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The use of evolutionary and swarm intelligence algorithms, has become a very popular option to solve complex real-world optimization problems. However, in their original versions, these algorithms lack a mechanism to han...

The rapid expansion of conversational artificial intelligence (AI) usage in healthcare, nutrition, and digital health education has made prompting a routine part of professional and personal practice. However, each AI pr...

The development goal of artificial intelligence is to enable machines to think and act like humans, solving complex problems, and more importantly, interacting effectively in a complex, dynamic, and uncertain physical wo...

The rapid expansions of artificial intelligence (AI), big data (BD), and information and communication technologies (ICT) are driving substantial growth in electricity, water, and material demands, with data centers proj...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Computational modeling of protein-protein interactions (PPIs) is a high priority because it is essential for understanding nearly all cellular functions and for addressing the limitations of time-consuming experimental m...

Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of va...

Abstract This study examines the influence of divisor selection on the efficacy of advanced analytical spectrophotometric methods that integrate artificial intelligence (AI), green-chemistry principles, and white-analyti...

Sepsis remains one of the most complex and lethal syndromes in pediatric critical care, driven by dysregulated and heterogeneous host responses to infection. Despite decades of biomarker research, few biomarkers have bee...

Generative artificial intelligence systems increasingly enable novice users to create complex websites with minimal technical expertise; however, these users often struggle to evaluate the visual quality of AI-generated ...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

Artificial intelligence (AI) models developed for Global Navigation Satellite System Reflectometry (GNSS-R) observations have demonstrated competitive performance in estimating geophysical parameters, especially ocean su...

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...

In recent years， quantitative microbial risk assessment （QMRA） for food safety has developed rapidly both domestically and internationally. QMRA integrates multidisciplinary theoretical knowledge and technical meth...

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...

Generative Artificial Intelligence (GAI) is changing what can be done with Recommender Systems (RS) in e-commerce by allowing much more interactive, situationally aware, and highly tailored experiences for users. The pur...

Lysosomal dysfunction is a core pathological driver of neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS). Transcription factor EB (TFEB) serves as a master regulator of lysosomal biogenesis, and its ...

Next generation risk assessment (NGRA) demands a fundamental transformation in how toxicological test methods are validated. Traditional validation approaches, designed for animal tests and mainly for simple in vitro met...

Forest ecosystems play a fundamental role in sustaining global water cycles and ecological security, and accurate modeling of their eco-hydrological processes is essential for forest management, watershed regulation, and...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have th...

Biotic and abiotic stresses reduce crop yields, yet existing image‑based diagnostic models are often crop‑specific, computationally intensive, and poorly interpretable. This study present: (i) a multi-crop diagnostic...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...