Physiological features of the antioxidant system of the Equus caballus organism of different genotypes by Petrus K. Amulungu, Aleksandr V. Tkachev, Olga L. Tkacheva

“…In modern physiology, the features of the functional state of the body are increasingly being studied not in terms of breeds, age, and animal husbandry technologies, but in terms of DNA markers. …”
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Study of myelodysplastic features in patients with myelodysplastic syndromes by multicolor flow cytometry by O. Yu. Davydova, I. V. Galtseva, E. N. Parovichnikova, A. V. Kokhno, N. M. Kapranov, V. V. Troitskaya, E. A. Mikhailova, Z. T. Fidarova, T. N. Moiseeva, L. A. Kuzmina, E. A. Lukina, T. N. Obukhova, L. A. Grebenyuk, A. M. Kovrigina, V. N. Dvirnyk, V. G. Savchenko

“…The control group included 35 donors of allogeneic bone marrow. The analysis resulted in a conclusion on the Ogata score scale, the Wells prognostic scale and the combined Ogata–Wells scale. …”
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Decreased Expression of Aquaporins as a Feature of Tubular Damage in Lupus Nephritis by Maxime Melchior, Marie Van Eycken, Charles Nicaise, Thomas Duquesne, Léa Longueville, Amandine Collin, Christine Decaestecker, Isabelle Salmon, Christine Delporte, Muhammad Soyfoo

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Features of the course of whooping cough in children of the first three years of life by V. N. Timchenko, A. I. Petrakova, T. A. Kaplina, S. L. Bannova, E. V. Barakina, V. F. Sukhovetskaya, A. N. Nazarova, O. A. Leonicheva, O. V. Bulina, S. V. Buymistrov, N. A. Sidorova

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Features of the Epidemic Process of Viral Hepatitis A and E in the Russian Federation by A. N. Kaira, O. A. Svitich

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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

“…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). …”
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Systematic Review: Malware Detection and Classification in Cybersecurity by Sebastian Berrios, Dante Leiva, Bastian Olivares, Héctor Allende-Cid, Pamela Hermosilla

“…These studies cover a variety of detection techniques, including machine learning, deep learning and hybrid models, with a focus on feature extraction, malware behavior analysis and the application of advanced algorithms to improve detection accuracy. …”
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MODERN METHODS OF AUTOMATIC RECTANGLE OBJECTS DETECTION by E. S. Matusevich, I. E. Kheidorov

“…The algorithm for object detection based on correlation analysis, as well as the algorithm containing the use of Canny edge detector, Hough and Radon transform for lines detection, and then, depending on the properties of the object lines combining in the rectangular area, were explored. …”
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Insider threat detection for specific threat scenarios by Tian Tian, Chen Zhang, Bo Jiang, Huamin Feng, Zhigang Lu

“…Traditional methods mainly analyze user behavior patterns or convert behaviors into time sequences for further analysis. However, existing detection methods primarily focus on identifying abnormal users or behaviors, lacking the capability to pinpoint specific threats. …”
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An experimental method for detecting objects in an aqueous environment by Kuzmin Yuri, Proshkin Stanislav

“…The methodology is underpinned by a comprehensive mathematical analysis of electromagnetic field diffraction caused by elongated conductive and non-conductive spheroids in an aqueous environment, specifically when interacting with a grounded cable. …”
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Transient Fault Detection in Networked Control Systems by Xiong-Feng Huang, Chun-Jie Zhou, Shuang Huang, Kai-Xin Huang, Xuan Li

“…And the transient faults are excavated in node level and system level, in which parameter match and model-based detections are employed. Moreover, the key implementation aspects of the proposed approach in NCSs are detailed on parameterization of FBS models, criteria, and feature parameters of faults, fault monitoring, fault detection, and real-time scheduling considering fault detection. …”
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基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…During the feature engineering stage, the Spearman’s rank correlation coefficient analysis was applied (preset threshold |ρ|>0.8) to eliminate highly collinear features. …”
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Multimodal malware classification using proposed ensemble deep neural network framework by Sadia Nazim, Muhammad Mansoor Alam, Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Su’ud

“…This study presents a state-of-the-art malware analysis framework that employs a multimodal approach by integrating malware images and numeric features for effective malware classification. …”
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Dry-Type Air-Core Series Reactor Turn-to-Turn Short Circuit Fault Detection Method Based on Multi-Parameter Data Fusion by WANG Yin, WANG Yuanyuan, CAO Chengjun, ZHANG Lizhi, YIN Youpeng, JI Hongzhen, DOU Di

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Cross-Modal Insights into Urban Green Spaces Preferences by Jiayi Yan, Fan Zhang, Bing Qiu

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Abnormality-aware multimodal learning for WSI classification by Thao M. Dang, Qifeng Zhou, Yuzhi Guo, Hehuan Ma, Saiyang Na, Thao Bich Dang, Jean Gao, Junzhou Huang

“…By combining abnormal detection with multimodal feature integration, our framework offers an efficient and scalable solution for advancing computational pathology.…”
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Optimised hybrid deep learning classification model for kidney stone diagnosis by Y Jini Jacob, Bethanney Janney J, Hemalatha RJ, Preethi S

“…An optimized AlexNet-GRU model is introduced in this work for detection of kidney stone, feature extraction, and classification. …”
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A Novel Deep Learning Model for Human Skeleton Estimation Using FMCW Radar by Parma Hadi Rantelinggi, Xintong Shi, Mondher Bouazizi, Tomoaki Ohtsuki

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Concept of natural genome reconstruction. Part 3. Analysis of changes in the amount of telomeric DNA in colony cells as a new amplified feature that arose during the processing of... by V. S. Ruzanova, S. G. Oshikhmina, G. S. Ritter, E. V. Dolgova, S. S. Kirikovich, E. V. Levites, Y. R. Efremov, T. V. Karamysheva, A. G. Bogomolov, M. I. Meschaninova, A. L. Mamaev, O. S. Taranov, S. V. Sidorov, S. D. Nikonov, O. Y. Leplina, A. A. Ostanin, E. R. Chernykh, N. A. Kolchanov, A. S. Proskurina, S. S. Bogachev

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G2Grad-CAMRL: An Object Detection and Interpretation Model Based on Gradient-Weighted Class Activation Mapping and Reinforcement Learning in Remote Sensing Images by Shoulin Yin, Liguo Wang, Muhammad Shafiq, Lin Teng, Asif Ali Laghari, Muhammad Faizan Khan

“…Aiming at the complex background of RSIs and the lack of interpretability of existing target detection models, and the problems in feature extraction between different network structures, different layers, and the accuracy of target classification, we propose an object detection and interpretation model based on gradient-weighted class activation mapping and reinforcement learning. …”
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