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IntroductionThe complex interplay between environmental dynamics, biodiversity loss, and public health necessitates advanced methodologies for quantifying and interpreting their interactions. Respiratory health, highly s...

Abstract B and T lymphocyte attenuator (BTLA) and herpes virus entry mediator (HVEM) are emerging immune checkpoint molecules implicated in immune dysregulation during critical illness. We investigated the prognostic rel...

Abstract Background Both the atherogenic index of plasma (AIP) and obesity have been implicated in cardiovascular disease (CVD) risk. This study aimed to investigate the associations of AIP and AIP-obesity indices (AIP-W...

Abstract Background Depression risk in older adults is a complex mental health issue influenced by multiple factors, including individual vulnerability and environmental exposure. Although many methods have been used to ...

Maintaining B-cell tolerance – the elimination of self-reactive B-cells – is literally a life-long challenge because the B-cell receptor mutates to generate millions of new variants during each immune response in the...

Abstract Building energy consumption is dominated by lighting and heating, ventilation, and air conditioning (HVAC) systems, whose operation is often inefficient due to inadequate control strategies and unreliable occupa...

BackgroundElderly patients with severe acute pancreatitis (SAP) have high mortality, yet reliable early risk stratification tools remain limited. The lactate-to-albumin ratio (LAR) has emerged as a potential prognostic b...

This article presents a comprehensive study of the current state, requirements, and development prospects of the data analyst and data scientist professions in the context of digital economic transformation and dynamic c...

ABSTRACT The formation of stray grains (SGs) remains a critical and pervasive challenge hindering the additive manufacturing (AM) of single crystals for high‐temperature aerospace applications. Here, we elucidate the m...

Abstract Background Effective modeling and parametric studies strengthen analyses of the influence of cotton fiber properties on the yarn properties, which are important for developing a higher-quality product. Machine l...

This research introduces a hybrid modeling framework that combines intricate combustion dynamics with machine learning (ML) to facilitate the decarbonization and retrofitting of traditional diesel engines utilizing Hydro...

We develop a generalized non-Hermitian Hamiltonian formalism for guided resonances in photonic crystal slabs, derived directly from Maxwell’s equations through a systematic guided-mode expansion. By expanding the elect...

Abstract The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced by cerium oxide nanoparticles across different bacterial str...

Abstract Background Landslides are one of the most frequent and damaging disasters in the Nepal Himalaya region, triggered primarily by intense rainfall events. With the increasing impacts of climate change, extreme prec...

"He construct validity in relation to the dimensionality or factor structure of the Beck Hopelessness Scale (BHS) has long been debated in psychometrics. Irrelevant variance due to item wording (method effects) can disto...

The construct validity in relation to the dimensionality or factor structure of the Beck Hopelessness Scale (BHS) has long been debated in psychometrics. Irrelevant variance due to item wording (method effects) can disto...

Abstract Hip fracture is a key global health challenge with an estimated incidence of 26 million new cases by 2050. Although the World Health Organization 's Intrinsic capacity (IC) framework provides a comprehensive app...

Abstract BackgroundCardiovascular magnetic resonance (CMR) is widely used across various cardiac conditions and systematically assesses cardiac anatomical structures and functional dynamics. Machine learning ...

Abstract This study introduces two recently developed bio-inspired metaheuristic algorithms, Artificial Protozoa Optimizer (APO, 2024) and Dung Beetle Optimizer (DBO, 2023), into long short-term memory (LSTM) networks fo...

Abstract The multicomponent thermal fluid (MTF) process is a pivotal technology for enhancing heavy oil recovery. However, its injection often triggers particle migration and deposition within reservoirs, leading to perm...

Media sosial telah menjadi bagian penting dalam kehidupan masyarakat, namun peningkatan penggunaannya sering dikaitkan dengan dampak negatif terhadap kesehatan mental seperti stres, adiksi, FoMo, dan insomnia. Upaya pred...

IntroductionThis study aimed to rigorously evaluate the psychometric properties of the Brief Self-Control Scale (BSCS) for use with early adolescents aged 10–14 years within Turkish culture. Given developmental diffe...

This study proposes a two-level stacking machine learning approach for predicting rainfall erosivity (Rm) in Taiwan, providing a flexible alternative to traditional empirical methods. Conventional models rely on limited ...

Graphical models allow modeling of complex dependencies among components of a random vector. In many applicationsof graphical models, however, for example microbiome data, the data have an excess number of zero values. W...