Yida Shen¹, Bin Dong², Quan Ma¹, Chao Dang^1,*, Congjian Li^2,*, Guojian Ren³, Shaozhan Wang^1,2, Xiaozhe Sun¹, Yong Ding⁴

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2025.077096 - 30 April 2026

Abstract This article explores the application of Physics-Informed Neural Networks (PINNs) in solving supersonic flow problems within a Laval nozzle, proposing innovative methods by integrating physical constraints and neural network optimization techniques. The main innovations of this study include the construction of a novel neural network architecture with shortcut connections to enhance the prediction of overall flow trends and local fluctuations, thereby improving convergence speed, reducing computational costs, and increasing the accuracy of flow field reconstruction. Additionally, this study designs a PINNs framework that incorporates specific physical knowledge (SPK) to improve model stability, generalization, and accuracy, More >

Wei Dong¹, Baoqi Guo², Weiwei Zhao², Hui Jian², Zhenzong He^2,*

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2025.075848 - 30 April 2026

Abstract This study explores the design of a tapered cathode flow channel in a proton exchange membrane fuel cell (PEMFC), leveraging artificial intelligence and multi-objective optimization techniques to attain an optimal configuration. First, the influence of the channel height ratio and mass flow rate on PEMFC performance was systematically examined. The results reveal that decreasing the height ratio and increasing the mass flow rate lead to reduction in the standard deviation of current density, accompanied by a monotonic rise in pressure drop. The average current density initially rises before exhibiting a slight decline. Subsequently, a surrogate… 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 >

Savindi Thathsarani¹, Ashan Lakshitha², Pasindu Pramodya², Praveen Perera², Rasanjali Samarakoon^1,*, Shagufta Henna³, Upaka Rathnayake^4,*

Phyton-International Journal of Experimental Botany, Vol.95, No.4, 2026, DOI:10.32604/phyton.2026.078657 - 28 April 2026

Abstract Accurately determining the optimal post-harvest storage period is still a major challenge in mango processing, especially for the Tom EJC (TEJC) variety, due to reliance on subjective visual evaluations, leading to inconsistent product quality and increased post-harvest losses. This study presents an artificial intelligence-based framework combining computer vision and physicochemical analysis to objectively predict the optimal post-harvest storage period of TEJC mango before processing. TEJC mangoes of grade one were stored for eight days at 24–28°C temperature and 66.4–80% relative humidity. Daily measurements of pH, Total Soluble Solids (TSS), firmness, and peel color parameters (L*,… More > Graphic Abstract

Cuifang Chang, Hua Fang, Xinfang Chen, Zhongfeng Yao, Yali Zhu, Caicai Ma, Qi Wang, Weibiao Liao^*

Phyton-International Journal of Experimental Botany, Vol.95, No.4, 2026, DOI:10.32604/phyton.2026.077290 - 28 April 2026

Abstract The cinnamoyl-CoA reductase (CCR) gene family plays a pivotal role in lignin biosynthesis and plant stress adaptation by catalyzing the first committed step in the monolignol-specific branch of the phenylpropanoid pathway. However, a comprehensive and systematic analysis of CCRs in the economically important Rosa genus remains lacking. Here, we conducted a systematic genome-wide investigation of CCR genes in a diploid species, Rosa chinensis, and a tetraploid cultivar, Rosa × hybrida. We identified 15 and 36 non-redundant CCR genes in R. chinensis and R. × hybrida, respectively. From these, we selected 14 high-confidence orthologs of RcCCR in the R. × hybrida genome as a core… More >

Hanna Ahrnberg^1,*, Kaija Appelqvist-Schmidlechner², Pekka Mustonen¹, Sari Fröjd³, Katja Aktan-Collan¹

International Journal of Mental Health Promotion, Vol.28, No.4, 2026, DOI:10.32604/ijmhp.2026.077244 - 28 April 2026

Abstract Objectives: Positive Youth Development is an evidence-based, holistic approach that underlines adolescents’ strengths, competence, and interests instead of deficits, thus promoting psychosocial well-being in adolescents. This study aims to explore adolescents’ perceived impacts of the Finnish service-learning program “Gutsy Go”, which is based on a Positive Youth Development approach. Methods: The program educates 8th-grade comprehensive school students to perform good deeds in their communities and enhances adolescents’ psychosocial well-being. Focus group interviews were conducted two to three weeks after the program week with 61 program participants. The data was analyzed using qualitative content analysis. Results: Four broad More >

Xixi Chu¹, Run Guo¹, Yujin Wang^2,*, Zhong Li³

Journal of Psychology in Africa, Vol.36, No.2, pp. 153-159, 2026, DOI:10.32604/jpa.2026.072738 - 29 April 2026

Abstract Bootleg innovation serves as a vital supplement to routine innovation, yet strengths-based leadership mechanisms driving such informal behavior remain underexplored. This study examined the mediation mechanism of growth need strength, as well as the boundary condition set by work centrality, in the association between strengths-based leadership and bootleg innovation. We employed a time-lagged design across two waves to gather data from 375 employees within the technology sector (Wave 1, n = 583; Wave 2, n = 425). The final sample consisted of 47.5% males, with 67.7% aged between 30 and 40. Hierarchical regression results found More >

Jingjie He^1,*, Yuhui Jing^2,3, Xiaopeng Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080458 - 27 April 2026

Abstract In high-heat-flux environments, traditional cooling channels often fail to satisfy concurrent requirements for high heat transfer efficiency, temperature uniformity, and minimal pumping power. This study proposes an engineering-oriented topology optimization method for fluid-solid conjugate heat transfer to address the conflict between thermal performance and flow resistance under non-uniform heat sources. We introduce a pseudo-three-dimensional conjugate heat transfer model governed by Darcy’s law. This formulation retains three-dimensional effects, such as sidewall conduction and non-uniform surface heat flux. Moreover, the governing equations are reduced to two dimensions, thereby significantly enhancing computational efficiency. To resolve the discrepancy between More >

Anh-Vu Nguyen¹, Tien-Chuong Vu¹, Ba-Duan Nguyen¹, Hoang-Anh Pham^1,*, Ravipudi Venkata Rao²

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080453 - 27 April 2026

Abstract Structural optimization is essential for finding optimal designs in practical engineering tasks. Metaheuristic algorithms have been widely applied in structural optimization problems in recent years, especially when dealing with discrete design variables, the nonlinearity of the objective function and constraints. Unlike gradient-based algorithms, which rely on the slope variation of a function, metaheuristic algorithms do not require derivative calculations and thus avoid being trapped in local optimum. However, metaheuristic algorithms often require numerous function evaluations, involving costly structural analyses, thus increasing computational load considerably. This paper investigates a method to reduce computational load, specifically by… More >

An Xu¹, Zhixiong Liu¹, Hua Rong², Liang Han¹, Wei Shi³, Jun Huang³, Jiyang Fu^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079375 - 27 April 2026

Abstract In structural optimization, data-driven surrogate models are often explored as alternatives to finite element analysis to reduce computational cost. However, conventional neural networks usually fail to capture key structural characteristics and are limited to predicting global responses (e.g., top displacement), but usually fail to achieve accurate internal force predictions with conventional training data volumes. As a result, most existing studies involving surrogate models did not concern internal force constraints. To address this issue, this study proposes a structural optimization framework based on a pre-trained Physics-Informed Neural Network (PINN) surrogate model. By embedding static equilibrium equation… More >