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355 results for “Test Developer”
Test case selection through novel methodologies for software application developments
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Data from: A simple, cost-effective emitter for controlled release of fish pheromones: development, testing, and application to management of the invasive sea lamprey
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Development and testing of a novel Killer-Rescue self-limiting gene drive system in Drosophila melanogaster
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Data from: Testing the role of phenotypic plasticity for local adaptation: growth and development in time-constrained Rana temporaria populations
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Data from: Development and testing of an environmental DNA (eDNA) assay for endangered Atlantic sturgeon to assess its potential as a monitoring and management tool
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Synthetic river datasets built for testing and development of the Surface Water and Ocean Topography mission discharge algorithms
<p><strong>1.Summary</strong></p> <p>Datasets used for testing the performance of discharge estimation algorithms built in support of the Surface Water and Ocean Topography satellite mission. The benchmarking manuscript entitled “Exploring the factors controlling the performance of the Surface Water and Ocean Topography mission discharge algorithms” is currently under review at Water Resources Research. Once the manuscript is accepted, its DOI will be included here.</p> <p><strong>2.File description</strong></p> <p>The dataset is divided into four groups: 1-Ideal data, 2-Varying Temporal Sampling, 3-Measurement Uncertainty, and 4-SWOT Sampling and Uncertainty. Ideal data contains daily measurements with no observational uncertainty. Varying Temporal Sampling downsamples the ideal measurements considering different temporal frequencies with complete sets assuming: 1 measurement every 2 days, 3 days, 4 days, 5 days, 7 days, 10 days, and 21 days. The measurement uncertainty set adds errors to cross-sectional heights and widths, which are used to compute reach average height, width, and slope considering error corruption. The final set SWOT Sampling and Uncertainty accounts for SWOT temporal sampling and measurement uncertainty. Sets containing uncertainty have extra height, width, and slope attributes with the word true appended to the attribute name. Such attributes represent the uncorrupted measurements at the cross-section and reach scales. Height, width, and slopes for the SWOT sampling and Uncertainty dataset containing the value of negative 9999 denote points that are not observed at a particular location and time step.</p> <p>Data will be contained in one NetCDF file per river. The file contains the following groups and variables:</p> <p><strong>/River_Info/</strong></p> <p>Name: River name, data type: char</p> <p>QWBM: Mean annual discharge from the water balance model WBMsed (Cohen et al., 2014)</p> <p>rch_bnd: Reach boundaries measured in meters from the upstream end of the model</p> <p>gdrch: Reaches used in the study. Used to exclude small reaches defined around low-head dams and other obstacles where Manning’s equation should not be applied.</p> <p><strong>/XS_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>Z: Bed elevation in meters. Dimension: Cross-section, time step.</p> <p>xs_rch: Reach number for each cross-section. Dimension: Cross-section,1.</p> <p>X: Flow distance measured from the most upstream end of the model to the cross-section (meters). Dimension: Cross-section, 1.</p> <p>longitude: Cross-section longitude in decimal degrees. Dimension: Cross-section,1.</p> <p>latitude: Cross-section latitude in decimal degrees. Dimension: Cross-section,1.</p> <p>W: River width in meters. Dimension: Cross-section, time step.</p> <p>Wtrue: River width in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>Q: Discharge (m<sup>3</sup>/s). Dimension: Cross-section, time step.</p> <p>H: Water surface elevation in meters. Dimension: Cross-section, time step.</p> <p>Htrue: Water surface elevation in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>A: Cross-sectional area of flow in m<sup>2</sup>. Dimension: Cross-section, time step.</p> <p>P: Wetted perimeter in meters. Dimension: Cross-section, time step.</p> <p>n: Manning’s roughness. Dimension: Cross-section, time step.</p> <p><strong>/Reach_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>W: Reach averaged river width in meters. Dimension: Reach, time step.</p> <p>Wtrue: Reach averaged river width in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the width value with no uncertainty.</p> <p>Q: Reach averaged discharge (m<sup>3</sup>/s). Dimension: Reach, time step.</p> <p>H: Reach averaged water surface elevation in meters. Dimension: Reach, time step.</p> <p>Htrue: Reach averaged water surface elevation in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>S: Reach averaged water surface slope in meters per meter. Reach, time step.</p> <p>Strue: Reach averaged water surface slope in meters per meter. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the slope value with no uncertainty.</p> <p>A: Reach averaged area of flow in m<sup>2</sup>. Dimension: Reach, time step.</p> <p><strong>References</strong></p> <p>Cohen, S., A. J. Kettner, and J. P. M. Syvitski (2014), Global suspended sediment and water discharge dynamics between 1960 and 2010: Continental trends and intra-basin sensitivity, <em>Glob. Planet. Change</em>, <em>115</em>, 44-58, doi: <a href="https://doi.org/10.1016/j.gloplacha.2014.01.011">https://doi.org/10.1016/j.gloplacha.2014.01.011</a>.</p> <p> </p>
Manually written or Generated tests? a study with developers and maintenance tasks
<p>Software testing is an important part of software development. In addition to finding faults in the code, good tests should help developers to correct faults and be easily updated in case of modifications due to code changes. Automatically generated tests can save time and may lead to higher code coverage. However, these tests may be less readable and not based on realistic scenarios.<br> Few pieces of research have been done to evaluate whether automatically generated tests are maintainable and support developers when maintaining code. To further investigate this issue, we perform an empirical study with 20 real developers to compare how they perform maintenance tasks with automatically generated (Evosuite or Randoop) and manually-written test cases. Our results indicate that automatically generated tests can be a great help for identifying faults during maintenance. Also, we found that all strategies were similar at helping to produce correct bug fixes and with similar efficiency. Therefore, we can say that developers may integrate generated test suites into the project at any stage.</p>
Data from: All-trans retinoic acid disrupts development in ex vivo cultured fetal rat testes. II: modulation of mono-(2-ethylhexyl) phthalate toxicity
Humans are universally exposed to low levels of phthalate esters (phthalates), which are used to plasticize polyvinyl chloride. Phthalates exert adverse effects on the development of seminiferous cords in the fetal testis through unknown toxicity pathways. To investigate the hypothesis that phthalates alter seminiferous cord development by disrupting retinoic acid signaling in the fetal testis, gestational day 15 fetal rat testes were exposed for 1-3 days to 10-6 M all-trans retinoic acid (ATRA) alone or in combination with 10-6 to 10-4 M mono-(2-ethylhexyl) phthalate (MEHP) in ex vivo culture. As previously reported, exogenous ATRA reduced seminiferous cord number. This effect was attenuated in a concentration-dependent fashion by MEHP co-exposure. ATRA and MEHP-exposed testes were depleted of DDX4-positive germ cells but not Sertoli cells. MEHP alone enhanced the expression of the retinoic acid receptor target Rbp1 and the ovary development-associated genes Wnt4 and Nr0b1, and suppressed expression of the Leydig cell marker, Star, and the germ cell markers, Ddx4 and Pou5f1. In co-exposures, MEHP predominantly enhanced the gene expression effects of ATRA, but the Wnt4 and Nr0b1 concentration-responses were non-linear. Similarly, ATRA increased the number of cells expressing the granulosa cell marker FOXL2 in testis cultures, but this induction was attenuated by addition of MEHP. These results indicate that MEHP can both enhance and inhibit actions of ATRA during fetal testis development and provide evidence that retinoic acid signaling is a target for phthalate toxicity in the fetal testis.
Data from: Logical validation and evaluation of practical feasibility for the SCRuM (School Clinical Rugby Measure) test battery developed for young adolescent rugby players in a resource-constrained environment
There is a growing impetus towards usage of test batteries in talent identification (TID) programmes in rugby. Consequently, there are many test batteries in existence profiling anthropometric, physiological characteristics and rugby-specific skills. There is no consensus in the literature on the constituent variables and corresponding tests required to inform TID programs. Following development of a new test battery called the SCRuM (School Clinical Rugby Measure), this study aimed at establishing face, logical validity and practical feasibility of included tests. The test battery, initially comprised of 23 items, had its face and logical validity evaluated by five (5) adolescent rugby coaches and 20 rugby experts, respectively. Logical validation was conducted in two questionnaire-based rounds with Content Validity Index (I-CVI) calculated for each variable. Subsequently, a cross-sectional study targeting 30 local rugby coaches was conducted to determine the perceived practical feasibility of each test item. The results showed excellent I-CVI (>0.78) for 17 variables (speed, weight, height and skin fold measures, repeated high-intensity exercise performance ability, prolonged high-intensity intermittent running ability, change of direction speed, anaerobic capacity, lower-and upper body muscular power and strength, muscular flexibility, reactive agility, passing for accuracy, tackling proficiency, and catching). However, three tests, namely, Reactive Agility, One Repetition Maximum Back Squat and One Repetition Maximum Bench Press had low test-feasibility indices (T-FI< 35) suggesting practicality concerns with implementation in the Zimbabwean context. Thus, these findings suggest the need for substitution or development of new practically feasible tests for upper-and lower body muscular strength and reactive agility.
Data from: Development of G: a test in an amphibious fish
Heritable variation in, and genetic correlations among, traits determine the response of multivariate phenotypes to natural selection. However, as traits develop over ontogeny, patterns of genetic (co)variation and integration captured by the G matrix may also change. Despite this, few studies have investigated how genetic parameters underpinning multivariate phenotypes change as animals pass through major life history stages. Here, using a self-fertilizing hermaphroditic fish species, mangrove rivulus (Kryptolebias marmoratus), we test the hypothesis that G changes from hatching through reproductive maturation. We also test Cheverud's conjecture by asking whether phenotypic patterns provide an acceptable surrogate for patterns of genetic (co)variation within and across ontogenetic stages. For a set of morphological traits linked to locomotor (jumping) performance, we find that the overall level of genetic integration (as measured by the mean-squared correlation across all traits) does not change significantly over ontogeny. However, we also find evidence that some trait-specific genetic variances and pairwise genetic correlations do change. Ontogenetic changes in G indicate the presence of genetic variance for developmental processes themselves, while also suggesting that any genetic constraints on morphological evolution may be age-dependent. Phenotypic correlations closely resembled genetic correlations at each stage in ontogeny. Thus, our results are consistent with the premise that – at least under common environment conditions - phenotypic correlations can be a good substitute for genetic correlations in studies of multivariate developmental evolution.
Data from: Synergism and antagonism of proximate mechanisms enable and constrain the response to simultaneous selection on body size and development time: an empirical test using experimental evolution
Natural selection acts on multiple traits simultaneously. How mechanisms underlying such traits enable or constrain their response to simultaneous selection is poorly understood. We show how antagonism and synergism among three traits at the developmental level enable or constrain evolutionary change in response to simultaneous selection on two focal traits at the phenotypic level. After 10 generations of 25% simultaneous directional selection on all four combinations of body size and development time in Manduca sexta (Sphingidae), the changes in the three developmental traits predict 93% of the response of development time and 100% of the response of body size. When the two focal traits were under synergistic selection, the response to simultaneous selection was enabled by juvenile hormone and ecdysteroids and constrained by growth rate. When the two focal traits were under antagonistic selection, the response to selection was due primarily to change in growth rate and constrained by the two hormonal traits. The approach used here reduces the complexity of the developmental and endocrine mechanisms to three proxy traits. This generates explicit predictions for the evolutionary response to selection that are based on biologically informed mechanisms. This approach has broad applicability to a diverse range of taxa, including algae, plants, amphibians, mammals, and insects.
Data from: Further development of the Assessment of Military Multitasking Performance: iterative reliability testing
The Assessment of Military Multitasking Performance (AMMP) is a battery of functional dual-tasks and multitasks based on military activities that target known sensorimotor, cognitive, and exertional vulnerabilities after concussion/mild traumatic brain injury (mTBI). The AMMP was developed to help address known limitations in post concussive return to duty assessment and decision making. Once validated, the AMMP is intended for use in combination with other metrics to inform duty-readiness decisions in Active Duty Service Members following concussion. This study used an iterative process of repeated interrater reliability testing and feasibility feedback to drive modifications to the 9 tasks of the original AMMP which resulted in a final version of 6 tasks with metrics that demonstrated clinically acceptable ICCs of > 0.92 (range of 0.92–1.0) for the 3 dual tasks and > 0.87 (range 0.87–1.0) for the metrics of the 3 multitasks. Three metrics involved in recording subject errors across 2 tasks did not achieve ICCs above 0.85 set apriori for multitasks (0.64) and above 0.90 set for dual-tasks (0.77 and 0.86) and were not used for further analysis. This iterative process involved 3 phases of testing with between 13 and 26 subjects, ages 18–42 years, tested in each phase from a combined cohort of healthy controls and Service Members with mTBI. Study findings support continued validation of this assessment tool to provide rehabilitation clinicians further return to duty assessment methods robust to ceiling effects with strong face validity to injured Warriors and their leaders.
Do Developers Use Static Application Security Testing (SAST) Tools Straight Out of the Box? A large-scale Empirical Study
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GRIPP-2 checklist for 'Patient and public involvement in the design and protocol development for a platform randomised trial to evaluate diagnostic tests to optimise antimicrobial therapy (PROTECT)'
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MarTREC 6017: Development of Rapid Setting Soil-Cement Mixture Designs and Performance Testing
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Development and preliminary testing of a temporally controllable weather modification rocket with spatial seeding capacity: dataset
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Development and Testing of Nutritional Algorithms (NACHO)
ClinicalTrials.gov study NCT05825469. IPD Sharing: YES. Countries: 1. Publications: 0.
Developing and Testing Culturally Based Educational Videos for Puerto Rican and African American Home Hospice Caregivers
ClinicalTrials.gov study NCT06024278. IPD Sharing: NO. Countries: 2. Publications: 0.
The Development and Pilot Testing of a New MR Imaging Protocol to Quantify Myeloma Disease Burden and Bone Loss
ClinicalTrials.gov study NCT03951220. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Meet Me on the Pitch: Developing and Testing a Community-Based Sports and Behavioral Health Intervention for Youth
ClinicalTrials.gov study NCT07339228. IPD Sharing: YES. Countries: 1. Publications: 0.
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.