Hummingbirds have evolved to hover and manoeuvre with exceptional flight control. This is enabled by their musculoskeletal system that successfully exploits the agile motion of flapping wings. Here, we synthesize existing empirical and modelling data to generate novel hypotheses for principles of hummingbird wing actuation. These may help guide future experimental work and provide insights into the evolution and robotic emulation of hummingbird flight. We develop a functional model of the hummingbird musculoskeletal system, which predicts instantaneous, three-dimensional torque produced by primary (pectoralis and supracoracoideus) and combined secondary muscles. The model also predicts primary muscle contractile behaviour, including stress, strain, elasticity and work. Results suggest that the primary muscles (i.e. the flight 'engine') function as diverse effectors, as they do not simply power the stroke, but also actively deviate and pitch the wing with comparable actuation torque. The results also suggest that the secondary muscles produce controlled-tightening effects by acting against primary muscles in deviation and pitching. The diverse effects of the pectoralis are associated with the evolution of a comparatively enormous bicipital crest on the humerus.
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http://dx.doi.org/10.1098/rspb.2022.2076 | DOI Listing |
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December 2024
Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, UP, India.
Speaker verification in text-dependent scenarios is critical for high-security applications but faces challenges such as voice quality variations, linguistic diversity, and gender-related pitch differences, which affect authentication accuracy. This paper introduces a Gender-Aware Siamese-Triplet Network-Deep Neural Network (ST-DNN) architecture to address these challenges. The Gender-Aware Network utilizes Convolutional 2D layers with ReLU activation for initial feature extraction, followed by multi-fusion dense skip connections and batch normalization to integrate features across different depths, enhancing discrimination between male and female speakers.
View Article and Find Full Text PDFInt J Lang Commun Disord
December 2024
Hearing, Speech & Language Center, Sheba Medical Center, Tel Hashomer, Israel.
Background: Head and neck cancer (HNC) is amongst the 10 most common cancers worldwide and has a major effect on patients' quality of life. Given the complexity of this unique group of patients, a multidisciplinary team approach is preferable. Amongst the debilitating sequels of HNC and/or its treatment, swallowing, speech and voice impairments are prevalent and require the involvement of speech-language pathologists (SLPs).
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December 2024
Institute of Agriculture and Life Science, Gyeongsang National University, Jinju, 52828, Republic of Korea.
Heat stress (HS) is an impactful condition in ruminants that negatively affects their physiological and rumen microbial composition. However, a fundamental understanding of metabolomic and metataxonomic mechanisms in goats under HS conditions is lacking. Here, we analyzed the rumen metabolomics, metataxonomics, and serum metabolomics of goats (n = 10, body weight: 41.
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December 2024
Animal Biotechnology Division, National Institute of Animal Science, Rural Development Administration, Wanju, Republic of Korea.
Small intestinal organoids are similar to actual small intestines in structure and function and can be used in various fields, such as nutrition, disease, and toxicity research. However, the basal-out type is difficult to homogenize because of the diversity of cell sizes and types, and the Matrigel-based culture conditions. Contrastingly, the apical-out form of small intestinal organoids is relatively uniform and easy to manipulate without Matrigel.
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December 2024
School of Public Health, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China.
The study aims to address the critical issue of toxic side effects resulting from drug combinations, which can significantly increase health risks, clinical complications, and lead to drug being withdrawn from the market. A model named TSEDDI (toxic side effects of drug-drug interaction) has been developed to improve the identification of drug pairs that may induce toxicity or adverse reactions. By utilizing drug chemical structures and diverse proteins, we employ a convolutional neural network (CNN) to extract features from molecular images, enzyme proteins, transporter proteins, and target proteins.
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