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793 results for “Test effectiveness”
Figure 3. Negative Caspase-3 in Investigation of protective effects of lithium borate on spermatogenesis and testes histopathology against cadmium-induced acute toxicity in rats
Figure 3. Negative Caspase-3 expressions in testes tissues of control and LTB groups (A and C), severe Caspase-3 expression in spermatocytes of Cd group (arrowheads) (B), mild Caspase- 3 expression in spermatocytes (arrowheads) of LTB + Cd group (D), IHC - P, Bar: 20 µm.
Figure 1 in Investigation of protective effects of lithium borate on spermatogenesis and testes histopathology against cadmium-induced acute toxicity in rats
Figure 1. Testicular tissue, normal anatomical appearance (A), oedema, hyperaemia, congestion and haemorrhage (B), normal anatomical appearance (C), moderate oedematous and mild hyperaemic (D).
Notch Effect in Acrylonitrile Styrene Acrylate (ASA): Tensile and Fracture Tests - FRADDCO project
<p>This dataset contains tensile and fracture tests of specimens made of acrylonitrile–styrene–acrylate (ASA) material, manufactured by fused filament fabrication (FFF). The files include 9 tensile specimens and 72 single-edge-notch bending (SENB) specimens containing U-notches with different nominal notch radii (from 0 mm -crack-like defects- up to 2.0 mm) and fabricated with three different raster orientations: 0/90, 30/−60 and 45/−45.</p>
Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection
<p>Data Package for "Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection"</p> <p>This package contains data generated as part of our experiments on adaptive fitness function selection as part of unit test generation for Java systems.</p> <p>This paper is currently under submission. A draft of the paper is included in the data package.</p> <p>This package contains experimental data (in folder "experiment_data"), including goal attainment, fault detection, time per generation, and choices made by the reinforcement learning algorithm. In the folder "test_suites", the suites generated by each technique are included for each project. </p> <p>If you have questions, please contact Gregory Gay at greg@greggay.com.</p> <p>NOTE: A small number of items are currently missing from this data package and will be added shortly. Please make sure you have the latest version of this package.</p>
Farm and regional levels' database used to test the effectiveness of slope and distance from buildings in approximating the pastoral site-use intensity of alpine pastures
<p>The excel file contains the two databases used in the paper “Slope and distance from buildings are easy-to-retrieve proxies for estimating livestock site-use intensity in alpine summer pastures” to test the effectiveness of slope and distance from buildings in approximating the pastoral site-use intensity of alpine pastures.</p> <p>The database in the ‘farm level’ sheet has been used to assess if slope and distance from buildings were good predictors of site-use intensity at farm level, i.e. the number of GPS locations counted within sample units was modelled as a function of the two proxies. Moreover, this database has been used to evaluate if the expected transition of Vegetation Ecological Groups (VEGs) from the shrub-encroached to the nitrophilous ones corresponded to a real site-use intensity gradient as represented by the stocking rates measured through GPS locations, i.e. by modelling the total number of GPS locations within sample units in function VEGs.</p> <p>The database in the ‘Regional level’ sheet has been used to evaluate if the five VEGs were effectively discriminated by distance from buildings and slope. Two models were performed by specifying either slope and distance from buildings as response variables and VEG as fixed factor.</p>
Testing the effectiveness of genetic monitoring using genetic non-invasive sampling
<p>1. Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling as a cost-effective population-wide genetic monitoring approach. Genetic non-invasive sampling has, however, known limitations which may impact the accuracy of downstream genetic analyses.</p> <p>2. Here, using high quality SNP data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures.</p> <p>3. We found that genetic non-invasive sampling at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled.</p> <p>4. We show that genetic non-invasive sampling at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.</p>
A Study to Test if Fremanezumab is Effective in Preventing Episodic Migraine in Patients 6 to 17 Years of Age
ClinicalTrials.gov study NCT04458857. IPD Sharing: YES. Countries: 9. Publications: 1.
Effect of Direct-from-blood Bacterial Testing on Antibiotic Administration and Clinical Outcomes
ClinicalTrials.gov study NCT06069206. IPD Sharing: YES. Countries: 1. Publications: 18.
A Study to Test if TEV-50717 is Effective in Relieving Tics Associated With Tourette Syndrome (TS)
ClinicalTrials.gov study NCT03571256. IPD Sharing: YES. Countries: 10. Publications: 1.
Study Testing Response Effect of KY1005 Against Moderate-to-Severe Atopic Dermatitis, The STREAM-AD Study
ClinicalTrials.gov study NCT05131477. IPD Sharing: YES. Countries: 12. Publications: 3.
Testing the effectiveness of genetic monitoring using genetic non-invasive sampling
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Data from: Testing the evolutionary potential of an alpine plant: Phenotypic plasticity in response to growth temperature outweighs parental environmental effects and other genetic causes of variation
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Data for: Testing the population-level effects of stress-induced susceptibility in the ranavirus-wood frog system
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A genome-wide test for paternal indirect genetic effects on lifespan in Drosophila melanogaster
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Data from: The effects of stress and glucocorticoids on vocalizations: a test in North American red squirrels
Acoustic signaling is an important means by which animals communicate both stable and labile characteristics. Although it is widely appreciated that vocalizations can convey information on labile state, such as fear and aggression, fewer studies have experimentally examined the acoustic expression of stress state. The transmission of such public information about physiological state could have broad implications, potentially influencing the behavior and life history traits of neighbors. North American red squirrels (Tamiasciurus hudsonicus) produce vocalizations known as rattles that advertise territorial ownership. We examined the influence of changes in physiological stress state on rattle acoustic structure through the application of a stressor (trapping and handling the squirrels) and by provisioning squirrels with exogenous glucocorticoids (GCs). We characterized the acoustic structure of rattles emitted by these squirrels by measuring rattle duration, mean frequency, and entropy. We found evidence that rattles do indeed exhibit a "stress signature." When squirrels were trapped and handled, they produced rattles that were longer in duration with a higher frequency and increased entropy. However, squirrels that were administered exogenous GCs had similar rattle duration, frequency, and entropy as squirrels that were fed control treatments and unfed squirrels. Our results indicate that short-term stress does affect the acoustic structure of vocalizations, but elevated circulating GC levels do not mediate such changes.
Assessment of the Effect of a Test Setup on the Input Impedance Measurement of Cables (Dataset)
<p>The dataset includes the source of all measured and simulated data utilized in the paper titled<i> "Assessment of the Effect of a Test Setup on the Input Impedance Measurement of Cables".</i><br>Simulation data is available in ".xlsx" format, whereas measurement data is provided in ".s1p" format. </p>
16S sequences from mesocosms experiment testing the effect of Siganus rivulatus on marine microorganisms
<p>Nutrient cycling is a key biogeochemical process underlying the functioning of marine ecosystems. Yet, the contribution of fishes is still poorly understood. This is problematic considering the current modifications of fish assemblages experienced in certain regions such as the Mediterranean Sea, and their potential consequences in terms of ecosystem functioning. In this study, we used a mesocosm experiment to test the effect of nutrient recycling by an invasive marine herbivorous fish (<em>Siganus rivulatus</em>) on planktonic and benthic microbial communities. The response of these communities was assessed using a variety of analytical approaches such as measures of nutrient concentration, flow cytometry, and metabarcoding of the 16S rRNA gene. Our results show that several microbial compartments of marine ecosystems respond to the nutrients released by fish through excretion and egestion. The nutrients contained in the macroalgae consumed by <em>S. rivulatus</em> were excreted in large amounts as dissolved nutrients, which resulted in higher concentrations of N-based nutrients in the water (NH<sub>4</sub>, NO<sub>2</sub>/NO<sub>3</sub>). This excess of N in the system was associated with higher abundances of planktonic microbes (phyto- and bacterioplankton), modifications of the structure of planktonic bacterial communities, and the tissue composition of the remaining macroalgae. Non-assimilated nutrients were released in the form of feces under the shelters where the fish spent most of their time and defecated during the night, leading to local increases in diversity and significant shifts in the structure of sediment bacterial communities. Overall, our results suggest that the impact of <em>S. rivulatus</em> on planktonic microbes was related to the indirect bottom-up effect induced by excreted nutrients while its effect on benthic microbes was due to a direct release of microbes from its gut microbiome. This study represents one of the first assessment of the effect of nutrient recycling by fishes on the microbial communities from several compartments of marine ecosystems and one of the first evidence of the invisible effect of invasive species on the microbial components of marine ecosystems.</p>
Dataset: Testing for effects of growth rate on isotope trophic discrimination factors and evaluating the performance of Bayesian stable isotope mixing models experimentally: a moment of truth?
<p><span>Discerning assimilated diets of wild animals using stable isotopes is well established where potential dietary items in food webs are isotopically distinct. With the advent of mixing models, and Bayesian extensions of such models (Bayesian Stable Isotope Mixing Models, BSIMMs), statistical techniques available for these efforts have been rapidly increasing. The accuracy with which BSIMMs quantify diet, however, depends on several factors including uncertainty in tissue discrimination factors (TDFs; <em>Δ</em>) and identification of appropriate error structures. Whereas performance of BSIMMs has mostly been evaluated with simulations, here we test the efficacy of BSIMMs by raising domestic broiler chicks (<em>Gallus gallus domesticus</em>) on four isotopically distinct diets under controlled environmental conditions, ideal for evaluating factors that affect TDFs and testing how BSIMMs allocate individual birds to diets that vary in isotopic similarity. For both liver and feather tissues,<em> δ</em><sup>13</sup>C and <em>δ </em><sup>15</sup>N values differed among dietary groups. <em>Δ</em><sup>13</sup>C of liver, but not feather, was negatively related to the rate at which individuals gained body mass. For <em>Δ</em><sup>15</sup>N, we identified effects of dietary group, sex, and tissue type, as well as an interaction between sex and tissue type</span><span><span>, </span></span><span><span>with f</span></span><span>emales having higher liver <em>Δ</em><sup>15</sup>N relative to males. For both tissues, BSIMMs allocated most chicks to correct dietary groups, especially for models using combined TDFs rather than diet specific TDFs, and those applying a multiplicative error structure. These findings provide new information on how biological processes affect TDFs and confirm that adequately accounting for variability in consumer isotopes is necessary to optimize performance of BSIMMs. Moreover, they demonstrate experimentally that these types of models reliably characterize consumed diets when appropriately parameterized.<span> </span></span></p>
Testing nectar price effect on bumblebee feeding by automatized computer-controlled laboratory platform
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Dataset for Cost-effective Simulation-based Test Selection in Self-driving Cars Software with SDC-Scissor
<p><strong>SDC-Scissor tool for Cost-effective Simulation-based Test Selection in Self-driving Cars Software</strong></p> <p>This dataset provides test cases for self-driving cars with the BeamNG simulator. Check out the repository and demo video to get started.</p> <p><strong>GitHub:</strong> <a href="https://github.com/ChristianBirchler/sdc-scissor">github.com/ChristianBirchler/sdc-scissor</a></p> <p>This project extends the tool competition platform from the <a href="https://github.com/se2p/tool-competition-av">Cyber-Phisical Systems Testing Competition</a> which was part of the <a href="https://sbst21.github.io/">SBST Workshop in 2021</a>.</p> <p><strong>Usage</strong></p> <p><strong>Demo</strong></p> <p> <a href="https://youtu.be/Cn8p648KnfQ">YouTube Link</a></p> <p><strong>Installation</strong></p> <p>The tool can either be run with <a href="https://docs.docker.com/get-docker/">Docker</a> or locally using <a href="https://python-poetry.org/docs/">Poetry</a>.</p> <p>When running the simulations a working installation of <a href="https://beamng.gmbh/research/">BeamNG.research</a> is required. Additionally, this simulation cannot be run in a Docker container but must run locally.</p> <p>To install the application use one of the following approaches:</p> <ul> <li>Docker: <code>docker build --tag sdc-scissor .</code></li> <li>Poetry: <code>poetry install</code></li> </ul> <p><strong>Using the Tool</strong></p> <p>The tool can be used with the following two commands:</p> <ul> <li>Docker: <code>docker run --volume "$(pwd)/results:/out" --rm sdc-scissor [COMMAND] [OPTIONS]</code> (this will write all files written to <code>/out</code> to the local folder <code>results</code>)</li> <li>Poetry: <code>poetry run python sdc-scissor.py [COMMAND] [OPTIONS]</code></li> </ul> <p>There are multiple commands to use. For simplifying the documentation only the command and their options are described.</p> <ul> <li>Generation of tests: <ul> <li><code>generate-tests --out-path /path/to/store/tests</code></li> </ul> </li> <li>Automated labeling of Tests: <ul> <li><code>label-tests --road-scenarios /path/to/tests --result-folder /path/to/store/labeled/tests</code></li> <li><em>Note:</em> This only works locally with BeamNG.research installed</li> </ul> </li> <li>Model evaluation: <ul> <li><code>evaluate-models --dataset /path/to/train/set --save</code></li> </ul> </li> <li>Split train and test data: <ul> <li><code>split-train-test-data --scenarios /path/to/scenarios --train-dir /path/for/train/data --test-dir /path/for/test/data --train-ratio 0.8</code></li> </ul> </li> <li>Test outcome prediction: <ul> <li><code>predict-tests --scenarios /path/to/scenarios --classifier /path/to/model.joblib</code></li> </ul> </li> <li>Evaluation based on random strategy: <ul> <li><code>evaluate --scenarios /path/to/test/scenarios --classifier /path/to/model.joblib</code></li> </ul> </li> </ul> <p>The possible parameters are always documented with <code>--help</code>.</p> <p><strong>Linting</strong></p> <p>The tool is verified the linters <a href="https://flake8.pycqa.org/en/latest/">flake8</a> and <a href="https://pylint.org/">pylint</a>. These are automatically enabled in <a href="https://code.visualstudio.com/">Visual Studio Code</a> and can be run manually with the following commands:</p> <pre>poetry run flake8 . poetry run pylint **/*.py</pre> <p><strong>License</strong></p> <p>The software we developed is distributed under GNU GPL license. See the <a href="https://github.com/ChristianBirchler/sdc-scissor/blob/main/LICENSE.md">LICENSE.md</a> file.</p> <p><strong>Contacts</strong></p> <p>Christian Birchler - Zurich University of Applied Science (ZHAW), Switzerland - <a href="mailto:birc@zhaw.ch">birc@zhaw.ch</a></p> <p>Nicolas Ganz - Zurich University of Applied Science (ZHAW), Switzerland - <a href="mailto:gann@zhaw.ch">gann@zhaw.ch</a></p> <p>Sajad Khatiri - Zurich University of Applied Science (ZHAW), Switzerland - <a href="mailto:mazr@zhaw.ch">mazr@zhaw.ch</a></p> <p>Dr. Alessio Gambi - Passau University, Germany - <a href="mailto:alessio.gambi@uni-passau.de">alessio.gambi@uni-passau.de</a></p> <p>Dr. Sebastiano Panichella - Zurich University of Applied Science (ZHAW), Switzerland - <a href="mailto:panc@zhaw.ch">panc@zhaw.ch</a></p> <p><strong>References</strong></p> <ul> <li>Christian Birchler, Nicolas Ganz, Sajad Khatiri, Alessio Gambi, and Sebastiano Panichella. 2022. Cost-effective Simulation-based Test Selection in Self-driving Cars Software with SDC-Scissor. In 2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER), IEEE.</li> </ul> <p><strong>If you use this tool in your research, please cite the following papers:</strong></p> <pre><code>@INPROCEEDINGS{Birchler2022, author={Birchler, Christian and Ganz, Nicolas and Khatiri, Sajad and Gambi, Alessio, and Panichella, Sebastiano}, booktitle={2022 IEEE 29th International Conference on Software Analysis, Evolution and Reengineering (SANER), title={Cost-effective Simulationbased Test Selection in Self-driving Cars Software with SDC-Scissor}, year={2022}, }</code></pre>
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.