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8,038 results for “validation.”
Mapping file used for input validation in Quest for Orthologs
<pre>Mapping file used in the validation step and the map_relation.py step of the uploaded file format in QfO 2018 bechmarking workflow (https://github.com/qfo/benchmark-webservice/tree/elixir).</pre>
Focusgroepen, demografische gegevens respondenten, cognitive load en outdegrees i.k.v. validering SNI (pilootstudie)
<p>Dit zijn alle data (met uitzondering van de ruwe SNI data, zie andere dataset) verzameld i.k.v. de pilootstudie van het SNI. Deze pilootstudie was de basis voor de validering van het SNI. Drie lagere en 2 secundaire scholen namen deel aan deze pilootstudie. Deze dataset bevat:</p> <p>- De demografische gegevens van de respondenten (zie 'Overkoepelende data pilootstudie) en een apart bestand met de demografische gegevens van de respondenten die deelnamen aan het kwalitatief luik (dit zijn de interviews en focusgroepen, zie data participanten kwali luik). Naast de demografische gegevens bevatten deze databestanden ook de scores op de cognitive load scale en de outdegree van iedere respondent voor de 4 netwerkvragen.</p> <p>- De audiobestanden van de interviews en focusgroepen.</p> <p>- De transcripties van de interviews en focusgroepen.</p> <p>- Een document waarin de opbouw van de interviews en focusgroepen worden toegelicht (zie 'organisatie en leidraad...').</p> <p>- Een verslag van ieder interview/focusgroep.</p>
A soil moisture-dependent model to simulate water table depth and proportions of surface and subsurface runoff and its validation at basin scale
<p>The data is the simulations of the SMD-model, Sy-mdoel, adn Noah-MP in three basins in China and the USA. The vaiables are monthly water table depth, soil moisture, subsurface and total runoff. </p>
Validation of FHL-5TEST
<p>The dataset contains responses during the validation study of the FHL-5TEST conducted in 2018 in the Philippines. </p>
DESIGN AND VALIDATION OF THE INVENTORY OF NEGATIVE TEACHER ATTITUDES TOWARDS THE CARE OF STUDENTS WITH TYPE 1DIABETES MELLITUS (INAPAD)
<p>Data set of the article: <em>DESIGN AND VALIDATION OF THE INVENTORY OF NEGATIVE TEACHER ATTITUDES TOWARDS THE CARE OF STUDENTS WITH TYPE 1DIABETES MELLITUS (INAPAD)DESIGN AND VALIDATION OF THE INVENTORY OF NEGATIVE TEACHER ATTITUDES TOWARDS THE CARE OF STUDENTS WITH TYPE 1DIABETES MELLITUS (INAPAD)</em></p>
Dataset related to the article "Validation of a new wearable device for type 3 sleep test without flowmeter" 2021
<p><strong>Background: </strong>Ventilation monitoring during sleep is performed by sleep test instrumentation that is uncomfortable for the patients due to the presence of the flowmeter. The objective of this study was to evaluate if an innovative type 3 wearable system, the X10X and X10Y, is able to correctly detect events of apnea and hypopnea and to classify the severity of sleep apnea without the use of a flowmeter.</p> <p><strong>Methods: </strong>40 patients with sleep disordered breathing were analyzed by continuous and simultaneous recording of X10X and X10Y and another certified type 3 system, SOMNOtouch, used for comparison. Evaluation was performed in terms of quality of respiratory signals (scores from 1, lowest, to 5, highest), duration and classification of apneas, as well as identification and duration of hypopneas.</p> <p><strong>Results: </strong>580 periods were evaluated. Mean quality assigned score was 3.37±1.42 and 3.25±1.35 for X10X and X10Y and SOMNOtouch, respectively. The agreement between the two systems was evaluated with grades 4 and 5 in 383 out of 580 cases. A high correlation (r2 = 0.921; p<0.001) was found between the AHI indexes obtained from the two systems. X10X and X10Y devices were able to correctly classify 72.3% of the obstructive apneas, 81% of the central apneas, 61.3% of the hypopneas, and 64.6% of the mixed apneas when compared to SOMNOtouch device.</p> <p><strong>Conclusion: </strong>The X10X and X10Y devices are able to provide a correct grading of sleep respiratory disorders without the need of a nasal cannula for respiratory flow measurement and can be considered as a type 3 sleep test device for screening tests.</p>
Is SF-12 a valid and reliable measurement of health-related quality of life among adults with Marfan syndrome? A confirmatory study
<p>Dataset from Udugampolage N, Caruso R, Panetta M, Callus E, Dellafiore F, Magon A, Marelli S, Pini A. Is SF-12 a valid and reliable measurement of health-related quality of life among adults with Marfan syndrome? A confirmatory study. PLoS One. 2021 Jun 9;16(6):e0252864. doi: 10.1371/journal.pone.0252864. PMID: 34106976; PMCID: PMC8189474.</p> <p>Abstract</p> <p><strong>Introduction: </strong>The structural validity and reliability of the Short-Form Health Survey 12 (SF-12) has not yet been tested in adults with the Marfan syndrome (MFS). This gap could undermine an evidence-grounded practice and research, especially considering that the need to assess health-related quality of life in patients with MFS has increased due to the improved life expectancy of these patients and the need to identify their determinants of quality of life. For this reason, this study aimed to confirm the dimensionality (structural validity) of the SF-12, its concurrent validity, and its reliability (internal consistency).</p> <p><strong>Methods: </strong>We performed a cross-sectional study in a convenience sample of 111 Italian adults with MFS, collecting anamnestic and socio-demographic information, the SF-12, and short-form Health Survey 36 (SF-36). A confirmatory factor analysis was performed to verify whether the items of SF-12 related to physical restrictions, physical functioning, and bodily pain were retained by the physical summary component of the SF-12. The items referred to the role limitations due to emotional issues, social functioning, and mental health were retained by the mental summary component (MCS12). SF-36 was used to assess the concurrent validity of SF-12, hypothesizing positive correlations among the equivalent summary scores.</p> <p><strong>Results: </strong>The two-factor structural solution resulted in fitting the sample statistics adequately. The internal consistency was adequate for the two factors. Furthermore, the physical and mental summary scores of the SF-36 were positively correlated with their equivalent summary scores derived from the SF-12.</p> <p><strong>Conclusions: </strong>This study confirmed the factor structure of the SF-12. Therefore, the use of SF-12 in clinical practice and research for assessing the health-related quality of life among adults with MFS is evidence-grounded. Future research is recommended to determine whether the SF-12 shows measurement invariance in different national contexts and determine eventual demographic variation in the SF-12 scores among patients with MFS.</p>
Validation in Spanish and British English of the Transgender Inclusive Behavior Scale (TIBS).
<p>Data sets of the article Validation in Spanish and British English of the Transgender Inclusive Behavior Scale (TIBS).</p> <p>SPSS data sets were used to perform Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) in Spain and the United Kingdom.</p>
data set related to article Validation of the Proposed Specifiers for Conduct Disorder (PSCD) Scale in a Sample of Italian Students
<p>This record contains raw data related to article Validation of the Proposed Specifiers for Conduct Disorder (PSCD) Scale in a Sample of Italian Students</p>
Dataset for manuscript "Development of a 3D cytotoxicity assay for the validation of T cell anti-tumor reactivity"
<p>Dataset of the raw data files for the manuscript <em>Development of a 3D cytotoxicity assay for the validation of T cell anti-tumor reactivity. </em>Access upon request only. </p>
Validation of manifold-based direct control for a brain-to-body neural bypass - Data
<p>This repository contains the raw data of the study "<em>Validation of manifold-based direct control for a brain-to-body neural bypass". </em></p>
Dataset for the project "Towards precision medicine in psychiatry: clinical validation of a combinatorial pharmacogenomic approach" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-2016-02361697)
<p><strong>Dataset for the project “Towards precision medicine in psychiatry: clinical validation of a combinatorial pharmacogenomic approach” Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-2016-02361697)</strong></p> <p><strong>Aim 1</strong>: Assessment of the validity and clinical utility of a pharmacogenetic test in the selection of antidepressant treatment for patients with Major Depressive Disorder.</p> <p><strong>Aim 2</strong>: Pharmacokinetic analysis and identification of novel genetic variants linked with no response to treatment and/or with the occurrence of side effects.</p> <p><strong>Aim 3</strong>: Implementation of the combinatorial algorithm based on possible new findings.</p> <p>This dataset contains :</p> <ul> <li><strong>RawData_Aim1</strong></li> </ul> <p>· Materials and Methods for Aim 1 (Materials and methods_RawData_Aim1)</p> <p>· An Excel table (RF16 - Genotyping - Aim1) with the following sheets:</p> <p>- Sheet 1: Genotyping results</p> <p>- Sheet 2: Metabolizer phenotype results for CYP2D6 and CYP2C19 genes</p> <ul> <li><strong>RawData_Aim2</strong></li> </ul> <p>· Materials and methods Sequencing_RawData_Aim2</p> <p>· Materials and methods Pharmacokinetics_RawData_Aim2</p> <p>· VCF data from sequencing analysis (filtered_variants - Aim2)</p> <p>· Pharmacokinetics analysis (Pharmacokinetics Data_Aim2)</p> <ul> <li><strong>RawData_Aim3</strong></li> </ul> <p>· An Excel table with data from clinical assessments (Clinical Data_Aim3)</p>
Ecological validity of performance-based cognitive screeners in amyotrophic lateral sclerosis: preliminary evidence
<p>Dataset associated with the paper "Ecological validity of performance-based cognitive screeners in amyotrophic lateral sclerosis:<br>preliminary evidence". Data cannot be made publicly available on ethical-legal grounds but can be made available upon reasonable request of interested researchers to the corresponding author (Dr. Barbara Poletti; e-mail: b.poletti@auxologico.it), who will forward a request for a data transfer agreement to the relevant Ethical Committee.</p>
Development and validation of a prediction model using sella magnetic resonance imaging-based radiomics and clinical parameters for diagnosis of growth hormone deficiency and idiopathic short stature: A multicenter, cross-sectional study
Open the record for dataset details and reuse information.
Artifacts for Code Coverage Profiler Validation with Debugging Support
<p><strong>Code Coverage Profiler Validation with Debugging Support</strong></p> <p>Table of Contents</p> <ul> <li>Background</li> <li>Install</li> <li>Usage</li> <li>Experiment</li> <li>Violations</li> <li>Bugs</li> </ul> <p><strong>Background</strong></p> <p><strong>DeCov</strong> is the tool for code coverage profiler validation with debugging support. We totally submit 24 bug reports for gcov and llvm-cov. Of these 24 bug reports, 18 are confirmed/fixed by developers, 2 are marked as duplicate, and the other 4 bug reports are waiting for the developers' confirmation.</p> <p><strong>Install</strong></p> <p>This project uses <a href="https://gcc.gnu.org/">gcc</a>, <a href="http://www.gnu.org/software/gdb/">gdb</a>, <a href="http://llvm.org/">llvm</a> and <a href="http://lldb.llvm.org/">lldb</a>. Go check them out if you don't have them locally installed.</p> <p><code>apt install gcc gdb llvm lldb </code></p> <p><strong>Usage</strong></p> <p>To use DeCov for gcov validation:</p> <p><code>python3 decov-gcov-pexpect.py -s test.c </code></p> <p>or</p> <p><code>python3 decov-gcov-pexpect.py -s testprograms </code></p> <p>To use DeCov for llvm-cov validation:</p> <p><code>python3 decov-llvmcov-pexpect.py -s test.c </code></p> <p>or</p> <p><code>python3 decov-llvmcov-pexpect.py -s testprograms </code></p> <p><strong>Experiment</strong></p> <p>First, download the gcc-10.1.0.tar.xz:</p> <p><code><code>wget http://ftp.gnu.org/gnu/gcc/gcc-10.1.0/gcc-10.1.0.tar.xz </code></code></p> <p>Then, unzip gcc-10.1.0:</p> <p><code>tar -xvf gcc-10.1.0.tar.xz </code></p> <p>Finally, run Decov over the testsuite of gcc-10.1.0:</p> <p><code>python3 decov-gcov-pexpect.py -s gcc-10.1.0/gcc/testsuite/ </code></p> <p>or</p> <p><code>python3 decov-llvmcov-pexpect.py -s gcc-10.1.0/gcc/testsuite/ </code></p> <p>Note that, we recommend to use the parallel option when using our tool if your computer has multi-cores:</p> <p><code>python3 decov-gcov-pexpect.py --parallel -s gcc-10.1.0/gcc/testsuite/ </code></p> <p>or</p> <p><code>python3 decov-llvmcov-pexpect.py --parallel -s gcc-10.1.0/gcc/testsuite/ </code></p> <p><strong>Violations</strong></p> <p>Experimental data are in the Expr folder:</p> <ul> <li>files-DIFFCOV-gcc.txt and files-DIFFCOV-clang.txt list the filenames in the testsuites of GCC-10.1.0 that the coverage statistics from coverage profilers inconsistent with the hit count from debuggers</li> <li>DIFFCOV-Gcov-vs-GDB.txt and DIFFCOV-LLVMcov-vs-LLDB.txt list the filesname and the the respected lines of code that violating <em>HMR</em>, coverage statistics is not consistent with the hit count</li> <li>files-SAMECOV-gcc.txt and files-SAMECOV-clang.txt list the filenames in the testsuites of GCC-10.1.0 that the coverage statistics from coverage profilers consistent with the hit count from debuggers.</li> <li>files-CPLERROR-gcc.txt and files-CPLERROR-clang.txt list the filenames in the testsuites of GCC-10.1.0 that cannot be correctly compiled independently by respected compilers</li> </ul> <p><strong>Bugs</strong></p> <p>Bugs reported by <strong>DeCov</strong> for LLVM-cov:</p> <p>llvm-cov 48818 Status History: "NEW"</p> <p>llvm-cov 48795 Status History: "NEW"</p> <p>llvm-cov 48278 Status History: "NEW" -> "DUPLICATE"</p> <p>llvm-cov 48264 Status History: "NEW" -> "INVALID" -> "REOPENED"</p> <p>llvm-cov 48263 Status History: "NEW"</p> <p>llvm-cov 45850 Status History: "New" -> "CONFIRMED"</p> <p>llvm-cov 45849 Status History: "New" -> "FIXED" -> "REOPENED" -> "FIXED"</p> <p>llvm-cov 45846 Status History: "NEW" -> "CONFIRMED"</p> <p>llvm-cov 45845 Status History: "NEW" -> "CONFIRMED"</p> <p>llvm-cov 45844 Status History: "NEW" -> "DUPLICATE"</p> <p>llvm-cov 45821 Status History: "NEW" -> "CONFIRMED"</p> <p>llvm-cov 45678 Status History: "NEW" -> "CONFIRMED"</p> <p>llvm-cov 45595 Status History: "NEW" -> "CONFIRMED"</p> <p>Bugs reported by <strong>DeCov</strong> for Gcov:</p> <p>gcov 97925 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 97924 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 97923 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 97917 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 97910 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 93757 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 93735 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 93726 Status History: "UNCONFIRMED" -> "WAIT"</p> <p>gcov 93725 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 93706 Status History: "UNCONFIRMED" -> "NEW"</p> <p>gcov 93680 Status History: "UNCONFIRMED" -> "NEW"</p>
The development and validation of an Inhomogeneous Wind Scheme for Urban Street
<p>The dataset contains:</p> <ul> <li>The CFD simulation results of vertical wind profile at six typical positions with the simulation settings in <a href="https://github.com/krmyArag/IWSUS.git">https://github.com/krmyArag/IWSUS.git</a>. (fig3-fig5) </li> <li>Wind profiles schemes and functions based on inhomogenous urban canopy in IWSUS-v0.1. (fig6-fig7, supplement.docx)</li> <li>Validation of wind profiles: observation and simulation in varies scenerios(Fig 8 - 10)</li> <li>Validation of surface energy flux and skin temperature in and over a street canyon in Gotherburg: observation and simulations. </li> </ul> <p>The CFD simulation result data for perpendicular and parallel scenerios can be found at https://doi.org/10.5281/zenodo.7371305 and https://doi.org/10.5281/zenodo.7371804 respectively.</p>
Dataset related to article "Transversal hepatectomies: Classification and intention-to-treat validation of new parenchyma-sparing procedures for deep-located hepatic tumors"
<p>This record contains raw data related to article “Transversal hepatectomies: Classification and intention-to-treat validation of new parenchyma-sparing procedures for deep-located hepatic tumors"</p> <p> </p> <p>Background: Deep-located liver tumors involving hepatic veins at the caval confluence or main Glisso- nean pedicles generally require a major hepatectomy. An intraoperative ultrasound guidance policy opened a possibility to opt for parenchyma-sparing procedures as alternatives to major hepatectomy, called transversal hepatectomies. We ought to standardize the procedure and analyze the surgical outcome, oncological suitability, and salvageability.</p> <p>Methods: This is a retrospective cohort study. All consecutive patients undergoing hepatectomies for liver tumors between January 2005 and August 2020 were reviewed. Transversal hepatectomies were classified as follows: upper transversal hepatectomy: resection of the posterosuperior segments along with at least 1 hepatic vein and preservation of the anteroinferior ones; roller coaster hepatectomy: transversal hepatectomy with tumor vessel detachment from at least 2 hepatic veins; and lower transversal hepatectomy: amputation of the distal portion of at least 1 hepatic vein with tumor vessel detachment from first/second-order Glissonean pedicles. Morbidity, mortality, local recurrences, and salvageability in cases of relapse were considered.</p> <p>Results: A total of 61 transversal hepatectomies were performed: 40 (66%) upper transversal hepatec- tomies, 19 (31%) roller coaster hepatectomies, and 2 (3%) lower transversal hepatectomies. The median preserved liver volume was 67% (range 41e86). Mortality was 0, and major morbidity was 6%. Local recurrence occurred in 7 (11%) patients. Ten out of 34 (29%) patients with liver-only recurrence received redo surgery.</p> <p>Conclusion: Transversal hepatectomies offer a new parenchyma-sparing perspective for the manage- ment of complex tumor presentation, which would otherwise demand major tissue removal or even unresectability. Safety, adequate local control, and salvageability are further pillars of this approach herein systematized.</p>
Validity and diagnostics of the Reading the Mind in the Eyes Test (RMET) in non-demented amyotrophic lateral sclerosis (ALS) patients
<p>Dataset associate with the paper: "Validity and diagnostics of the Reading the Mind in the Eyes Test (RMET) in non-demented amyotrophic lateral sclerosis (ALS) patients".</p>
CBE validation and market share
<p>Dataset of CBE validation and market share</p>
Validation of a Bluetooth-Enabled Load Cell for Objective and Accessible Assessment of Lower Extremity Strength
<p>Raw data used in validating a novel rehabilitation system (PhyzViz) against an isokinetic dynamometer (Biodex, gold standard) for plantarflexion maximal voluntary isometric contractions (MVICs).</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.