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A Lightweight and Small Sample Bearing Fault Diagnosis Algorithm Based on Probabilistic Decoupling Knowledge Distillation and Meta-Learning.
Sensors (Basel)
December 2024
College of Information, Liaoning University, Shenyang 110036, China.
Rolling bearings play a crucial role in industrial equipment, and their failure is highly likely to cause a series of serious consequences. Traditional deep learning-based bearing fault diagnosis algorithms rely on large amounts of training data; training and inference processes consume significant computational resources. Thus, developing a lightweight and suitable fault diagnosis algorithm for small samples is particularly crucial.
View Article and Find Full Text PDFAISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules.
Pharmaceuticals (Basel)
December 2024
Computational Biology Laboratory, Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu 603203, Tamil Nadu, India.
Inflammation serves as a vital response to diverse harmful stimuli like infections, toxins, or tissue injuries, aiding in the elimination of pathogens and tissue repair. However, persistent inflammation can lead to chronic diseases. Peptide therapeutics have gained attention for their specificity in targeting cells, yet their development remains costly and time-consuming.
View Article and Find Full Text PDFThe Application of Machine Learning on Antibody Discovery and Optimization.
Molecules
December 2024
School of Pharmacy & School of Biological and Food Engineering, Changzhou University, Changzhou 213164, China.
Antibodies play critical roles in modern medicine, serving as diagnostics and therapeutics for various diseases due to their ability to specifically bind to target antigens. Traditional antibody discovery and optimization methods are time-consuming and resource-intensive, though they have successfully generated antibodies for diagnosing and treating diseases. The advancements in protein data, computational hardware, and machine learning (ML) models have the opportunity to disrupt antibody discovery and optimization research.
View Article and Find Full Text PDFPM-YOLO: A Powdery Mildew Automatic Grading Detection Model for Rubber Tree.
Insects
November 2024
School of Tropical Agriculture and Forestry, Hainan University, Danzhou 571737, China.
Powdery mildew has become a significant disease affecting the yield and quality of rubber trees in recent years. It typically manifests on the leaf surface at an early stage, rapidly infecting and spreading throughout the leaves. Therefore, early detection and intervention are essential to reduce the resulting losses due to this disease.
View Article and Find Full Text PDFDetection of Rat Pain-Related Grooming Behaviors Using Multistream Recurrent Convolutional Networks on Day-Long Video Recordings.
Bioengineering (Basel)
November 2024
School of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China.
In experimental pain studies involving animals, subjective pain reports are not feasible. Current methods for detecting pain-related behaviors rely on human observation, which is time-consuming and labor-intensive, particularly for lengthy video recordings. Automating the quantification of these behaviors poses substantial challenges.
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