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A Subunit Vaccine Harboring the Fusion Capsid Proteins of Porcine Circovirus Types 2, 3, and 4 Induces Protective Immune Responses in a Mouse Model.
Viruses
December 2024
College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030801, China.
Coinfections with porcine circovirus types 2, 3, and 4 (PCV2, PCV3, and PCV4) are increasingly being detected in the swine industry. However, there is no commercially available vaccine which prevents coinfection with PCV2, PCV3, and PCV4. The development of a vaccine expressing capsid (Cap) fusion proteins of multiple PCVs represents a promising approach for broadly preventing infection with PCVs.
View Article and Find Full Text PDFDevelopment of a Synthetic VP1 Protein Peptide-Based ELISA to Detect Antibodies Against Porcine Bocavirus Group 3.
Viruses
December 2024
Xinjiang Key Laboratory of New Drug Study and Creation for Herbivorous Animals (XJ-KLNDSCHA), College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi 830052, China.
Porcine bocavirus (PBoV), classified within the genus Bocaparvovirus, has been reported worldwide. PBoV has been divided into group 1, group 2, and group 3. PBoV group 3 (G3) viruses are the most prevalent in China.
View Article and Find Full Text PDFOptimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation.
Sensors (Basel)
December 2024
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Breast cancer is a significant cause of death from cancer in women globally, highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumor identification is essential for diagnosis, treatment, and monitoring, emphasizing the importance of advanced imaging technologies that provide detailed views of tumor characteristics and disease. Recently, a new imaging modality named synthetic correlated diffusion imaging (CDI) has been showing promise for enhanced prostate cancer delineation when compared to existing MRI imaging modalities.
View Article and Find Full Text PDFPoint Cloud Wall Projection for Realistic Road Data Augmentation.
Sensors (Basel)
December 2024
Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea.
Several approaches have been developed to generate synthetic object points using real LiDAR point cloud data for advanced driver-assistance system (ADAS) applications. The synthetic object points generated from a scene (both the near and distant objects) are essential for several ADAS tasks. However, generating points from distant objects using sparse LiDAR data with precision is still a challenging task.
View Article and Find Full Text PDFTemporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems.
Sensors (Basel)
December 2024
Department of Computer Science, University of Bristol, Bristol BS8 1QU, UK.
Detecting anomalies in distributed systems through log analysis remains challenging due to the complex temporal dependencies between log events, the diverse manifestation of system states, and the intricate causal relationships across distributed components. This paper introduces a TLAN (Temporal Logical Attention Network), a novel deep learning framework that integrates temporal sequence modeling with logical dependency analysis for robust anomaly detection in distributed system logs. Our approach makes three key contributions: (1) a temporal logical attention mechanism that explicitly models both time-series patterns and logical dependencies between log events across distributed components, (2) a multi-scale feature extraction module that captures system behaviors at different temporal granularities while preserving causal relationships, and (3) an adaptive threshold strategy that dynamically adjusts detection sensitivity based on system load and component interactions.
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