Industrial data-driven machine learning soft sensing for optimal operation of etching tools by Feiyang Ou, Henrik Wang, Chao Zhang, Matthew Tom, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…A statistical analysis method involving point-biserial correlation and the Mean Absolute Error (MAE) difference score is introduced to select the optimal candidate datasets for aggregation, further improving the effectiveness of data aggregation. …”
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Unlocking the Potential of Remanufacturing Through Machine Learning and Data-Driven Models—A Survey by Yong Han Kim, Wei Ye, Ritbik Kumar, Finn Bail, Julia Dvorak, Yanchao Tan, Marvin Carl May, Qing Chang, Ragu Athinarayanan, Gisela Lanza, John W. Sutherland, Xingyu Li, Chandra Nath

“…These challenges arise from uncertainties surrounding core quality and functionality, return times, process variation required to meet product specifications, and the end-of-use (EoU) product values, as well as their new life expectancy after extended use as a ‘market product’. …”
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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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Investigating the Relationship Between Liquidity Risk, Credit Risk, and Solvency Risk in Banks Listed on the Iranian Capital Market: A Panel Vector Error Correction Model by Pejman Peykani, Mostafa Sargolzaei, Cristina Tanasescu, Seyed Ehsan Shojaie, Hamidreza Kamyabfar

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Resilient $${\mathcalligra {H}}_\infty$$ filter design for networked control systems under communication jamming cyberattacks by Muhammad Ali, Ghulam Mustafa, Hasnain Ahmad, Muhammad Abid, Salman Habib, Roobaea Alroobaea, Ali ELrashidi

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On the development of a systemic (biopsychosocial) prediction model for cardiovascular disease. Part I by O. Yu. Shchelkova, M. V. Iakovleva, D. A. Eremina, R. Yu. Shindrikov, N. E. Kruglova, I. A. Gorbunov, E. A. Demchenko

“…A total of 245  indicators were taken into account; they were expertly divided into five groups: clinical, socio-behavioural, personality characteristics, emotional state indicators, and cognitive functioning indicators. 3)  The missing cells in the sampling matrix were filled in by means of mathematical modelling and neural networks. 4) An exploratory factor analysis of all characteristics in the allocated groups was performed, resulting in 24  factors: 3  in the group of clinical characteristics (“Coronary heart disease”, “Transplantation”, “Patient’s age and duration of heart failure”), 6  in the group of socio-behavioural (“Social and occupational orientation”, “Keeping a habitual lifestyle in spite of illness”, “Occupational strain”, “Lifestyle”, “Non-adherent behaviour”, “Occupational stress”), 5  in the group of personality characteristics (“Attitude towards illness”, “Motivational orientation”, “Decreased resilience”, “Irrational beliefs”, “Coping strategies and coping resources”), 4 in the group of emotional state characteristics (“Dominant emotional state and feelings”, “Quality of life and mood”, “Absence of anxiety at the moment of the study”, “Functioning in conditions of illness”), 6  in the group of characteristics of cognitive functioning (“Neuropsychological characteristics”, “Spatial–constructive thinking and pace of mental activity”, “Visual memory”, “Attention and verbal–logical thinking”, “Verbal memory”, “No significant decrease in IQ”).…”
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State and development prospects of dental care for the Ukrainian population by O. V. Voznyi, S. M. Hermanchuk, V. I. Struk, V. I. Bida, A. V. Pohorila

“…Materials and methods. For the analysis, selected data of scientific literature, statistical indicators of the Ministry of Health of Ukraine and the Center of Medical Statistics of the Ministry of Health of Ukraine were used. …”
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Effects of combination antihypertensive therapy on intracardiac hemodynamics and blood vessels in patients with coronary heart disease, post-infarction cardiosclerosis and arterial... by M. M. Dolzhenko, S. A. Bondarchuk, L. Ye. Lobach

“…When analyzing the indicators of diastolic function in the second group, a highly significant (p < 0.05) decrease in E/A, E/E’, IO of the LA has been revealed; data analysis on the morphofunctional state indicators of the extracranial arteries has shown a CIM reduction and a decrease in PSV and RI. …”
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Prediction Method of Air Braking Force of Heavy Load Train Based on Fuzzy Logic-based Neural Network by SHI Ke, ZHANG Zhengfang, BAI Jinglei, JIANG Jie

“…Firstly, radial basis function neural network (RBF-NN) is used to train off-line data of air braking, and off-line prediction rules of air braking force in the form of fuzzy logic are obtained. …”
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Synoptic Level Fluctuations of the White Sea by Kondrin Aleksey, Korablina Anastasia

“…The surge run-offs and run-ups are explored based on the analysis of residual sea level fluctuations (RSL), which is determined by removing the tidal component from the observational data. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

“…While groundwater-dependent ecosystems (GDEs) occupy only a small portion of the Earth’s surface, they hold significant ecological value by providing essential ecosystem services such as habitat for flora and fauna, carbon sequestration, and erosion control. However, GDE functionality is increasingly threatened by human activities, rainfall variability, and climate change. …”
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Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model by Sadra Shadkani, Yousef Hemmatzadeh, Amirreza Pak, Soroush Abolfathi

“…The proposed framework integrates feedforward neural networks (FFNN), long short-term memory (LSTM) networks, stochastic gradient descent (SGD), and radial basis function (RBF) models, augmented with a first-order differencing technique. …”
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Clusters of patients with non-ST-segment elevation acute coronary syndrome depending on the laboratory data by D. N. Nedbaeva, V. S. Mikhaleva, E. A. Zolotova, O. V. Sirotkina, G. A. Kukharchik

“…To identify clusters of patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS) depending on the laboratory data, including platelet function tests.Material and methods. …”
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Locomotive Video Monitoring System by 刘应军

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Impact of Digital Transformation on Accelerating Enterprise Innovation—Evidence from the Data of Chinese Listed Companies by Jiqiong Liu, Chunyan Liu, Shuai Feng

“…Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. …”
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The Data-Driven Performance Prediction of Lattice Structures: The State-of-the-Art in Properties, Future Trends, and Challenges by Siyuan Yang, Ning Dai, Qianfeng Cao

“…The current applications of performance-prediction methods, which are data-driven and related to material properties, structural properties, and performance under conditions of coupled multi-physical fields, are analyzed, and this analysis further extends to the data-driven methods in relation to their prediction of lattice structure functionality. …”
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Identifying key genes in COPD risk via multiple population data integration and gene prioritization. by Afeefa Zainab, Hayato Anzawa, Kengo Kinoshita

“…Lung function measurements are often used as indicators for COPD risk prediction; therefore, we used lung function GWAS data from two populations, Japanese and European, and re-evaluated them using a multi-population gene prioritization approach. …”
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Whole genome sequence data of Pediococcus pentosaceus NIBL1955 isolated from riceNCBI by Jeong-Ah Yoon, Se-Young Kwun, Hye-Jin Hong, Min-Kyung Ju, Sang-Min Shim, Myoung-Dong Kim

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A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data. by Bronwyn K Brew, Flaminia Chiesa, Cecilia Lundholm, Anne Örtqvist, Catarina Almqvist

“…Characterization was then performed with regression analyses using diagnostic data: lung function and immunological biomarkers, parent-reported medication use and risk-factors. …”
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Status assessment and management strategy of a large bridge based on massive real time data by Feng Zhou, Zhihao Cui

“…This study aims to enhance the understanding of the state of large-scale bridge structures by accurately analyzing the structural changes of bridges through extensive real-time monitoring data. By conducting a comparative analysis of field load test data and simulation calculations of linear models, this research seeks to provide a precise assessment of structural indices, identify potential risks, and develop appropriate preventive measures. …”
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