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Dataset results
236 results for “Behavior Modeling”
Extinction and ecosystem function debt across dispersal rate and behavior in a heterogeneous metacommunity model
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Multi-omic brain and behavioral correlates of cell-free fetal DNA methylation in macaque maternal obesity models (NMR datasets, maternal plasma and infant brain)
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Drugs prescribed in Phelan-McDermid Syndrome differentially impact sensory behaviors in shank3 zebrafish models
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Universality in the mechanical behavior of vertex models for biological tissues
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Data from: Hidden Markov models reveal tactical adjustment of temporally-clustered courtship displays in response to the behaviors of a robotic female
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Data from: Fibroblasts modulate epithelial cell behavior within the proliferative niche and differentiated cell zone within a human colonic crypt model
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From behavior to circuit modeling of light-seeking navigation in zebrafish larvae
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Data from: Sleep, inflammation, and cognitive behavior of aged wild-type mice subjected to diffuse brain injury and aged 3xTg-AD mice as a model of Alzheimer’s disease
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Data from: Does the house sparrow Passer domesticus represent a global model species for egg rejection behavior?
Conspecific brood parasitism (CP) is a facultative breeding tactic whereby females lay their eggs in the nests of conspecifics. In some species, potential host individuals have evolved the ability to identify and reject foreign eggs from their nest. Previous studies suggest that the ubiquitous House Sparrow Passer domesticus in Spain and South Africa employs both CP and parasitic egg rejection, while a population in China does not. Given the species' invasive range expansions, the House Sparrow represents a potentially excellent global model system for egg rejection across variable ecological conditions. The present study examines House Sparrow responses to experimental parasitism at three geographically distinct locations (in Israel, North America, and New Zealand) to provide a robust test of how general the findings of the previous studies are. In all three geographic regions egg rejection rates were negligible and not statistically different from background rates of disappearance of control eggs, suggesting that the House Sparrow is not a suitable model species for egg rejection experiments on a global scale.
Data from: Analyzing movement behavior and dynamic space-use strategies among habitats using multi-event capture-recapture modeling
1.The environment of most species is heterogeneous at different spatial and temporal scales; this heterogeneity can have a direct effect on various components of fitness. As a consequence, individual space-use and movement strategies are central issues in ecology and conservation and receive considerable attention from researchers. 2.In the last 30 years, this issue has led to the development of capture–recapture models that allow movement between sites to be quantified, while handling imperfect detection. For studies involving numerous recapture sites in which the emphasis is on dispersal or migration rather than movement between particular sites, Lagrange et al. recently proposed a parsimonious CR multi-event model that contrasts individuals that move and individuals that stay in place, irrespective of the sites involved. 3.In this study, we developed a generalized version of this model to allow survival probability and movement probability to differ for different types of habitat to which the individual sites may be assigned. We investigated the potential of this new parameterization by studying the movements of an amphibian, the yellow-bellied toad (Bombina variegata), in a set of breeding and resting/foraging ponds. 4.Our capture-recapture multi-event model provides a highly flexible tool allowing users to model movements within and between several habitats. This approach can be potentially used to study movement behavior and space-use strategies of a wide range of taxa.
Data from: A dynamic state model of migratory behavior and physiology to assess the consequences of environmental variation and anthropogenic disturbance on marine vertebrates
Integrating behavior and physiology is critical to formulating new hypotheses on the evolution of animal life-history strategies. Migratory capital breeders acquire most of the energy they need to sustain migration, gestation and lactation before parturition. Therefore, when predicting the impact of environmental variation on such species, a mechanistic understanding of the physiology of their migratory behavior is required. Using baleen whales as a model system, we developed a dynamic state variable model that captures the interplay among behavioral decisions, energy, reproductive needs and the environment. We applied the framework to blue whales (Balaenoptera musculus) in the Eastern North Pacific Ocean, and explored the effects of environmental and anthropogenic perturbations on female reproductive success. We demonstrate the emergence of migration to track prey resources, enabling us to quantify the trade-offs among capital breeding, body condition, and metabolic expenses. We predict that periodic climatic oscillations affect reproductive success less than unprecedented environmental changes do. The effect of localized, acute anthropogenic impacts depended on whales' behavioral response to the disturbance; chronic, but weaker, disturbances had little effect on reproductive success. Because we link behavior and vital rates by modeling individuals' energetic budgets, we provide a general framework to investigate the ecology of migration and assess the population consequences of disturbance, while identifying critical knowledge gaps.
BSO-GBD:Behavior Sequence-Oriented GitHub Bot Detection model
<p>Our dataset is primarily divided into three parts. Firstly, there are human accounts (Human) and bot accounts (Bot). Both of these types appear similar to regular developer accounts, lacking any distinctive markings. The second category comprises self-bot accounts, typically formed by GitHub apps. These accounts generally bear an explicit "bot" label, and we exclude them in our classification.</p> <p>The dataset is structured as follows: a total of 4786 ordinary accounts, with 4325 being Human accounts and 461 being Bot accounts. Each account internally consists of a CSV table with the following fields: user_name; repo_name; event_type_L1; event_type_L2; event_type_L3; timestamp. These data constitute our raw dataset.</p>
A computationally efficient method for parameter sensitivity analysis of microbially-explicit biogeochemical models accounting for long-term behavior
<p>The dataset is for the manuscript entitled "A computationally efficient method for parameter sensitivity analysis of microbially-explicit biogeochemical models accounting for long-term behavior".</p>
Artifacts for paper "PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing" submitted to TOSEM
<p>The project includes the data and code used in the submitted TOSEM paper titled "PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing"</p>
Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment
<p>quantization benchmark</p>
Behavioral analysis for market anomalies with heterogeneous agent model
<p>This paper investigates the effect of heterogeneity and bounded rationality on market anomalies in price formation. We establish a heterogeneous agent model under prospect theory, where asset price fluctuation is determined by evolutionary dynamics system embedded in the model. Specifically, our model includes three types of expectation schemes related to different decision-making progresses: the rational scheme, the emotional scheme and the noise scheme. Agents under emotional scheme make decisions based on the cumulative prospect theory framework, which makes psychological factor tractable. By analyzing the distribution of return rate under selected parameters, we show that the model return shares the same pattern as those of SSE 50 Index. Furthermore, we investigate the factors of option implied volatility smile based on dynamic system, and the results suggest that the smile anomaly may be associated with the tail risk of the underlying asset's return distribution, which is effected by market stability and psychological factors.</p>
Verifying the Conformance of Human Behavior Using Hybrid Models - Synthetic Event Logs
<p>Synthetic event logs used in the evaluation of the approach for the verification of conformance checking of human behavior, using hybrid process models.</p>
The effects of exploratory behavior on physical activity in a common animal model of human disease, zebrafish (Danio rerio)
<p>Zebrafish (Danio rerio) are widely accepted as a multidisciplinary vertebrate model for neurobehavioral and clinical studies, and more recently have become established as a model for exercise physiology and behavior. Individual differences in activity level (e.g., exploration) have been characterized in zebrafish, however, how different levels of exploration correspond to differences in motivation to engage in swimming behavior has not yet been explored. We screened individual zebrafish in two tests of exploration: the open field and novel tank diving tests. The fish were then exposed to a tank in which they could choose to enter a compartment with a flow of water (as a means of testing voluntary motivation to exercise). After a 2-day habituation period, behavioral observations were conducted. We used correlative analyses to investigate the robustness of the different exploration tests. Due to the complexity of dependent behavioral variables, we used machine learning to determine the personality variables that were best at predicting swimming behavior. Our results show that contrary to our predictions, the correlation between novel tank diving test variables and open field test variables was relatively weak. Novel tank diving variables were more correlated with themselves than open field variables were to each other. Males exhibited stronger relationships between behavioral variables than did females. In terms of swimming behavior, fish that spent more time in the swimming zone spent more time actively swimming, however, swimming behavior was inconsistent across the time of the study. All relationships between swimming variables and exploration tests were relatively weak, though novel tank diving test variables had stronger correlations. Machine learning showed that three novel tank diving variables (entries top/bottom, movement rate, average top entry duration) and one open field variable (proportion of time spent frozen) were the best predictors of swimming behavior, demonstrating that the novel tank diving test is a powerful tool to investigate exploration. Increased knowledge about how individual differences in exploration may play a role in swimming behavior in zebrafish is fundamental to their utility as a model of exercise physiology and behavior.</p>
A Hydrodynamic-Based Physical Unified Modeling for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behavior
<p>Simulation results for manuscript "A Hydrodynamic-Based Physical Unified Modelling Framework for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behaviour", submitted to Water Resources Research.</p>
A Hydrodynamic-Based Physical Unified Modeling for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behavior
<p>Simulation results for manuscript "A Hydrodynamic-Based Physical Unified Modelling Framework for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behaviour", submitted to Water Resources Research.</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.