Exploring RNA cargo in extracellular vesicles for pleural mesothelioma detection by Agnieszka Kraft, Michaela B. Kirschner, Vanessa Orlowski, Manuel Ronner, Caroline Bodmer, Valentina Boeva, Isabelle Opitz, Mayura Meerang

“…Conclusions This is the first study to characterize the transcriptomic profile of EVs secreted by PM primary cell cultures, demonstrating their potential as biomarker source for early detection. Further investigation of the functional role of PM-EVs will provide new insights into disease biology and therapeutic avenues.…”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…The SZ symptoms can significantly impair daily functioning, underscoring the need for advanced diagnostic tools. …”
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Survey on key technologies for protective DNS service by MA Yongzheng, LI Hongtao, MA Zhongsheng, HU Weihong, ZHANG Zhongxian

“…The domain name system (DNS) is a naming service for Internet resources that provides the function of converting from domain names to IP addresses. …”
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MDV ClimEx: An open-source tool for exploring climate anomalies in the McMurdo Dry Valleys of Antarctica by Renée F. Brown, Gavin P. Wagner

“…In the McMurdo Dry Valleys (MDVs), three decades of high-resolution meteorological monitoring offer a rare opportunity to characterize climate baselines and detect anomalous conditions that may signal extreme events capable of triggering hydrological and ecological responses. …”
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A lightweight object detection approach based on edge computing for mining industry by Muhammad Wahab Hanif, Zhanli Li, Zhenhua Yu, Rehmat Bashir

“…A model is proposed to improve real‐time performance for edge mining detection tasks. Detection performance is enhanced by incorporating a Pixel‐wise Normalization Spatial Attention Module (PN‐SAM) into the MobileNet‐v3 bneck structure and replacing the h‐swish activation function with Mish, providing more prosperous gradient information transfer. …”
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Circulating cell-free DNA methylation patterns indicate cellular sources of allograft injury after liver transplant by Megan E. McNamara, Sidharth S. Jain, Kesha Oza, Vinona Muralidaran, Amber J. Kiliti, A. Patrick McDeed, Digvijay Patil, Yuki Cui, Marcel O. Schmidt, Anna T. Riegel, Alexander Kroemer, Anton Wellstein

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Optimized decomposition and identification method for multiple power quality disturbances by Wang Zhaoqing, Chang Yanzhao, Chen Jianlei, Bao Weiyu

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Soil Moisture Time Series Using Gamma‐Ray Spectrometry Detection Representing a Scale of Tens‐of‐Meters by Mie Andreasen, Steven Van derVeeke, Han Limburg, Ronald Koomans, Majken Caroline Looms

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Water quality anomaly detection research based on GRU-PINN model by Zhao Xinyu

“…Maintaining high-quality water resources is essential for sustainable urban water resource management and public health. …”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

“…In addition, the need for comprehensive train detection including pantograph-catenary systems and running gears, lead to an increased number of on-board devices, resulting in fewer computational resources available for each detection system, and complicating equipment installation and maintenance. …”
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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

“…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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DEM-based topographic change detection considering the spatial distribution of errors by Yufeng He, Shaohua Lei, Wen Dai, Xi Chen, Bo Wang, Yehua Sheng, Hui Lin

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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

“…However, traditional methods of tire defect detection have encountered problems such as slow detection speed, complex tire defect backgrounds, and limited hardware resources. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. Through this pruning strategy, the model further reduces its dependence on computing resources while maintaining key performance. …”
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Identification, functional analysis, and clinical applications of defective viral genomes by Xiaowei Yan, Yitong Pan, Peiying Li, Li Zhu, Jianhai Yu, Chenguang Shen, Bao Zhang, Wei Zhao

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A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

“…Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). …”
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Advances in the detection of virulence genes of Staphylococcus aureus originate from food by Yingying Zhao, Dandan Xia, Panpan Ma, Xiaofeng Gao, Wenyi Kang, Jinfeng Wei

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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…These results underscore the model’s feasibility and robustness compared to other state-of-the-art object detection models. The source code and dataset will be available through the GitHub repository.…”
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Study on lightweight strategies for L-YOLO algorithm in road object detection by Ji Hong, Kuntao Ye, Shubin Qiu

“…The demand for real-time, efficient object detection systems is growing. However, traditional algorithms often suffer from large parameter sizes and high computational costs, limiting their applicability in resource-constrained environments. …”
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