In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications by Nagarjuna Prakash Dalbanjan, Karuna Korgaonkar, Manjunath P. Eelager, Basavaraj Neelappa Gonal, Arihant Jayawant Kadapure, Suresh B. Arakera, Praveen Kumar S.K.

“…Key computational tools such as molecular modelling, machine learning, computational fluid dynamics, and bioinformatics are thoroughly investigated, with a focus on their contributions to understanding drug loading, toxicity, targeting strategies, and nano-bio interactions. …”
Get full text

A Universal Framework for Skill-Based Cyber-Physical Production Systems by Max Hossfeld, Andreas Wortmann

“…This paper proposes a universal framework for skill-based cyber–physical production systems (CPPS) that formalizes production knowledge into machine-processable formats. Key contributions include a novel conceptual model for skill-based production processes and an automated method to derive production plans from high-level CPPS skills for production planning and execution. …”
Get full text

Rationalization of diagnostic examination periods for metalwork elements of subway escalators by V. N. Dyatlov, D. P. Kononov

“…Petersburg Metro” in the amount of 218 pieces in the period from 2005 to 2019 were used, design documentation, statistical methods and mathematical modeling methods were used.   Results. The use of a mathematical model and the principle of rationalization can significantly reduce the time and, consequently, other costs in determining the corrosion effect.   …”
Get full text

Research Progress on Coarse and Fine Sediment Exchange Near Riverbed by JIN Zhong-wu, LI Shan, LU Jin-you, GUO Xiao-hu

“…This study proposes three innovative future directions: (1) integrating prototype observation data to establish unified theoretical formulas for sediment exchange; (2) developing high-precision observation technologies to overcome the bottleneck in dynamically capturing random sediment collision processes; and (3) combining machine learning with physical models to build predictive systems for sediment state transitions. …”
Get full text

Design and performance analysis of wear-resistant micro-groove cutting tool: Numerical simulation and experimental study by Feilong Du, Fukuan Chen, Tao Zhou, Hongfei Yao, Xuefeng Zhao, Dongwei Zhu, Lin He

“…This investigation establishes a novel computational framework integrating finite element modeling (FEM), machine learning (ML)-based predictive analysis, and multi-objective genetic algorithm (GA) optimization for micro-groove tool design. …”
Get full text

Management concepts of mobile road-builder machinery by Dmitry Yakovlevich Parshin, Denis Gennadyevich Shevchuk

“…For the first time, system and structural status assessment criteria for MRBM are formulated; the control concepts of the mobile objects groups are analyzed; recommendations for selecting the type of control are given. Mathematical models of the traffic flows establishing the dependence of the motion speed on the traffic density, and a mathematical model of the traffic route optimization for the mobile road-building machinery are presented. …”
Get full text

Specificity of the operator’s activity performing the work with the forecasting tools of technologically and chronologically interconnected events in the system of continuous forec... by V. V. Savluchinskij

“…Creation of an automated continuous forecasting system based on tracking information flows requires the development of a number of algorithms and machine programs to build a model of the forecast object based on the obtained identification features, to optimize a branched technologically and chronologically interconnected network of hierarchically coordinated events with an example of the work of the operator performing the work with the prediction tool in the system continuous forecasting and tracking information E flows.…”
Get full text

Artificial Intelligence In Language Education: Exploring Prompting Strategies To Foster Argumentative Writing Skills by Marco Mezzadri, Mariapaola Paita

“… The rapid advancement of Artificial Intelligence (AI), particularly Large Language Models (LLMs), calls for a thorough examination of not only of the opportunities for innovation but also the conditions necessary to foster a productive and informed human-machine relationship in education. …”
Get full text

Landslide spatial prediction using data-driven based statistical and hybrid computational intelligence algorithms by Xia Zhao, Wei Chen, Paraskevas Tsangaratos, Ioanna Ilia, Qingfeng He

“…Optimization of landslide susceptibility model driven by geological environment: a key challenge for disaster reduction in mountainous areas. …”
Get full text

A review on agrowaste based activated carbons for pollutant removal in wastewater systems by Karinate Valentine Okiy, Joseph Nwabanne Tagbo, Walter Peter Echeng

“…The deployment of mathematical and machine learning approaches (ANN and novel GMDH algorithms) in optimization of batch and continuous adsorption processes are also highlighted. …”
Get full text

Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Our method employs Long Short-Term Memory networks and Transformer architectures to model complex temporal dependencies in I/O traces, generating predictive access probability distributions for data blocks. …”
Get full text

From STEM-EDXS data to phase separation and quantification using physics-guided NMF by Adrien Teurtrie, Nathanaël Perraudin, Thomas Holvoet, Hui Chen, Duncan T L Alexander, Guillaume Obozinski, Cécile Hébert

“…The algorithm is based on non-negative matrix factorization (NMF) incorporating a physics-guided factorization model. It optimizes a Poisson likelihood, under additional simplex constraint together with user-chosen sparsity-inducing and smoothing regularizations, and is based on iterative multiplicative updates. …”
Get full text

Data analysis-based framework for the design and assessment of chemical process plants: a case study in amine gas-treating systems by Rahul Gupta, Gladys Navas, Daniela Galatro

“…This work presents a process-integrity assessment framework to chemical process design that combines first principles, heuristics, vendor specifications, standards/codes, data analysis, and machine learning modelling, hypothesized as an efficient route for optimal process design. …”
Get full text

Gaseous hydrocarbons absorption by ILs: insights from artificial intelligence strategy by Reyhaneh Alborz, Mohammad Mahmoudnezhad, Alireza Baghban

“…Furthermore, the GPR models outperformed the widely used COSMO-RS thermodynamic model, demonstrating superior accuracy and computational efficiency. …”
Get full text

Fractal-Based Robotic Trading Strategies Using Detrended Fluctuation Analysis and Fractional Derivatives: A Case Study in the Energy Market by Ekaterina Popovska, Galya Georgieva-Tsaneva

“…Findings from this research show how the combination of fractals with statistical and machine learning models can improve complex trading strategies implementation for the energy markets.…”
Get full text

Advances in Wastewater-Based Epidemiology for Pandemic Surveillance: Methodological Frameworks and Future Perspectives by Weihe Zhu, Daxi Wang, Pengsong Li, Haohao Deng, Ziqing Deng

“…This review critically examines the methodological framework of WBE systems through the following three core components: (1) sampling strategies that address spatial–temporal variability in wastewater systems, (2) comparative performance of different platforms in pathogen detection, and (3) predictive modeling integrating machine learning approaches. We systematically analyze how these components collectively overcome the limitations of conventional surveillance methods through early outbreak detection, asymptomatic case identification, and population-level trend monitoring. …”
Get full text

AI-based prediction of traffic crash severity for improving road safety and transportation efficiency by Ayman Mohamed Mostafa, Bader Aldughayfiq, Mayada Tarek, Alaa S. Alaerjan, Hisham Allahem, Murtada K. Elbashir, Mohamed Ezz, Eslam Hamouda

“…The methodology incorporates feature engineering, clustering techniques such as K-Means and HDBSCAN, with oversampling methods such as RandomOverSampler, SMOTE, Borderline-SMOTE, and ADASYN to address class imbalance, along with Correlation-Based Feature Selection (CFS) and Recursive Feature Elimination (RFE) for optimal feature selection. Among the evaluated classifiers, the Extra Trees (ET Classifier) ensemble model demonstrated superior performance, achieving 96.19% accuracy and an F1-score (macro) of 95.28%, ensuring a well-balanced prediction system. …”
Get full text

Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…By combining these methods with advancements in data processing, such as machine learning and predictive modeling, the potential for broader applications becomes evident. …”
Get full text

Hierarchical control and emulation of a wave energy hyperbaric converter by Isaac R. Machado, Paula B. Garcia‐Rosa, Edson H. Watanabe

Get full text

Deepfakes in Visual Art: Differentiating AI-Generated Art From Human Art Using Convolutional Neural Networks (CNN) by Ngonidzashe Tinago, Silas Formunyuy Verkijika, Kelibone Eva Mamabolo

“…Using the AI-ArtBench dataset, the optimal model achieves a 99% classification accuracy, even when tested on art from a different generative model. …”
Get full text