Aakash Deep^*, Sushil Kumar, Bhagwan Singh Chaudhary

Revue Internationale de Géomatique, Vol.35, pp. 79-100, 2026, DOI:10.32604/rig.2026.074969 - 05 February 2026

Abstract The assessment of groundwater quality is crucial for ensuring its safe and sustainable use for domestic and agricultural purposes. The Kurukshetra district in the Indian state of Haryana relies heavily on groundwater to meet household and agricultural needs. Sustainable groundwater management must be assessed in terms of suitability for domestic and agricultural needs in a region. The current study analyzed pre-monsoon geochemical data from groundwater samples in the study area for 1991, 2000, 2010, and 2020. A Geographic Information System (GIS) was used to create spatial distribution maps for hydrogen ion concentration, total hardness, total… More >

Hasan Kaan Kucukerdem^*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074188 - 30 January 2026

Abstract Root-zone temperature (RZT) strongly affects plant growth, nutrient uptake and tolerance to environmental stress, making its regulation a key challenge in greenhouse cultivation in cold climates. This study aimed to assess the potential of passive techniques, namely black polyethylene mulch and row covers, for modifying RZT dynamics in lettuce (Lactuca sativa L.) production and to evaluate the predictive performance of the eXtreme Gradient Boosting (XGBoost) algorithm. Experiments were conducted in Iğdır, Türkiye, over a 61-day period, with soil temperature continuously monitored at depths of 1–30 cm under mulched and non-mulched conditions, alongside measurements of greenhouse air… More >

Lei Yang, Yang Liu^*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.073529 - 28 January 2026

Abstract Background: This study aims to investigate the underlying mechanisms between parental marital conflict and adolescent short video dependence by constructing a chain mediation model, focusing on the mediating roles of experiential avoidance and emotional disturbance (anxiety, depression, and stress). Methods: Conducted in January 2025, the research recruited 4125 adolescents from multiple Chinese provinces through convenience sampling; after data cleaning, 3957 valid participants (1959 males, 1998 females) were included. Using a cross-sectional design, measures included parental marital conflict, experiential avoidance, anxiety, depression, stress, and short video dependence. Results: Pearson correlation analysis revealed significant positive correlations among all variables.… More >

Yue Cui¹, Ziqing Yang², Hao Gao^1,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.072986 - 28 January 2026

Abstract Background: In the Chinese context, the impact of short video applications on the psychological well-being of older adults is contested. While often examined through a pathological lens of addiction, this perspective may overlook paradoxical, context-dependent positive outcomes. Therefore, the main objective of this study is to challenge the traditional Compensatory Internet Use Theory by proposing and testing a chained mediation model that explores a paradoxical pathway from social support to life satisfaction via problematic social media use. Methods: Data were collected between July and August 2025 via the Credamo online survey platform, yielding 384 valid responses… More >

Myunghoon Roh¹, Katalin Parti², Diego Gomez-Baya^3,*, Cheryl E. Sanders⁴, Elizabeth K. Englander⁵

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.072605 - 28 January 2026

Abstract Background: Bullying is a current social and educational problem with detrimental consequences in adolescence and later life stages. Previous research has explored the risk or protective factor at different socio-ecological levels, but further integration is needed to examine the relationships of family characteristics. This study examines how parenting style and attachment relate to adolescents’ bullying and cyberbullying, and whether parental phubbing mediates these links. Methods: Grounded in social bonding theory, we surveyed a cross-sectional convenience sample of U.S. college students (N = 545; Mean_age = 19.60, SD = 1.41) who retrospectively reported middle/high-school experiences from Massachusetts, Colorado,… More >

Shengkang Zhang¹, Yong Jin^2,*, Soon Poh Yap^1,*, Haoyun Fan¹, Shiyuan Li³, Ahmed El-Shafie⁴, Zainah Ibrahim¹, Amr El-Dieb⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075351 - 29 January 2026

Abstract Concrete-filled steel tubes (CFST) are widely utilized in civil engineering due to their superior load-bearing capacity, ductility, and seismic resistance. However, existing design codes, such as AISC and Eurocode 4, tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core. To address this limitation, this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer (PKO), a nature-inspired algorithm, to enhance the accuracy of shear strength prediction for CFST columns. Additionally, quantile regression is employed to construct prediction intervals for… More >

Guangyu Xu^1,2, Yuxin Liu¹, Bo Yang¹, Siyu Lu^3,*, Chao Liu⁴, Junmin Lyu⁵, Wenfeng Zheng^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074938 - 29 January 2026

Abstract Soft-tissue motion introduces significant challenges in robotic teleoperation, especially in medical scenarios where precise target tracking is critical. Latency across sensing, computation, and actuation chains leads to degraded tracking performance, particularly around high-acceleration segments and trajectory inflection points. This study investigates machine learning-based predictive compensation for latency mitigation in soft-tissue tracking. Three models—autoregressive (AR), long short-term memory (LSTM), and temporal convolutional network (TCN)—were implemented and evaluated on both synthetic and real datasets. By aligning the prediction horizon with the end-to-end system delay, we demonstrate that prediction-based compensation significantly reduces tracking errors. Among the models, TCN More >

Bin Ou^1,2,3,4, Haoquan Chi^1,3, Xu’an Qian^1,3, Shuyan Fu^1,3, Zhirui Miao^1,3, Dingzhu Zhao^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.074757 - 29 January 2026

Abstract Deformation prediction for extra-high arch dams is highly important for ensuring their safe operation. To address the challenges of complex monitoring data, the uneven spatial distribution of deformation, and the construction and optimization of a prediction model for deformation prediction, a multipoint ultrahigh arch dam deformation prediction model, namely, the CEEMDAN-KPCA-GSWOA-KELM, which is based on a clustering partition, is proposed. First, the monitoring data are preprocessed via variational mode decomposition (VMD) and wavelet denoising (WT), which effectively filters out noise and improves the signal-to-noise ratio of the data, providing high-quality input data for subsequent prediction… More > Graphic Abstract

Maddina Dinesh Kumar^1,#, S. U. Mamatha², Khalid Masood³, Nehad Ali Shah^4,#, Se-Jin Yook^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074680 - 29 January 2026

Abstract Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces. The trapezoidal cavity form is compared with its thermal and flow performance, and it is revealed that trapezoidal fins tend to be more efficient, particularly when material optimization is critical. Motivated by the increasing need for sustainable energy management, this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid. The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties; hence, optimising these properties… More >

Menwa Alshammeri^1,2,*, Noshina Tariq³, NZ Jhanji^4,5, Mamoona Humayun⁶, Muhammad Attique Khan⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074627 - 29 January 2026

Abstract Artificial Intelligence (AI) is changing healthcare by helping with diagnosis. However, for doctors to trust AI tools, they need to be both accurate and easy to understand. In this study, we created a new machine learning system for the early detection of Autism Spectrum Disorder (ASD) in children. Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning. For this, we combined several different models, including Random Forest, XGBoost, and Neural Networks, into a single, more powerful framework. We used two different types More >