to the ducting used by us.<br> A manuscript with results from these experiments is available as Richter, M. E., et al., 2023, The Effect of Pseudofrazil Particle Entrainment on Salinity Measurements, Earth and Space Science, doi:10.1029/2022EA002564</p> <p>. </p>
Radio-frequency C-V measurements with subattofarad sensitivity: data and analysis script
<p>The attached files include:</p> <ul> <li>QCoDeS database containing all of the raw data underlying the results presented in the publication "Radio-frequency CV measurements with subattofarad sensitivity" by F.K. Malinowski at al. published in Physical Review Applied in 2022</li> <li>Jupyter Notebook file with Python scripts, that processes the raw data and outputs the figures embedded in the publication (except for the schematics of the devices and the rf circuitry).</li> </ul>
Angle measurements with 3D Vector antenna for localization purposes – open-access datasets
<p>This dataset contains data on positioning measurements of the angle of arrival (AoA) as well as the azimuth angle estimation using the MUSIC Algorithm. The data was collected from four ports (p1,p2,p3,p4) of a 3D Vector Antenna (3D VA) provided by ENAC. Data were captured in a laboratory environment with conditions that affect the positioning performance. </p>
Secondary Data: Measuring Person-centred Care in German Nursing Homes – Exploring Construct Validity of the Dementia Policy Questionnaire using Adjusted Multiple Correspondence Analysis
<p>This is the secondary data set and R-Code of R statistical software (version 4.0.4) to explore construct validity of the German Dementia Policy Questionnaire using Adjusted Multiple Correspondence Analysis.</p>
Total magnetic field measurements Piton de la Fournaise 2017-2019-2020
<p>Piton de la Fournaise northern profile</p> <p>* File number:<br> nT_yyyy_mm_dd.txt</p> <p>* File format (5 columns): <br> Coordinates (in m) Total magnetic field <br> X Y Z pre-filtered magnetic data (in nT) index of quality (>80)</p> <p><br> * Magnetic reiteration campaigns funded by:<br> ANR contract 16-CE04-0004-01 SlideVOLC<br> ANR contract 21-CE49-0015 Scan4Volc<br> Centre National d'Études Spatiales (CNES)<br> Laboratory of Excellence ClerVolc </p>
Dataset for "Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements"
<p>The final dataset used in manuscript "Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements" by Kohonen et al. (2022). The dataset contains carbonyl sulfide (COS) and carbon dioxide (CO2) eddy covariance flux data and in-situ meteorological data measured at Hyytiälä forest in Juupajoki, Southern Finland, as well as GPP estimates derived from COS and CO2 flux measurements as described in the manuscript from January 2013 to December 2017. Raw data are available upon request from the author.</p>
OMOP2OBO Measurement Mappings
<p><strong>OMOP2OBO Measurement Mappings V1.0</strong></p> <p>The mappings in this repository were created between OMOP standard measurement concepts (i.e., LOINC) to the Human Phenotype Ontology (HPO), Chemical Entities of Biological Interest (CheBI), Vaccine Ontology (VO), National Center for Biotechnology Information Taxon Ontology (NCBITaxon), Protein Ontology (PRO), Cell Ontology (CL), and the Uber-anatomy Ontology (UBERON).</p> <p>For each measurement, all levels of the test result (results above, below, and within a reference range) were mapped, not only those deemed clinically relevant. Results outside of a reference range, but not currently deemed clinically relevant (as advised by the literature or consultation via domain expert), were annotated to the nearest relevant ontology concept ancestor. For example, when annotating the results of a test for Asparagus IgE Ab RAST class [Presence] in Serum (LOINC:15547-3), a result above a reference range would be annotated with an increased anti-plant-based food allergen IgE antibody level (HP:0410228). While a low level of this antibody may not be deemed clinically relevant, it is still outside of the provided reference range and thus was annotated to the nearest applicable concept ancestor, abnormal immunoglobulin level (HP:0010701). There is one exception to this rule: all measured drugs and toxins (entities not normally found in the human body) with normal results (results that were not outside of a given reference range) were annotated to the same HP concept as the clinically relevant result and logically negated. For example, Amphetamine [Presence] in Urine by Screen (LOINC:19343-3), a positive finding was mapped to a positive urine amphetamine test (HP:0500112) and a negative finding was mapped to a positive urine amphetamine test and logically negated (NOT HP:0500112).</p> <p>LOINC2HPO currently aligns LOINC to HP. The current work extends existing LOINC2HPO annotations to match the OMOP2OBO mappings in the following two ways: (1) annotations were updated if new and/or more specific concepts had been added to the HP; and (2) existing mappings were expanded to include the measurement substance (body fluids, tissues, and organs via Uberon), the entity being measured (chemicals, metabolites, or hormones via ChEBI; cell types via CL; and proteins and protein complexes via PR), and the species of the measured entities (organism taxonomy via NCBITaxon). Consistent with LOINC2HPO, all measurements lacking sufficient specimen detail (those measured in non-specific body substances) were annotated as “Unspecified Sample” and all measurements without a valid result type were annotated as “Not Mapped test Type”. All modifications to the original LOINC2HPO annotations were meticulously recorded in the mapping evidence field enabling users to easily identify when an original LOINC2HPO annotation had been updated.</p> <p>For this OMOP domain, the owl:complementOf (“not” and was used to model normal test results), owl:intersectionOf (“and”), and owl:unionOf (“or”) constructors were used to construct semantically expressive mappings.</p> <p><br> <strong>Mapping Details</strong><br> Mappings included in this set were generated automatically using OMOP2OBO or through the use of a Bag-of-words embedding model using TF-IDF. Cosine similarity is used to compute similarity scores between all pairwise combinations of OMOP and OBO concepts and ancestor concepts. To improve the efficiency of this process, the algorithm searches only the top 𝑛 most similar results and keeps the top 75th percentile among all pairs with scores >= 0.25. Manually created mappings are also included.</p> <p><strong><em>Mapping Categories</em></strong></p> <ul> <li><strong>Automatic One-to-One Concept</strong>: Exact label or synonym, dbXRef, or expert validated mapping @ concept-level; 1:1</li> <li><strong>Automatic One-to-One Ancestor:</strong> Exact label or synonym, dbXRef, or expert validated mapping @ concept ancestor-level; 1:1</li> <li><strong>Automatic One-to-Many Concept: </strong>Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many</li> <li><strong>Automatic One-to-Many Ancestor:</strong> Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many</li> <li><strong>Manual One-to-One: </strong>Hand mapping created using expert suggested resources; 1:1</li> <li><strong>Manual One-to-Many:</strong> Hand mapping created using expert suggested resources; 1:Many</li> <li><strong>Cosine Similarity:</strong> score suggested mapping -- manually verified</li> <li><strong>UnMapped:</strong> No suitable mapping or not mapped type</li> </ul> <p><em><strong>Mapping Statistics</strong></em><br> Additional statistics have been provided for the mappings and are shown in the table below. This table presents the counts of OMOP concepts by mapping category and ontology:</p> <table align="center"> <thead> <tr> <th scope="col">Mapping Category</th> <th scope="col">HPO</th> <th scope="col">UBERON</th> <th scope="col">ChEBI</th> <th scope="col">CL</th> <th scope="col">PR</th> <th scope="col">NCBITaxon</th> </tr> </thead> <tbody> <tr> <td>Automatic One-to-One Concept</td> <td>20</td> <td>1981</td> <td>268</td> <td>129</td> <td>19</td> <td>286</td> </tr> <tr> <td>Automatic One-to-Many Concept</td> <td>49</td> <td>5</td> <td>0</td> <td>24</td> <td>0</td> <td>0</td> </tr> <tr> <td>Automatic One-to-One Ancestor</td> <td>43</td> <td>426</td> <td>1149</td> <td>5</td> <td>5</td> <td>207</td> </tr> <tr> <td>Automatic Constructor - Ancestor </td> <td>0</td> <td>1</td> <td>12</td> <td>1</td> <td>0</td> <td>0</td> </tr> <tr> <td>Cosine Similarity</td> <td>113</td> <td>50</td> <td>160</td> <td>35</td> <td>45</td> <td>56</td> </tr> <tr> <td>Manual</td> <td>10663</td> <td>319</td> <td>1446</td> <td>185</td> <td>1590</td> <td>2357</td> </tr> <tr> <td>Manual One-to-Many</td> <td>49</td> <td>1118</td> <td>528</td> <td>18</td> <td>133</td> <td>196</td> </tr> <tr> <td>UnMapped</td> <td>184</td> <td>184</td> <td>529</td> <td>3688</td> <td>2296</td> <td>982</td> </tr> </tbody> </table> <p><br> <strong>Provenance and Versioning: </strong>The V1.0 deposited mappings were created by OMOP2OBO v1.0.0 on October 2022 using the OMOP Common Data Model V5.0 and OBO Foundry ontologies downloaded on September 14, 2020. </p> <p><strong>Caveats:</strong> Please note that these are the original mappings that were created for the preprint. They have not been updated to current versions of the ontologies. In our experience, this should result in very few errors, but we do suggest that you check the ontology concepts used against current versions of each ontology before using them.</p> <p> </p> <p><strong>Important Resources and Documentation</strong></p> <ul> <li>GitHub: <a href="https://github.com/callahantiff/OMOP2OBO">OMOP2OBO</a></li> <li>Project Wiki: <a href="https://github.com/callahantiff/OMOP2OBO/wiki">OMOP2OBO - wiki</a></li> <li>Zenodo Community: <a href="https://zenodo.org/communities/omop2obo">OMOP2OBO</a></li> <li>Preprint Manuscript: <a href="https://doi.org/10.5281/zenodo.5716421">10.5281/zenodo.5716421</a></li> </ul>
In-stream solar radiation measurements in Miramichi River basin (Canada)
<p>This dataset and associated analysis describe the spatial (catchment and reach scale) and temporal (seasonal, daily and hourly scales) variability in the transmission coefficient, that is the ratio of in-stream solar radiation to above-canopy solar radiation which represents the proportion of incoming solar radiation reaching streams. Data were collected in the Miramichi River basin (Canada). In-stream solar radiation measurements were taken in a small headwater stream (Trib), a medium-sized stream (CatBk) and a wide river (LSWM).</p> <p> </p> <p> </p> <p> </p>
Data for "Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air 1 Quality in Beijing, China."
<p>These are the datasets that have been used for the article "Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air 1 Quality in Beijing, China," which is published in the journal <em>Atmospheric Chemistry and Physic</em><em>s</em>, by Foreback et al. (2022).</p>
Data set with length measurments of niches in Chachabamba
<p>For the metrological analysis, this type of data was obtained from a 3D point cloud and all measurements for Chachabamba architectural remains were collected in two data sets.The first group belongs to the central part of the sanctuary, called sector A, and consists of 39 measurements. The second group of measurements was collected from the water fountains located in the four corners of sector A, where 31 measurements were collected.</p>
Dataset of lake ozone flux measurements and auxiliary data
<p>Dataset of O<sub>3</sub> fluxes measured by the eddy covariance system over Lake Kuivajärvi during 23 days period in August and September 2012. The lake is located in the vicinity of the Hyytiälä Forestry Field Station and SMEAR II Station in Southern Finland. The dataset consists of post-processed and quality filtered fluxes and auxiliary measurements that were used in the analysis. The flux measurements were performed on the lake platform, by using an ultrasonic anemometer (Metek USA-1, GmbH, Elmshorn, Germany) to measure the three wind velocity components and sonic temperature and a fast chemiluminescent gas analyzer FOS (Sextant Technology Ltd, New Zealand) that measured O<sub>3</sub> concentration. </p>
Results of ultrasound measurements of sea-ice cores sampled during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019
<p>This dataset details the results of testing sea ice cores collected during the SCALE 2019 Winter Cruise using ultrasound techniques. </p>
Supplementary files for paper: "Design and fabrication of an electrostatic precipitator for infrared spectroscopy" in Atmospheric Measurement Techniques, 2022.
<ol> <li>File of absorbance spectra and hypothetical thickness for each sample.</li> <li>MATLAB function to perform clean crystal spectrum subtraction and baseline correction (described in the paper).</li> </ol>
The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip, supplementary table 3
<p>Supplementary table 3: Summary statistics from an EWAS assessing the relationship between variance in DNA methylation value and DNA input level.</p>
Data/Code: Objective monitoring of functional recovery after total knee and hip arthroplasty using sensor-derived gait measures
<p>Abstract</p> <p>Background: Inertial sensors hold the promise to objectively measure functional recovery after total knee (TKA) and hip arthroplasty (THA), but their value in addition to patient-reported outcome measures (PROMs) has yet to be demonstrated. This study investigated recovery of gait after TKA and THA using inertial sensors, and compared results to recovery of self-reported scores of pain and function.</p> <p>Methods: PROMs and gait parameters were assessed before and at two and fifteen months after TKA (n=24) and THA (n=24). Gait parameters were compared with healthy individuals (n=27) of similar age. Gait data were collected using inertial sensors on the feet, lower back, and trunk. Participants walked for two minutes back and forth over a 6m walkway with 180° turns. PROMs were obtained using the Knee Injury and Osteoarthritis Outcome Scores and Hip Disability and Osteoarthritis Outcome Score.</p> <p>Results: Gait parameters recovered to the level of healthy controls after both TKA and THA. Early improvements were found in gait-related trunk kinematics, while spatiotemporal gait parameters mainly improved between two and fifteen months after TKA and THA. Compared to the large and early improvements found in of PROMs, these gait parameters showed a different trajectory, with a marked discordance between the outcome of both methods at two months post-operatively.</p> <p>Conclusion: Sensor-derived gait parameters were responsive to TKA and THA, showing different recovery trajectories for spatiotemporal gait parameters and gait-related trunk kinematics. Fifteen months after TKA and THA, there were no remaining gait differences with respect to healthy controls. Given the discordance in recovery trajectories between gait parameters and PROMs, sensor-derived gait parameters seem to carry relevant information for evaluation of physical function that is not captured by self-reported scores.</p>
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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)
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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.