Design of mTCN framework for disaster prediction a fusion of massive machine type communications and temporal convolutional networks by M. Umadevi, J. Arun Kumar, S. Vishnu Priyan, C. Vivek

“…Abstract Natural disasters such as floods, tsunamis, and earthquakes significantly impact lives and infrastructure, highlighting the urgent need for accurate and real-time prediction systems. Current methods often suffer from limitations in scalability, privacy, and real-time data integration, particularly in large-scale disaster scenarios. …”
Get full text

Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

“…After the backbone network processes the input image through convolution, the data pass through the enhanced feature pyramid module, where it is iteratively processed by multiple weighted branches. Unlike conventional methods, the multi-scale feature extraction module that we designed not only improves the extraction of high-level semantic features but also optimizes the distribution of low-level shape feature weights through the synergistic interactions of the branches, all while preserving the inherent properties of the image. …”
Get full text

Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…By generating computational data, predicting the efficacy of pharmaceuticals, and assessing their safety, AI and quantum computing can accelerate and optimize the process of identifying potential drug candidates. …”
Get full text

EADRL: Efficiency-aware adaptive deep reinforcement learning for dynamic task scheduling in edge-cloud environments by J. Anand, B. Karthikeyan

“…The learning rate adapts over time to reward trends, improving convergence while maintaining stability under varying load conditions. …”
Get full text

Use of <i>Melilotus officinalis</i> extracts with antioxidant potential in a protective coating for tomatoes by M. A. Mulyukin, D. A. Baranenko, Y. Yu. Petrova, O. S. Sutormin

“…The goal of the research was to evaluate the effect of a protective coating for tomatoes enriched with Melilotus officinalis extracts with pronounced antioxidant activity. The Methods. The extraction conditions were optimized: the dried plant material was ground to a particle size of 0.2-0.5 mm, the raw material to extractant ratio was 1:100, and the extraction time was 5 days. …”
Get full text

Adaptation of the Academic Disciplines “General Psychology” and “Psychology Workshop” for Students with Disabilities: A Case Study of the “Ukraine” University by I. V. Kushchenko, O. L. Matsiuk

“…Students expressed a need for more diverse learning materials (audio, video), an increased number of consultations, and tutoring support. Instructors, while using various adapted teaching methods, emphasized the lack of specialized resources and insufficient time for individual student support. …”
Get full text

Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS by Kaiyue Xia MM, Shupeng Chen MD, Yingjian Zeng MD, Nana Tang MD, Meiling Zhang MD

“…Introduction Drug-induced myelosuppression (DIM) is a serious side effect of several medications, particularly chemotherapy, immunosuppressants, and targeted therapies, which can lead to infections, anemia, and bleeding. While these drugs are effective, their adverse effects can disrupt treatment plans and reduce quality of life. …”
Get full text

Forecasting outbound student mobility: A machine learning approach. by Stephanie Yang, Hsueh-Chih Chen, Wen-Ching Chen, Cheng-Hong Yang

“…<h4>Methods</h4>To analyze outbound student mobility in Taiwan using time series methods, this study aims to propose a hybrid approach FSDESVR which combines feature selection (FS) and support vector regression (SVR) with differential evolution (DE). …”
Get full text

Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction by L. Raymond Guo, Jifu Tan, M. Courtney Hughes

“…IntroductionPublic health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. …”
Get full text

Regional differences and distributional dynamic evolution of science and technology innovation driven green development efficiency in Chinese agriculture by Lingling Wang, Min Li, Panpan Zhang

“…The results show a clear regional imbalance, with the eastern region showing higher efficiency due to strong investment in innovation and policy coordination effects, while the central and western regions are lagging behind due to fragmented resource allocation and weak institutional support. …”
Get full text

Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models. by Al Mahmud Siam, Pankaj Bhowmik, Md Palash Uddin

“…Our framework integrates three complementary feature selection techniques: Pearson correlation, information gain (IG), and random forest importance (RFI), each optimized for the dataset's characteristics. Pearson Correlation eliminates redundancy by removing highly correlated features, while IG and RFI evaluate the relevance of the remaining features. …”
Get full text

Capacitive deionisation for water desalination review: experimental and simulation by Rokhsareh Akbarzadeh, Mathias Ernst, Robert Meißner, Bodo Fiedler

“…The review also explores simulation methods, including reactor modeling, computational fluid dynamics, molecular dynamics, and numerical approaches, and machine learning highlighting their synergy with experiments in optimizing CDI performance and guiding scale-up. …”
Get full text

Elevated Serum Fibroblast Growth Factor 21 and Associated Metabolic Dysregulation in Polycystic Ovary Syndrome: A Case–Control Study by Tayf H Raheem, Murtadha Jawad Mohammed

“…Standard enzymatic colorimetric assays were used for lipid measurements, while liver enzymes were determined via spectrophotometric methods. …”
Get full text

On the Combination of Harmonics and Polynoms in Econometric Modeling of RUB/AZN Exchange Rate by L. M. Mamedova

“…The official statistics of the State Statistics Committee of Azerbaijan were used; classical methods of mathematical analysis and economic analysis; methods of econometrics, harmonic (Fourier) analysis, statistical spectral analysis, “Fourier analysis” of the MS Excel add-in, tools of the Eviews 8 application package with the standard deviation and average approximation error being taken into account, the necessary statistical procedures required for identifying and estimating the parameters of the model and checking its adequacy and accuracy.Results. …”
Get full text

Enhancing the Distinguishability of Minor Fluctuations in Time Series Classification Using Graph Representation: The MFSI-TSC Framework by He Nai, Chunlei Zhang, Xianjun Hu

“…Existing time series classification (TSC) methods struggle to achieve high classification accuracy when these minor fluctuations serve as the primary distinguishing feature. …”
Get full text

Innovative machine learning approaches for complexity in economic forecasting and SME growth: A comprehensive review by Mustafa I. Al-Karkhi, Grzegorz Rza̧dkowski

“…Specifically, the findings highlight that the integration of ensemble methods and deep learning models has achieved significant improvements in prediction accuracy, while interpretability tools such as SHAP and LIME enhance transparency and user trust. …”
Get full text

Fungicidal protection of sunflower against the main leaf diseases by S. Retman, N. Bazykina

“…To determine the technical efficiency of the novel fungicides against the diseases of leaves sunflower and to establish the optimal terms of fungicidal treatments for the zone of the Right Bank Forest-steppe of Ukraine. …”
Get full text

Development and application of an early prediction model for risk of bloodstream infection based on real-world study by Xiefei Hu, Shenshen Zhi, Yang Li, Yuming Cheng, Haiping Fan, Haorong Li, Zihao Meng, Jiaxin Xie, Shu Tang, Wei Li

“…However, existing diagnostic methods are flawed by low specificity, long detection times and high demands on testing platforms. …”
Get full text

Aplikasi untuk Mencari Kelayakan Siswa Penerima Bantuan Pendidikan dengan Metode Simple Additive Weighting (Studi Kasus : SMK NU Ma'arif Kudus) by Syaifuddin Syaifuddin, Solikhin Solikhin, Eko Riyanto

“…The contribution to SMK NU Ma’arif 2 Kudus in this study was the making of an application to find out the eligibility of student beneficiaries using the SAW method. This can assist the committee in implementing the education aid fund distribution program in an optimal, transparent, on target and equitable manner and can be used as decision support for stakeholders. …”
Get full text

Epidemiology, pathogenesis and management of atrial fibrillation in athletes - a narrative review by Jan Zabierowski, Anna Tomasiewicz, Maciej Pachana, Piotr Kukuła, Marcin Piersiak, Hubert Sawczuk, Julia Marschollek, Maciej Ziomek

“… Background:Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting millions worldwide. While moderate physical activity is known to reduce AF risk, endurance athletes, particularly males, appear to have a higher prevalence of AF. …”
Get full text