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Lytic Spectra of Tailed Bacteriophages: A Systematic Review and Meta-Analysis.
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Department of Molecular Microbiology, Institute of Experimental Medicine, Saint Petersburg 197022, Russia.
As natural predators of bacteria, tailed bacteriophages can be used in biocontrol applications, including antimicrobial therapy. Also, phage lysis is a detrimental factor in technological processes based on bacterial growth and metabolism. The spectrum of bacteria bacteriophages interact with is known as the host range.
View Article and Find Full Text PDFFP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n.
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School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450000, China.
To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. First, the C2f_GhostV2 module has been designed to replace the original C2f module.
View Article and Find Full Text PDFAnalyzing and Modeling the Dynamic Electrical Characteristics of Nanocomposite Large-Range Strain Gauges.
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Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA.
Flexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. In addition to the non-linear viscoelastic behavior of the strain gauge material itself, the dynamic response of the sensors is even more difficult to capture due to spikes in the resistance during strain path changes.
View Article and Find Full Text PDFBayesian Architecture for Predictive Monitoring of Unbalance Faults in a Turbine Rotor-Bearing System.
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Department of Mechanical Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan.
Unbalance faults are among the common causes of interruptions and unexpected failures in rotary systems. Therefore, monitoring unbalance faults is essential for predictive maintenance. While conventional time-invariant mathematical models can assess the impact of these faults, they often rely on proper assumptions of system factors like bearing stiffness and damping characteristics.
View Article and Find Full Text PDFMachine Learning-Based Modeling of pH-Sensitive Silicon Nanowire (SiNW) for Ion Sensitive Field Effect Transistor (ISFET).
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CNRS, LAAS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France.
The development of ion-sensitive field-effect transistor (ISFET) sensors based on silicon nanowires (SiNW) has recently seen significant progress, due to their many advantages such as compact size, low cost, robustness and real-time portability. However, little work has been done to predict the performance of SiNW-ISFET sensors. The present study focuses on predicting the performance of the silicon nanowire (SiNW)-based ISFET sensor using four machine learning techniques, namely multilayer perceptron (MLP), nonlinear regression (NLR), support vector regression (SVR) and extra tree regression (ETR).
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