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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 ...

This study develops five predictive models based on regression trees to estimate the Effective Electrical Conductivity (CEE) of irrigation water in the Green Belt of Mendoza, Argentina. Using 468 water samples and physic...

The propagation dynamics of water hammer pressure waves in gas-liquid pipelines are predominantly influenced by gas-phase compressibility. To investigate the effects of the gas-liquid ratio and flow regime on the velocit...

Abstract Industrialization and urbanization exacerbate global environmental health challenges, with pollutants from industrial and vehicular emissions (e.g., PAHs, NOx, PM2.5) posing significant risks. Growing evidence l...

BackgroundDespite growing evidence supporting deep brain stimulation (DBS) for treatment- resistant depression (TRD), how stimulation delivered across hemispheres or across multiple targets interact to shape large-scale ...

Background: Latent tuberculosis infection (LTBI) remains a critical reservoir for the global tuberculosis (TB) epidemic, particularly in South Asia, where high population density and socioeconomic disparities amplify its...

Contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired kidney injury, is associated with poor clinical outcomes, highlighting the need for accurate prediction. In this study, we u...

To analyze the effects of temperature, concentration, and reaction time on the denitration rate of double based spherical gun propellant (DBSGP) and to investigate the denitration reaction-diffusion coupling process for ...

Predictive modeling of natural sediment-laden flows requires rheometric protocols that are both reproducible and time-aware of sediment dynamics. This study establishes a standard measurement protocol for homogeneous sed...

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...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

Global food supply chains continue to expand in scale and complexity, heightening risks of fraud, mislabeling, and cross-contamination across certification systems. These vulnerabilities are particularly consequential fo...

Low birth weight (LBW), defined as birth weight below 2,500 grams, remains a significant public health concern in India, affecting approximately 17.29% of infants according to NFHS-5 data. This study aimed to develop and...

Introduction Conducting surveys on domestic violence across diverse countries, particularly in lower-middle-income nations like Nepal, poses significant challenges in understanding and addressing the multifaceted dynamic...

BackgroundClimate change is increasingly recognized as a critical driver affecting the transmission and distribution of parasitic diseases. However, a comprehensive synthesis of the global research landscape in this inte...

Colorimetric assays offer a low-cost, accessible means of diagnostic testing but often suffer from subjective interpretation and variability caused by inconsistent imaging conditions. To address these challenges, we pres...

Abstract Artificial intelligence (AI) is emerging as a transformative tool for stormwater management with the potential to enhance resilience, efficiency, and equity across urban water systems. This paper examines the op...

Land degradation, driven primarily by deforestation and urbanization, presents a growing threat to ecological integrity and sustainable development, particularly in rapidly urbanizing regions. This study analyzes histori...

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 Background Terpenes and phenolic compounds are multifunctional plant metabolites that contribute to defense, signaling, and ecological interactions, while supporting industrial applications. Here, we implemented...

Prediction of building occupancy is a very important element of structural health monitoring (SHM), smart building systems, and energy management. In this study, a number of visualization tools are used to analyze the pe...

Abstract We developed SPARFlow, an open-source KNIME workflow for structure–activity or structure–property relationship (SAR/SPR) analyses. The workflow integrates data preprocessing, chemical structure curation, sim...

In recent years, fuzzy soft topology has emerged as a powerful approach that contributes significantly to advancing practical applications in uncertain environments, especially in information systems design, predictive m...