Deep Learning-Based Fault Diagnosis via Multisensor-Aware Data for Incipient Inter-Turn Short Circuits (ITSC) in Wind Turbine Generators by Qinglong Wang, Shihao Cui, Entuo Li, Jianhua Du, Na Li, Jie Sun

“…These faults can cause fluctuations in the output voltage, frequency, and power of wind turbines, eventually leading to overheating, equipment damage, and rising maintenance costs if not detected early. Although significant progress has been made in condition monitoring, the current methods still fall short of the robustness required for early fault diagnosis in complex operational settings. …”
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Modulation of fibroblast behavior by Leishmania: a pathway to understanding disease progression in cutaneous leishmaniasis by Tarcisio Navegante de Queiroz Filho, Brenda Furtado Costa, Ana Paula Drummond Rodrigues

“…Interestingly, both the promastigote and amastigote forms of the parasite have also been detected in fibroblasts, revealing the complex interactions during the infection. …”
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Malarial pigment-induced lipoperoxidation, inhibited motility and decreased CCR2 and TNFR1/2 expression on human monocytes by Oleksii Skorokhod, Valentina Barrera, Elena Valente, Daniela Ulliers, Koji Uchida, Evelin Schwarzer

“…Objective: Malaria remains an important life-threatening disease that provokes a complex immune response, marked by an initial immune boost followed by long-term suppression, warranting further study. …”
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An Advanced Approach for Predicting Workpiece Surface Roughness Using Finite Element Method and Image Processing Techniques by Taoming Chen, Chun Li, Zhexiang Zou, Qi Han, Bing Li, Fengshou Gu, Andrew D. Ball

“…Workpiece surface quality is a critical metric for assessing machining quality. However, due to the complex coupling characteristics of cutting factors, accurately predicting surface roughness remains challenging. …”
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Overall architecture design of row/column scanning silicon-based focal plane switch array LiDAR transmitter system by Yu Wang, Yue Wang, Zeyang Zhang, Hang Cheng, Yuanhui Li, Guohui Yang, Kuang Zhang, Chunhui Wang

“…This architecture allows each optical path to control multiple grating couplers for simultaneous transmission, integrating both time-domain and spatial detection to enhance system detection efficiency and accuracy. …”
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Chemical analysis using miniaturized and Portable 3D printed systems: Where are we now? by Miryam Perrucci, Imran Ali, Fotouh R. Mansour, Halil I. Ulusoy, Songül Ulusoy, Abuzar Kabir, Ornella Abollino, Agnese Giacomino, Paolo Inaudi, Marcello Locatelli, Erika Maria Ricci

“…Interest in miniaturized systems is further fueled by the theoretical principle that reducing flow rates enhances the surface-to-volume ratio, thereby improving detection sensitivity.Building on this theoretical foundation—particularly the goals of portability, efficient sampling, and on site analysis—innovative approaches such as microfluidics and 3D printing have been employed to develop compact fluidic systems. …”
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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

“…Results Participants reported notable gains in diagnostic efficiency and resource allocation, underscoring AI’s potential to reduce turnaround times for routine tests and enhance detection of abnormalities. …”
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An In-Depth Study of Personalized Anesthesia Management Models in Gastrointestinal Endoscopy Based on Multimodal Deep Learning by Hanqi Shi, Hongyu Wang, Xibing Ding, Zheng Dang

“…This model was designed to enhance anesthesia management efficiency and disease detection rates. In collaboration with the Department of Anesthesiology at Renji Hospital, which is affiliated with the Shanghai Jiao Tong University School of Medicine, data pertaining to anesthesia were collected from 398 patients, who were undergoing gastrointestinal endoscopy. …”
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Online evaluation method for MMC submodule capacitor aging based on CapAgingNet by Xinlan Deng, Youhan Deng, Liang Qin, Weiwei Yao, Min He, Kaipei Liu

“…Submodule capacitor aging poses significant challenges to the safe operation of modular multilevel converter (MMC) systems. Traditional detection methods rely predominantly on offline tests, lacking real-time evaluation capabilities. …”
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Direct and bisulfite-free 5-methylcytosine and 5-hydroxymethylcytosine sequencing at single-cell resolution with scTAPS and scCAPS +  by Xiufei Chen, Jingfei Cheng, Linzhen Kong, Xiao Shu, Haiqi Xu, Masato Inoue, Marion Silvana Fernández-Berrocal, Dagny Sanden Døskeland, Magnar Bjørås, Shivan Sivakumar, Yibin Liu, Jing Ye, Chun-Xiao Song

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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…Key challenges include spectral distortions from high-frequency spatial data, high computational complexity, and limited training data, particularly for new-generation sensors with unique noise patterns. …”
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Experimental Demonstration of Superconducting Series Nanowire Photon-Number-Resolving Detector at 660 nm Wavelength by Ruiying Xu, Xu Tao, Qi Chen, Xiang Li, Guanghao Zhu, Lin Kang, Labao Zhang, Xiaoqing Jia, Xuecou Tu, Qingyuan Zhao, Biaobing Jin, Weiwei Xu, Jian Chen, Peiheng Wu

“…The results of our 6-element PNR device show clear evidence of <italic>n</italic>-photons differentiation with <italic>n</italic> ranging from 1 to 6. The system detection efficiency reaches 54&#x0025; with the dark counts rate below 10&#x00A0;Hz at 660&#x00A0;nm. …”
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Capsule phase microextraction methodology: Applications and future perspective by Shaikh Manirul Haque, Abuzar Kabir, Torki Zughaibi, Noorfatimah Yahaya, Bharti Jain, Rajeev Jain, Masoom Raza Siddiqui

“…Extraction plays a crucial role in the quantitative analysis of analytes across various matrices, particularly in biological and other complex samples, where accurate detection and determination would be challenging without effective extraction. …”
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WF-SwinUnet: A Window Fusion-based RFI Segmentation Model and Its Application in FAST by QingYun Li, MingHui Li, Dongjun Yu, Jie He

“…However, the traditional thresholding method cannot adapt to the complex baseline noise because it relies on manual parameter adjustment and assumes a constant threshold value, it also faces bottlenecks such as the failure to detect weak interferences and the ambiguous positioning of the boundary. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Machine learning models can process complex datasets, identify hidden patterns, and facilitate early risk detection, enabling banks to implement preventive measures before risks materialize. …”
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ReAcc_MF: Multimodal Fusion Model with Resource-Accuracy Co-Optimization for Screening Blasting-Induced Pulmonary Nodules in Occupational Health by Junhao Jia, Qian Jia, Jianmin Zhang, Meilin Zheng, Junze Fu, Jinshan Sun, Zhongyuan Lai, Dan Gui

“…To enhance computational efficiency and interpretability, we design a soft voting ensemble classifier, eliminating the need for complex deep learning architectures. …”
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A Real-Time Approach for Assessing Rodent Engagement in a Nose-Poking Go/No-Go Behavioral Task Using ArUco Markers by Thomas Smith, Trevor Smith, Fareeha Faruk, Mihai Bendea, Shreya Kumara, Jeffrey Capadona, Ana Hernandez-Reynoso, Joseph Pancrazio

“…Behavioral neuroscience requires precise and unbiased methods for animal behavior assessment to elucidate complex brain–behavior interactions. Traditional manual scoring methods are often labor-intensive and can be prone to error, necessitating advances in automated techniques. …”
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EXAMINING THE IMPACT OF FEATURE SELECTION TECHNIQUES ON MACHINE AND DEEP LEARNING MODELS FOR THE PREDICTION OF COVID-19 by Hafiza Zoya Mojahid, Jasni Mohamad Zain, Marina Yusoff, Abdul Basit, Abdul Kadir Jumaat, Mushtaq Ali

“…Feature selection is a vital preprocessing step for identifying the most informative features in complex datasets, enhancing the efficiency and accuracy of machine learning models. …”

Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…Traditional deterministic methods often fail to capture the dynamic interactions within wind farms, thereby underscoring the need for ML-integrated approaches that enhance precision in energy forecasting, fault detection, and exergy analysis. This PRISMA-ScR review synthesizes recent advancements in ML techniques, including Random Forest, Long Short-Term Memory networks, and hybrid models, demonstrating significant improvements in predictive accuracy and operational efficiency. …”
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Development of an AI model for pneumothorax imaging: Dataset and model optimization strategies for real-world deployment by Wen-Chang Tseng, Yung-Cheng Wang, Wei-Chi Chen, Kang-Ping Lin

“…Conclusions: The AI model shows potential in pneumothorax detection, but performance is influenced by data diversity, image quality, and clinical complexity. …”
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