Design and investigation of charge plasma-based TMD heterojunction TFET biosensor for ultrasensitive detection by Monika Kumari, Niraj Kumar Singh, Vinay Kantipudi, Manodipan Sahoo

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Self-Powered Microsystem for Ultra-Fast Crash Detection via Prestressed Triboelectric Sensing by Yiqun Wang, Yuhan Wang, Xinzhi Liu, Xiaofeng Wang, Keren Dai, Zheng You

“…We further developed a self-powered, compact (<4.5 cm3) microsystem that integrates the shock sensor, a signal processing module, airbag triggering circuitry, and a high-g-resistant supercapacitor as a backup power source. The microsystem achieves ultra-fast shock detection and airbag activation with a delay of less than 0.2 ms. …”
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Comparison of genotyping assays for detection of targeted CRISPR/Cas mutagenesis in highly polyploid sugarcane by Eleanor J. Brant, Eleanor J. Brant, David May, David May, Ayman Eid, Ayman Eid, Fredy Altpeter, Fredy Altpeter

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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…Finally, the Variable Minimum Point Distance Intersection over Union (VMPDIoU) loss is proposed to optimize the model’s loss function. This method employs variable input parameters to directly calculate key point distances between predicted and ground-truth boxes, more accurately reflecting positional differences between detection results and reference targets, thus effectively improving the model’s mean Average Precision (mAP). …”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

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A diagnosis method based on graph neural networks embedded with multirelationships of intrinsic mode functions for multiple mechanical faults by Bin Wang, Manyi Wang, Yadong Xu, Liangkuan Wang, Shiyu Chen, Xuanshi Chen

“…Additionally, a graph-level based fault diagnosis network model is designed to enhance feature learning capabilities for graph samples and enable flexible application across diverse signal sources and devices. Experimental validation with datasets including independent vibration signals for gear fault detection, mixed vibration signals for concurrent gear and bearing faults, and pressure signals for hydraulic cylinder leakage characterization demonstrates the model's adaptability and superior diagnostic accuracy across various types of signals and mechanical systems.…”
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YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…Unmanned Aerial Vehicles (UAVs) face a significant challenge in balancing high accuracy and high efficiency when performing real-time object detection tasks, especially amidst intricate backgrounds, diverse target scales, and stringent onboard computational resource constraints. …”
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Development and validation of microwave-assisted extraction for phenolic compound profiling in diverse oyster mushrooms (Pleurotus spp.) sourced from various geographical regions by M Umar Harun, Miguel Palma, Widiastuti Setyaningsih

“…Seven phenolic compounds—p-coumaric acid, t-cinnamic acid, p-hydroxybenzaldehyde, p-hydroxybenzoic acid, quercetin-3-glucoside, gallic acid, and vanillic acid—were effectively extracted and quantified using ultra-performance liquid chromatography with photodiode array detection. Application of this method across oyster mushroom samples from different geographical sources revealed significant variation in phenolic compound concentrations, with Pleurotus pulmonarius exhibiting the highest level of gallic acid at 433.90 ± 7.77 μg g−1 (DM) and Pleurotus ostreatus var. …”
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Two-photon excitation fluorescence in ophthalmology: safety and improved imaging for functional diagnostics by Vineeta Kaushik, Michał Dąbrowski, Michał Dąbrowski, Luca Gessa, Nelam Kumar, Humberto Fernandes

“…Recent advances in laser-source manufacturing have made it possible to minimize the exposure of in vivo measurements within safety, while achieving sufficient signals to detect for functional images, making TPEF a viable option for human application. …”
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Analysis of physicochemical, functional, and antioxidant properties of four different Indian seaweed species by Radheshyam B. Bajad, Meenatai G. Kamble, Sumit R. Gawai, Irshaan Syed, Mrinmoy Roy

“…Thus, the selected four marine seaweeds act as a good source of functional components and can be utilized for the development of functional food products such as bread, biscuits, cookies, tea, snacks, soups and beverages.…”
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Evaluation of the retinal morphological and functional findings in optic neuritis related to multiple sclerosis by Katanić-Pasovski Katarina, Rančić Nemanja, Pasovski Viktor, Sajić Marija, Resan Mirko, Dinčić Evica

“…The aim of the study was to determine the diagnostic and prognostic value of structural and functional examination using novel ‘swept-source’ optical coherence tomography (SS-OCT) and OCT angiography (OCTA) techniques in patients with MS who experienced RBN. …”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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Identification and functional analysis of novel precursor genes in cyclic peptide biosynthesis in Pseudostellaria heterophylla by Jiao Xu, Wei Zheng, Xiaohong Ou, Hua He, Changgui Yang, Lanping Guo, Chenghong Xiao, Weike Jiang, Guoping Shu, Tao Zhou

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Conscious and unconscious perception of pitch shifts in auditory feedback during vocalization: Behavioral functions and event-related potential correlates by Daniel Suchý, Roozbeh Behroozmand, Henry Railo

“…Source localization of the ERPs suggested that conscious pitch shift detection was associated with increased neural activity within the temporal, frontal and parietal cortical networks known to be involved in speech motor control. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

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Relationships between vegetation indices and surface reflectance: Implications for detecting and monitoring sandification in arid regions by Yifan Yue, Wenzhi Zhao, Rentao Liu

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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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The Advanced Role of Carbon Quantum Dots in Nano-Food Science: Applications, Bibliographic Analysis, Safety Concerns, and Perspectives by Abdul Majid, Khurshid Ahmad, Liju Tan, Waqas Niaz, Wang Na, Li Huiru, Jiangtao Wang

“…This article discussed the sources, fabrication methods, advantages, and limitations of CQDs as a sensing for the detection of food contaminants. …”
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