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 >

Weiguo Chen¹, Xiaobin Hong^1,*, Kai Chen¹, Yunyun Deng¹, Bin Zhang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082376 - 30 June 2026

Abstract Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems. During the detection of ship T-shaped pipes using ultrasonic guided waves, signal overlap arises from the diffusion of guided wave branches. To address this issue, an intelligent wave-guidance mechanism based on acoustic metamaterials is proposed for dynamic propagation control of ultrasonic guided waves. First, a metamaterial unit composed of a stainless steel substrate and a copper column is designed. The control of bandgap characteristics by lattice constant, column diameter, and column height is systematically… More > Graphic Abstract

Gaoteng Yuan^1,*, Ping Qiu², Qika Lin³, Jianchu Lin¹, Xiang Li¹, Dongping Gao⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.081152 - 30 June 2026

Abstract Epilepsy is a chronic neurological disorder characterized by recurrent seizures, posing significant challenges to patients’ quality of life. Accurate classification of seizure states is crucial for effective intervention. This paper presents a deep learning-based approach for epileptic seizure classification by integrating multi-feature analysis of electroencephalogram (EEG) signals. The proposed method begins with signal preprocessing, including denoising, segmentation, and label construction. Subsequently, a comprehensive set of temporal, spectral, and wavelet-based features—such as signal mean, power, heart rate, and wavelet coefficients—is extracted. Feature selection is then performed using the Maximal Information Coefficient (MIC) to identify the most… More > Graphic Abstract

Xiaofei Nie^1,2,*, Amir Pakpour^2,3, Yanqiong Ouyang⁴, Maria Björk^2,3

International Journal of Mental Health Promotion, Vol.28, No.6, 2026, DOI:10.32604/ijmhp.2026.078747 - 23 June 2026

Abstract Objectives: This study aims to examine the temporal associations among psychological distress, mindfulness, childbirth trauma, and postpartum post-traumatic stress disorder (PTSD) symptoms across the first three months postpartum and test whether mindfulness mediates these longitudinal pathways. Methods: This prospective longitudinal cohort study followed Chinese postpartum women at one week (T1), one month (T2), and three months (T3) after childbirth. A total of 210 women completed baseline assessments, with 173 and 148 participants retained at T2 and T3, respectively. Psychological distress, mindfulness, childbirth trauma, and postpartum PTSD symptoms were assessed using validated self-report measures. Cross-lagged panel models… More >

Guanghua He¹, Jinlong Qi^1,*, Yao Feng¹, Jiayi Han¹, Heng Chen², Baoming Huang³, Jiangtao Li³

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.076354 - 27 May 2026

Abstract The identification of the traveling wave head is an important factor affecting the accuracy of fault traveling wave positioning. In practice, in addition to the attenuation of traveling wave amplitude and rising speed caused by distribution line factors, various traveling wave sensors can also cause transmission distortion of high-frequency traveling wave signals, which in turn affects the calibration of traveling wave arrival time and the accuracy of fault distance measurement. The inversion technology of sensor transmission characteristics using analytical methods has limited ability to reflect factors such as stray capacitance and sensor differences. In comparison,… More >

Sajid Ullah Khan^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079440 - 08 May 2026

Abstract Healthcare, education, technological advancement, and farming are the key challenges facing developing countries, with agriculture unquestionably playing an important role in economic growth. Ensuring adequate food production is essential for citizens’ survival, as it is anticipated that efforts in this area would result in increased food productivity. A key approach to enhancing field productivity involves meticulous care of its components, starting with the production of crops. Wheat leaf rust poses a severe threat, particularly to young seedlings, constituting a significant fungal disease that can cause a 25% reduction in wheat productivity. To overcome these issues,… More >

Guohai Jia¹, Yongjia Ma¹, Yuanyuan Li², Yuling Cheng², Dan Huang^2,*

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2026.076516 - 30 April 2026

Abstract Microwave vacuum drying (MVD) is a promising technique for enhancing drying efficiency and product quality in ginger processing. In this study, the effects of microwave power, vacuum degree, and slice thickness on the MVD behavior of ginger slices were systematically investigated. The drying performance of MVD was also compared with hot-air drying (HAD) and microwave drying (MD). The results showed that increasing microwave power and vacuum degree, together with reducing slice thickness, significantly accelerated moisture removal, with microwave power being the dominant factor. Under comparable conditions, MVD required only one-sixth of the drying time of… More >