Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…IntroductionElectrencephalography (EEG)-based brain-computer interfaces (BCIs) have become popular as EEG is accepted as the simplest and non-invasive neuroimaging modality to record the brain's electrical activity. In the current BCI research context, apart from predicting extremity movements, recent BCI studies have been interested in accurately predicting finger movements of the same hand using different pattern recognition methods over EEG data collected based on motor imagery (MI), through which a mental image of the desired action is generated when a person ideally simulates or imagines carrying out a certain motor task. …”
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A Step-by-Step Harmonization Process for Nutritional Epidemiology Purposes: A Methodological Work of the Collaborative PROMED-COG Pooled Cohorts Study by Federica Prinelli, Silvia Conti, Claire T. McEvoy, Caterina Trevisan, Stefania Maggi, Giuseppe Sergi, Marianna Noale

“…In particular, the challenge was the harmonization procedure for dietary habits that required several steps: (i) access to documentation from the original studies, (ii) discussion with the researchers responsible for each dataset; (iii) exploration of each dataset before the final harmonization; (iv) agreement on portion size and food frequency standardization, and food classification for healthy dietary pattern computation; (v) name, definition, and categorization of the harmonized common variable and the original variables, for each study; (vi) development and application of the algorithm to obtain the harmonized variables from the original ones; and (vii) final pooled dataset preparation. …”
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Aryana-bs: context-aware alignment of bisulfite-sequencing reads by Hassan Nikaein, Ali Sharifi-Zarchi, Afsoon Afzal, Saeedeh Ezzati, Farzane Rasti, Hamidreza Chitsaz, Govindarajan Kunde-Ramamoorthy

“…It outperforms existing methods, such as BSMAP, bwa-meth, Bismark, BSBolt, and abismal, particularly in robustness against genomic biases and alignment of longer, higher-error reads, demonstrating suitability for cancer research and cell-free DNA studies. While the Expectation-Maximization (EM) algorithm provides only modest initial improvements, it establishes a valuable framework for future refinement and potential enhancements in sensitive applications.…”
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Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage by Tingli Cheng, Minyou Chen, Yingxiang Wang, Bo Li, Muhammad Arshad Shehzad Hassan, Tao Chen, Ruilin Xu

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A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons by Liya Li, Liya Li, Ying Hu, Ying Hu, Xiaojun Wang, Pei Sun, Tingwei Quan

“…Advances in molecular labeling techniques and optical imaging technologies have spurred extensive research into the patterns of long-range neuronal projections. …”
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SankeyNetwork: A clear and concise visualization tool for bibliometric data by Sher-Wei Lim, Willy Chou, Lifan Chen

“…Slope graphs showed upward trends in four core elements over the past four years.The study concludes that these methods provide clearer insights while reducing visual complexity, and recommends combining performance sheets, Sankey diagrams, and slope graphs in future bibliometric analyses to better detect hotspots and evolving research patterns. • Sankey diagrams to enhance traditional bibliometric visualization methods. • Analyzing 2252 articles from Journal of METHODSX (2020–2024) to highlight author collaborations. • Key insights include the prominence of U.S., and Symbiosis International (India) in author collaborations.…”
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A method for identifying relevant topics of pilot simulator training based on clustering of flight safety reports by Z. R. Zabbarov, A. K. Volkov

“…Natural language processing (NLP) technologies, in one of their applications, provide effective research of patterns and trends in large sets of textual data. …”
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Analysis and Application of Grey-Markov Chain Model in Tax Forecasting by Huidi Zhang, Yimao Chen

“…Grey-Markov chain model formed by the combination of grey forecasting and Markov chain forecasting can not only reveal the general developmental trend of time series data, but also predict their state change patterns. Based on the summary and analysis of previous research works, this paper expounds the current research status and significance of tax forecasting, elaborates the development background, current status, and future challenges of the Grey-Markov chain model, introduces the basic principles of grey forecasting model and Markov chain model, constructs the Grey-Markov chain model, analyzes the model’s residual error and posteriori error tests, conducts the analysis of Grey-Markov chain model, performs grey forecasting model construction and its state division, implements the calculation of transition probability matrix and the determination of tax forecasting value, discusses the application of the Grey-Markov chain model in tax forecasting, and finally carries out a simulation experiment and its result analysis. …”
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The relationship between clinical-anamnestic data and cell-free fetal DNA level assessed by semiconductor sequencing within non-invasive prenatal testing by E. S. Vashukova, O. A. Tarasenko, A. R. Maltseva, A. K. Popova, O. V. Pachuliia, O. N. Bespalova, A. S. Glotov

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A feature fusion network with spatial-temporal-enhanced strategy for the motor imagery of force intensity variation by Ankai Ying, Ankai Ying, Ankai Ying, Jinwang Lv, Jinwang Lv, Jinwang Lv, Junchen Huang, Junchen Huang, Junchen Huang, Tian Wang, Peixin Si, Peixin Si, Jiyu Zhang, Guokun Zuo, Guokun Zuo, Guokun Zuo, Guokun Zuo, Jialin Xu, Jialin Xu, Jialin Xu, Jialin Xu

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Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers by Merouane Boudraa, Akram Bennour, Mouaaz Nahas, Rashiq Rafiq Marie, Mohammed Al-Sarem

“…Leveraging vision transformer models, our methodology effectively learns complex patterns and features from extracted patches, enabling precise identification of writers across historical manuscripts. …”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…Focusing on 15 typical aging communities in Kundulun District, Baotou City, a 17-dimensional dataset encompassing building characteristics, demographic structure, and energy consumption patterns was collected through field surveys. Key influencing factors (e.g., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. …”
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A Deep Learning Model Leveraging Time-Series System Call Data to Detect Malware Attacks in Virtual Machines by A. Alfred Raja Melvin, Jaspher W. Kathrine, Andrew Jeyabose, D. Cenitta

“…The raw VMM system call traces are transformed into novel Time Series System Call patterns and utilized by a deep learning algorithm for training and building the classifier model. …”
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Hierarchical Embedded System Based on FPGA for Classification of Respiratory Diseases by Trong-Thanh Han, Kien Le Trung, Phuong Nguyen Anh, Anh Do Trung

“…Objectives: This research aims to design and develop a hierarchical embedded system that utilizes respiratory sound features for diagnosing COPD and other respiratory disorders. …”
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Efficient curve fitting with penalized B-splines for oceanographic and ecological applications by Kwan-Young Bak, Dong-Young Lee, Ju-Seong Lee, Hee-Jung Jee, R. Jisung Park, Ja-Yong Koo, Jae-Hwan Jhong

“…By leveraging group penalties and the Alternating Direction Method of Multipliers (ADMM) algorithm, the method ensures consistency across response variables and computational efficiency. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…The model enhances reservoir characterization by capturing complex lithological patterns, supporting better zonation and well placement. …”
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Nonlinear energy consumption analysis of shallow-buried bias tunnel stability with improvement of failure mode by Wei Luo, Shirui Liu, Zhi Tao, Haifeng Wang, Xun Gan

“…Abstract Numerous tunnels are often sited in shallow depths and sloping strata due to topographic and geomorphological constraints, however, the evolutionary mechanisms of slip surfaces and instability patterns under asymmetric loading remain unclear. On the basis of the Terzaghi failure hypothesis and the logarithmic spiral failure mode of shallow tunnels in slope areas, combined with the nonlinear failure criterion of soil and the upper bound theorem of limit analysis, this study proposes a new calculation formula for the surrounding rock pressure of shallow tunnels in slope areas considering slope top loads. …”
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A Gamified AI-Driven System for Depression Monitoring and Management by Sanaz Zamani, Adnan Rostami, Minh Nguyen, Roopak Sinha, Samaneh Madanian

“…One of its key strengths is a research-ready design that enables real-time simulation, algorithm testing, and hypothesis exploration without relying on large-scale human trials. …”
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Machine Learning Advancements in Urban Traffic Simulation: A Comprehensive Survey by Harshit Maheshwari, Li Yang, Richard W. Pazzi

“…Traditional simulation models often struggle to capture the intricacies of urban traffic patterns, leading to unrealistic simulations, which negatively affect traffic management and urban planning. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Gene expression in single cell RNA sequencing (scRNA-seq) data was assessed using the AUcell algorithm. In the TCGA [LUAD] dataset, disulfidptosis-related enrichment scores were calculated using ssGSEA, and core gene sets were identified through the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. …”
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