Mohamed ElKashouty^1,*, Mohd Yawar Ali Khan^1,*, Samyah Salem Refadah²

Revue Internationale de Géomatique, Vol.35, pp. 161-177, 2026, DOI:10.32604/rig.2026.079702 - 30 April 2026

Abstract Water scarcity is a significant challenge in arid and semi-arid countries, underscoring the importance of thoroughly studying groundwater resources. Egypt, especially in the Darb El-Arbaein region of the southern Western Desert, faces various water challenges and relies primarily on groundwater from the Nubian Sandstone aquifer. Proper management of this groundwater is essential for addressing these challenges. The study examines the spatial and temporal variations in the hydrogeochemistry of the Nubian sandstone aquifer. Data collected from the aquifer’s monitoring network include key hydrogeochemical parameters, such as total dissolved solid (TDS) and piezometric heads, over different periods.… More >

Xiang Chen^1,2,3,*, Shugang Sun¹, Xingxing Wang³, Yelin Deng²

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2026.077731 - 30 April 2026

Abstract Large-capacity energy storage batteries exhibit thermal behaviors markedly different from conventional cylindrical or pouch cells. Due to their multilayer electrode structure, they show pronounced anisotropy in thermal conductivity between through-thickness and in-plane directions. This results in uneven heat diffusion and internal–external temperature gradients that surface sensors cannot capture. Moreover, heat generation varies with temperature and state of charge (SOC) owing to changes in internal resistance. To address these challenges, an equivalent circuit and anisotropic electrothermal coupled model were established, with heat generation and transfer processes analytically derived. Parameter identification was performed through capacity calibration, specific More >

Aoyu Zheng¹, Ye Wang^1,2,*, Huanhuan Li¹, Yuanfeng Lu^1,3,*

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2026.075766 - 30 April 2026

Abstract Subway operations generate substantial heat, and inadequate dissipation can progressively degrade tunnel thermal conditions. The thermal distribution within the surrounding rock is critical for calculating the load on subway environmental control systems. However, the heat transfer patterns in the surrounding rock for intersecting tunnels remain poorly understood. Therefore, this study employs COMSOL software to numerically analyze the impact of intersecting line layouts on the temperature field distribution within the surrounding rock. Results indicate that when tunnels intersect, heat accumulates in the surrounding rock near the intersection. Compared to the single-tunnel structure, intersecting tunnels exhibit higher… More >

Dongmei Lian^#, Zhou Li^#, Bizhen Lin, Shaoping Zhang, Susu Yuan, Yunfa Yao, Yudong Ju, Zhengfeng Lai^*

Phyton-International Journal of Experimental Botany, Vol.95, No.4, 2026, DOI:10.32604/phyton.2026.078378 - 28 April 2026

Abstract Pepper (Capsicum annuum L.) is highly susceptible to chilling stress, which severely constrains its growth and productivity. Although the eco-friendly biostimulant γ-polyglutamic acid (γ-PGA) has shown promise in enhancing plant tolerance to abiotic stresses, its specific role and underlying mechanisms in alleviating chilling injury in pepper remain poorly understood. This study systematically investigated the physiological and molecular mechanisms by which foliar application of 100 mg·L⁻¹ γ-PGA enhances chilling tolerance in pepper seedlings. Our results demonstrated that γ-PGA pretreatment significantly mitigated chilling-induced growth inhibition and promoted root development, evidenced by a 110.8% increase in the number of root… More >

Nishu Gupta^1,*, Manuel J. C. S. Reis²

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.082568 - 27 April 2026

Abstract This article has no abstract. More >

Rafael de Oliveira Silva^1,2,*, Roberto Outa³, Fábio Roberto Chavarette⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080607 - 27 April 2026

Abstract The reliable detection of cracks in engineering materials remains a fundamental challenge in nondestructive testing, especially in applications that require automated inspection, reduced instrumentation costs, and robustness under noisy operational conditions. Traditional nondestructive evaluation techniques often rely on complex sensing setups or expert-dependent interpretation, which can limit scalability and real-time applicability. In this context, this study addresses the scientific problem of achieving reliable and automated crack detection using simplified sensing architectures combined with intelligent data-driven analysis. This work proposes an intelligent signal classification framework for crack detection in polymeric materials based on machine learning and… More >

Tianzhe Jiao, Yuming Chen, Xiaoyue Feng, Chaopeng Guo, Jie Song^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080595 - 27 April 2026

Abstract Knowledge distillation bridges the performance gap between camera-based and LiDAR-based 3D detectors by leveraging the precise geometric information from LiDAR. However, cross-modal knowledge transfer remains challenging due to the inherent modality heterogeneity between LiDAR and camera data, which often leads to instability during training. In this work, we find that these instabilities are closely related to distribution mismatch in the cross-modal feature space and noisy teacher signals. To address this issue, we propose a novel distribution-aware cross-modal distillation framework, named DA-T3D. Specifically, we first explicitly model the LiDAR teacher’s Bird’s-Eye-View (BEV) feature distribution and use… More >

Maram Fahaad Almufareh^1,*, Mamoona Humayun², Sadia Din^3,*, Khalid Haseeb⁴, Amr Munshi⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080287 - 27 April 2026

Abstract The real-time systems perform key functionalities in various fields to automate the communication and response in critical events. The Internet of Things (IoT), integrated with numerous physical objects, gathers environmental data, processes it at the edge, and provides intelligent decisions while routing health records to processing units. However, the dynamic and resource-constrained nature of IoT-based healthcare environments introduces significant challenges related to latency, transmission costs, and the reliable interaction of devices amid uncertain activities. In this work, we propose a framework for a consistent and trustworthy system that uses a weighted trust aggregation model to More >

Mustaqeem Khan¹, Ufaq Khan², Mamoun Awad¹, Nazar Zaki¹, Guiyoung Son³, Soonil Kwon^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079697 - 27 April 2026

Abstract Knowledge distillation has shown impressive results in different fields, including detection, recognition, and generation. These models are excellent at tasks such as speech recognition, but they need to be shrunk down using adaptive knowledge distillation (AKD). The use of AKD can improve human-computer interactions and streamline data collection in the field of Speech Emotion Recognition (SER). This study presents a high-level approach that employs a novel adaptive knowledge distillation (AKD) with spatio-temporal transformers to acquire advanced semantic features from the input signal. This method uses an instance-by-instance correlation between the teacher and a student to determine the More >

Muhammad Waqar¹, Zeshan Aslam Khan^1,*, Arthur Chang^2,*, Zhishan Guo³, Chun-Liang Lai⁴, Chuan-Yu Chang⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.078892 - 27 April 2026

Abstract Lung cancer (LC) is among the dangerous cancers spreading progressively, and a timely LC diagnosis becomes a dire need of the time. Various imaging-based studies have been conducted for accurate LC examination through computed tomography (CT), X-ray, and histopathology. Worldwide, the proportion of LC-affected patients in hospitals is growing, thereby increasing imaging data for fast processing and early examination. To facilitate histopathological imaging-based automated and timely decision making for accurate LC prediction, a Context Aware Fusion Network (CAFNet) for holistic feature learning and spatially localized feature learning is proposed in this study for the efficient… More >