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This article emphasizes the critical importance of public administration effectiveness during a full-scale war, highlighting the capacity of government to respond efficiently to security challenges, maintain public order...

Machine learning (ML) is becoming increasingly crucial in many fields of engineering but has not yet played out its full potential in bioprocess engineering. While experimentation has been accelerated by increasing level...

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

Selected aspects of methodological developments in socio-economic research are addressed from a conceptual perspective, with outlining the areas of transformations in methodology, and illustrating the feasibilities of it...

Abstract Accurate prediction of compressive strength is important for the efficient design of sustainable concrete incorporating palm oil fuel ash (POFA). This study developed a hybrid artificial neural network model opt...

ABSTRACT Efficient exploration is critical in handling sparse rewards and partial observability in deep reinforcement learning. However, most existing intrinsic reward methods based on novelty rely on single‐step obser...

Abstract Background The research shows the impact of land use forms and population density on the spatial variation of COVID-19 cases and deaths. Selected elements of land use that influence the number of COVID-19 cases ...

Clinical research and real-world observational studies are essential for advancing the diagnosis and treatment of rare diseases, such as inborn errors of immunity/primary immune disorders (IEI/PID). To support efficient ...

Recently, higher education has undergone significant changes due to the use of digital technologies and innovations. The use of innovative platforms, hybrid models and online services cannot overcome the requirements of ...

Learning correlations from data forms the foundation of today's machine learning (ML) and artificial intelligence research. While contemporary methods enable the automatic discovery of complex patterns, they are prone to...

This study provides a quantitative framework for wellbeing outcome prediction through intentional cognitive pattern alteration. We demonstrated 81.67% accurate prediction of wellbeing states, in a three-level classificat...

Abstract Background Bacterial diseases include any illness caused by bacteria. Bacteria are tiny microorganisms that can only be seen with a microscope. Other types of microorganisms include viruses, fungi, and some para...

"Left Bundle Branch Block (LBBB) diagnosis is crucial for patient stratification and the selection of individuals who are likely to respond to Cardiac Resynchronization Therapy (CRT). The pathophysiological distinction b...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

This paper presents a machine learning-based framework for predicting contractor performance in the construction industry by integrating contractor profile information with work package characteristics. The proposed appr...

ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equival...

The February 2026 issue presents 17 research papers within its regular section, covering a wide range of areas including Artificial Intelligence (AI), Machine Learning (ML), Web and Cloud Technologies, Recommender System...

An accurate intraoperative assessment of tissue perfusion in digestive surgery is critical to prevent complications such as anastomotic leakage, an event in which a surgical connection between organs fails to heal proper...

High-quality, openly accessible clinical datasets remain a significant bottleneck in advancing both research and clinical applications within medical artificial intelligence. Case reports, often rich in multimodal clinic...

Relevance. Fundamentally new infrastructure and production solutions implemented in the Arctic macroregion can subsequently be scaled both in the subarctic regions and in the country as a whole, which determines the impo...

Silicon photonics switches are emerging as a key technology for realizing energy-efficient networks, spanning from intra data center to wafer-scale interconnections. This review focuses on recent developments and prospec...

Foodborne pathogen outbreaks impose a substantial and escalating burden on global public health, food systems, and economies, with the World Health Organization estimating over 600 million illness episodes and 420,000 de...

Artificial intelligence (AI), machine learning (ML), and advanced computing techniques are now central to the digital transformation journey, reshaping industries, academia, and society. This special issue of the Journal...

Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...