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13 results for “Methodology testing”
Dataset for "Methodology for fast testing of carbon-based nanostructured 3D electrodes in vanadium redox flow battery"
<p>Here, we describe a technique for integrating carbon-based rod-like nanomaterials into a vanadium redox flow battery and a methodology for fast nanomaterial performance testing. The technique is based on creating a fixed nanomaterial bed sandwiched between two graphite felt electrodes, forming a 3D flow-through electrode in the battery. Performing various positive and negative control experiments, we show the beneficial effect of a nanostructured bed on the primary battery characteristics obtained from short-term electrochemical experiments. We then characterize carbon nanotubes exhibiting promising electrochemical behavior in vanadium electrolytes, as observed in our previous study. The load curves obtained from charge-discharge steps at various current densities and electrolyte flow rates revealed considerable differences in the performance of the tested materials, with few-walled carbon nanotubes reaching unsurpassable characteristics. Although developed for vanadium redox flow batteries, the method enables testing tube-like and rod-like (nano-)materials as electrodes for other flow battery systems. </p>
Figure 1. Experimental units for feeding rates tests with terrestrial isopods and fecal pellets from different food sources. A in Coprophagy in detritivores: methodological design for feeding studies in terrestrial isopods (Crustacea, Isopoda, Oniscidea)
Figure 1. Experimental units for feeding rates tests with terrestrial isopods and fecal pellets from different food sources. A) Treatment access; coprophagy is allowed. B) Treatment removal; coprophagy and bacterial activity on feces are avoided. C) Treatment net; coprophagy is avoided and bacterial activity on feces allowed. D) Fecal pellet from carrot (left) and decomposing leaf (right) consumption.
Transcriptomic characterization of 2D and 3D human induced pluripotent stem cell-based in vitro models as New Approach Methodologies for developmental neurotoxicity testing
<p><strong>Abstract:</strong> The safety and developmental neurotoxicity (DNT) potential of chemicals remain critically understudied due to limitations of current in vivo testing guidelines, which are low throughput, resource-intensive, and hindered by species differences that limit their relevance to human health. To address these issues, robust new approach methodologies (NAMs) using deeply characterized cell models are essential. This study presents the comprehensive transcriptomic characterization of two advanced human-induced pluripotent stem cell (hiPSC)-derived models: a 2D adherent and a 3D neurosphere model of human neural progenitor cells (hiNPCs) differentiated up to 21 days. Using high-throughput RNA sequencing, we compared gene expression profiles of 2D and 3D models at three developmental stages (3, 14, and 21 days of differentiation). Both models exhibit maturation towards post-mitotic neurons, with the 3D model maturing faster and showing a higher prevalence of GABAergic neurons, while the 2D model is enriched with glutamatergic neurons. Both models demonstrate broad applicability domains, including excitatory and inhibitory neurons, astrocytes, and key endocrine and especially the understudied cholinergic receptors. Comparison with human fetal brain samples confirms their physiological relevance. This study provides novel in-depth applicability insights into the temporal and dimensional aspects of hiPSC-derived neural models for DNT testing. The complementary use of these two models is highlighted: the 2D model excels in synaptogenesis assessment, while the 3D model is particularly suited for neural network formation as observed as well in previous functional studies with these models. This research marks a significant advancement in developing human-relevant, high-throughput DNT assays for regulatory purposes.</p> <p><strong>This data sets contains:</strong></p> <p><strong>Tab. S1</strong> - Significant genes results</p> <p><strong>Tab. S2</strong> - Enriched pathways_GO_Biological Processes</p> <p><strong>Tab. S3</strong> - Enriched pathways_GO_Cellular Components</p> <p><strong>Tab. S4</strong> - Enriched pathways_GO_Molecular Function</p> <p><strong>Tab. S5</strong> - Enriched pathways_KEGG</p> <p><strong>Tab. S6</strong> - EnrichEnriched pathways_Panther</p> <p><strong>Tab. S7</strong> - Enriched pathways_Reactome</p> <p><strong>Tab. S8</strong> - Gene counts</p> <p><strong>Tab. S9</strong> - Gene selection for targeted analysis</p>
Implementing Traceability Repositories as Graph Databases for Software Quality Improvement: Datasets used to test our methodology that is presented in the paper 10.1109/QRS.2018.00040
<p>The first dataset is the Event Based Traceability for Managing Evolutionary Change (EBT), it is a public dataset provided by CoEST, the original artifacts and trace links are represented in XML and text format. From the EBT dataset, we selected the 41<em> requirements </em>and 25<em> test case </em>artifacts, in addition to the answer set of 51 trace links which relates the <em>requirements </em>with the<em> test case. </em>Artifacts and trace links are prepared in XML format<strong>. </strong>The data set contains XML for each artifact such as RQ.xml, EBTrelations.xml is the answer set file, TradModel.xml which describes the defined model and TradTraceabilityRule.xml that includes the rules applied for trace link types.</p> <p> </p> <p>The second dataset AgileOERP is collected from commercial management tool to customize an open source ERP applying agile methodology. It contains 350<em> user stories (US), </em>1323<em> tasks (TS) </em>and 198<em> developer test (DT) </em>artifacts, in addition to answer set of trace links that manually generated by developers which relates the <em>user story </em>artifact with<em> task (</em>1304) artifact, as such relates the <em>task </em>artifact with<em> developer test </em>artifact (65). Artifacts and trace links are prepared in XML format<strong>. </strong>The data set contains XML for each artifact such as US.xml, ERPrelations.xml is the answer set file, AgileModel.xml which describes the defined model and AgileTraceabilityRule,xml that includes all rules applied for trace links type</p> <p> </p> <p>The original dataset of the last dataset is the Aqualush irrigation system which is used as a case study in “C. Fox, Introduction to Software Engineering Design: Processes, Principles and Patterns with UML2. Addison-Wesley, 2006”. The trace links are generated and provided in “E. Ben Charrada, D. Caspar, C. Jeanneret, and M. Glinz, towards a benchmark for traceability, in Joint EVOL and IWPSE 2011, pp. 21-30”, in HTML format. For our work, we selected the <em>software requirements specification (</em>396 SRS), <em>user level requirements (</em>48 ULR), <em>use case (</em>74 UC), <em>detailed design (85 DD) </em>and <em>software architecture(15 SArch) </em>artifacts in addition to the answer set of trace links that relate the SRS with other artifacts(4038) and thus relates the DD artifact with other artifacts (1719) . Artifacts and trace links are prepared in XML<strong>. </strong>The data set contains XML for each artifact such as SRS.xml, AqualushRelations.xml is the answer set file, TradModel.xml which describes the defined model and TradTraceabilityRule.xml that includes the rules applied for trace link types.</p>
Test case selection through novel methodologies for software application developments
<p>Test case selection is to minimize the time and effort spent for software testing in real time practice. During the course of software testing, the software firms are in want of techniques to finish the testing in a stipulated time, whilst uncompromising on quality. The motto is to select subset of test cases rather to take up all available test cases to uncover most of the bugs. Clustering of test cases using ranking and also based on similarity coefficients is to be implemented. The experimented results have to show up the techniques proposed improving the catching up of errors in a comparatively shorter duration. In this research, eleven different features were considered in order to cluster the test cases. There are two methodologies implemented. In the first methodology, each cluster will cover set of specific features to a certain percentage. Depending on the feature's coverage, cluster of test cases can be selected. These clusters were formed using ranking methodology. In the second methodology, similarity among test cases based on eleven features is found. Then max-min composition is used to find fuzzy equivalences, upon which clusters are formed. Most similar test cases are clustered.</p>
T790M Mutation Testing in Blood by Different Methodologies
ClinicalTrials.gov study NCT03363139. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Test case selection through novel methodologies for software application developments
Open the record for dataset details and reuse information.
T790M Plasma Testing Methodology Comparison and Clinical Validation
ClinicalTrials.gov study NCT02997501. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Pilot Test of COVID-19 Related Clinical Outcome Assessment Methodology and Qualitative Evidence of Content Validity
ClinicalTrials.gov study NCT05207293. IPD Sharing: UNDECIDED. Countries: 2. Publications: 0.
¹³C-Methacetin Breath Test (MBT) Methodology Study
ClinicalTrials.gov study NCT01205074. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Refinement and Testing of Recruitment Methodology for Behavioral Medication Adherence Interventions Using Behavioral Science-based Approaches
ClinicalTrials.gov study NCT06569290. IPD Sharing: NO. Countries: 1. Publications: 0.
Testing Design Thinking Methodology to Engage Hispanic and Latino Families of Autistic Children in Research.
ClinicalTrials.gov study NCT06111092. IPD Sharing: YES. Countries: 0. Publications: 0.
Implementation of Prognostic Methodologies to Cryogenic Propellant Loading Test-bed
Prognostics methodologies determine the health state of a system and predict the end of life and remaining useful life. This information enables operators to take maintenance related decisions, thus effectively streamlining operational and mission-level activities. Prognostics testbeds help in the prototyping, development, and maturation of prognostic technologies. In this work, we present a prognostics testbed for pneumatic valves. Pneumatic valves are critical components in many industrial processes, and the testbed will be used to showcase how remaining life prediction works in the context of cryogenic refueling operations. The testbed allows for the injection of time-varying leaks with specified damage progression profiles in order to emulate common valve faults. In addition, the testbed contains a battery used to power some components, allowing the study of the effects of battery degradation on the operation of the valves. Prognostic algorithms will utilize sensor data collected from the different transducers in order to estimate component health and make life predictions, based on mathematical models describing the underlying physics of component degradation and employing a Bayesian filtering algorithm for state-parameter estimation from which life predictions are made.
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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.