EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

“…Unfortunately, optimization of diagnostic algorithms and wide implementation of instrumental diagnostics (ultrasound examination, computed tomography, fiber endoscopy) do not improve the situation. …”
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Dynamics of quality of life of head and neck cancer patients after treatment. Clinical significance by A. V. Karpenko, R. R. Sibgatullin, A. A. Boyko, M. G. Kostova, O. M. Nikolayeva, E. M. Trunin

“…The study objective is to evaluate the quality of life as one of the main parameters that determines the effectiveness of treatment of patients with head and neck squamous cell carcinoma.Materials and methods. …”
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Experimental investigation of shaft misalignment effects on bearing reliability through vibration signal analysis using machine learning and deep learning by Fransiskus Tatas Dwi Atmaji, Jamasri, Hari Agung Yuniarto, I Made Miasa

“…Six classification models—five machine learning algorithms (Multilayer Perceptron, Random Forest, Decision Tree, K-Nearest Neighbors, and Adaptive Boosting) and one deep learning model (Long Short-Term Memory, LSTM)—were evaluated for classifying four levels of misalignment severity. …”
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How real is the long-lasting effect of tumor necrosis factor α inhibitors? Focus on immunogenicity by D.E. Karateev

“…Currently, the main method for preventing ADAb formation is to strictly follow the recommenda- tions for using biological drugs in combination of disease-modifying anti-rheumatic drugs (first of all, with methotrexate). …”
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Intelligent fault diagnosis of shearer based on simplified interval kernel global-local feature fusion by Ning LI, Hua DING, Xiaochun SUN, Zeping LIU, Guoshu PU

“…As one of the main equipment in coal mining, the health status of shearer is difficult to be accurately monitored due to some factors such as harsh working environment and narrow operating space, and it is highly susceptible to the impact of coal and rock, which can cause faults and directly affect the working efficiency of shearer. …”
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Establishment of a prediction model and immune infiltration characteristics of atherosclerosis progression based on neutrophil extracellular traps-related genes by Yuan Gao, Lele Hui, Gang Dou, Xiaoying Chang, Yue Tang, Hao Liu, Zebiao Xu, Bing Xu

“…These pathologic changes are closely related to AS progression and are the main contents of AS progression. Immune infiltration analysis revealed 4 immune cells associated with IPH, among them resting dendritic cells, which were closely related to SLC25A4. …”
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MANAGING THE DEVELOPMENT OF AGRO-INDUSTRIAL CLUSTERS by D. V. Zavyalov, O. V. Saginova, N. B. Zavyalova

“…As one of the measures capable to refract a similar negative situation, development of the concept of management of agro-industrial clusters formed on the basis of an information system of "a digital cluster" which includes algorithms and methods of optimization of information, material and financial flows for achievement of desirable indicators of economic activity by all participants of cluster structure is recommended. …”
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Certainty of Linear Interrelation of Technical and Economic Parameters of Power Units of 300 МWt Thermal Power Stations by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, A. A. Rustamova

“…It would seem that there is a quite fully developed mathematical apparatus for regression and correlation analysis, a set of algorithms and calculation programs. But there is one specific feature that, if it is not taken into account, further increases the risk of an erroneous decision. …”
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Improved YOLOv8 Model for Phenotype Detection of Horticultural Seedling Growth Based on Digital Cousin by Yuhao Song, Lin Yang, Shuo Li, Xin Yang, Chi Ma, Yuan Huang, Aamir Hussain

“…Moreover, a case study of watermelon seedings is examined, and the results of the 3D reconstruction of the seedlings show that our model outperforms classical segmentation algorithms on the main metrics, achieving a 91.0% mAP50 (B) and a 91.3% mAP50 (M).…”
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Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles by Shaojun Chen, Yiyuan Luo, Lihua Zhang

“…Subsequently, we employed two machine learning analyses—least absolute shrinkage and selection operator (LASSO) and random forest algorithms– to pinpoint shared hub gene between the two diseases. …”
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The problems of enforcement of decisions on the deprivation of the driver's license by O. Beketov, S. Koryts

“…It is possible to identify the main causes of the problem of law enforcement, placing them in order of importance:1. …”
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Enhancing river and lake wastewater reuse recommendation in industrial and agricultural using AquaMeld techniques by J. Priskilla Angel Rani, C. Yesubai Rubavathi

“…This study uses AquaMeld and Multi-Layer Perceptron with Recurrent Neural Network (MLP-RNN) algorithms to create a complete recommendation system. …”
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La Teoría del andamiaje como herramienta de construcción del pensamiento matemático by Cesar Orlando Vargas Mantilla, Sonia Maritza Mendoza Lizcano, Wlamyr Palacios Alvarado

“…Therefore, it is necessary to analyze the teaching-learning processes, and more specifically, the construction of mathematical thinking, from an innovative and agile perspective that breaks with traditional learning patterns of repeating algorithms and implementing formulas. The concept of scaffolding is presented as a tool for knowledge appropriation, as a social way of learning and capturing mathematical knowledge, skills, and abilities. …”
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Structural and social determinants of health: The multi-ethnic study of atherosclerosis. by Lilah M Besser, Sarah N Forrester, Milla Arabadjian, Michael P Bancks, Margaret Culkin, Kathleen M Hayden, Elaine T Le, Isabelle Pierre-Louis, Jana A Hirsch

“…Two individuals systematically reviewed titles, abstracts, and full text to determine the final number of papers (n = 431) that focused on at least one SSDOH variable as an exposure, outcome, or stratifying/effect modifier variable of main interest (discrepancies resolved by a third individual). …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…We collected leaf images of 33 pear varieties against natural backgrounds, including 5 main cultivation species and inter-species selection varieties. …”
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Semi-Implicit Numerical Integration of Boundary Value Problems by Maksim Galchenko, Petr Fedoseev, Valery Andreev, Endre Kovács, Denis Butusov

“…The novel blinking solver concept is introduced to overcome the main shortcoming of the semi-implicit schemes, namely, the low convergence on exponential solutions. …”
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Indoor levels of volatile organic compounds and formaldehyde from emission sources at elderly care centers in Korea. by Kyoungho Lee, Jae-Hyun Choi, Seokwon Lee, Hee-Jin Park, Yu-Jin Oh, Geun-Bae Kim, Woo-Seok Lee, Bu-Soon Son

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Utrophin haploinsufficiency does not worsen the functional performance, resistance to eccentric contractions and force production of dystrophic mice. by Antoine Boulanger Piette, Dounia Hamoudi, Laetitia Marcadet, Frédérique Kyomi Labelle, Rares Ovidiu David, Sabrina Bossé, Anteneh Argaw, Jérôme Frenette

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From Continent to Ocean: Investigating the Multi-Element and Precious Metal Geochemistry of the Paraná-Etendeka Large Igneous Province Using Machine Learning Tools by J. J. Lindsay, H. S. R. Hughes, C. M. Yeomans, J. C. Ø. Andersen, I. McDonald

“…Here, we use an unsupervised machine learning approach (featuring the PCA, t-SNE and k-means clustering algorithms) to investigate the geochemistry of a set of (primarily basaltic) onshore and offshore PELIP lavas. …”
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Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data by T. Radke, S. Fuchs, C. Wilms, I. Polkova, I. Polkova, I. Polkova, M. Rautenhaus, M. Rautenhaus

“…<p>Detection of atmospheric features in gridded datasets from numerical simulation models is typically done by means of rule-based algorithms. Recently, the feasibility of learning feature detection tasks using supervised learning with convolutional neural networks (CNNs) has been demonstrated. …”
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