Ayoube Baalla^*, Mourad Najjaoui, Thami Ait-Taleb, Hassan Chaib

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.7, 2026, DOI:10.32604/fdmp.2026.083469 - 31 July 2026

Abstract The complex interplay of heat transfer mechanisms, namely conduction, natural convection, and radiation, within hollow block roofs exposed to solar irradiation gives rise to an inherently nonlinear thermal exchange problem. A key yet insufficiently explored question is the extent to which this nonlinearity governs the macroscopic thermal behavior of roofing systems. In this study, a computational investigation is conducted on two roof configurations incorporating five hollow block geometries representative of common construction practices in hot climatic regions. The objective is to identify the optimal design capable of minimizing heat losses and thereby enhancing the overall… More >

Xuewen Cao^*, Zhe Chen, Gaoya Ding, Wei You

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.7, 2026, DOI:10.32604/fdmp.2026.080209 - 31 July 2026

Abstract A two-dimensional Computational Fluid Dynamics (CFD) model, grounded in classical nucleation theory, is developed to investigate CO₂ frosting and the associated heat transfer under cryogenic conditions. The model integrates gas–solid phase-change kinetics with multiphysics transport equations to capture the coupled phenomena governing frost formation. The Peng–Robinson equation of state is employed to predict CO₂ frost points in binary mixtures, with model predictions validated against experimental data, yielding errors in frost thickness and thermal conductivity below 15%. The results demonstrate that decreasing the cryogenic wall temperature from 160 K to 150 K increases the average frost thickness… More >

Sonia Mansouri^1,*, Yassmine Abidi^1,2, Leila Riahi³, Ali Ltifi²

Phyton-International Journal of Experimental Botany, Vol.95, No.7, 2026, DOI:10.32604/phyton.2026.083697 - 30 July 2026

Abstract Doubled haploid technology is an important tool for accelerating barley breeding by enabling the rapid development of fully homozygous lines. However, the efficiency of androgenesis in barley remains highly genotype-dependent and is strongly influenced by pretreatment conditions, particularly cold exposure. Despite advances in barley anther culture protocols, the optimal duration of cold pretreatment to enhance androgenic response and green plant regeneration remains poorly understood for many breeding materials. This study therefore aimed to examine the effects of genotype and cold pretreatment duration on androgen induction and regeneration efficiency in spring barley lines. Fifteen barley lines,… More >

Sachin Tom, Eva Gutheil^*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.084886 - 27 July 2026

Abstract A single droplet heating, vaporization, and detailed combustion model is developed for pure p-xylene (p-C₈H₁₀) in hot air. p-C₈H₁₀ is a combustible solvent in precursor solutions, for instance, with titanium tetraisopropoxide (TTIP) for the production of TiO2 nanoparticles. In the present one-dimensional mathematical model, a spherically symmetric p-xylene droplet in hot air is considered, resolving both the droplet (liquid phase) and the ambience (gas phase). The calculation of the vaporization rate includes the Stefan velocity at the droplet surface. In the gas phase, a detailed chemical reaction scheme is used. Elementary reactions are… More >

José González-Cabrero^1,2, Carmelo Gómez^1,2, Manuel Paredes³, Francisco Cavas^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.082643 - 27 July 2026

Abstract The development of accurate digital twin models of the human cornea is a key factor for planning and monitoring eye treatments and clinical supervision. Corneal tissue can be simulated with the implementation of hyperelastic models based on strain energy density functions. However, the number of hyperelastic models and the parameters’ variation that define these models hinder comparison across different studies. Furthermore, parameter calculations based on a single test are an ill-posed problem. In this research, a novel sequential methodology based on collagen fibril crimping strain threshold has been implemented to calculate the corneal material’s parameters. More > Graphic Abstract

Tianqi Wang, Yang Li, Zhisong Pan^*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083923 - 23 July 2026

Abstract Existing knowledge distillation methods for object detection struggle to bridge the teacher-student capacity gap and overlook the inherent differences between classification and regression subtasks. To address these issues, we propose a Bridging Multi-dimensional Gaps Knowledge Distillation (BMGKD) method, which comprises two core modules: a feature difference distillation module and a response difference distillation module. The feature difference distillation module achieves global feature structural alignment via improved centered kernel alignment and performs local key feature alignment using joint spatial and channel-wise cosine similarity masks. The response difference distillation module constructs a dynamic classification mask and a… More >

Nada Alzaben¹, Muhammad I. Khan², Hafeez Ur Rehman Siddiqui³, Abeer Rashad Mirdad⁴, Saeed Ali Bahaj^5,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083649 - 23 July 2026

Abstract Industrial predictive maintenance is a critical challenge in modern manufacturing, where unexpected equipment failures cause significant economic losses through downtime, repair costs, and disrupted production. Conventional maintenance approaches, whether reactive or schedule-based, are becoming inadequate to manage the high-dimensional sensor information of the IoT-enabled machineries. The paper presents a novel hybrid neuro-symbolic digital twin that builds upon Remaining Useful Life (RUL) estimation by combining temporal transformers, physics-informed constraints, and counterfactual reasoning. The model integrates complementary approaches into a single and interpretable predictive system. A temporal transformer backbone is a model of long-range dependencies in multivariate… More >

Xiangyi Le¹, Deyu Lin^1,2,*, Yufei Zhao², Wang Miao³, Yong Liang Guan²

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083306 - 23 July 2026

Abstract The emergence of Unmanned Aerial Vehicle (UAV)-enabled Wireless Energy Transfer (WET) and Simultaneous Wireless Information and Power Transfer (SWIPT) technology provide a promising solution to overcome the energy sustainability limitations of traditional harvesting-reliant sensor networks. However, in large-scale Battery-free SWIPT-enabled Sensor Networks (BSSN) characterized by sparse node distribution and heterogeneous energy consumption and harvesting rates, employing a single UAV for energy replenishment often suffers from insufficient operation continuity and low charging efficiency. To overcome these challenges, a Multi-UAV Collaborative Energy Charging for BSSN Based on Multi-Agent Deep Deterministic Policy Gradient (MCEC-MADDPG) is proposed in this… More >

Byeongjeong Kim, Jeonghyun Park, Joonho Yang, Hwanhee Lee^*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.082460 - 23 July 2026

Abstract Long-context question answering over narrative documents remains challenging because many questions require reconstructing event sequences while preserving local contextual flow under limited context budgets. Existing retrieval-augmented generation (RAG) methods typically retrieve document snippets independently, which can fragment narratives and harm temporal dependencies. We propose ChronoRAG, a retrieval framework for narrative question answering that first converts sequential document chunks into concise relation descriptions and then retrieves relevant units together with their adjacent chronological context. This design preserves retrieval precision while providing the generator with coherent local narrative structure. Experiments on NarrativeQA and GutenQA show that ChronoRAG More >

Qiuhao Xu^1,2, Chen Wang^1,3,*, Xi Wen¹, Lurong Jiang¹, Wenying Zheng^4,*, Zhengkui Chen¹

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.082310 - 23 July 2026

Abstract The convergence of Generative Artificial Intelligence and biometric recognition is reshaping modern healthcare. It enables more adaptive and intelligent human–machine interactions. Epilepsy, a common neurological disorder affecting millions worldwide, relies heavily on electroencephalography (EEG) signals for diagnosis and monitoring. Wearable consumer devices with EEG sensors support continuous physiological data collection. However, transmitting sensitive biometric data to centralized servers introduces serious privacy and security risks. Federated learning (FL) provides a distributed training framework that keeps raw data on local devices. Despite this advantage, existing FL methods remain vulnerable to gradient leakage attacks, where adversaries may infer More >