Pioneering machine learning techniques to estimate thermal conductivity of carbon-based phase change materials: A comprehensive modeling framework by Raouf Hassan, Alireza Baghban

“…A dataset of 482 samples, incorporating various nanoparticle types, concentrations, PCM types, and operating temperatures, was curated and refined using the Monte Carlo Outlier Detection algorithm. Extensive machine learning algorithms were explored; however, CatBoost, XGBoost, ANN, Random Forest, and Gradient Boosting emerged as the most accurate models. …”
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Snake-inspired trajectory planning and control for confined pipeline inspection with hyper-redundant manipulators by Junjie Zhu, Mingming Su, Longchuan Li, Yuxuan Xiang, Jianming Wang, Xuan Xiao

“…To address this issue, a pipeline inspection approach that combines nonlinear model predictive control (NMPC) with the snake-inspired crawling algorithm(SCA) is proposed. …”
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Stellar Streams Reveal the Mass Loss of Globular Clusters by Yingtian Chen, Hui Li, Oleg Y. Gnedin

“…In this work, we employ a novel particle spray algorithm that can accurately reproduce the morphology of streams of various orbital types, enabling us to uncover the relationship between the GC mass-loss history and stream density profiles. …”
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Design of an Intelligent Energy Management Prototype for an Electric Lighting Network on a Raspberry Pi Board by Jouahri Mohammed Amine, Moukhtari Manal, Oulhaj Nabil, Khimouj Mounir, Tajer Abdelouahed, Boulghasoul Zakaria

“…Traffic density is assessed in real time by an image processing system using the YOLOv8 algorithm, which identifies and counts vehicles captured by the cameras. …”
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Sensitivity Analysis of Unmanned Aerial Vehicle Composite Wing Structural Model Regarding Material Properties and Laminate Configuration by Artur Kierzkowski, Jakub Wróbel, Maciej Milewski, Angelos Filippatos

“…A Multi-Objective Genetic Algorithm (MOGA), well suited for complex engineering problems, was employed alongside Design of Experiments to develop a precise response surface model, achieving predictive errors of 0% for mass and 2.99% for frequency. …”
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Adaptive Filter Updating for Energy-Efficient Top- Queries in Wireless Sensor Networks Using Gaussian Process Regression by Jiping Zheng, Baoli Song, Yongge Wang, Haixiang Wang

“…The mechanism can reduce transmissions of redundant data by utilizing filters. However, existing algorithms based on filters consume a vast amount of energy due to filter updating. …”
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TECHNOLOGY TRANSFER RISK MANAGEMENT IN THE CONDITIONS OF SCIENTIFIC INTERNATIONALISATION by Iryna Novikova, Alla Stepanova, Oksana Zhylinska, Anastasiia Samoilikova

“…Thus, the study aims to develop an algorithm for managing key risks that arise in the exchange of technology in the scientific and educational environment in the context of the internationalisation of science. …”
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Modern aspects of diagnostics and treatment of <i>H. pylori</i> infection from standpoint of stomach cancer prophylaxis by A. A. Sheptulin, T. L. Lapina

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Robust time series analysis for forecasting photovoltaic energy yield by Sapundzhi Fatima, Chikalov Aleksandar, Georgiev Slavi, Georgiev Ivan, Todorov Venelin

“…This study introduces an approach to forecasting the power output of a photovoltaic (PV) system by employing an ARIMA-based algorithm. Two distinct ARIMA models were designed – one generated via SPSS and one selected by the researchers. …”
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Design and Application of an Energy Management System Based on Artificial Intelligence Technology by Hongye Lin, Xuanying Bai, Chun Li, Shenghan Xu, Haibin Xu, Zne-Jung Lee, Yun Lin, Qunshan Zhou, Jingxun Cai

“…The system adopts sensor technology and data acquisition equipment to monitor various types of energy consumption in buildings in real time, efficiently process and predict these data through machine learning algorithms, and finally visualize the results. …”
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Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

“…Pre-processing in both algorithms focuses on segmentation of heart sounds into discrete cardiac cycles. …”
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Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES by J.B. Ghasemi, E. Zolfonoun, R. Khosrokhavar

“…The combinations of inductively coupled plasma-optical emission spectrometry (ICP-OES) and three classification algorithms, i.e., partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LS-SVM) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of Iranian bottled mineral waters, were explored. …”
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Measured spectrum environment map dataset with multi-radiation sources in urban scenariosMendeley Data by Haotian Zou, Qiuming Zhu, Qianhao Gao, Jie Wang, Zhipeng Lin, Yang Huang, Qihui Wu, Weizhi Zhong

“…Its applications include the verification of spectrum map completion algorithms, wireless channel modelling, deep learning-driven signal prediction, and the optimization of Wi-Fi/cellular networks.…”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…This paper explores the application of Deep Reinforcement Learning (DRL) to optimize adaptive observation strategies for multi-AUV systems in complex marine environments. Traditional algorithms struggle with the strong coupling between environmental information and observation modeling, making it challenging to derive optimal strategies. …”
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Artificial Intelligence in the Organization of Nursing Care: A Scoping Review by João Ventura-Silva, Maria Manuela Martins, Letícia de Lima Trindade, Ana da Conceição Alves Faria, Soraia Pereira, Samuel Spiegelberg Zuge, Olga Maria Pimenta Lopes Ribeiro

“…Conclusions: AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.…”
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A framework of crop water productivity estimation from UAV observations: A case study of summer maize by Minghan Cheng, Ni Song, Josep Penuelas, Matthew F. McCabe, Xiyun Jiao, Yuping Lv, Chengming Sun, Xiuliang Jin

“…To address this challenge, our research develops an innovative UAV-based monitoring framework through systematic integration of long-term multispectral/thermal infrared observations with multi-model fusion: (1) Surface Energy Balance Algorithm for Land (SEBAL) and FAO-56 Penman-Monteith models for evapotranspiration (ET) estimation; (2) Random Forest algorithm incorporating four phenotypical growth indicators for yield estimation, ultimately enabling CWP quantification. …”
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Study on the factors influencing the impaired abilities of daily living in middle-aged and older adult arthritis patients based on binary logistic regression and categorical decisi... by Bao-xuan Zhang, Bao-xuan Zhang, Bao-xuan Zhang, Jin-ping Luo, Jin-ping Luo, Jin-ping Luo, Jia-ying Sun, Jia-ying Sun, Jia-ying Sun, Ming-hui Geng, Ming-hui Geng, Ming-hui Geng, Yi-fan Mou, Yi-fan Mou, Yi-fan Mou, Nan-nan Cheng, Nan-nan Cheng, Nan-nan Cheng, Zhao-xuan Wang, Zhao-xuan Wang, Zhao-xuan Wang, Wen-qiang Yin, Wen-qiang Yin, Wen-qiang Yin, Zhong-ming Chen, Zhong-ming Chen, Zhong-ming Chen, Dong-ping Ma, Dong-ping Ma, Dong-ping Ma

“…Variables with significant differences in univariate analysis were included in binary logistic regression model and decision tree model based on the E-CHAID algorithm to explore the factors associated with impaired ADL in middle-aged and older adult arthritis patients in China.ResultsThe results of the logistic regression model indicated that sex, place of residence, age, education level, falls, Internet usage, depressive symptoms, pain, self-rated health, and number of comorbid chronic diseases were the influencing factors for impaired ADL. …”
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Modified Сomplex Treatment of the Cirhotic Patients with the Hepatopulmonary Syndrome of the Different Severity Degrees: Pathogenetic Reasoning and Efficiency by Abrahamovych M., Abrahamovych O., Tolopko S., Ferko M.

“…Engaging of the different organs and systems into the pathological process, including the organs of the respiratory system, interpretated as syntropic co­ and polymorbid lesions, including the most common ­ hepatopulmonary syndrome (HPS), in many cases determines the severity of the general condition of the cirrhotic patients, leads to a significant reduction of their life quality, disability, has a decisive prognostic value at all the stages of the treatment and is the leading cause of the death of the hepatological patients. …”
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Dosing and Safety Profile of Aficamten in Symptomatic Obstructive Hypertrophic Cardiomyopathy: Results From SEQUOIA‐HCM by Caroline J. Coats, Ahmad Masri, Michael E. Nassif, Roberto Barriales‐Villa, Michael Arad, Nuno Cardim, Lubna Choudhury, Brian Claggett, Hans‐Dirk Düngen, Pablo Garcia‐Pavia, Albert A. Hagège, James L. Januzzi, Matthew M. Y. Lee, Gregory D. Lewis, Chang‐Sheng Ma, Martin S. Maron, Zi Michael Miao, Michelle Michels, Iacopo Olivotto, Artur Oreziak, Anjali T. Owens, John A. Spertus, Scott D. Solomon, Jacob Tfelt‐Hansen, Marion van Sinttruije, Josef Veselka, Hugh Watkins, Daniel L. Jacoby, Polina German, Stephen B. Heitner, Stuart Kupfer, Justin D. Lutz, Fady I. Malik, Lisa Meng, Amy Wohltman, Theodore P. Abraham

“…Conclusions A site‐based dosing algorithm targeting the lowest effective aficamten dose reduced left ventricular outflow tract gradient with a favorable safety profile throughout SEQUOIA‐HCM. …”
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Panel Method for 3D Inviscid Flow Simulation of Low-Pressure Compressor Rotors with Tip-Leakage Flow by Valentin Caries, Jérôme Boudet, Eric Lippinois

“…This paper presents a low-order three-dimensional approach for predicting the inviscid flow around low-pressure compressors. …”
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