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39 results for “activity budget”
Figure 1 in Seasonal variations in the time - activity budget of Royle's pika in the Western Himalayaı India
Figure 1. Proportions (%) of time during which adult Royle's pika were active at different elevations and in different seasons.
Data from: Accelerometers can measure total and activity-specific energy expenditure in free-ranging marine mammals only if linked to time-activity budgets
Energy expenditure is an important component of foraging ecology, but is extremely difficult to estimate in free-ranging animals and depends on how animals partition their time between different activities during foraging. Acceleration data have emerged as a new way to determine energy expenditure at a fine scale but this needs to be tested and validated in wild animals. This study investigated whether vectorial dynamic body acceleration (VeDBA) could accurately predict the energy expended by marine predators during a full foraging trip. We also aimed to determine whether the accuracy of predictions of energy expenditure derived from acceleration increased when partitioned by different types of at-sea activities (i.e. diving, transiting, resting and surface activities). To do so, we equipped 20 lactating northern (Callorhinus ursinus) and 20 lactating Antarctic fur seals (Arctocephalus gazella) with GPS, time-depth recorders and tri-axial accelerometers and obtained estimates of field metabolic rates using the doubly labelled water (DLW) method. VeDBA was derived from tri-axial acceleration, and at-sea activities (diving, transiting, resting and surface activities) were determined using dive depth, tri-axial acceleration and travelling speed. We found that VeDBA did not accurately predict the total energy expended by fur seals during their full foraging trips (R2 = 0·36). However, the accuracy of VeDBA as a predictor of total energy expenditure increased significantly when foraging trips were partitioned by activity and when activity-specific VeDBA was paired with time-activity budgets (R2 = 0·70). Activity-specific VeDBA also accurately predicted the energy expenditures of each activity independent of each other (R2 > 0·85). Our study confirms that acceleration is a promising way to estimate energy expenditures of free-ranging marine mammals at a fine scale never attained before. However, it shows that it needs to be based on the time-activity budgets that make up foraging trips rather than being derived as a single measure of VeDBA applied to entire foraging trips. Our activity-based method provides a cost-effective means to accurately calculate energy expenditures of fur seals using acceleration and time-activity budgets, that can be transfered to studies on other species.
Wave Activity Budget Dataset
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Figure 6 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 6. Behaviours exhibited by captive-born collared peccaries grouped into the territorial and exploratory categories. a) Dorsal gland mark; b) Rub head on ground/object; c) Nose ground; d) Nose air; e) Tasting; f) Root.
Figure 4 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 4. Behaviours exhibited by captive-born collared peccaries grouped into the social affiliative category. a) Head toss; b) Mutual rub neck; c) Mutual rub; d) Weak bite; e) Roll; f) Play in mud.
Figure 3 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 3. Behaviours exhibited by the captive-born collared peccaries grouped into reproductive category. a) Chin on back; b) Chin on head; c) Nurse; d) Mount.
Figure 1 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 1. Behaviours exhibited by the captive-born collared peccaries grouped into the locomotion and inactivity categories. a) Sequence from left to right: inactive, walking, trotting and running; b) Yawning; c) Stretching, and d) Sleeping.
Figure 2 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 2. Behaviours exhibited by the captive-born collared peccaries grouped into the social aggressive category. a) Stand over; b) Agonistic squabble; c) Tooth clack; d) Kneel; e) Lift with snout.
Figure 7 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 7. Behaviours exhibited by captive-born collared peccaries grouped into the exploratory, antipredator and maintenance categories. a) Flehmen; b) Erect dorsal bristles; c) Escaping; d) Scratching; e) Grooming.
Figure 5 in Ethogram and time-activity budget of the collared peccary (Pecari tajacu, Tayassuidae): implications for husbandry and welfare
Figure 5. Behaviours exhibited by captive-born collared peccaries grouped into the social affiliative category. a) Nose; b) Nose back; c) Nose rump; d) Nose dorsal gland; e) Nose nose; f) Nose belly.
Data from: Too hot to die? The effects of vegetation shading on past, present, and future activity budgets of two diurnal skinks from arid Australia
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Data from: Accelerometers can measure total and activity-specific energy expenditure in free-ranging marine mammals only if linked to time-activity budgets
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Рис. 6. Суточный бюΑжет времени основных виΑов ΑеятеΛьности поΑземной поΛевки (на примере активности ♂ № 4; июΛь 2000 г., манеж БиНИИ) Fig. 6. Daily time budget of the main activities of the common pine vole. (on the example of the activity of ♂ No. 4; July 2000, measured in a pen at the Scientific Research Institute of Biology) in Spatial Organization Of Common Pine Vole (Microtus Subterraneus Selys-Longchamps, 1836) Colonies
Рис. 6. Суточный бюΑжет времени основных виΑов ΑеятеΛьности поΑземной поΛевки (на примере активности ♂ № 4; июΛь 2000 г., манеж БиНИИ) Fig. 6. Daily time budget of the main activities of the common pine vole. (on the example of the activity of ♂ No. 4; July 2000, measured in a pen at the Scientific Research Institute of Biology)
Figures 2-7 from: Back JP, Suzin A, Aguiar LM (2019) Activity Budget and Social Behavior of Urban Capuchin Monkeys (Sapajus sp.) (Primates, Cebidae). Zoologia 36: 1-10. https://doi.org/10.3897/zoologia.36.e30845
Figures 2-7 Social webs expressing interactions (in percentage of the total observation records) for each sex-age dyad of urban capuchin monkeys in each social behavior: (2) social play, n = 1,476 events; (3) grooming, n = 547; (4) threat, n = 241; (5) aggression, n = 31; (6) allocarrying, n = 193; (7) food sharing, n = 39. Percentages of emissions and receptions are in decreasing order in all columns, except for social play. Line thickness is proportional to the percentages of interactions of each dyad. (AF) adult females, (JUV) juveniles, (AM) adult male, (SUB) subadults, (INF) infants.
Figure 1 from: Back JP, Suzin A, Aguiar LM (2019) Activity Budget and Social Behavior of Urban Capuchin Monkeys (Sapajus sp.) (Primates, Cebidae). Zoologia 36: 1-10. https://doi.org/10.3897/zoologia.36.e30845
Figure 1 Proportions of records (in percentage) of behavioral categories in the activity budget of sex-age classes of urban capuchin monkeys. Boxes represent the interquartile ranges; horizontal lines within the boxes represent the medians; whiskers indicate minimum and maximum values; circles indicate the proportions of records per hour of observation. Different letters indicate significant differences between sex-age classes. Kruskal-Wallis followed by Dunn's test; p ≤ 0.05. (AF) adult females, (AM) adult male, (SUB) subadults, (JUV) juveniles.
Figure 3 in Diurnal time-activity budget and foraging techniques of red-crested pochards (Netta rufina) wintering at the wetlands of West Bengal, India
Figure 3. Month-wise and time-wise proportional time budget of the RCPs. Values are given in percentages of the time spent in the diurnal activities (mean value ± SD; n = 32; 96-h observation).
Figure 3 in Seasonal variations in the time - activity budget of Royle's pika in the Western Himalayaı India
Figure 3. The time–activity budget of adult Royle's pika at different elevations and seasons in western Himalaya.
Figure 2 in Seasonal variations in the time - activity budget of Royle's pika in the Western Himalayaı India
Figure 2. Photographic images of the different behaviours of Royle's pika. (a) foraging; (b) adult and juvenile activity in the same location without interaction; (c) vigilance; (d) musing; (e,f) auto-grooming by washing and scratching; (g,h) nest building with dry grass and plastic.
ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints. Datasets, Benchmark Results, and Torch Files.
<div> <div># ConBatch-BAL: Batch Bayesian Active Learning under Budget Constraints. Datasets, Benchmark Results, and Torch Files.</div> <br> <div>## Table of Contents</div> <br> <div>- [Overview](#overview)</div> <div>- [Folder Structure](#folder-structure)</div> <div>- [Contents](#contents)</div> <div>- [Licenses](#licenses)</div> <br> <div>## Overview</div> <div>This project contains three datasets along with stored results from the conducted benchmark analysis and torch files for running or reproducing active learning experiments.</div> <br> <div>## Folder Structure</div> <br> <div>```plaintext</div> <div>conBatchBAL_datasets/</div> <div>├── benchmark_results/</div> <div>├── benchmark_torch_files/</div> <div>├── build6k/</div> <div>├── mnist6k/</div> <div>└── nieman17k/</div> <div>```</div> <br> <div>## Contents:</div> <div>- benchmark_results/: This directory contains the results and config files for reproducing the experiments presented in the paper.</div> <br> <div>- benchmark_torch_files/: This folder contains the required torch (and json) files to run/reproduce active learning experiments.</div> <br> <div>- build6k/: This folder contains approximately 6000 aerial images of buildings in Rotterdam with their corresponding energy efficiency class and geolocation.</div> <br> <div>- mnist6k/: This folder contains approximately 6000 images of digits *artificially* geolocated in Rotterdam. The geolocations correspond to the buildings contained on the *build6k* dataset.</div> <br> <div>- nieman17k/: This folder contains approximately 17000 aerial images of buildings in Rotterdam with their corresponding typology class and geolocation.</div> <br> <div>**Additional readme files are included in each directory.**</div> <br> <div>## Licenses</div> <br> <div>- build6k/</div> <div>The build6k dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) [LICENSE](https://creativecommons.org/licenses/by/4.0/), allowing for use, distribution, and modifications with proper attribution.</div> <br> <div>- mnist6k/</div> <div>The mnist6k dataset is released under the CC BY-SA 3.0 [LICENSE](https://creativecommons.org/licenses/by-sa/3.0/).</div> <br> <div>- nieman17k/</div> <div>The nieman17k dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) [LICENSE](https://creativecommons.org/licenses/by/4.0/), allowing for use, distribution, and modifications with proper attribution.</div> <br> <div>- Benchmark Results and Torch Files</div> <div>The benchmark results and Torch files generated as part of this project are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) [LICENSE](https://creativecommons.org/licenses/by/4.0/), allowing for use, distribution, and modifications with proper attribution.</div> <br> <div>**License details are included separately in each directory**</div> </div>
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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)
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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.