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2,015 results for “context”
Data from: Mesocarnivore community structure under predator control: unintended patterns in a conservation context
Across the Mediterranean, conservation programmes often operate concomitantly with hunting interests within game-lands. Carnivore guilds lie at the interface between contrasting management goals, being simultaneously fundamental components of ecosystems and targets of predator control to reduce predation on game species. Here, we evaluate the composition and spatial structure of a mesocarnivore community in a protected area of Southeast Portugal, with high economic investment in conservation and significant hunting activity. Between June and August 2015, we deployed 77 camera-traps across a ~80 km2 area. We report on interspecific disparities in mesocarnivore occupancy and associated environmental determinants. Contrasting occupancy states suggest an unbalanced community, biased towards the widespread occurrence of the red fox Vulpes vulpes ("ψ" ̂ = 0.92±0.04) compared to other species (stone marten Martes foina, European badger Meles meles, Egyptian mongoose Herpestes ichneumon, common genet Genetta genetta, and Eurasian otter Lutra lutra) exhibiting spatially-restricted occupancy patterns ("ψ" ̂ / naïve occupancy < 0.35). The feral cat Felis silvestris catus was the exception ("ψ" ̂ = 0.48±0.11) and, together with the stone marten, exhibited a positive association with human settlements. These findings are consistent with theoretical predictions on how mesocarnivore communities are shaped by the effects of non-selective predator control, paradoxically favouring species with higher population growth rates and dispersal abilities, such as the red fox. Our results reinforce the need to understand the role of predator control as a community structuring agent with potential unintended effects, while exposing issues hindering such attempts, namely non-selective illegal killing or biased/concealed information on legal control measures.
Data from: Genetic diversity of oilseed rape fields and feral populations in the context of coexistence with GM crops
Despite growing concern about transgenes escaping from fields, few studies have analysed the genetic diversity of crops in an agroecosystem over several years. Accurate information about the dynamics and relationship of the genetic diversity of crops in an agroecosystem is essential for risk assessment and policies concerning the containment of genetically modified crops and their coexistence with crops grown by conventional practices. Here, we analysed the genetic diversity of oilseed rape plants from fields and feral populations over 4 years in an agricultural landscape of 41 km2. We used exact compatibility and maximum likelihood assignment methods to assign these plants to cultivars. Even pure lines and hybrid cultivar seed lots contained several genotypes. The cultivar diversity in fields reflected the conventional view of agroecosystems quite well: that is, there was a succession of cultivars, some grown for longer than others because of their good performance, some used for one year and then abandoned, and others gradually adopted. Three types of field emerged: fields sown with a single cultivar, fields sown with two cultivars, and unassigned fields (too many cultivars or unassigned plants to reliably assign the field). Field plant diversity was higher than expected, indicating the persistence of cultivars that were grown for only one year. The cultivar composition of feral populations was similar to that of field plants, with an increasing number of cultivars each year. By using genetic tools, we found a link between the cultivars of field plants in a particular year and the cultivars of feral population plants in the following year. Feral populations on road verges were more diverse than those on path verges. All of these findings are discussed in terms of their consequences in the context of coexistence with genetically modified crops.
Data from: Multi-scale effects of habitat structure and landscape context on a vertebrate with limited dispersal ability (the brown-throated sloth, Bradypus variegatus)
As human population, food consumption, and demand for forest products continue to rise over the next century, the pressures of land use change on biodiversity are projected to intensify. In tropical regions, countryside habitats that retain abundant tree cover and structurally complex canopies may complement protected areas by providing suitable habitats and landscape connectivity for a significant portion of the native biota. Species with low dispersal capabilities are among the most at risk of extinction as a consequence of land use change. We assessed how the spatial distribution of the brown-throated sloth (Bradypus variegatus), a model species for a vertebrate with limited dispersal ability, is shaped by differences in habitat structure and landscape patterns of countryside habitats in north-central Costa Rica using a multi-scale framework. We quantified the influence of local habitat characteristics and landscape context on sloth occurrence using mixed-effects logistic regression models. We recorded 27 sloths within countryside habitats and found that both local and landscape factors significantly influenced their spatial distribution. Locally, sloths favored structurally complex habitats, with greater canopy cover and variation in tree height and basal area. At the landscape scale, sloths demonstrated a preference for habitats with high proportions of forest and nearly large tracts of forest. Although mixed-use areas and tree plantations are not substitutes for protected forests, our results suggest they provide important supplemental habitats for sloths. To promote the conservation and long-term viability of sloth populations in the tropical countryside, we recommend for land managers to retain structurally complex vegetation and large patches of native habitat.
Data from: Genetic and population monitoring of two small black bear (Ursus americanus) populations in Alabama, within a regional context.
One of the major concerns in conservation today is the loss of genetic diversity which is a frequent consequence of population isolation and small population sizes. Fragmentation of populations and persecution of carnivores has posed a substantial threat to the persistence of free ranging carnivores in North America since the arrival of European settlers. Black bears have seen significant reductions in range size from their historic extent, which is most pronounced in the southeastern United States and even more starkly in Alabama where until recently bears were reduced to a single geographically isolated population in the Mobile River Basin. Recently a second population has naturally re-established itself in northeastern Alabama. We sought to determine size, genetic diversity and genetic connectivity for these two populations in relation to other regional populations. Both populations of black bears in Alabama had small population sizes and had moderate to low genetic diversity, but showed different levels of connectivity to surrounding populations of bears. The Mobile River Basin population had a small population size at only 86 individuals (76-124, 95% C.I.), the lowest genetic diversity of compared populations (richness =2.33, Ho and He =0.33), and showed near complete genetic isolation from surrounding populations across multiple tests. The newly recolonizing population in northeastern Alabama had a small but growing population doubling in 3 years (34 individuals 26-43, 95% C.I.), relatively moderate genetic diversity compared to surrounding populations (richness = 3.32, Ho =0.53, He =0.65), and showed a high level of genetic connectivity with surrounding populations.
Data from: Ecological context and the probability of mistakes underlie speed choice
1.Movement is fundamental to the ecology of animals, and an animal's choice of movement speed determines the duration, energetic costs, and probability of success of any given activity. It is often assumed that animals should use maximum speeds when escaping from predators, but an increasing number of studies find animals rarely move as fast as they can in nature because faster speeds come with a greater chance of mistakes. Mathematical modelling suggests that, when escaping predators, prey animals should optimise speeds to simultaneously outrun their pursuer and minimise their probability of slipping. This can be particularly important when running along narrow structures like branches. When foraging, however, animals should avoid moving at high speeds, which are often energetically costly and decrease the ability to detect food or predators. 2.In this study, we examined how trade-offs between speed and probability of slipping influenced the speed choice of wild antechinus (Antechinus mysticus) during escaping and foraging behaviours. We also examined how this trade-off affected foraging behaviour. 3.Antechinus ran significantly faster when escaping (1.207 ± 0.033 ms-1) than foraging (0.145 ± 0.002 ms-1), and slipped 37% more often during escapes. However, foraging antechinus still slipped frequently on narrow branches, despite running an order of magnitude more slowly than they did on wide branches. Furthermore, antechinus slipped at lower speeds when foraging than they did when escaping, suggesting that avoiding mistakes is less highly prioritized when foraging. 4.Antechinus visited the feeding station accessed by a wide branch more frequently (and ate more while there) compared with feeding stations accessed by narrow branches, even when those branches were 33% or 67% shorter. This suggests that foraging decisions may be based on potential limitations to speed and the probability of slipping over distance to cover. 5.Though activities such as running can be fundamental to animals' fitness, a general framework to understand how animals select speeds in nature is still being developed. We test the assumption that animals choose running speeds to minimise their motor mistakes, and demonstrate the cost of mistakes is likely to be different across ecological and behavioural contexts.
Data from: Context-dependent expression of sexual dimorphism in island populations of the common wall lizard (Podarcis muralis)
The condition-dependent sexual dimorphism model explains the evolution and maintenance of sexual dimorphism in traits targeted by sexual selection, and predicts that the magnitude of sexual dimorphism depends on the variability of individual condition, male traits being more variable than female corresponding traits. Most convincing examples concern insects, while studies among vertebrates are scanty because manipulating condition often is not possible, and the time to reach sexual maturity may be too long. Islands offer a unique opportunity to compare how the environment affects the expression of sexual dimorphism, since they represent 'natural experimental sets' in which different populations of the same species may experience alternative environmental constraints. We investigated the occurrence of context-dependent expression in sexual dimorphism of head shape in insular populations of the common wall lizards (Podarcis muralis) inhabiting the Tuscan Archipelago (Tyrrhenian Sea). Alternative models were formulated: H0 assumes that the sexual dimorphism is uninfluenced by islands, H1 assumes the only effect of phylogeny, H2A and H2B account for the biogeography of the archipelago (island size and distance from the mainland), while H3 assumes island-specific effects on sexual dimorphism. Models were compared using Akaike's information criterion adjusted for multivariate analyses. All hypotheses performed better than H0, but H3 largely outperformed all other alternative hypotheses, indicating that environmental features of islands play an additive effect to ontogenetic, biogeographic and genetic factors in defining variation in head shape sexual dimorphism. Our results support the hypothesis of a context-dependent sexual dimorphism in common wall lizards
Data from: Context-specific learning and its implications for social learning
Social learning is widespread but the causes for variation in the use of social versus private information are not always clear. Alongside adaptive explanations, suggesting that animals learn socially only when it is indeed adaptive to do so, it is also possible that the use of social learning is limited by mechanistic constraints. A common, but frequently overlooked challenge for social learning mechanisms is the need to allow learners to solve a problem through watching it being solved by others. This requires animals to be able to shift between contexts: from the context of the observed solution, to the context of the unsolved problem. For instance, for the social learning of cues associated with hidden food, an individual that merely sees a conspecific exploiting the food must, in the later absence of demonstrators or visible rewards, also learn to explore the cue for itself. Here we show that this shift in context can indeed be difficult. In two experiments involving sand colors, house sparrows trained with hidden seeds learned to search for hidden seeds (based on food-color association) better than sparrows trained with exposed seeds. However, the latter showed color preference when tested with seeds exposed on both sand colors. These results demonstrate that context-specific learning makes it difficult to generalize reward-cue association from "exposed" to "hidden" conditions, which may explain why social learning is often more effective when it is based on socially facilitated active search (for hidden food), similar to that used in the context of independent foraging.
Data from: Direct and plant trait-mediated effects of the local environmental context on butterfly oviposition patterns
Variation in the intensity of plant-animal interactions over different spatial scales is widespread and might strongly influence fitness and trait selection in plants. Differences in traits among plant individuals have been shown to influence variation in interaction intensities within populations, while differences in environmental factors and community composition are shown to be important for variation over larger scales. However, little is still known about the relative importance of the local environmental context vs. plant traits for the outcome of interactions within plant populations. We investigated how oviposition by the seed-predator butterfly Phengaris alcon on its host plant Gentiana pneumonanthe was related to host plant traits and to local environmental variation, as well as how oviposition patterns translated into effects on host plant fruit set. We considered the local environmental context in terms of height of the surrounding vegetation and abundance of the butterfly's second host, Myrmica ants. The probability of oviposition was higher in plants that were surrounded by lower vegetation, and both the probability of oviposition and the number of eggs increased in early-flowering and tall plants with many flowers in the three study populations. Flowering phenology, shoot height and flower production were, in turn, related to higher surrounding vegetation. Myrmica abundance was correlated with vegetation height, but had no effect on oviposition patterns. Oviposition and subsequent seed predation by the caterpillars strongly reduced host plant fruit set. Our results show that plant-animal interactions are context-dependent not only because the context influences the abundance or the behavior of the animal interactor, but also because it influences the expression of plant traits that affect the outcome of the interaction. The results also demonstrate that heterogeneity in environmental conditions at a very local scale can be important for the outcomes of interactions.
Drei Harlekine / Three Harlequins - In context
Experimenting with background and how it is when models are shown in context. [Original models](https://sketchfab.com/3d-models/drei-harlekine-three-harlequins-924b850d72bd46478ab650cfa353d94d) are available. Background done using a sphere with an image texture taken by an [Insta360](https://www.insta360.com/). Added bonus: zoom out of the sphere and get street view. Source: Objaverse 1.0 / Sketchfab
Context Model of Aurora Image Analysis
<p>Context model for an experiment implemented in Python that classifies Aurora images. Auhtor of the script is Daisuke Kitao.</p>
X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains
<p>Supplementary information from the paper "X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains", features in a Geological Society Publication in memory of Professor Martin Brasier, University of Oxford.</p> <p>Datasets comprise:<br> -- A zipped Drishti volumes for all CT scans reported in the paper, which can be used for both 3D visualisations and to inspect the underlying data.<br> -- A .7z split zip file of one Drishti volume above 2GB.<br> -- An HDMI movie showing digital visualisations for all of the scans reported in the paper. </p>
FIGURE 2. Geology and stratigraphy context. A in A new specimen of the theropod dinosaur Baryonyx from the early Cretaceous of Portugal and taxonomic validity of Suchosaurus
FIGURE 2. Geology and stratigraphy context. A, Stratigraphic log at Praia das Aguncheiras; B, Cretaceous geological formations at Espichel Cape (based on Manuppella 1994); C, Lisbon and Tagus Valley Mesozoic sedimentary rocks based on Liñán, 2001; D, Portuguese Mesozoic sedimentary rocks based on Liñán, 2001. Abbreviations: C2Ga, Galé Formation; C1Ro, Rodízio Formation; C1Cr, Cresmina Formation; C1Re, Regatão Formation; C1HB, Ladeiras, Rochadouro, Areia do Mastro, Papo-Seco and Boca do Chapim Formations; C1Ma, Maceira marls and reefal limestones; C1GL, Vale de Lobos and Guia grés, mudstones and limestones; C1Ca - Mudstones and sandstones of Porto da Calada Fm.
Dataset from "Rewarded visual items capture attention only in heterogeneous contexts"
<p>Dataset from the following publication: Feldmann-Wüstefeld, T., Brandhofer, R. & Schubö, A. (2016). Rewarded visual items capture attention only in heterogeneous contexts. Psychophysiology, 53, 1063-1073. DOI: 10.1111/psyp.12641</p>
Data of paper "Grid ,Hydrodynamic boundary and Uncertainty analysis of 2D-SWEs in the context of digital twins: Taking numerical simulation of river networksas an example"
<p>论文数据 “数字孪生背景下2D-SWEs的网格、水动力边界和不确定性分析:以河流网络数值模拟为例”</p>
Online repository for Paper "AgentFL: Scaling LLM-based Fault Localization to Project-Level Context"
<h3>Summary</h3> <p>This is the online repository for the arXiv paper "AgentFL: Scaling LLM-based Fault Localization to Project-Level Context".</p> <p>We also provide the results for the TSE'25 paper "SOAPFL: A Standard Operating Procedure for LLM-based Method-Level Fault Localization".</p> <h3>Environment</h3> <ul> <li><a href="https://github.com/rjust/defects4j/tree/v1.4.0">Defects4J-V1.4.0</a> (Note that the buggy items in V1.4.0 is identical with V1.2.0, we use V1.4.0 to avoid some problems in V1.2.0)</li> <li><a href="https://github.com/rjust/defects4j/tree/v2.0.0">Defects4J-V2.0.0</a></li> <li>Python version >= 3.8.5</li> </ul> <h3>Defects4J Mod</h3> <p>Before running AgentFL, please apply the files under the <code>AgentFL/Defects4J_mod</code> directory to modify your Defects4J V1.4.0/V2.0.0.</p> <h3>Run AgentFL</h3> <p>Set your own OpenAI API key in <code>AgentFL/camel/model_backend.py</code></p> <p>It's easy to run AgentFL for localizing a bug with the following command:</p> <p><code>python3 run.py --config <CONFIG_DIR> --version <D4J_VERSION> --project <PROJECT> --bugID <BUG_ID> --model <GPT_MODEL_NAME></code></p> <p>For example:</p> <p><code>python3 run.py --config Default --version 1.4.0 --project Closure --bugID 26 --model GPT_3_5_TURBO</code></p> <p>More configs can be seen under the directory <code>AgentFL/Config</code></p> <h3>Results</h3> <p>We release all of the results of AgentFL in the <code>AgentFL/Results</code> directory, including the evaluation results on Defects4J V1.4.0/V2.0.0 and the ablation study result.</p> <p>For each bug, we record all of the prompts, responses, and intermediate outputs.</p> <blockquote> <p>NEW: We have released the newest results for TSE'25 paper "SOAPFL: A Standard Operating Procedure for LLM-based Method-Level Fault Localization". The results can be found in the `<a href="https://zenodo.org/api/records/16938304/draft/files/SoapFL_results.zip/content" target="_blank" rel="noopener noreferrer">SoapFL_results.zip</a>` file!</p> </blockquote> <h3>Human Evaluation Results</h3> <p>The human evaluation results can be found in the file <code>AgentFL/EvaluationResult/DebugResult_d4j140_GPT35_human.xlsx</code></p> <h3>System Messages for Agents</h3> <ul> <li>Test Code Reviewer:</li> </ul> <blockquote> <p>You are a Test Code Reviewer. We share a common interest in collaborating to successfully locate the buggy code that cause the test suite to fail. You can examine the test code and the initialized classes to analyze the similar behavior of the failed tests within the test suite. To locate the bug, you must write a response that appropriately solves the requested instruction based on your expertise.</p> </blockquote> <ul> <li>Source Code Reviewer</li> </ul> <blockquote> <p>You are a Source Code Reviewer. we are both working at DebugDev. We share a common interest in collaborating to successfully locate the buggy code that cause the test suite to fail. Your main responsibilities is to generate a comment for each covered method base on the method call relationship. To locate the bug, you must write a response that appropriately solves the requested instruction based on your expertise.</p> </blockquote> <ul> <li>Software Test Engineer</li> </ul> <blockquote> <p>You are a Software Test Engineer. We share a common interest in collaborating to successfully locate the buggy code that cause the test suite to fail. You main responsibilities include examining the information of the failed tests to analyze the possible causes of the test failures, and determining the method that need to be fixed. To locate the bug, you must write a response that appropriately solves the requested instruction based on your expertise.</p> </blockquote> <ul> <li>Software Architect</li> </ul> <blockquote> <p>You are a Software Architect. We share a common interest in collaborating to successfully locate the buggy code that cause the test suite to fail. You are very familiar with the architecture of the software, the functions of each class and method in the software. You main responsibilities include examining the given information to locate the possible buggy classes and buggy methods. To locate the bug, you must write a response that appropriately solves the requested instruction based on your expertise.</p> </blockquote>
Pre-training and fine-tuning dataset for transformers consisting of basic blocks and their execution times (average, minimum, and maximum) along with the execution context of these blocks, for various Cortex processors M7, M4, A53, and A72.
<p>We are making public the dataset used for training CAWET, a tool for estimating the Worst-Case Execution Time (WCET) of basic blocks using the Transformer XL model. CAWET leverages the Transformer architecture for accurate WCET predictions, and its training involves two main phases: self-supervised pre-training and fine-tuning.</p><p>CAWET undergoes a pre-training process on a substantial corpus of basic blocks to enable the Transformer to grasp the intricacies of the assembly language in focus. For this, we utilized CodeNet \cite{codenet}, a comprehensive collection of publicly submitted solutions to competitive programming challenges, comprising roughly 900,000 C programs. These programs were cross-compiled to the target architecture and subsequently disassembled using GNU binary utilities with objdump. The textual output from objdump, post a series of basic parsing operations (e.g., address extraction, separation of basic blocks), serves as the foundation for an extensive pre-training dataset. We employed this dataset to develop a vocabulary model utilizing sentence piece \cite{sentencepiece}. Following the completion of the sentence piece model's training, it becomes ready for use in tokenizing any binary programs written in the target instruction set.</p><p>The fine-tuning phase of CAWET involves its adaptation to basic blocks along with their contextual information. Here, we used a varied and openly accessible collection of programs, namely, The Algorithms (accessible at: <a href="https://github.com/TheAlgorithms/C">https://github.com/TheAlgorithms/C</a>), MiBench \cite{mibench}, and Polybench \cite{polybench}.</p><p>The provided zip file encompasses the following directories:</p><p>Fine_Tuning: This includes four distinct files, each tailored for a specific processor: Cortex_M4, Cortex_M7, Cortex_A53, and Cortex_72. Each file encompasses the basic block under analysis (bbUA), the preceding 10 basic blocks executed prior to it, and timing information related to the bbUA (mean, min, max, normalization, etc.).</p><p>Pre_Training: This comprises two extensive files, dataset_CortexA and dataset_CortexM, utilized for pre-training the transformers for the Masked Language Modeling Task (MLM). Additionally, it includes the sentence piece model and the necessary code to facilitate accurate tokenization.</p><p>For additional information, please refer to the CAWET paper or contact us at <a href="mailto:ea_amalou@esi.dz">ea_amalou@esi.dz</a></p><p> </p><p>Citation:</p><p>@inproceedings{amalou2023cawet,</p><p> title={CAWET: Context-Aware Worst-Case Execution Time Estimation Using Transformers},</p><p> author={Amalou, Abderaouf N and Fromont, Elisa and Puaut, Isabelle},</p><p> booktitle={35th Euromicro Conference on Real-Time Systems (ECRTS 2023)},</p><p> year={2023},</p><p> organization={Schloss Dagstuhl-Leibniz-Zentrum f{\"u}r Informatik}</p><p>}</p><p> </p><p><strong>Bibliography</strong>:</p><p>codenet</p><p>@article{codenet2021,</p><p> title={CodeNet: A large-scale AI for code dataset for learning a diversity of coding tasks},</p><p> author={Puri, Ruchir and Kung, David S and Janssen, Geert and Zhang, Wei and Domeniconi, Giacomo and Zolotov, Vladimir and Dolby, Julian and Chen, Jie and Choudhury, Mihir and Decker, Lindsey and others},</p><p> journal={arXiv preprint arXiv:2105.12655},</p><p> year={2021}</p><p>}</p><p>sentencepiece</p><p>@article{sentencepiece2018,</p><p> title={Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing},</p><p> author={Kudo, Taku and Richardson, John},</p><p> journal={arXiv preprint arXiv:1808.06226},</p><p> year={2018}</p><p>}</p><p>mibench</p><p>@inproceedings{polybench2014,</p><p> title={Understanding polybench/c 3.2 kernels},</p><p> author={Yuki, Tomofumi},</p><p> booktitle={International workshop on polyhedral compilation techniques (IMPACT)},</p><p> pages={1--5},</p><p> year={2014}</p><p>}</p><p>polybench: </p><p>@inproceedings{mibench,</p><p> title={MiBench: A free, commercially representative embedded benchmark suite},</p><p> author={Guthaus, Matthew R and Ringenberg, Jeffrey S and Ernst, Dan and Austin, Todd M and Mudge, Trevor and Brown, Richard B},</p><p> booktitle={4th IEEE international workshop on workload characterization},</p><p> year={2001}</p><p>}</p>
FIGURE 14 in Trans-Japan Sea land-bridge disjunction: A case of vicariance in the subterranean genus Nipponasellus (Crustacea, Isopoda, Asellidae) in a largescale biogeographical context
FIGURE 14. Dendrogram based on UPGMA cluster analysis using the faunistic similarity data obtained for each landscape cluster: AUa, Amur-Ussury area; SSd, South Seaside district; MSd, East Manchuria Seaside district (see ESupplement5.pdf).
FIGURE 15 in Trans-Japan Sea land-bridge disjunction: A case of vicariance in the subterranean genus Nipponasellus (Crustacea, Isopoda, Asellidae) in a largescale biogeographical context
FIGURE 15. Paleogeographic reconstruction before opening of the Japan Sea: (a) Oligocene (following Itoh 2017, p. 86, fig. 1); (b) Early Miocene (modified from Uemura 2006; in Ozawa 2016, p. 137, fig. 14). Nipponasellus (red dots), Phreatoasellus (yellow dots), Sibirasellus (green dots).
FIGURE 13 in Trans-Japan Sea land-bridge disjunction: A case of vicariance in the subterranean genus Nipponasellus (Crustacea, Isopoda, Asellidae) in a largescale biogeographical context
FIGURE 13. Scanning electron micrographs of pleopod 2 of Nipponasellus matsumotoi spec. nov., adult male: (A) pair of pleopods 2, ventral view; (B) endopodite of pleopod 2, right; (C, D) appendix masculina enlarged, right and left.
FIGURE 11. Nipponasellus matsumotoi spec. nov., holotype X54659 in Trans-Japan Sea land-bridge disjunction: A case of vicariance in the subterranean genus Nipponasellus (Crustacea, Isopoda, Asellidae) in a largescale biogeographical context
FIGURE 11. Nipponasellus matsumotoi spec. nov., holotype X54659/Cr-2477-FEFU, male, 5.5 mm: (A) pereopod 1, with enlarged palm; (B) pereopod 2; (C) pereopod 3; (D) pereopod 4; (E) pereopod 5; (F) pereopod 6; (G) pereopod 7.
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.