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8,038 results for “validation”
Experimental feeding validates nanofluidic array technology for DNA detection of ungulate prey in wolf scats
<p><span>The study of carnivores' diet is a key component to enhance knowledge on the ecology of predators and their effect on prey populations. Although molecular approaches to detect prey DNA in carnivore scats are improving, the validation of their accuracy, a prerequisite for reliable applications within ecological frameworks, is still lagging behind the methodological advances. Indeed, variation in detection probability among prey species can occur, representing a potentially insidious source of bias in food-habit studies of carnivores. Calibration of DNA-based methods involves the optimization of specificity and sensitivity and, whereas priority is usually given to the former to avoid false positives, sensitivity is rarely investigated so that false negatives may be largely overlooked. </span></p> <p><span>We conducted feeding trials with captive wolves (</span><em><span>Canis lupus</span></em><span>) to validate a nanofluidic array technology recently developed for detection of multiple prey species in scats. Using 371 scat samples from 12 wolves fed with a single-prey diet, the sensitivity of our nanofluidic array method varied between 0.45 and 0.95 for the six main ungulate prey species. The method sensitivity was enhanced by using multiple markers per species and by a relatively low threshold for the number of amplifying markers required to confirm a detection. Yet, at least two markers should be used to avoid false positives. By acknowledging sources of bias in sensitivity to reliably interpret results of DNA-based dietary methods, our study highlights the relevance of feeding experiments to optimally calibrate the relative thresholds to define a positive detection and investigate occurrence and extent of biases in sensitivity.</span></p>
SQAT v1_0: dataset of validation sounds
<p>Dataset of test sounds used to verify the psychoacoustic metrics implemented in the first release of the sound quality analysis toolbox (SQAT), version 1.0.</p> <p>In order to reproduce the verification codes in the <validation> folder of SQAT, this repository of test sounds needs to be downloaded and the paste <validation_SQAT_v1_0> has to be included in the <sound_files> folder of the toolbox.</p>
In silico prediction and biophysical validation of novel 14-3-3σ homodimer stabilizers
<p>this dataset is related to "In silico prediction and biophysical validation of novel 14-3-3σ homodimer stabilizers" Aljabal G., Teh, A.-H., Yap B.K.</p>
SRL data feedback in higher education and validation of microlearning proposal
<p>This dataset corresponds to those used for the SRL in the category Feedback. It also presents the data collected from a process of expert validation of a training proposal based on microlearning for the development of digital teacher competence related to feedback. </p>
National Taiwan Museum Rational Validity Assessment, May 2023
<p>This is the data gathered in order to perform a rational validity assessment of the National Taipei Museum, checking its displayed collection against its mission statement.</p>
Campype Validation Dataset
<p>Here you will find the raw reads and assembled genomes that were used to test CamPype (<a href="https://github.com/JoseBarbero/CamPype">https://github.com/JoseBarbero/CamPype</a>).</p>
Validation of a SARS-CoV-2 surrogate neutralization test detecting neutralizing antibodies against the major variants of concern
<p>SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) as well as VOC Delta, Omicron BA.1, BA.2 and BA.5. Performances were compared to the reference virus neutralization test (VNT) against the respective VOC using three different cohorts collected during the COVID waves. Pre-COVID samples confirmed 100% specificity of the sVNT. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman’s r=0.7081 for BA.1, r=0.7205 for BA.2 and r=0.6042 for BA.5), and for WT (r=0.8458) and Delta-sVNT (r=0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD commercial kits “Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit” and “Genscript cPass kit” revealed an overall good correlation ranging from 0.8673 to -0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity resulting in a Youden Index of 78.24. This midway trend was further confirmed on 100 double-vaccinated individuals. The BA.2-sVNT performance was similar to that of the Genscript test. Finally, sVNT ability to assess neutralizing antibodies against Omicron BA.5 was validated on a double-vaccinated cohort (n=100) and an Omicron-breakthrough infection cohort (n=91). Correlation analysis revealed a strong association (r=0.8583) between BA.5-sVNT and VNT. Accurate classification was confirmed by receiving operating characteristic (ROC) analysis reporting an area under the curve (AUC) of 0.9543. In conclusion, the sVNT allows for efficient prediction of immune protection against the various VOCs.</p>
Immunoassay and proteomics dataset: Identification and validation of urine CXCL-9 as a biomarker for diagnosis of acute interstitial nephritis
<p>Background: Acute tubulointerstitial nephritis (AIN) is one of the few causes of acute kidney injury with diagnosis-specific treatment options. However, due to the need to obtain a kidney biopsy for histological confirmation, AIN diagnosis can be delayed, missed, or incorrectly assumed. Here we identify and validate urine CXCL-9, an interferon-γ-induced chemokine involved in lymphocyte chemotaxis, as a diagnostic biomarker for AIN.</p> <p>Methods: In a prospectively-enrolled cohort with pathologist-adjudicated histological diagnoses (<em>discovery cohort</em>), we tested the association of 180 immune proteins measured by an aptamer-based assay with AIN and validated the top protein, CXCL-9, using sandwich immunoassay. We externally validated these findings in 2 cohorts with biopsy-confirmed diagnoses (<em>validation cohorts</em>) and examined mRNA expression differences in kidney tissue from patients with AIN and controls.</p> <p>Results: In aptamer-based assay, urine CXCL-9 was 7.6-fold higher in AIN than controls (<em>P</em>=1.23·10<sup>-5</sup>). Urine CXCL-9 measured by sandwich immunoassay was associated with AIN in the discovery cohort (n=204; 15% AIN) independently of currently available clinical tests for AIN (adjusted odds ratio for highest vs lowest quartile: 6.0; 95% CI: 1.8-20). Similar findings were noted in external validation cohorts, where CXCL-9 had an AUC of 0.94 (0.86-1.00) for AIN diagnosis. <em>CXCL9</em> mRNA expression was 3.9-fold higher in kidney tissue from patients with AIN (n=19) as compared with controls (n=52; P=5.8·10<sup>-6</sup>).</p> <p>Conclusion: We identified CXCL-9 as a biomarker for AIN diagnosis using aptamer-based urine proteomics, confirmed this association using sandwich immunoassays in discovery and validation cohorts, and observed higher expression of this protein in kidney biopsies with AIN. </p>
Validation of Polish-language questionnaires for assessing the quality of life of patients with Primary Ciliary Dyskinesia (PCD-QOL)
<p>In recent years, questionnaires were published in English to assess the quality of life of patients with PCD for adults, adolescents aged 13-17, and children aged 6-12 and their caregivers. The aim of this study was to prepare a Polish version of the questionnaires and validate them in specific age groups with the participation of Polish patients with PCD.</p>
ARCH-COMP 2023 Category Report: Falsification - Validation
<p>ARCH-COMP 2023 is an international competition on verifying continuous and hybrid systems. This archive refers to the falsification category of this competition. It contains the traces submitted for validation and the corresponding validation results.</p>
DP1577 – Carex ornithopoda Willd. (Cyperaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP1577 – Carex ornithopoda Willd. (Cyperaceae) – Détermination valide.
DP0690 – Malva alcea L. (Malvaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP0690 – Malva alcea L. (Malvaceae) – Détermination valide.
DP0539 – Rosa pendulina L. (Rosaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP0539 – Rosa pendulina L. (Rosaceae) – Détermination valide.
DP0033 – Aconitum napellus L. (Ranunculaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP0033 – Aconitum napellus L. (Ranunculaceae) – Détermination valide.
DP1845 – Phegopteris dryopteris (L.) Fée (Cystopteridaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP1845 – Phegopteris dryopteris (L.) Fée (Cystopteridaceae) – Détermination valide.
DP1290 – Lysimachia nummularia L. (Primulaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP1290 – Lysimachia nummularia L. (Primulaceae) – Détermination valide.
DP0410 – Physalis alkekengi L. (Solanaceae) – Détermination valide. in L'herbier Daniel Pellé (DP) - La collection d'un botaniste amateur de l'Aube (France)
DP0410 – Physalis alkekengi L. (Solanaceae) – Détermination valide.
Initial Sample of HYPERNETS Hyperspectral Surface Reflectance Measurements for Satellite Validation from the Barrax Site in Spain
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the Gobabeb HYPERNETS site in Barrax, Spain (BASP). It is a subset of the complete data record which consists of the best quality BASP measurements which could be used for satellite validation over the three day test deployment period. </p> <p>The provided NetCDF files are the L2A hypernets products with surface reflectances, their associated uncertainties and error-correlation information. The reflectance in the L2A products is the Hemispherical-directional Reflectance Factor (HDRF) defined as: HDRF = π L / E where L is the directional upwelling radiance (with field of view of 5 degrees) and E is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance). These reflectances have dimensions of wavelength and series, where each series is a set of measurements for a given geometry (combination of viewing zenith and azimuth angle). In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, number of valid scans used, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The BASP site was a temporary installation over the period of the 20<sup>th</sup> – 22<sup>nd</sup> July 2022 during the Surface Reflectance Intercomparison eXperiment (SRIX) campaign (https://frm4veg.org/srix4veg/) at the Las Tiesas experimental farm in Barrax, Spain. This location was selected due to its typical clear skies, flat terrain, and well-managed crops. The HYPSTAR®-XR (eXtended Range) was deployed in a small corn field next to the ongoing UAV experiment. The instrument was deployed on a 3.5m high pole with a short extended boom at 1.3m height from the crops, with measurements running every 30 minutes throughout the day (UTC+2) and measuring between viewing zenith angles of 0-60 degrees.</p> <p>The HYPSTAR®-XR instruments deployed at each land HYPERNETS site consist of a VNIR and a SWIR sensor and autonomously collect data between 380-1700 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm and the SWIR sensor has 220 channels between 1000 and 1700 nm with a FWHM of 10 nm. The hypernets_processor (Goyens et al. 2021; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. All of the products have associated uncertainties (divided into random and systematic uncertainties, including error-correlation information) which were propagated using the CoMet toolkit (www.comet-toolkit.org). </p> <p>To obtain this dataset, we start from the full BASP data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to remove outliers and only supply the best quality data suitable for satellite validation. To remove the outliers, a sigma-clipping method is used. First reflectances are extracted in separate 2 hour windows throughout the day (to account for BRDF differences due to different solar position) for 4 different wavelengths (500, 900, 1100 and 1600 nm). Outliers in these reflectances are then identified by iteratively calculating the mean reflectance trend with time (by binning the data per maximum 30 data points), calculating the standard deviation from this trend, and masking any data that is more than 3 standard deviations away from the trend. This process is repeated on the unmasked data until the standard deviation does not vary by more than 5% between two iterations. The masks for the 4 different wavelengths are then combined (keeping only measurements for which none of the 4 wavelengths is an outlier). The reflectances and associated uncertainties for any masked series (i.e. a geometry that is masked either by the sigma-clipping procedure or from the masks of the hypernets_processor) are replaced by NaNs. Any sequence that has more than half of its series masked is removed entirely. For BASP specifically, viewing zenith angles above 30 degrees have been removed, as well as any west-facing angles azimuth angles of 263,273 or 293 degrees) for viewing zenith angles of 5 degrees and 10 degrees. </p> <p>Note: In the accompanying .csv description file the measurement times are listed in (BST/ UTC+1) after UK time.</p>
Validation of the satellite-estimated sedimentation rates in reservoirs using 10-m Sentinel-2 satellites and water level data
<p><strong>Overview</strong>: The database contains data used for the validation of satellite-based sedimentation rates in eight reservoirs across the central and western United States using 10-m Sentinel-2 imagery and in-situ level data. Additional validation of the results from combining Sentinel-2 imagery with simulated 27-day Sentinel-3 altimetry levels is also included.</p> <p> </p> <p><strong>This dataset includes</strong>:</p> <ol> <li>Satellite-derived area-level duplets</li> <li>Bathymetry curves from satellite-based estimates</li> <li>Bathymetry curves from survey data</li> <li>Validation</li> </ol>
Validation of references provided by ChatGPT
<p>Validation of references provided by ChatGPT for the generation of communication strategies for the long-term involvement of participants in Citizen Science projects.<br> <br> Article: <strong>Unlocking long-term engagement with citizen science: communication strategies driven by complex thinking under an AI-assisted approach.</strong></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.