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8,038 results for “validation”
Figs 30-32 in Notes on Graptodytes SEIDLITZ, 1887, re-instatement of G. laeticulus (SHARP, 1882) as valid species and description of Tassilodytes nov.gen. from Algeria (Coleoptera, Dytiscidae, Hydroporinae, Siettitiina)
Figs 30-32: Tassilodytes parisii (GRIDELLI, 1939) (30) holotype, dorsal surface; (31) same, ventral surface; (32) holotype labels (scale bar 4.0 mm).
Figs 28-29 in Notes on Graptodytes SEIDLITZ, 1887, re-instatement of G. laeticulus (SHARP, 1882) as valid species and description of Tassilodytes nov.gen. from Algeria (Coleoptera, Dytiscidae, Hydroporinae, Siettitiina)
Figs 28-29: Graptodytes narentinus (ZIMMERMANN, 1915) (28) lectotype, habitus (scale bar 2.0 mm); (29) lectotype labels.
Figs 12-14 in Notes on Graptodytes SEIDLITZ, 1887, re-instatement of G. laeticulus (SHARP, 1882) as valid species and description of Tassilodytes nov.gen. from Algeria (Coleoptera, Dytiscidae, Hydroporinae, Siettitiina)
Figs 12-14: Graptodytes laeticulus (SHARP, 1882), details of ventral surface (12) arrows pointing to abruptly narrowed epipleuron and row of ridges; (13) row of ridges, enlarged; (14) deeply incised hind margin of metacoxal processes with broadly rounded lobes.
Figs 1-2 in Notes on Graptodytes SEIDLITZ, 1887, re-instatement of G. laeticulus (SHARP, 1882) as valid species and description of Tassilodytes nov.gen. from Algeria (Coleoptera, Dytiscidae, Hydroporinae, Siettitiina)
Figs 1-2: Graptodytes laeticulus (SHARP, 1882) (1) lectotype, habitus, glue-card with Sharp's male gender symbol; (2) lectotype labels.
Figure 2-Validation of a Web Application by Using a Limited Number of Web Pages
<p>Simplifying the method of verification and testing of the web applications and maximising<br> the quality of the verification is the principal objective for the time being. We consider that the<br> method we describe in the previous sections is an important step in this matter and, by combining<br> the present techniques of verification and testing with the mode of reducing the objects that need to<br> be tested we can obtain very good results in obtaining web application of very good quality that<br> function correctly. We believe that this idea of selecting certain components from a web application<br> can be developed by using other methods of comparison among the components (that can use notion<br> as those introduces in [3], [4], [7]).</p>
The Brain and Propranolol Pharmacokinetics in the Elderly-Figure 1.(a)Results of the Monte-Carlo simulations to describe pharmacokinetics of young patients with validation from the Taegtmeyer 2014 publication(Taegtmeyer et al., 2014)
<p>Propranolol has been found to be therapeutically effective, to obtain a clinical response by<br> beta-adrenoceptor blockade, at plasma levels of greater than 20 ng/mL(Coltart et al., 1971;<br> Frishman, 1988; Johnsson and Regàrdh, 1976). Thus, to display the data, we used highlighted<br> plasma concentration where the pharmacokinetic curve falls below 20ng/mL threshold for<br> therapeutic efficacy in the patient’s plasma.</p>
Validation of liquefaction retrofitting techniques from geotechnical centrifuge small scale models
<p>The dataset is composed by the results of 37 dynamic geotechnical centrifuge tests performed in the frame of the project:</p> <p>H2020-DRA-2015 <strong>LIQUEFACT: </strong><em>Assessment and mitigation of Liquefaction potential across Europe: a holistic approach to protect structures/infrastructure for improved resilience to earthquake-induced Liquefaction disasters.</em></p> <p>The experiments firstly reproduced on reduced scale models the liquefaction conditions and secondly tested the effectiveness of three mitigation techniques: vertical drains, horizontal drains, induced partial saturation.</p> <p>The dataset is strictly linked to the document <strong>"DELIVERABLE D4.2 - Report on validation of retrofitting techniques from small scale models"</strong>. This document is of public access and can be downloaded from the website of the project <a href="http://www.liquefact.eu/">www.liquefact.eu</a></p> <p>The document D4.2 illustrates the testing programme, the objectives, the experimental procedures and gives the elements for the interpretation of data.</p>
Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset
<p>Set of 200 3D point clouds used in the validation of "Leaf and wood classification framework for terrestrial LiDAR point clouds". This dataset is a collection of point clouds simulated by a Monte-Carlo ray tracing (librat) using four 3D tree models from the fourth phase RAMI exercise (Widlowski et al, 2015).</p>
Leaf and wood classification framework for terrestrial LiDAR point clouds: Field data validation dataset
<p>Set of 10 3D point clouds used in the validation of "Leaf and wood classification framework for terrestrial LiDAR point clouds". This dataset is a collection of single trees scanned around the globe, from different biomes (both forest and urban areas), using the Riegl VZ-400 terrestrial laser scanner.</p>
Validation of a standardized MRI method for liver fat and T2* quantification
<p><strong>Dataset description:</strong> These data have been uploaded and shared as part of the manuscript <em>“Validation of a standardized MRI method for liver fat and T2* quantification, Chloe Hutton, Michael L. Gyngell, Matteo Milanesi, Alexandre Bagur, and Michael Brady, Perspectum Diagnostics, Oxford, United Kingdom", which was submitted for publication to PLOS ONE on August 27th 2018.</em></p> <p><strong>Details:</strong> The LMSIDEAL_Results.zip file extracts into 28 MATLAB files (MATLAB R2017b) corresponding to LMS IDEAL PDFF results calculated as described in the above manuscript for 28 sets of publicly-available phantom data available from another repository. The original phantom data can be accessed from (<a href="http://dx.doi.org/10.5281/zenodo.48266)">http://dx.doi.org/10.5281/zenodo.48266)</a> and are described in detail in [Hernando et al., Magn Reson Med. 2017;77:1516-1524. doi: 10.1002/mrm.26228. Epub 2016 Apr 15.].</p> <p>To summarise, the original phantom data were acquired using one phantom at six sites, covering: 3 vendors (GE Healthcare, Siemens and Philips); 2 field strengths (1.5T and 3T); and 2 protocols. One of the six sites had two sets of data (one at the beginning of the phantom study and one at the end), to give (6+1)x2x2=28 sets of data in total. The phantom consisted of 11 vials with oil/water concentrations: 0%, 2.6%, 5.3%, 7.9%, 10.5%, 15.7%, 20.9%, 31.2%, 41.3%, 51.4%, 100%. The data from each system, and for each protocol, involved 6 echoes of complex-valued multi-echo gradient echo MR images.</p> <p>Each of the 28 LMSIDEAL_Results_* MATLAB files contains 3 MAT files:</p> <p>LMSIDEAL_PDFF - contains PDFF maps (sized X x Y x 3 slices)</p> <p>ROI - contains x,y coordinates for each ROI (sized 2 x 11) (circular ROI with diameter approximately = 19.5mm)</p> <p>MEAN - contains mean for each slice and each ROI (sized 3 x 11)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Dataset of the article: "Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor".
<p>Excel document that contains the data of the article: ‘Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor’. This dataset shows the values obtained during the experimental period and it complements the corresponding article.</p>
Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration
<p>Interactive plots showing the correlation between histological parameters of optic nerves and chiasm, and metrics derived from diffusion MRI in a rat model of unilateral retinal ischemia.</p> <p> </p> <p>There are two .html files, each containing an interactive figure, one for data pertaining to the optic nerve, the other for the chiasm. The left panel shows the correlation matrix. Click on any cell to see the corresponding scatter plot on the right panel. </p>
The impact of biological bedforms on near-bed and subsurface flow: a laboratory validated numerical study of flow in the vicinity of pits and mounds
<p>The data were used in the paper "The impact of biological bedforms on near-bed and subsurface flow: a laboratory validated numerical study of flow in the vicinity of pits and mounds" which was submitted to "Journal of Geophysical Research-Earth Surface". In this paper, a novel, unified water-sediment three-dimensional model is developed to investigate the impact of simulated biogenic bedforms. The impact of biogenic bedforms on near-bed turbulence and sediment entrainment is discussed in gravelly substrates. Biogenic bedform morphology has an important role in determining the spatial extent of up- and down-welling flow.</p>
Validated onshore and offshore time series for European countries (1979-2017)
<p>This repository comprises hourly time series representing the onshore and offshore wind capacity factors in every European country (EU-28 except the islands Malta and Cyprus plus Norway and Switzerland) from 1979 to 2017. The term capacity factor is defined as the ratio between the delivered power and the cumulative installed capacity. 3 letter codes (ISO-3166-3) are used to identify the countries.</p> <p>For every country, onshore wind time series are included. For some of the countries, offshore wind time series are also included. In both cases, the time series include data for the period 1979-2017. However, for every year, the installed capacity layout is kept fixed and corresponds to turbines running in 2015. By doing so the time series for different years represent the weather influenced on the wind generation and are not impacted by differences in installed capacities.</p> <p>To obtain onshore and offshore wind time series, wind velocity from Climate Forecast System Reanalysis (CFSR) dataset has been converted into electricity generation and aggregated at country level. The methodology was described in detail and validated for Denmark in <a href="https://www.sciencedirect.com/science/article/pii/S0360544215012815">Andresen <em>et al</em>., Energy 93 (2015)</a>. In the text annexed to the data files, a description of the data and parameters used to bias-correct the modelled time series for every European country is provided.</p> <p>The license for the AU REatlas wind time series dataset is: <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International (CC BY 4.0)</a></p> <p>When using this data please make sure you include the following citation:</p> <p><em>M. Victoria and Gorm B. Andresen, Validated onshore and offshore time series for European countries (1979-2017), RE-INVEST project (2019) </em></p> <p>More information can be requested from M. Victoria (<a href="mailto:mvp@eng.au.dk">mvp@eng.au.dk</a>) and Gorm B. Andresen (<a href="mailto:gba@eng.au.dk">gba@eng.au.dk</a>).</p> <p>These time series were generated in the framework of <a href="https://reinvestproject.eu/">RE-INVEST project</a>. A similar dataset comprising solar photovoltaic time series at national scale can be accessed through the zenodo repository <a href="https://zenodo.org/record/2613651#.XPZ00mNS8uU">10.5281/zenodo.1321809</a> and details can be found in <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/pip.3126">Victoria and Andresen, Prog. In Phot.: Res and App. (2019) </a> </p> <p> </p> <p> </p>
Validity of accelerometry in step detection and gait speed measurement in orthogeriatric patients (DATASET)
<p>see README.txt for descriptions of files and formats<br> </p>
Validation of experimental charge-density refinement strategies: when do we overfit?
<p>A cross-validation method is supplied to judge between various strategies in multipole <a href="http://reference.iucr.org/dictionary/Refinement">refinement</a> procedures. Its application enables straightforward detection of whether the <a href="http://reference.iucr.org/dictionary/Refinement">refinement</a> of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested data sets it was possible to prove that the multipole parameters of atoms in comparable chemical environments should be constrained to be identical. In an automated approach, this method additionally delivers parameter distributions of <em>k</em> different refinements. These distributions can be used for further error diagnostics, <em>e.g.</em> to detect erroneously defined parameters or incorrectly determined reflections. Visualization tools show the variation in the parameters. These different refinements also provide rough estimates for the standard deviation of topological parameters.</p> <p>published in IUCrJ (2017). 4, 420–430</p> <p>Raw diffraction data, integration, scaling, corrections and final refinements of structures <strong>1</strong> an <strong>2</strong> are provided.</p> <p> </p>
Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial (Data for independent validation study)
<p>Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health relevant data from patients. However, to date, limited data and results have been published detailing real-world patient compliance, demonstrating accuracy in target indications or examining what novel insights and clinical value can be derived. Here we present novel, digital mobility data from two studies: an independent, non-interventional validation study with elderly, naturally slow walking subjects, and a global, multi-site phase IIb clinical trial involving patients with age-related muscle loss and slow walking speed (sarcopenia). Based on these data, we validate the accuracy of a novel algorithm for capturing in-clinic and real-world gait speed in frail, slow-walking adults. We demonstrate the feasibility of continuous monitoring with a wearable inertial sensor in elderly adults in real-world settings, and propose minimum thresholds for compliance required for robust capture of gait behaviors in this population. We also show how simple, inferred contextual information, describing the length of a given walking bout, can explain some of the variation in real-world gait speed, and use this information to demonstrate for the first time a relationship between in-clinic performance and real-world gait speed behavior. This work lays a foundation for exploration of the clinical relevance and value of such measures and is a first step in building a more complete chain of evidence between standardized physical performance assessment, real-world behavior, and subjective perceptions of mobility, independence and health.</p> <p>This dataset contains data collected during the independent validation study: derived data from raw accelerometry data, and summary performance data.</p> <p>The full dataset, including raw accelerometry data, is available here: <a href="https://mueller-et-al-2019.s3.amazonaws.com/index.html">https://mueller-et-al-2019.s3.amazonaws.com/index.html</a></p>
Dataset Validation of seven type 2 diabetes mellitus risk scores in a population-based cohort. The CoLaus Study
<p>This dataset is related to "Validation of seven type 2 diabetes mellitus risk scores in a population-based cohort. The CoLaus Study".</p> <p>Vanessa Kraege*, Janko Fabecic*, Pedro Marques Vidal, Gérard Waeber and Marie Méan</p> <p>*Contributed equally; co-first authors</p>
KPIs for the validation of the GreenSoul behavioural models
<p>This document presents both the methodology followed to select the Key Performance Indicators (KPI) and the final KPIs selected to measure the impact achieved by the actions carried on during the pilots. To select the KPIs we first have prepared a comprehensive list of KPIs to consider, then we follow a Delphi Method to reach a consensus among a panel of experts about the how to score every KPI in several aspects and finally we perform a descriptive statistical analysis to select the best set of KPIs.</p>
Dataset for "Validation of a Prognostic Staging for Metastatic Uveal Melanoma: A Collaborative Study of the European Ophthalmic Oncology Group"
<p>Raw data corresponding to the paper entitled: "<strong>Validation of a Prognostic Staging for Metastatic Uveal Melanoma: A Collaborative Study of the European Ophthalmic Oncology Group</strong><strong>" </strong>published in <em>Am. J. Ophthalmol.</em> 2016 Aug;168:217-226 by Kivelä <em>et al.</em></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.