Search Results (2)

How environmental features (e.g., people, enrichment, or other animals) affect movement is an important element for the study of animal behavior, biomechanics, and welfare. Here we present a stationary overhead camera-based persistent monitoring framework for the investigation of bottlenose dolphin (Tursiops truncatus) response to environmental stimuli. Mask R-CNN, a convolutional neural network architecture, was trained to automatically detect 3 object types in the environment: dolphins, people, and enrichment floats that were introduced to stimulate and engage the animals. Detected objects within each video frame were linked together to create track segments across frames. The animals’ tracks were used to parameterize their response to the presence of environmental stimuli. We collected and analyzed data from 24 sessions from bottlenose dolphins in a managed lagoon environment. The seasons had an average duration of 1 h and around half of them had enrichment (42%) while the rest (58%) did not. People were visible in the environment for 18.8% of the total time (∼4.5 h), more often when enrichment was present (∼3 h) than without (∼1.5 h). When neither enrichment nor people were present, the animals swam at an average speed of 1.2 m/s. When enrichment was added to the lagoon, average swimming speed decreased to 1.0 m/s and the animals spent more time moving at slow speeds around the enrichment. Animals’ engagement with the enrichment also decreased over time. These results indicate that the presence of enrichment and people in, or around, the environment attracts the animals, influencing habitat use and movement patterns as a result. This work demonstrates the ability of the proposed framework for the quantification and persistent monitoring of bottlenose dolphins’ movement, and will enable new studies to investigate individual and group animal locomotion and behavior. Full article

Protective efficiency of filtering dust respirators depends on the properties of filter materials from which filters are made and the structure of a half mask frame, which influences how tightly the respirator fits the face. The conducted studies on the “Lepestok 40” dust respirator revealed a large air leakage through the gaps occurring along the obturation strip. Therefore, the purpose of the study is to develop a dust respirator to provide high level of protection and usability by improving the half mask frame design. A scheme for designing a dust respirator: analysis of operating conditions for the dust respirator; facial anthropometric measurements of potential users; designing a 3D model of half mask frame; laboratory testing of the protective properties of the product. A distinctive feature of this approach is considering the facial anthropometric dimensions of employees of a particular enterprise, standard sizes formation of 3D facial models, which is the basis for designing a half mask frame for dust respirator. A new half mask frame design for dust respirator with a variable geometry of fitting to the face surface has been developed, due to special attachment points that allow changing its size according to the anthropometric dimensions of user’s face. Full article