Reactive oxygen species (ROS) production and breakdown have been studied in detail in plant-pathogenic fungi, including the rice blast fungus, Magnaporthe oryzae; however, the examination of the dynamic process of ROS production in real time has proven to be challenging. We resynthesized an existing ROS sensor, called HyPer, to exhibit optimized codon bias for fungi, specifically Neurospora crassa, and used a combination of microscopy and plate reader assays to determine whether this construct could detect changes in fungal ROS during the plant infection process. Using confocal microscopy, we were able to visualize fluctuating ROS levels during the formation of an appressorium on an artificial hydrophobic surface, as well as during infection on host leaves. Using the plate reader, we were able to ascertain measurements of hydrogen peroxide (H O ) levels in conidia as detected by the MoHyPer sensor. Overall, by the optimization of codon usage for N. crassa and related fungal genomes, the MoHyPer sensor can be used as a robust, dynamic and powerful tool to both monitor and quantify H O dynamics in real time during important stages of the plant infection process.
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http://dx.doi.org/10.1111/mpp.12392 | DOI Listing |
Sensors (Basel)
January 2025
Institute of Intelligent Manufacturing Technology, Shenzhen Polytechnic University, Shenzhen 518000, China.
This paper introduces a novel energy-efficient lightweight, void hole avoidance, localization, and trust-based scheme, termed as Energy-Efficient and Trust-based Autonomous Underwater Vehicle (EETAUV) protocol designed for 6G-enabled underwater acoustic sensor networks (UASNs). The proposed scheme addresses key challenges in UASNs, such as energy consumption, network stability, and data security. It integrates a trust management framework that enhances communication security through node identification and verification mechanisms utilizing normal and phantom nodes.
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January 2025
Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three modalities-RGB, thermal, and depth-using datasets collected with infrared array sensors and LiDAR sensors in controlled scenarios and varying resolutions (16 × 12 to 640 × 480) to explore their effectiveness in person identification. Preprocessing techniques, including YOLO-based cropping, were employed to improve subject isolation.
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January 2025
Laboratory of Intelligent Control, Rocket Force University of Engineering, Xi'an 710025, China.
Experts and scholars from various nations have proposed studying low Earth orbit (LEO) satellite signals as the space-based signals of opportunity (SOPs) for navigation and positioning. This method serves as a robust alternative in environments where global navigation satellite systems (GNSS) are unavailable or compromised, providing users with high-precision, anti-interference, secure, and dependable backup navigation solutions. The rapid evolution of LEO communication constellations has spurred the development of SOPs positioning technology using LEO satellites.
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January 2025
School of Computer Science, Hubei University of Technology, Wuhan 430068, China.
Large visual language models like Contrastive Language-Image Pre-training (CLIP), despite their excellent performance, are highly vulnerable to the influence of adversarial examples. This work investigates the accuracy and robustness of visual language models (VLMs) from a novel multi-modal perspective. We propose a multi-modal fine-tuning method called Multi-modal Depth Adversarial Prompt Tuning (MDAPT), which guides the generation of visual prompts through text prompts to improve the accuracy and performance of visual language models.
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January 2025
Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.
Conventional endoscopy is limited in its ability to examine the small bowel and perform long-term monitoring due to the risk of infection and tissue perforation. Wireless Capsule Endoscopy (WCE) is a painless and non-invasive method of examining the body's internal organs using a small camera that is swallowed like a pill. The existing active locomotion technologies do not have a practical localization system to control the capsule's movement within the body.
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