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1,956 results for “test data”
PhageHostLearn - training and test data
<p>This Zenodo repository contains all the training and test data necessary to reproduce the analyses in our manuscript "<strong>P</strong><strong>rediction of <em>Klebsiella</em> phage-host specificity at the strain level</strong>", including raw genome sequences, processed phage RBPs and <em>Klebsiella</em> K-loci sequences and the phage-host interaction data.</p>
Pin-on-disc tests with friction and wear depth data at increasing temperatures: dry sliding between 100Cr6 sphere against 100Cr6 ring.
<p>This dataset has been collected during 6 ball-on-disc tests. The objective of the tests was to assess the influence of temperature on wear and friction between steel-to-steel counterfaces.</p> <p>Materials: 100Cr6 sphere against 100Cr6 ring. Both components have been extracted from a FAG axial bearing. Surface roughness: sphere Ra: 0.04 microns; ring: 0.42 microns.</p> <p>test conditions (test 1/2/3/4/5/6):</p> <p>vertical load: 10N</p> <p>sliding speed: 0.1 m/s</p> <p>sliding distance: 500 m</p> <p>temperature: 23/50/80/110/140/170 °C</p> <p>wear track radius: 27.8/22.6/29/27/24/22 mm</p>
Data from: Does losing reduce the tendency to engage with rivals to reach mates? An experimental test
<p>Male-male contests for access to females or breeding resources is critical in determining male reproductive success. Larger males and those with more effective weaponry are more likely to win fights. However, even after controlling for such predictors of fighting ability, studies have reported a winner-loser effect: previous winners are more likely to win subsequent contests, while losers often suffer repeated defeats. While the effect of winning-losing is well-documented for the outcome of future fights, its effect on other behaviors (e.g., mating) remains poorly investigated. Here, we test whether a winning versus losing experience influenced subsequent behaviors of male mosquitofish (<em>Gambusia holbrooki</em>) towards rivals and potential mates. We housed focal males with either a smaller or larger opponent for 24 hours to manipulate their fighting experience to become winners or losers, respectively. The focal males then underwent tests that required them to enter and swim through a narrow corridor to reach females, bypassing a cylinder that contained either a larger rival male (competitive scenario), a juvenile or was empty (non-competitive scenarios). The tests were repeated after one week. Winners were more likely to leave the start area and to reach the females, but only when a larger rival was presented, indicating higher levels of risk-taking behavior in aggressive interactions. This winner-loser effect persisted for at least one week. We suggest that male mosquitofish adjust their assessment of their own and/or their rival's fighting ability following contests in ways whose detection by researchers depends on the social context.</p>
Comparing coronary stent material performance on a common geometric platform through simulated bench testing: Supporting data
<p>Data including UMATs and Abaqus input files related to the paper 'Comparing coronary stent material performance on a common geometric platform through simulated bench testing' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jmbbm.2012.02.013" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.jmbbm.2012.02.013</span></a></p>
Testing Data: LIDAR Driven Stemflow Mapping
<p>Data in this upload was and continues to be used for the validation of the model discussed in the paper with the following doi: <a href="http://dx.doi.org/10.2139/ssrn.4600550" target="_blank" rel="noopener">10.2139/ssrn.4600550</a>. These files are sub sections of QSMs generated using SimpleTree and constitue use cases that 1. cover then necessary functionality of the model and 2. assist in the discovery and identification of errors when the model is changed.<br><br>The git repository at the below link leverages GitHub Actions CI/CD to run a suite of 65 tests whenever a pull request is made to the main branch. Model outputs (given these files as inputs) were hand validated and are used to ensure consistent/expected model results. These outputs are stored in the below repository under 'canopyHydrodynamics/test/expected_results'.</p> <p>Repository: https://github.com/wischmcj/canopyHydrodynamics</p>
Data to test for the early learning of the foraging niche hypothesis in Great Tits
<p><span>This is the data set for the paper “</span><span><strong>Did you learn what to eat from your parents? A test of the early learning of the foraging niche hypothesis in Great Tits </strong><em><span><strong>Parus major</strong>”, </span></em><em><span>published in</span></em><em><span> <strong>Journal of Avian Biology</strong>. </span></em></span></p> <p><span><span>We collected information on foraging preferences of breeding Great Tits during twelve years (2011-2022) in the field station of Can Catà, within Collserola Natural Park (Cerdanyola, Barcelona, NE Iberian Peninsula, 45º 27' N, 2º 8' E). To obtain data about nestlings’ diet, we attached infra-red Micro-D cameras (Mini Colour Sony IR Camera SK-C170IR) to the nest top inside the nest-box and focused on the entrance, thus allowing us to identify delivered prey. Nests were recorded from 07:00-13:00h (five hours).</span></span></p> <p><span><span>Prey were classified into three categories -caterpillars, spiders and others- because caterpillars and spiders are the most important prey types for Mediterranean populations of Great Tits. The size of each prey item was determined according to a semi-quantitative scale in relation to beak size of the Great Tit, which has an average size of 9 mm. Size categories were: 1=small (smaller than beak size), 2 = medium (similar to beak size), 3 = large (larger than beak size).</span></span></p> <p><span><span>Data refers to percentage of caterpillars, percentage of spiders, percentage of ‘other prey’ and mean prey size (of all prey categories). To perform the analyses the percentage of each type of prey (caterpillars, spiders and ‘other prey’) were square-root transformed to approximate normality. Since the diet of individuals may vary across years due to changing weather conditions and environmental factors affecting prey availability, before comparing an individual’s diet across different years, data was standardised for different variables using a generalised linear mixed-effects model fitted by restricted maximum likelihood. Variables included were ‘year’, ‘sex’, ‘age’ (to distinguish if the breeding individual was yearling or adult), ‘brood size’, ‘brood age’, ‘date of recording’ (taken as the number of days from 1st April to control for phenology), and the proportion of oak trees in relation to Aleppo Pines within 25m of the nest-box. Analysis allowed to extracte residuals for further analysis, which appear in the four provided tables. </span></span></p> <p><span><span>For each individual we provide prey data corresponding to the chick stage and the data from the adult stage. Data is divided in four different sheets, using different variants of the diet data that individuals received as a chick: (1) using exclusively the father’s data (referred to as <em>Father Data</em>), (2) using only the mother’s data (referred to as <em>Mother Data</em>), (3) using the <em>mean of both parents</em>’ prey data (referred to as Mean Data), and (4) using <em>weighted parents data</em> depending on the number of provisioning trips (giving more importance to the prey delivered by the most actively feeding parent, referred to as Weighted Data). </span></span></p>
STEMMUS SCOPE emulator train test example data of 2014
<div> <div>The "csv" file contains land-atmosphere variables and latent heat flux (LEtot) simulated by STEMMUS-SCOPE (soil-plant model), version 1.5.0, see GitHub repository <a href="https://github.com/EcoExtreML/STEMMUS_SCOPE" target="_blank" rel="noopener">STEMMUS-SCOPE</a>. The data spreads over 19 Fluxnet sites and for the year 2014 with hourly intervals. For more information see <a href="https://research-software-directory.org/projects/ecoextreml" target="_blank" rel="noopener">EcoExtreML project</a>.</div> <br> <div>This data was used as training data pairs to develop an emulator using a random forests regression algorithm, the "onnx" file. The target variable is "latent heat flux (LEtot)" and features are land-atmosphere variables. For more information about the emulator, see GitHub repository <a href="https://github.com/EcoExtreML/Emulator" target="_blank" rel="noopener">STEMMUS-SCOPE Emulator</a>.</div> <div> </div> <div>The model and data are used to create a tutorial on applying an explainability method, for example, Kernel SHAP using the package <a href="https://dianna.readthedocs.io/en/latest/" target="_blank" rel="noopener">DIANNA</a>. For more information see <a href="https://www.esciencecenter.nl/projects/deep-insight-and-neural-networks-analysis-dianna/" target="_blank" rel="noopener">Deep Insight and Neural Network Analysis (DIANNA) project</a>.</div> </div>
Data for: "A test of the mechanistic process behind the convergent agonistic character displacement hypothesis"
<p><strong>Abstract</strong></p> <p><span>In this era of rapid global change, understanding the mechanisms that enable or prevent species from co-occurring has assumed new urgency. The convergent agonistic character displacement (CACD) hypothesis posits that signal similarity enables co-occurrence of ecological competitors by promoting aggressive interactions that reduce interspecific territory overlap and hence, exploitative competition. In northwestern Switzerland, ca. 10% of <em>Phylloscopus sibilatrix</em> produce songs containing syllables that are typical of their co-occurring sister species, P. bonelli (“mixed singers”). To examine whether the consequences of P. sibilatrix mixed singing are consistent with CACD, we combined a playback experiment and an analysis of interspecific territory overlap. Although P. bonelli reacted more aggressively to playback of mixed P. sibilatrix song than to playback of typical P. sibilatrix song, interspecific territory overlap was not reduced for mixed singers. Thus, the CACD hypothesis was not supported, which stresses the importance of distinguishing between interspecific aggressive interactions and their presumed spatial consequences. </span></p> <p><span> </span></p>
Data from: Ecological forensic testing: Using multiple primers for eDNA detection of marine vertebrates in an estuarine lagoon subject to anthropogenic influences
<p>Many critical aquatic habitats are in close proximity to human activity (i.e., adjacent to residences, docks, marinas, etc.), and it is vital to monitor biodiversity in these and similar areas that are subject to ongoing urbanization, pollution, and other environmental disruptions. Environmental DNA (eDNA) metabarcoding is an accessible, non-invasive genetic technique used to detect and monitor species diversity and is a particularly useful approach in areas where traditional biodiversity monitoring methods (e.g., visual surveys or video surveillance) are challenging to conduct. In this study, we implemented an eDNA approach that used a combination of three distinct PCR primer sets to detect marine vertebrates within a canal system of Biscayne Bay, Florida, an ecosystem representative of challenging sampling conditions and a myriad of impacts from urbanization. We detected fish species from aquarium, commercial, and recreational fisheries, as well as invasive, cryptobenthic, and endangered vertebrate species, including charismatic marine mammals such as the protected West Indian manatee, <em>Trichechus manatus</em>. Our results support the potential for eDNA analyses to supplement traditional biodiversity monitoring methods and ultimately serve as an important tool for ecosystem management. This approach minimizes stress or disturbance to organisms and removes the intrinsic risk and logical limitations of SCUBA diving, snorkeling, or deploying sensitive equipment in areas that are subject to high vessel traffic and/or low visibility. Overall, this work sets the framework to understand how biodiversity may change over different spatial and temporal scales in an aquatic ecosystem heavily influenced by urbanization and validates the use of eDNA as a complementary approach to traditional ecological monitoring methods.</p>
FIGURE A5 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A5. Scatter plot displaying how beam shift, measured by the apparent growth (scale) of the shell in the final x-ray radiograph relative to the first x-ray radiograph, varies with (1) time of day the scan was performed, and (2) the overall scan time. We found that beam shift decreased throughout the day, likely due to the tube warming up as more scans are run. There was no correlation between overall scan time and the amount of beam shift.
FIGURE A1.2 in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE A1.2. The range of volume measurements for each exposure times when three scans were reconstructed using ten methods. The blue dot represents the simple surface determination used for all shells in this study. The error bars represent the data range for each exposure time.
FIGURE 4. A in Testing the impact of two key scan parameters on the quality and repeatability of measurements from CT scan data
FIGURE 4. A video moving through slices of a pteropods shell scanned at 500 ms exposure time, with five xray radiographs averaged per view and an overall scan time of 75 minutes. There are streak artefacts perpendicular to the shell edge that are likely caused by beam hardening or shell movement during the scan. For video file, see https://palaeo-electronica.org/content/2020/ 2923-investigating-ct-scan-quality.
Fig. 6 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 6 Comparison of the duty cycle in the songs of the T. armeniaca complex and T. caudata (left panel) and the Tettigonia viridissima group (right panel)
Fig. 2 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 2 Oscillograms of the song of the Tettigonia viridissima group (1–9) and T. cantans (10) recorded at two speeds: 1 T. cf. longealata (MO: Ajabo, T = 20 °C), 2 T. cf. vaucheriana (MO: N Fes, T = 20 °C), 3 T. cf. vaucheriana (MO: Bouchfaa W of Taza, T = 21 °C), 4 T. cf. vaucheriana (MO: Tilougguite Pass, T = 23 °C), 5 T. cf. vaucheriana and cf. longealata (MO: El Kebab, T = 25 °C), 6 T. cf. vaucheriana (MO: El Kebab, T = 28–30 °C), 7 T. cf. viridissima (MO: S Aïn Zora, T = 22 °C), 8 T. cf. viridissima (MO: S Aïn Zora, T = 25 °C), 9 T. viridissima (BG: Sofia, T = 27 °C), and 10 T. cantans (IT: Val Malene; from Massa et al. 2012, T = 15 °C)). Scale bar for A is 10 s and for B 2 s
Fig. 5 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 5 Appearance of some taxa of Western Palaearctic Tettigonia (relative size proportions between photos not retained). a T. cantans, male, Germany, Gunzenhausen; b T. cantans, female, Germany, Gunzenhausen; c T. uvarovi Ebner, 1946—male, holotype, Siberia (NHMW), lateral view; d same, dorsal view; e T. caudata, male, Bulgaria, Russe district, Byala; f T. acutipennis Ebner, 1946—male, holotype, "Kleinasien 1914 | Marasch, Tölg. | coll. R. Ebner" (NHMW), dorsal view; g same, lateral view; h T. armeniaca, male, Armenia, Djermuk; i T. armeniaca, male, Turkey, Ispir; j T. viridissima morphotype of longealata, male, Morocco, El Kebab; k T. viridissima morphotype of longealata, female, Morocco, El Kebab; l T. viridissima morphotype of vaucheriana, male, Morocco, El Kebab; and m T. viridissima, male and female in copula, Bulgaria, Haskovo district, Kostilkovo village
Fig. 4 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 4 Phylogenetic tree of the genus Tettigonia based on BI analysis of concatenated COI-ITS1-ITS2 sequences. BI posterior probability (PP) values are shown near resolved branches (only support values above 0.50). Species groups, as defined by genetic and morpho-acoustic data, are distinctly shaded, and the respective branches are marked with an open circle and a capital letter as follows: "A"—T. viridissima group, "B"—T. caudata group, and "C"—T. cantans group. Haplotype codes correspond to Table 1 in the Supplement, followed by morphological identification. Squares on the right side of names correspond to relative wing length: filled squares short wings and open squares long wings;
Fig. 7 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 7 Relationship between the duration of chirps and inter-chirp intervals in T. caudata and the Tettigonia armeniaca complex. Green triangles mark recordings from Ispir, Turkey, where monosyllabic, disyllabic, and polysyllabic songs of T. armeniaca were recorded, as well as a song of T. caudata (Color figure online)
BRAIN Journal-High Performance Data mining by Genetic Neural Network-Figure 7 . Test Accuracy with prograess generation
<p>In the training phase, the neural network weights errors are minimized and network design<br> problem which the objective function to an acceptable level. In test step we have better results<br> because weights of neural network are adjusted by genetic algorithm and back propagation method.<br> Of course achievement to accuracy with 83.5% is reason using of good feature with minimum error.</p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 3. Symbols definition for a graph-based test
<p>In this scenario, we intend to generate a random graph and compute a deep first-search node list. The first defined random symbol is n, namely the number of nodes in the graph as an integer from 5 to 9. The next symbol is named g and denotes the graph object created randomly using 3 parameters: the number of nodes, the minimum, and the maximum value for the weight. For the number of nodes, we used the previously computed value of n, whereas for the weights, we used two constants 0 and 1 since the graph is not weighted</p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 4. Online test assessment example
<p>Thus, applying these restrictions the computed solution is C, E, G, J, L, H, I and is unique. Node C is the starting node since it is the first from the lexicographical point of view. The first step CE is the only choice coping with the restrictions from the [CE, CG, and CJ] edges. Next, EG is the first edge in the list of [EG, EJ]. The next step is GJ which is the only choice. Edge JL is another unique choice. Edge LH is the next step from the list [LH, LI]. Finally, the last edge is obtained by backtracking to node L and then taking edge LI. These restrictions allow us to drive the student to build only one solution from the possible set of solutions. This will determine an easier way of comparing the student’s answer with the answer of the computer. Another more general solution is to use validation functions which require implementation in domain libraries written in JavaScript. </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.