Precision medicine in oncology: role and prospects of mass spectrometry by E. S. Khmelevskaya, E. A. Perina, E. E. Buyko, A. A. Ufandeev, O. A. Kaidash, V. V. Ivanov, A. N. Baikov, E. V. Parochkina, E. V. Udut

“…Mass spectrometry is becoming an indispensable tool in basic and applied research due to its sensitivity, specificity, and accuracy. It allows for efficient analysis of complex biological compounds, even at low concentrations. …”
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Developing an ISO11783-compliant prescription map for variable rate spraying in vineyards based on 3D canopy reconstruction by Björn Poss, Nikos Tsoulias, Galibjon M. Sharipov, Andreas Heiß, Dimitrios S. Paraforos

“…With the advent of the digital era in viticulture and the use of increasingly complex implements from different manufacturers, a standardised communication interface is essential. …”
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Development and validation of a UPLC-MS/MS method for the simultaneous estimation of Ertugliflozin and Sitagliptin in bulk and tablet dosage forms: Assessment of greenness and blue... by Voohitha Manukonda, Santhoshi Priya Dandamudi, Praveen Kumar Kusuma, Gouthami Thumma, Kiran Gangarapu

“…Green analytical chemistry emphasizes the use of energy-efficient instruments, minimization of hazardous substances, and reduction of waste. …”
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DCMC-UNet: A Novel Segmentation Model for Carbon Traces in Oil-Immersed Transformers Improved with Dynamic Feature Fusion and Adaptive Illumination Enhancement by Hongxin Ji, Jiaqi Li, Zhennan Shi, Zijian Tang, Xinghua Liu, Peilin Han

“…Given the substantial morphological and dimensional variations of target defects (e.g., carbon traces produced by surface discharge inside the transformer), the intelligent and efficient extraction of carbon trace features from complex backgrounds becomes critical for robotic inspection. …”
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Synergistic Hierarchical AI Framework for USV Navigation: Closing the Loop Between Swin-Transformer Perception, T-ASTAR Planning, and Energy-Aware TD3 Control by Haonan Ye, Hongjun Tian, Qingyun Wu, Yihong Xue, Jiayu Xiao, Guijie Liu, Yang Xiong

“…These systems require reliable sensor-based object detection and efficient, safe, and energy-aware path planning. …”
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Field programmable silicon microring WDM transceiver leveraging monolithically integrated phase-change materials by Xing Yang, Shihuan Ran, Ziquan Li, Liangjun Lu, Yu Li, Ngon Phu Wai, MingHua Zhang, Guo-Qiang Lo, Jianping Chen, Linjie Zhou

“…These advancements position Sb2Se3-integrated MRRs as a promising solution for large-scale, energy-efficient photonic transceivers in next-generation optical communication systems.…”
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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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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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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…Breast cancer is a leading cause of morbidity and mortality among women worldwide, arising from malignant cell transformations in breast tissue. Early detection is paramount as it significantly improves survival rates and reduces the complexity and cost of treatment. …”
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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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Strategy of Surgical Treatment of Patients with Pigment Dispersion Syndrome and Myopia by S. N. Sakhnov, O. A. Klokova, P. A. Karagodina, T. I. Arlanova, A. A. Leonova

“…Purpose: to conduct a prospective study of the results of surgical treatment of patients with pigment dispersion syndrome and complex myopic astigmatism. Materials and methods. …”
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USING ARTIFICIAL INTELLIGENCE (AI) AND DEEP LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT by Joseph Olorunfemi AKANDE

“…Recent advancements in machine learning, particularly deep learning, offer significant potential for improving the efficiency and effectiveness of risk management systems. …”
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Hierarchical segmentation framework with dynamic parameter optimization for accurate stem-leaf partitioning and phenotypic extraction in maize by Yingjie Zhao, Dongjie Liu, Jiangtan Yao, Zhen Wang, Xuanyu Mu, Zongwei Jia

“…However, traditional phenotyping methods relying on manual measurements or two-dimensional images have significant limitations in terms of efficiency and accuracy, particularly in effectively analyzing the complex three-dimensional structures of plants. …”
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VIOS-Net: A Multi-Task Fusion System for Maritime Surveillance Through Visible and Infrared Imaging by Junquan Zhan, Jiawen Li, Langtao Wu, Jiahua Sun, Hui Yin

“…The proposed model, VIOS-Net, integrates the advantages of both visible and infrared data sources to meet the challenges of all-weather, all-day ship monitoring under complex environmental conditions. VIOS-Net employs a Shared Bottom network architecture, utilizing both shared and specific feature extraction modules at the model’s lower and upper layers, respectively, to optimize the system’s recognition capabilities and maximize data utilization efficiency. …”
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Integrating pyramid vision transformer and topological data analysis for brain tumor by Dhananjay Joshi, Bhupesh Kumar Singh, Kapil Kumar Nagwanshi, Nitin S. Choubey

“…IntroductionBrain tumor (BT) classification is crucial yet challenging due to the complex and varied nature of these tumors. We present a novel approach combining a Pyramid Vision Transformer (PVT) with an adaptive deformable attention mechanism and Topological Data Analysis (TDA) to address the complexities of BT detection. …”
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