A Novel Microelectrode Based on Joule Heating and Impedance Spectroscopy for Inducing and Monitoring the Aggregation of HCV-Specific Probes by Reda Abdelbaset, Omar E. Morsy, Mariam Hossam Eldin, Sherif M. Shawky, Yehya H. Ghallab, Yehea Ismail

“…The world urgently needs new methods to quickly and efficiently detect mutated viruses. An RNA-AuNP-based colorimetric biosensor is a highly sensitive, specific, and cost-effective tool that enables rapid, visual detection of target molecules for applications in disease diagnostics, environmental monitoring, and forensic analysis. …”
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Performance Evaluation of 3-D Convolutional Neural Network for Multitemporal Flood Classification Framework With Synthetic Aperture Radar Image Data by Dodi Sudiana, Indra Riyanto, Mia Rizkinia, Rahmat Arief, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo, Ketut Wikantika

“…The framework employs a 3-D convolutional neural network (3-D CNN) to process multitemporal SAR data from Sentinel-1 (S-1). …”
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A Study on Denoising Autoencoder Noise Selection for Improving the Fault Diagnosis Rate of Vibration Time Series Data by Jun-gyo Jang, Soon-sup Lee, Se-Yun Hwang, Jae-chul Lee

“…These findings demonstrate that incorporating real high-frequency components from vibration data into the DAE training process is effective in enhancing both noise removal and fault diagnosis performance.…”
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Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…In clinical settings, where whole-slide images of histological lymph nodes are involved, it is crucial to identify and detect breast cancer metastases. Patient survival rates increase significantly with early detection. …”
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Frequency-Adaptive Current Control of a Grid-Connected Inverter Based on Incomplete State Observation Under Severe Grid Conditions by Min Kang, Sung-Dong Kim, Kyeong-Hwa Kim

“…Particularly, with the aim of avoiding the grid frequency dependency of the system model, as well as the complex online discretization process, observer design is developed in the stationary reference frame. …”
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Comparative Analysis of Machine Learning Methods with Chaotic AdaBoost and Logistic Mapping for Real-Time Sensor Fusion in Autonomous Vehicles: Enhancing Speed and Acceleration Pre... by Mehmet Bilban, Onur İnan

“…This study presents a novel artificial intelligence-driven architecture for real-time sensor fusion in autonomous vehicles (AVs), leveraging Apache Kafka and MongoDB for synchronous and asynchronous data processing to enhance resilience against sensor failures and dynamic conditions. …”
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Highly sensitive salinity sensing using annular one-dimensional photonic crystals by Hassan Sayed, Ashour M. Ahmed, Ali Hajjiah, M. A. Abdelkawy, Arafa H. Aly

“…The study describes the simulation process that uses the COMSOL Multiphysics technique and the Finite Element Method (FEM) to create annular 1D PCs, underscoring the criticality of precise management of layer thickness and uniformity. …”
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In-context learning enables multimodal large language models to classify cancer pathology images by Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather

“…Here, we systematically evaluate the model Generative Pretrained Transformer 4 with Vision capabilities (GPT-4V) on cancer image processing with in-context learning on three cancer histopathology tasks of high importance: Classification of tissue subtypes in colorectal cancer, colon polyp subtyping and breast tumor detection in lymph node sections. …”
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DVF-NET: Bi-Temporal Remote Sensing Image Registration Network Based on Displacement Vector Field Fusion by Mingliang Xue, Yiming Zhang, Shucai Jia, Chong Cao, Lin Feng, Wanquan Liu

“…The results validate the effectiveness of our approach and highlight its potential for various remote sensing tasks, including change detection, land cover classification, and environmental monitoring. …”
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Identifying skin surface chemicals as potential tuberculosis diagnostic biomarkers using ultra performance liquid chromatography-high resolution mass spectrometry by Madelien Wooding, Kornelis van Pletzen, Yvette Naudé

“…The sampler was directly desorbed into solvent within an LC vial, streamlining the extraction-to-analysis process. Utilising accurate mass and collision cross sections (CCS), fourteen biomarkers were tentatively identified, demonstrating the ability to differentiate TB patients from control groups. …”
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Subclinical Markers of Human Inflammatory Bowel Disease by Huiying Yang, Jerome I Rotter

“…One is the family study approach. The detection of subclinical abnormalities in unaffected relatives similar to those found in the probands can distinguish between an inherited predisposition and a secondary abnormality due to the disease process. …”
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Spatially Resolved Brillouin Spectral Hole Burning in PMF and SMF by Xiaoxuan Zhong, Hao Liang, Linghao Cheng, Jie Li, Liang Chen, Xiaoyi Bao, Bai-ou Guan

“…Since the frequency measurement accuracy of Brillouin sensor is inversely proportional to the FWHM of detected spectrum, the spectrum hole burning represents a potential for improving the Brillouin peak detection accuracy of distributed Brillouin sensor.…”
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An Automated Semantic Segmentation Methodology for Infrared Thermography Analysis of the Human Hand by Melchior Arnal, Cyprien Bourrilhon, Vincent Beauchamps, Fabien Sauvet, Hassan Zahouani, Coralie Thieulin

“…The results obtained are very positive: we were able to decompose the images acquired via IRT with our developed algorithms, regardless of the temperature variation, and this with processing times of less than a second. Thus, this technology can be used to study the long-term thermal kinetics of the human hand by automatic feature detection, even in situations where the hand temperature experiences a significant variation.…”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Results: Indeed, the findings showed that the multimodal approaches were practical, especially the combinations involving EEG with physiological signals, thus improving the accuracy of classification, even surpassing 90% in some studies. Key signal processing techniques used during this process include spectral features, connectivity analysis, and frontal asymmetry detection, which helped enhance the performance of recognition. …”
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Operation sequence of bidirectional endoscopy with topical anesthesia affected colonoscopy performance: a randomized controlled trial by Qing Wang, Yue Sui, Jingwen Gong, Xing Chen

“…After finishing the previous process, the subsequent one was performed immediately. …”
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Improvement of fetus growth restriction diagnostics in pregnant women by means of biochemical markers that characterize the disorder of stress-adaptation by N. G. Kolokot

“…Regulatory and adaptive processes of the system “mother –placenta – fetus” state determination and detection of pregnant women adaptive capabilities specific features in case of fetus growth restriction based on a number of the blood plasma biochemical indicators. …”
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Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization by Castaka Agus Sugianto, Dini Rohmayani, Jhoanne Fredricka, Mohamed Doheir

“…Early and accurate disease detection is essential for preventing severe crop losses. …”
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A review of machine learning and internet-of-things on the water quality assessment: Methods, applications and future trends by Gangani Dharmarathne, A.M.S.R. Abekoon, Madhusha Bogahawaththa, Janaka Alawatugoda, D.P.P. Meddage

“…Explainable AI (XAI) which can explain the decision making process of ML, is underutilised, appearing in only a few recent studies. …”
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Clinical considerations on antimicrobial resistance potential of complex microbiological samples by Norbert Solymosi, Adrienn Gréta Tóth, Sára Ágnes Nagy, István Csabai, Csongor Feczkó, Tamás Reibling, Tibor Németh

“…The probability of detecting a phenotypically susceptible strain as resistant based on genotype is below 5% for 92% of ABs. …”
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Research on community characteristics of vegetation restoration in hilly power engineering based on multi temporal remote sensing technology by Chen Bin, Lei Dong, Huang Liangjun, Liu Qingdong, Zhao Xuan, Shi Yuanping

“…In order to accurately identify and evaluate the interference caused to vegetation environment during the construction process of current power transmission and transformation projects in hilly areas, especially in response to the obvious shortcomings of traditional unmanned aerial vehicles and manual detection methods, this study analyzes the composition of vegetation disturbance environment of power transmission and transformation projects in hilly areas from two aspects of natural environmental factors and human environmental factors. …”
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