Classification of power quality disturbances in microgrids using a multi-level global convolutional neural network and SDTransformer approach. by Junzhuo Jiang, Hao Wu, Changhua Zhong, Hong Song

“…The model effectively retains the signal's original one-dimensional temporal attributes while also delving into more complex features. This approach exhibits strong resistance to noise and enhanced generalization skills, markedly improving the detection accuracy of power quality issues within microgrids.…”
Get full text

Generation of Genuine Multipartite Entangled States via Indistinguishability of Identical Particles by Kobra Mahdavipour, Farzam Nosrati, Stefania Sciara, Roberto Morandotti, Rosario Lo Franco

“…We also show that this graph-theoretical approach allows for the optimization of the generation efficiency of specific multipartite entangled states by exploring a variety of generation schemes. …”
Get full text

Bridge Crack Segmentation Algorithm Based on Improved U-Net by Yanhao Fang, Jie LYu, Yonghua Xia, Yingke Wang

“…Initially, the model integrates an ECA (Efficient Channel Attention) module with the original U-Net to dynamically calibrate channel features. …”
Get full text

In-operando control of sum-frequency generation in tip-enhanced nanocavities by Philippe Roelli, Isabel Pascual Robledo, Iris Niehues, Javier Aizpurua, Rainer Hillenbrand

“…The tip acts as an efficient broadband antenna, focusing incident CW infrared illumination onto the nanocavity. …”
Get full text

Building rooftop extraction from high resolution aerial images using multiscale global perceptron with spatial context refinement by Qinglie Yuan

“…Overall, quantitative analysis and visual experiments confirmed that the proposed model is more efficient and superior to other state-of-the-art methods, with a 95.18% F1 score on the WHU dataset and a 93.29% F1 score on the Massub dataset.…”
Get full text

Investigation on potential bias factors in histopathology datasets by Farnaz Kheiri, Shahryar Rahnamayan, Masoud Makrehchi, Azam Asilian Bidgoli

“…The analysis was conducted on two cutting-edge DNN models: KimiaNet, a state-of-the-art DNN trained on TCGA images, and the self-trained EfficientNet. In this research study, the balanced accuracy metric is used to evaluate the performance of a model trained to classify data centers, which was originally designed to learn cancerous patterns, with the aim of investigating the potential factors contributing to the higher balanced accuracy in data center detection.…”
Get full text

Deep Space Insights: Machine Learning Revolutionizing Astrophysical Discoveries by Dutta Samya, Paul Prithwineel

“…It integrates Machine Learning as a highly impressive advancement for making scalable, efficient, and accurate tools for astronomical data which face increasing complexity and volume. …”
Get full text

Selective electrocatalytic nitrate reduction to dinitrogen: Mechanisms, catalysts, and challenges by Jiayu Chen, Anni Wu, Yongfeng Xie, Yumin Zhang, Hu Zheng, Wei Teng

“…While extensive research has focused on ammonia production, selective N2 production remains challenging due to complex pathways, limitations in detection, and the difficulty of controlling reaction on the electrocatalysts. …”
Get full text

Sustainable uric acid sensor based on a lab-fabricated electrode modified with rice straw-derived carbon materials by Pakin Noppawan, Jaroon Jakmunee, Andrew J. Hunt, Nontipa Supanchaiyamat, Suwiwat Sangon, Jamras Lerdsri, Thidarat Kruatian, Jantima Upan

“…The electrochemical oxidation of uric acid exhibits a distinct peak at 0.18 V in differential pulse voltammetry (DPV), indicative of efficient charge transfer kinetics. A linear range spanning 20 to 225 µM was obtained with a limit of detection (LOD) of 3.76 µM, signifying exceptional analytical sensitivity. …”
Get full text

A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…The YOLOV8, YOLOV11 on VOC2012 data and Object detection with Vision Transformers on Caltech 101 dataset are trained for Object detection. …”
Get full text

DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking, and Loop Closing by Hao Qu, Lilian Zhang, Jun Mao, Junbo Tie, Xiaofeng He, Xiaoping Hu, Yifei Shi, Changhao Chen

“…To mitigate cumulative positioning errors, DK-SLAM incorporates a novel online learning module that utilizes binary features for loop closure detection. This module dynamically identifies loop nodes within a sequence, ensuring accurate and efficient localization. …”
Get full text

Multimodal lightweight neural network for Alzheimer's disease diagnosis integrating neuroimaging and cognitive scores by Bhoomi Gupta, Ganesh Kanna Jegannathan, Mohammad Shabbir Alam, Kottala Sri Yogi, Janjhyam Venkata Naga Ramesh, Vemula Jasmine Sowmya, Isa Bayhan

“…Evaluation on the ADNI dataset demonstrates that Light-Mo-DAD achieves 98.0% accuracy, 98.5% sensitivity, and 97.5% specificity, highlighting its robustness in early AD detection. These results suggest that the proposed architecture not only enhances diagnostic accuracy but also offers strong potential for real-time, mobile deployment in clinical settings, supporting neurologists in efficient and reliable Alzheimer's diagnosis.…”
Get full text

Research on Concrete Crack Damage Assessment Method Based on Pseudo-Label Semi-Supervised Learning by Ming Xie, Zhangdong Wang, Li’e Yin

“…Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance.…”
Get full text

Rapid acquisition and surface defects recognition based on panoramic image of small-section hydraulic tunnel by Haoyu Wang, Jichen Xie, Jinyang Fu, Cong Zhang, Dingping Chen, Zhiheng Zhu, Xuesen Zhang

“…Small-section hydraulic tunnels are characterized by small spaces and various section forms, under complex environments, which makes it difficult to carry out an inspection by the mobile acquisition equipment. …”
Get full text

Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…Robotic-assisted endoscopy (EndoMaster, Magnetically Assisted Robotic Endoscopy) provides enhanced dexterity and stability, making complex procedures safer and more efficient. In therapeutic endoscopy, Endoscopic Submucosal Dissection and Endoscopic Mucosal Resection have expanded the therapeutic scope of GIE enabling minimally invasive removal of early-stage tumors, reducing the need for surgery. …”
Get full text

RDM-YOLO: A Lightweight Multi-Scale Model for Real-Time Behavior Recognition of Fourth Instar Silkworms in Sericulture by Jinye Gao, Jun Sun, Xiaohong Wu, Chunxia Dai

“…This study presents RDM-YOLO, a computationally efficient deep learning framework derived from YOLOv5s architecture, specifically designed for the automated detection of three essential behaviors (resting, wriggling, and eating) in fourth instar silkworms. …”
Get full text

A Comprehensive Review of Advanced Lactate Biosensor Materials, Methods, and Applications in Modern Healthcare by Yifeng Ding, Liuhong Yang, Jing Wen, Yuhang Ma, Ge Dai, Fengfeng Mo, Jiafeng Wang

“…With continued innovation, lactate sensors are expected to revolutionize personalized medicine, helping clinicians to increase treatment efficiency and improve the experience of their use.…”
Get full text

CO₂ Interaction Mechanism of SnO₂-Based Sensors with Respect to the Pt Interdigital Electrodes Gap by Adelina Stanoiu, Alexandra Corina Iacoban, Catalina Gabriela Mihalcea, Ion Viorel Dinu, Ovidiu Gabriel Florea, Ioana Dorina Vlaicu, Cristian Eugen Simion

“…Complex phenomenological investigations showed that moisture significantly affects the gas sensing performance. …”
Get full text

Pseudoneutralizing test for preclinical studies of vaccines against SARS-CoV-2 by B. S. Cherepovich, A. M. Kudryashova, N. P. Kartashova, A. V. Gracheva, V. A. Manuilov, I. A. Leneva, O. V. Borisova, O. A. Svitich

“…The purpose of this study was to evaluate efficiency of a competitive enzyme immunoassay which specifically detects antibodies that recognize the receptor-binding domain at the S1 subunit of SARS-CoV-2 coronavirus spike protein and block the formation of initiator infection complex between RBD and angiotensinconverting enzyme 2 (pseudo-neutralizing test, PNT) being applied at the stage of preclinical studies of anti- SARS-CoV-2 vaccine. …”
Get full text

Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling by Menglin Zhai, Juanli Jing, Shiqing Dou, Jiancheng Du, Rongbin Wang, Jichi Yan, Yaqin Song, Zhengmin Mei

“…Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. …”
Get full text