A new approach in prevention and correction of intradialysis hypotension in patients on maintenance hemodialysis by I. Yu. Drachev, V. Yu. Shilo, G. S. Dzhulay

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The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending by Ismael Mendoza, Andrii Torchylo, Thomas Sainrat, Axel Guinot, Alexandre Boucaud, Maxime Paillasa, Camille Avestruz, Prakruth Adari, Eric Aubourg, Biswajit Biswas, James Buchanan, Patricia Burchat, Cyrille Doux, Remy Joseph, Sowmya Kamath, Alex I. Malz, Grant Merz, Hironao Miyatake, Cécile Roucelle, Tianqing Zhang, LSST Dark Energy Science Collaboration

“…Additionally, BTK provides researchers who are developing a new deblending algorithm a framework to evaluate algorithm performance and make principled comparisons with existing deblenders. …”
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Internet of Things-Based Smart Infant-Incubators Using Machine Learning Analysis by Mahmoud Gamal, Ibrahim Radi, Amr Yousef, and Ali Gaber Mohamed Ali

“…A convolutional neural network (CNN) algorithm is used to take neonatal care a step further. …”
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Massive discovery of crystal structures across dimensionalities by leveraging vector quantization by ZiJie Qiu, Luozhijie Jin, Zijian Du, Hongyu Chen, Guanyao Mao, Yan Cen, Siqi Sun, Yongfeng Mei, Hao Zhang

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SOME ASPECTS OF SCANNING LASER OPHTHALMOSCOPY IN THE DIAGNOSTICS OF OPHTHALMOPATHOLOGY by S. A. Kochergin, S. Yu. Slonimsky, A. A. Ovsyanko, O. D. Gupalo

“…After the conducted research features and regularities of the reflectivity distribution of laser beams from the fundus structures are revealed. …”
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Developing an Integrative Data Intelligence Model for Construction Cost Estimation by Zainab Hasan Ali, Abbas M. Burhan, Murizah Kassim, Zainab Al-Khafaji

“…Artificial intelligence (AI) models have been effectively implemented in construction management studies in recent years owing to their capability to deal with complex problems. In this research, extreme gradient boosting is developed as an advanced input selector algorithm and coupled with three AI models, including random forest (RF), artificial neural network (ANN), and support vector machine (SVM) for cost estimation. …”
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Optimization of Transformation Coefficients Using Direct Search and Swarm Intelligence by Manusov V.Z., Matrenin P.V., Orlov D.V.

“…In addition, they can efficiently find quasi-optimal solutions converging to the global optimum. This research applies Particle Swarm Optimization algorithm (PSO). …”
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Voluntary Muscle Contraction Pattern in Cerebral Palsy by Reducing Guidance Force in Robot-Assisted Gait Training: A Proof of Concept Focused on a Single-Participant Study by Suncheol Kwon, Sora Park, Ji Hye Jung, Hyun Kyung Kim

“…A single-participant research design study was conducted with a gradual reduction in robotic assistance during robot-assisted gait training. …”
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Artificial intelligence in predicting pathogenic microorganisms’ antimicrobial resistance: challenges, progress, and prospects by Yan Li, Xiaoyan Cui, Xiaoyan Yang, Guangqia Liu, Juan Zhang

“…Finally, we discuss new perspectives and solutions for research into microbial resistance through algorithm optimization, dataset expansion, and interdisciplinary collaboration. …”
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An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999–2018 by Qun Tang, Yong Wang, Yan Luo

“…Abstract Current research on the association between demographic variables and dietary patterns with atherosclerotic cardiovascular disease (ASCVD) is limited in breadth and depth. …”
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Uncertainty aware energy management in microgrids with integrated electric bicycle charging stations and green certificate market by Hossein Shayeghi, Iraj Faraji Davoudkhani

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Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support by Ying-Yi Hong, Francisco I. Alano, Yih-der Lee, Chia-Yu Han

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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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Pathways to 30 × 30: Evidence-Based Lessons from Global Case Studies in Biodiversity Conservation by Susmita Dasgupta, David Wheeler, Brian Blankespoor

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EVOLUTION OF THE AGRICULTURAL LABOUR MARKET IN THE EUROPEAN UNION BETWEEN 2011-2020 by Cristina Vasilica ICOCIU, Ana-Maria IFRIM, Cătălin Ionuț SILVESTRU, Marius-Mihai MICU

“…In the current context, in which the pandemic crisis is wreaking havoc in all socio-economic fields, causing both loss of life and immeasurable economic losses, fundamental research conducted to identify directions for rapid and sustainable socio-economic recovery is of great importance. …”
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Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale by Monica Casella, Nicola Milano, Pasquale Dolce, Davide Marocco

“…IntroductionMissing data in psychometric research presents a substantial challenge, impacting the reliability and validity of study outcomes. …”
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Development of medium voltage single‐phase solid‐state transformer for high‐speed railway vehicles: Reduced scale verification results by Dong‐Uk Kim, Jin‐Hyuk Park, Seung‐Hwan Lee, Sungmin Kim

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Transient Coupled Flow Model for Matrix-Fracture in High-Pressure Gas Reservoirs Opened by Gas Drilling by Jiajie Liu, Gao Li, Zhi Ye, Wang He, Zhihao Zeng

“…This model is solved by Shaher Momani’s algorithm and CyabJiBe format, and the type curves of the pressure and flow velocity are plotted. …”
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Design optimization of university ideological and political education system based on deep learning by Shangle Ai, Huanhuan Ding

“…Firstly, this paper introduces the research methods in detail, including deep learning algorithm and model design, as well as the optimization design process of IPE system. …”
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Impact of Automated Truck Platooning on the Performance of Freeway Mixed Traffic Flow by Seolyoung Lee, Cheol Oh, Gunwoo Lee

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