Charge‐coupled device based on optical tomography system for monitoring two‐phase flow by J. Jamaludin, R. Abdul Rahim, H. Abdul Rahim, M.H. Fazalul Rahiman, J. Mohd Rohani

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Real Time System Scheduling Approach:Survey by Dhuha Abdullah, Israa Abood, Raya hamdi

“…In this paper, we aim to investigate the scheduling attributes and scope of research in real-time computing, and classify real-time system in two categories: algorithms for multiprocessor scheduling and algorithms for uniprocessor scheduling. …”
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Hardware-software complex for experimental research of electric drives of asynchronous motors with squirrel-cage rotor with traditional winding and motors with combined winding by A. N. Tsvetkov, Doan Ngok Shi

“…The creation of research stands implies the development of a hardware-software complex (HSC) based on high-speed computing devices. …”
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Developing a Critical Imagination for How Researchers can use Artificially Intelligent Tools Reflexively and Responsibly During Qualitative Literature Reviews by Kristen Foley, Caitlan McLean, Reece De Zylva, Gregorius Asa, Jordana Maio, Samantha Batchelor, Gideon Dzando, Ahmad Dimassi

“…Beyond only literature retrieval, some AI tools describe their use-value as being able to appraise and synthesise contrasting evidence within and across papers; work like ‘Spotify’ to cultivate a personalised ecosystem of research articles that evolves via algorithmic learning; and suggest new directions for research based on existing evidence about a topic and an assessment of knowledge gaps. …”
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Circadian rhythm disruption by PARP inhibitors correlates with treatment toxicity in patients with ovarian cancer and is a predictor of side effectsResearch in context by Deeksha Malhan, Janina Hesse, Nina Nelson, Kay Stankov, Jessica Nguyen, Ouda Aboumanify, Josefin Garmshausen, Gunther Rogmans, Bastian Czogalla, Jens Gerber, Martin Koch, Tomáš Kupec, Oliver Tomé, Ralf Witteler, Mustafa Deryal, Michael Eichbaum, Jalid Sehouli, Elena Ioana Braicu, Angela Relógio

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Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context by Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi

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Translational medicine research on the role of key gene network modulation mediated by procyanidin B2 in the precise diagnosis and treatment of multiple sclerosis by Jian Liu, Meng Pu, Di Guo, Ying Xiao, Jin-zhu Yin, Dong Ma, Cun-gen Ma, Qing Wang

“…Eight machine learning algorithms were employed to screen key genes, and nomograms and ROC curves were constructed to assess the value of the screened biomarker genes in MS diagnosis. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

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Intraspecific Differentiation of <I>Francisella tularensis</I> Strains Using Molecular-Genetic Methods. Complex Approach by N. A. Osina, D. A. Sitmbetov, O. A. Morozov, E. G. Bulgakova, A. V. Osin, S. S. Chekmareva, E. V. Sazanova, A. M. Senichkina, O. Yu. Lyashova, T. A. Polunina, Ya. M. Krasnov, Z. L. Devdariani, S. A. Shcherbakova

“…The aim of the study was to develop an algorithm for intraspecific differentiation of tularemia agent strains using a set of approaches based on amplification and sequencing technologies.Materials and methods. 97 strains of Francisella tularensis of various subspecies, biovars and subpopulations from the State Collection of Pathogenic Bacteria of the Russian Research Anti-Plague Institute “Microbe” were used in the work. …”
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Clinical Recommendations for the Diagnosis and Treatment of Chronic Myeloid Leukemia by AG Turkina, AYu Zaritskii, VA Shuvaev, EYu Chelysheva, EG Lomaia, EV Morozova, AK Golenkov, TI Pospelova, OA Shukhov, MS Fominykh, GA Gusarova, LA Kuz’mina, AO Abdullaev, IS Martynkevich

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Estimation and analysis of vegetation parameters for the water cloud model by Xiangdong Qin, Zhiguo Pang, Jingxuan Lu

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Corrigendum: Assessing cross-boundary wildfire hazard, transmission, and exposure to communities in the Italy-France Maritime cooperation area by Michele Salis, Liliana Del Giudice, Fermin Alcasena-Urdiroz, Roghayeh Jahdi, Bachisio Arca, Grazia Pellizzaro, Carla Scarpa, Pierpaolo Duce

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Gliflozins position update in the treatment algorithms for patients with type 2 diabetes mellitus and chronic kidney disease: new pathogenetic mechanisms and data from subanalyses... by O. Y. Sukhareva, Z. T. Zuraeva, M. S. Shamhalova

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Short-Term Wind Power Prediction Model Based on PSO-CNN-LSTM by Qingquan Lv, Jialin Zhang, Jianmei Zhang, Zhenzhen Zhang, Qiang Zhou, Pengfei Gao, Haozhe Zhang

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Long-term use of nonsteroidal anti-inflammatory drugs for pain control in patients with osteoarthritis: results of the 12-month observational study AELITA (Analgesia: Effective Tre... by A. E. Karateev, E. Yu. Polishchuk, E. S. Filatova, A. S. Potapova, V. A. Nesterenko, V. N. Amirdzhanova

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Photovoltaic Module Fault Detection Technology Based on Remote Sensing Technology and Deeplabv3+ Model by Xiaowei Xu, Mingxian Liu, Yongjie Nie, Ke Wang, Wenhua Xu

“…Combining remote sensing technology with Deeplabv3+ model, fast and accurate photovoltaic module fault detection can be achieved. The research results indicated that bilateral filtering and gamma filtering algorithms showed superior performance in testing, with the highest indicator evaluation results. …”
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Reliability growth model of quantum direct current electricity meter software based on optimization network by TIAN Teng, QIU Rujia, ZHAO Long, GENG Jiaqi, WANG Enhui, SUN Yu

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The Intelligent Sizing Method for Renewable Energy Integrated Distribution Networks by Zhichun Yang, Fan Yang, Yu Liu, Huaidong Min, Zhiqiang Zhou, Bin Zhou, Yang Lei, Wei Hu

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Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003–2018 by Zu-Ming You, Yuan-Sheng Li, Fan-Shuo Meng, Rui-Xiang Zhang, Chen-Xi Xie, Zhijiang Liang, Ji-Yuan Zhou

“…However, there has been no research on machine learning (ML) modelling between multiple heavy metal exposures and PCA risk. …”
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An improved extreme learning machine algorithm for prospectivity mapping of copper deposits using multi-source remote sensing data: a case study in the North Altyn Tagh, Xinjiang,... by Boqi Yuan, Qinjun Wang, Wentao Xu, Chaokang He, Wenyue Xie

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