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Abstract The proposed study is an integrated graph-theoretical and statistical model of predictive modeling and ranking of influenza strain drugs based on temperature-based topological indices. Chemical graphs were used ...

Abstract In this study, the effects of fuel blend ratio and engine speed on the performance and emissions of a spark-ignition (SI) engine fueled with gasoline–isopropanol blends were experimentally investigated, modele...

Abstract Liver fibrosis remains an unmet medical need with limited therapeutic options and high translational failure. Conventional two-dimensional stellate cell cultures and cytokine-induced organoids poorly recapitulat...

Abstract Land-use change strongly regulates soil physical, chemical, and biogeochemical properties, with major implications for soil organic carbon (SOC) storage in the Brazilian Amazon to a depth of 30 cm. This study a...

Abstract This study presents a novel hybrid methodology combining machine learning (ML) with conventional reservoir simulation to optimize waterflooding in the geologically complex Bahariya Formation, Western Desert, Egy...

Abstract Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogene...

Abstract This paper investigates the extent to which dishonest behavior can be predicted using behavioral personality traits and physiological information. An interpretable machine learning approach, SHapley Additive exP...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

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 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 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 Alkaline water electrolysis represents a promising pathway for green hydrogen production, yet comprehensive multi-physics simulation remains computationally prohibitive for practical design optimization. This st...