Jonghwa Lee¹, Youngho Kim^2,*

International Journal of Mental Health Promotion, Vol.28, No.8, 2026, DOI:10.32604/ijmhp.2026.081241 - 31 August 2026

Abstract Objectives: The present study aimed to investigate how environmental context modulates flow experience, mood states, and brain waves during moderate-intensity cycling. Methods: Fifty healthy adults were initially recruited; four participants withdrew during the study, resulting in a final sample of 46 participants. Flow experience was assessed using the Flow State Scale (FSS), mood states were measured using the Profile of Mood States (POMS), and cortical activity was recorded using a Quick-20 Dry EEG headset. Participants performed 300 s of moderate-intensity cycling under three environmental conditions: indoor, outdoor, and virtual reality (VR). Repeated-measures analysis of variance (ANOVA)… More >

Haitao Liu^1,*, Xuyang Wang¹, Shengcheng Quan¹, Qiaosheng Guo², Aichun Wang³, Lie Yang¹, Tingfang Zhang¹, Xiaojian Wu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085747 - 28 August 2026

Abstract Rapid advances in information and automation technologies have accelerated the development of smart manufacturing, thereby heightening the importance of reliable fault diagnosis for mechanical equipment. Although neural network-based algorithms are widely adopted in industrial applications due to their strong feature extraction and classification capabilities, their deployment in safety-critical fields such as aerospace remains limited. This limitation mainly arises from poor model interpretability and a heavy reliance on large-scale labeled training data. To address these challenges, this paper proposes an interpretable neural network framework that integrates discrete wavelet transform (DWT) with neural networks. Specifically, discrete wavelet… More >

Pengyu Wang¹, Tian Li¹, Jiye Zhang^1,*, Keyue Zhang², Jiawei Zhang^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.083990 - 28 August 2026

Abstract With the continuous expansion of rail transport capacity and the increasing speeds of freight trains, it has become increasingly common for passenger and freight trains to share the tracks on double-track or high-speed rail sections. To reveal the evolution of pressure wave characteristics during non-uniform-speed encounters between high-speed trains and freight trains on bridges, this study establishes a full-scale computational model of a steel truss flexible arch bridge and the conditions under which a train passes over it, with the bridge model serving solely as an aerodynamic boundary condition. The numerical simulation is based on… More >

Mengxue Li^1,2, Xinyi Chen^1,*, Yuxi Xie²

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079754 - 24 August 2026

Abstract Concrete stress is a critical indicator for evaluating the performance of concrete structures. To achieve non-contact testing of concrete stress, this study analyzed the propagation of laser-generated Rayleigh waves (R-wave) in concrete. A correlation model was established between the concrete stress and the R-wave velocity. To validate the theoretical analysis, ultrasonic experiments were conducted. The experimental results demonstrated that the stress history of concrete determines whether a stable linear relationship exists between the stress and the R-wave velocity. Additionally, the acoustoelastic coefficient of concrete was found to vary with its age. Based on these findings, More >

Kai Luo^1,2,*, Yuzhi Chen³

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079382 - 24 August 2026

Abstract Material property variability in carbon fiber-reinforced polymer composites is a major source of uncertainty in quantitative Lamb wave-based delamination imaging. Even minor deviations in elastic properties can alter dispersion characteristics and wave propagation behavior, thereby reducing the reliability of imaging-based assessments. To systematically investigate this effect, the present study examines the influence of subtle material variations on Lamb wave responses through combined numerical modeling and finite element simulations. Time-of-flight features at the excitation frequency are extracted using a continuous wavelet transform with Morlet wavelets, enabling robust identification of mode-dependent arrival information. Within a finite element… More >

Shengya Liu¹, Wei Bian^1,2, Linan Li^1,*, Yang Xue^1,2, Jingxun Yin³

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2025.074804 - 06 August 2026

Abstract Offshore wind energy plays a critical role in achieving global decarbonization goals, while the dynamic response mechanisms of megawatt-scale turbines under complex environmental conditions remain insufficiently characterized. Current research often oversimplifies the effects of monopile flexibility and its interaction with soil dynamics, leading to gaps in dynamic predictions. To address this limitation, this study develops a comprehensive 15-degree-of-freedom dynamic model for a 22 MW monopile offshore wind turbine (OWT) that incorporates nonlinear pile flexibility and soil-structure interaction through p-y and Q-z curves. The integrated analytical framework, established using Euler-Lagrange equations, enables coupled analysis of… More > Graphic Abstract

Muhammad Zaheer Sajid¹, Muhammad Fareed Hamid², Nauman Ali Khan^2,3,*, Imran Qureshi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.084724 - 27 July 2026

Abstract Digital pathology is rapidly transforming histopathological diagnosis, yet many existing deep learning models treat all spatial regions uniformly and do not exploit the multi-frequency structure of tissue, which limits both diagnostic accuracy and computational efficiency. This paper proposes WaSA-Net, an end-to-end architecture that integrates three complementary modules for histopathological image analysis. First, the Wavelet-Guided Tokenization (WGT) module decomposes input images into frequency-aware representations using learnable wavelet-like filters, so that both global tissue structures and fine-grained cellular patterns are exposed to attention from the first layer. Second, the Dynamic Sparse Attention with Pathology Priors (DSA-PP) module… More >

Xianhui Fan¹, Zongwei Li^1,*, Yuxuan Zhai¹, Zhenyu Li²

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083491 - 23 July 2026

Abstract Single-wave order picking in dynamic warehouses is a sequential multi-goal navigation problem. A robot must visit an ordered set of shelves and then a delivery station while avoiding moving obstacles under partial observability. Existing approaches either entangle long-horizon task logic with low-level obstacle avoidance or rely on static-environment assumptions that limit responsiveness in dynamic settings. This paper proposes the Single-Wave Dynamic Warehouse Navigation System (SW-DWNS), a lightweight scheduling framework that extends a pretrained ColorDynamic point-to-point local planner to ordered warehouse picking without retraining. The scheduler maintains a shelf queue, exposes only the active subgoal to… More >

Spandana Saggurthi¹, Anand Nayyar², Sk Hasane Ahammad¹, Sumendra Yogarayan^3,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.080058 - 23 July 2026

Abstract This work presents a multi-objective optimization framework for systematic design-space exploration of a 28 GHz single-stage cascode LNA (Low noise amplifier) in 22 nm FDSOI technology using NSGA-II and MOPSO algorithms. The objectives of the paper include simultaneous minimization of noise figure (NF) and power consumption while maximizing gain under matching and stability constraints. Using device parameters and circuit models that were developed for a 22 nm FDSOI process technology, an optimization framework was created in Python, with the passive components LG, LS, LD, LOUT, and COUT chosen to be the variables optimized. More >

Huajie Zhang^1,2, Xiaopeng Li^1,2, Hanlin Xiao^3,*, Lifeng Xing³, Wenyue Zhou^1,2

Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.086505 - 12 July 2026

Abstract This article has no abstract. More >