The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

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Predicting drug-target interactions using machine learning with improved data balancing and feature engineering by Md. Alamin Talukder, Mohsin Kazi, Ammar Alazab

“…The framework leverages comprehensive feature engineering, utilizing MACCS keys to extract structural drug features and amino acid/dipeptide compositions to represent target biomolecular properties. …”
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Mapping Disorders with Neurological Features Through Mitochondrial Impairment Pathways: Insights from Genetic Evidence by Anna Makridou, Evangelie Sintou, Sofia Chatzianagnosti, Iasonas Dermitzakis, Sofia Gargani, Maria Eleni Manthou, Paschalis Theotokis

“…Genetic, clinical and molecular data were analyzed to elucidate shared and distinct pathophysiological features. A comprehensive table synthesizes genetic causes, inheritance patterns, and neurological manifestations across disorders. …”
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Drug History and SLE Laboratory Findings Among Iraqi Patients: A Hospital‐Based Study by Hashim Talib Hashim, Ahmed Dheyaa Al‐Obaidi, Mustafa Najah Al‐Obaidi, Hossam Tharwat Ali, Idris Sula, Hozifa Alfaki, Abdelrahim Elamin, Alaa Hamza Hermis, Assalah Othman, Ahmed Qasim Mohammed Alhatemi

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Pore–Fracture Structure and Fractal Features of Carboniferous Taiyuan Formation Hydrocarbon Source Rocks as Investigated Using MICP, LFNMR, and FESEM by Dun Wu, Liu Zhao, Guangqing Hu, Wenyong Zhang

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Subdivision of river channel sand micro-scale facies with feature attention spatio-temporal network by Ruipu Zhao, Lili Zeng, Chendong Fu, Xiaoqing Zhao

“…Meanwhile, the spatio-temporal feature extraction module fully leverages spatial and sequential information from the logging data, enabling precise identification of river channel sand sedimentary micro-scale facies.ResultsThis method, applied to a real-world oilfield for residual oil development, subdivides deltaic river channel sand sedimentary micro-scale facies into four distinct types. …”
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Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Methods: High-dimensional metering data from a city energy provider is processed using a Convolutional Autoencoder (CAE) to extract deep features and reduce dimensionality. These features are then fed into a Cascaded Long Short-Term Memory (CLSTM) network, which identifies anomalous patterns in the data. …”
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Visualizing Relaxation in Wearables: Multi-Domain Feature Fusion of HRV Using Fuzzy Recurrence Plots by Puneet Arya, Mandeep Singh, Mandeep Singh

“…Among six evaluated classifiers, support vector machine (SVM) achieved the highest performance, with 96.6% accuracy and 100% specificity using only three selected features. Our approach offers both human-interpretable visual feedback through FRP and accurate automated detection, making it highly promising for objectively monitoring real-time stress and developing biofeedback systems in wearable devices.…”
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Features of heat and mechanical characteristics of pulsating flows in gas-air paths of piston engines with turbocharging by L. V. Plotnikov, Y. M. Brodov, B. P. Zhilkin, N. I. Grigoriev

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Conserved functional features of natural killer cell subsets in chicken, human, and murine immune systems by Seung Je Woo, Jaeryeong Kim, Hong Jo Lee, Kyung Youn Lee, Kyung Je Park, Jin-Kyoo Kim, Jin Lee Kim, Byung Chul Park, Minseok Seo, Jae Yong Han

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Deep learning based local feature classification to automatically identify single molecule fluorescence events by Shuqi Zhou, Yu Miao, Haoren Qiu, Yuan Yao, Wenjuan Wang, Chunlai Chen

“…In this study, we introduce DEBRIS (Deep lEarning Based fRagmentatIon approach for Single-molecule fluorescence event identification), a deep-learning model focusing on classifying local features and capable of automatically identifying steady fluorescence signals and dynamically emerging signals of different patterns. …”
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Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning by Jungpil Shin, Abu Saleh Musa Miah, Koki Hirooka, Md. Al Mehedi Hasan, Md. Maniruzzaman

“…While this method can capture broad patterns, it has several limitations, including a lack of focus on dynamic change, oversimplified feature representation, a lack of directional information, and missing micro-movements or subtle variations. …”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…This synergy enables effective learning of local features and long-term temporal patterns, resulting in precise predictions. …”
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Evolutionary dynamics of Orchid DL paralogs: gene duplication, functional divergence, and expression patterns across Orchid subfamilies by Francesca Lucibelli, Angela Carfora, Annette Becker, Katrin Ehlers, Serena Aceto

“…The study of transcription factor genes, such as the YABBY gene DROOPING LEAF, is crucial for understanding the molecular mechanisms underlying orchid development and evolution. This study aims to elucidate the evolutionary dynamics and expression patterns of DL genes across orchid subfamilies. …”
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Early Detection of ITSC Faults in PMSMs Using Transformer Model and Transient Time-Frequency Features by Ádám Zsuga, Adrienn Dineva

“…The Transformer model, leveraging self-attention mechanisms, captures both local transient patterns and long-range dependencies within the time-frequency feature space. …”
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EEG-based schizophrenia diagnosis using deep learning with multi-scale and adaptive feature selection by Alanoud Al Mazroa, Majdy M. Eltahir, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K, Jaehyuk Cho

“…There is a pressing need to develop an objective and effective diagnostic method for this specific type of schizophrenia. …”
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Dissecting the genetic features and evolution of Staphylococcus aureus sequence type 88: a global perspective by Ye Jin, Chenyang Gao, Gaoqin Teng, Zhenchao Zhou, Wangxiao Zhou, Man Huang

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Study on the gas outflow pattern and outflow prediction model of the return mining face under complex geological conditions by Yi Sun, Lulin Zheng, Hong Lan, Zhaoxing Yu, Jin Wang, Bo Li, Feng Yang, Fangbo Wen

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Gene expression noise in spatial patterning: hunchback promoter structure affects noise amplitude and distribution in Drosophila segmentation. by David M Holloway, Francisco J P Lopes, Luciano da Fontoura Costa, Bruno A N Travençolo, Nina Golyandina, Konstantin Usevich, Alexander V Spirov

“…Insofar as many of these are common features of genes (e.g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.…”
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Fusion of deep neural networks and infrared wave analysis for climate pattern prediction and shifting sand hazard Assessment by Huayu Lu, Marzieh Mokarram

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