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http://dx.doi.org/10.1016/j.lanepe.2023.100821 | DOI Listing |
Vet Res Commun
January 2025
Department of Biology, Faculty of Basic Science, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Ghrelin, a peptide hormone primarily produced in the enteroendocrine cells of the gastrointestinal tract, plays a vital role in regulating food intake, and energy balance in avian species. This review examines the complex interactions between ghrelin and the central signaling pathways associated with hunger regulation in birds. In contrast to mammals, where ghrelin typically promotes feeding behavior, its effects in birds appear more nuanced, exhibiting anorexigenic properties under certain conditions.
View Article and Find Full Text PDFAnimals capable of complex behaviors tend to have more distinct brain areas than simpler organisms, and artificial networks that perform many tasks tend to self-organize into modules (1-3). This suggests that different brain areas serve distinct functions supporting complex behavior. However, a common observation is that essentially anything that an animal senses, knows, or does can be decoded from neural activity in any brain area (4-6).
View Article and Find Full Text PDFSensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information Engineering, China University of Geosciences, Beijing 100083, China.
Extracting fragmented cropland is essential for effective cropland management and sustainable agricultural development. However, extracting fragmented cropland presents significant challenges due to its irregular and blurred boundaries, as well as the diversity in crop types and distribution. Deep learning methods are widely used for land cover classification.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Optical Materials and Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
Conventional Fourier domain Optical Coherence Tomography (FD-OCT) systems depend on resampling into a wavenumber () domain to extract the depth profile. This either necessitates additional hardware resources or amplifies the existing computational complexity. Moreover, the OCT images also suffer from speckle noise, due to systemic reliance on low-coherence interferometry.
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