In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure by Lamiae Elkhattabi, Imane Morjane, Hicham Charoute, Soumaya Amghar, Hind Bouafi, Zouhair Elkarhat, Rachid Saile, Hassan Rouba, Abdelhamid Barakat

“…Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. …”
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Modelling flame-to-fuel heat transfer by deep learning and fire images by Caiyi Xiong, Zilong Wang, Xinyan Huang

“…Results show that the proposed AI algorithm trained by flame images can predict both the convective and radiative heat flux distributions on the condensed fuel surface with a relative error below 20%, based on the input of real-time flame morphology that can be captured by a larger grid size. …”
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Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus by D. Yu. Sorokin, E. S. Trufanova, O. Yu. Rebrova, O. B. Bezlepkina, D. N. Laptev

“…We constructed recurrent neural network (RNN) to predict glucose concentration for 30-120 minutes, an algorithm for optimizing IP settings using prediction results. …”
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Mesh Smoothing of 3D Prosthesis and Orthosis Models by A. R. Sufelfa, A. S. Voznesensky, D. I. Kaplun

“…This paper considers specific features of methods currently used for denoising of a 3D model surface obtained by optical scanning. An algorithm for manufacturing an individual prosthetic and orthopedic product is developed. …”
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Principles of effective out-patient diagnostics of diffuse liver diseases by Komova A. G., M. V. Mayevskaya, V. T. Ivashkin

“…In the case of abnormal liver tests preliminary diagnosis was determined according to certain algorithm and these patients were recruited for further investigation and specifications of diagnosis in department of hepatology, University clinical hospital N 2, State educational government-financed institution of higher professional education «Sechenov First Moscow state medical university». …”
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Chronic Hepatitis С in Siberian Federal District: Analysis of a Case Rate and Evolution of Genotypes of the Originator by E. D. Savilov, S. I. Malov, I. V. Malov, O. B. Ogarkov, V. A. Astafev, N. N. Chemezova, I. A. Miroshnichenko

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Some Aspects of Modern Distance Learning Technologies in the Field of Fire Safety by V. V. Volodchenkova, N. V. Peregudova, D. N. Kurkin, O. V. Chirko

“…Distance learn- ing in the field of fire safety, organized based on a virtual learning environment, can provide pre-certification training for employees of organizations, and the lecturer can use modern training tools for the educational interaction.The authors propose a scheme of the educational environment for the listener, as well as the algorithm of the lecturer’s work in the format of distance learning in the basics of fire safety. …”
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A Novel SERS Silent-Region Signal Amplification Strategy for Ultrasensitive Detection of Cu²⁺ by Jiabin Su, Kaixin Chen, Ping Zhou, Nan Li

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Overlapping genes connect rheumatoid arthritis and head and neck cancer: coincidence or shared immune pathophysiology? by Ran Wang, Haiyang Li, Haiyang Li, Yifan Yang, Yifan Yang, Meng Lian, Meng Lian

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THE USE OF FORECASTING METHODS FOR DETERMINING THE MAIN TRENDS IN THE DEVELOPMENT OF PROFESSIONAL TRAINING SYSTEMS FOR SECOND LANGUAGE TEACHERS OF ROMANIA AND UKRAINE by Korolova Larysa

“…An algorithm for using forecasting techniques to determine the main trends in the development of professional training systems for second language teachers in Romania and Ukraine is presented. …”
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USE OF NONSTEROIDAL ANTI-INFLAMMATORY DRUGS FOR THE TREATMENT OF AXIAL SPONDYLOARTHRITIS, INCLUDING ANKYLOSING SPONDYLITIS, MONITORING THEIR EFFICACY AND SAFETY (DRAFT GUIDELINES O... by I. Z. Gaidukova, A. P. Rebrov, E. N. Otteva, V. V. Badokin, A. G. Bochkova, O. V. Bugrova, A. A. Godzenko, A. A. Dubikov, T. V. Dubinina, O. N. Ivanova, T. V. Korotaeva, S. A. Lapshina, O. B. Nesmeyanova, I. P. Nikishina, T. A. Raskina, O. A. Rumyantseva, A. V. Smirnov, A. V. Sitalo, Sh. F. Erdes

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Online Estimation of the State of Health for the Lithium-Ion Battery Based on Open Circuit Model by Pan Yajia, Junda Li, Wang Tian'An, Yang Shengxun, Zhang Yunxuan, Li Zigang, Hu Yanwen

“…The accurate prediction of the state of health (SOH) for lithium-ion batteries is of significant importance in proactively avoiding unsafe behavior. …”
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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

“…Combining the deep learning model with the multi model hierarchical classification algorithm, the remote sensing prediction map based on deep learning is used as the classification base map, and the normalized difference vegetation index threshold is used to classify the uncovered area. …”
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Coordinated Interaction Strategy of User-Side EV Charging Piles for Distribution Network Power Stability by Juan Zhan, Mei Huang, Xiaojia Sun, Zuowei Chen, Zhihan Zhang, Yang Li, Yubo Zhang, Qian Ai

“…Secondly, by combining urban transportation big data and prediction networks, high-precision inference of the spatiotemporal distribution of charging loads can be achieved. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Depth Integrated Multi-Task Prototypical Learning With Self Refinement for Unsupervised Domain Adaptation by Antonio Dauphin Fernando, Thumma Anirudh, Selvaraj Palanisamy, Karthika Prasad, Katia Alexander, Pandiyarasan Veluswamy, Rohini Palanisamy

“…The task-specific classifiers capture the semantic and depth features, and the task-integrated classifier captures the hidden semantic features from depth prediction. This framework ensures that the prototypes from respective heads learn better class-representative features using semantic information and depth cues. …”
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A hybrid model based on the photovoltaic conversion model and artificial neural network model for short-term photovoltaic power forecasting by Ran Chen, Shaowei Gao, Yao Zhao, Dongdong Li, Shunfu Lin

“…Backpropagation, gradient descent, and L2 regularization methods are applied in the structure of the ANN model to achieve the best weights, improve the prediction accuracy, and alleviate the effect of overfitting. …”
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Enhancing Process Control in Agriculture: Leveraging Machine Learning for Soil Fertility Assessment by Ashutosh Sarangi, Sailesh Kumar Raula, Sohamdev Ghoshal, Swadhin Kumar, Chinta Sai Kumar, Neelamadhab Padhy

“…<b>Result</b>: The results demonstrated that the machine learning classifier significantly improves prediction accuracy. We used LR, KNN, NB, and DT classifiers to increase the accuracy, as well as to increase the efficiency of the soil fertility assessment. …”
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Mental health of university students twenty months after the beginning of the full-scale Russian-Ukrainian war by Marina Polyvianaia, Yulia Yachnik, Jörg M. Fegert, Emily Sitarski, Nataliia Stepanova, Irina Pinchuk

“…Correlation between variables was calculated with Pearson correlation, adjusted with Benjamini-Hochberg procedure. To develop the predictive model the XGBoost algorithm was employed, additionally, the SHAP algorithm was utilized. …”
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A model for classifying information objects using neural networks and fuzzy logic by Vadym Mukhin, Valerii Zavgorodnii, Viacheslav Liskin, Sergiy Syrota, Aleksandra Czupryna-Nowak, Bohdan Rusyn, Arkadiusz Banasik, Jacek Woloszyn, Wojciech Kempa

“…Improve the efficiency of classification algorithms by fine-tuning neural network parameters and fuzzy logic rules, ensuring high accuracy and computational efficiency when processing large-scale educational datasets. …”
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