Ghadah Naif Alwakid^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-25, 2026, DOI:10.32604/cmc.2025.068666 - 10 November 2025

Abstract Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that significantly affects cognitive function, making early and accurate diagnosis essential. Traditional Deep Learning (DL)-based approaches often struggle with low-contrast MRI images, class imbalance, and suboptimal feature extraction. This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans. Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN). A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient (MCC)-based evaluation method into the design.… More >

Qin Qin¹, Xuan Jiang^1,*, Jinhua Jiang¹, Dongfang Zhao¹, Zimei Tu¹, Zhiwei Shen²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4849-4867, 2025, DOI:10.32604/cmc.2025.067919 - 23 October 2025

Abstract The effectiveness of industrial character recognition on cast steel is often compromised by factors such as corrosion, surface defects, and low contrast, which hinder the extraction of reliable visual information. The problem is further compounded by the scarcity of large-scale annotated datasets and complex noise patterns in real-world factory environments. This makes conventional OCR techniques and standard deep learning models unreliable. To address these limitations, this study proposes a unified framework that integrates adaptive image preprocessing with collaborative reasoning among LLMs. A Biorthogonal 4.4 (bior4.4) wavelet transform is adaptively tuned using DE to enhance character… More >

Tian Tian^1,2, Boyue Wang^1,2, Xiaxia He^1,2,*, Wentong Wang³, Meng Wang¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4885-4898, 2025, DOI:10.32604/cmc.2025.067795 - 23 October 2025

Abstract Attribute-graph clustering aims to divide the graph nodes into distinct clusters in an unsupervised manner, which usually encodes the node attribute feature and the corresponding graph structure into a latent feature space. However, traditional attribute-graph clustering methods often neglect the effect of neighbor information on clustering, leading to suboptimal clustering results as they fail to fully leverage the rich contextual information provided by neighboring nodes, which is crucial for capturing the intrinsic relationships between nodes and improving clustering performance. In this paper, we propose a novel Neighbor Dual-Consistency Constrained Attribute-Graph Clustering that leverages information from… More >

Juan Guerrero-Martín^*, Eladio Estella-Nonay, Margarita Bachiller-Mayoral, Mariano Rincón

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4729-4752, 2025, DOI:10.32604/cmc.2025.066083 - 23 October 2025

Abstract Neuropsychological tests, such as the Rey-Osterrieth complex figure (ROCF) test, help detect mild cognitive impairment (MCI) in adults by assessing cognitive abilities such as planning, organization, and memory. Furthermore, they are inexpensive and minimally invasive, making them excellent tools for early screening. In this paper, we propose the use of image analysis models to characterize the relationship between an individual’s ROCF drawing and their cognitive state. This task is usually framed as a classification problem and is solved using deep learning models, due to their success in the last decade. In order to achieve good… More >

Anastasia Vylegzhanina^1,2, Irina Shalaginova^2,*, Dana Korolevich¹, Dmitry Katserov¹, Alexandra Semenova¹, Maria Sidorova¹, Sergey Eresko³, Marat Airapetov³, Marina Pavlova², Anna Levina², Natalia Dyuzhikova²

BIOCELL, Vol.49, No.10, pp. 2007-2031, 2025, DOI:10.32604/biocell.2025.071198 - 22 October 2025

Abstract Objectives: Chronic stress can trigger neuroinflammation and gut microbiota alterations, contributing to post-stress disorders. Individual differences in stress responses, shaped by genetic and physiological factors, require better characterization. We aimed to investigate the long-term effects of chronic stress in rats selectively bred for high and low nervous system excitability. Methods: Adult male rats from two strains selectively bred for high (HT) and low (LT) excitability thresholds of the nervous system underwent a 15-day chronic emotional-pain stress protocol. Behavioral assessments (elevated plus maze), cytokine levels (TNF, IL-1β, IL-6, IL-10) in the hippocampus and amygdala measured by… More >

Gilciany Ribeiro Soares¹, Jiovana Kamila Vilas Boas¹, Fábio Steiner^1,2, Jorge González Aguilera^2,*, Alan Mario Zuffo³, José Vitor Marçal do Prado², Wellingthon da Silva Guimarães Júnnyor², Leandris Argentel- Martínez⁴, Luis Morales-Aranibar⁵

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2347-2363, 2025, DOI:10.32604/phyton.2025.066264 - 29 August 2025

Abstract Corn (Zea mays L.) is a very sensitive crop to phosphorus (P) deficiency during the early development phase, which may be a limiting factor for the sustainable production of this crop in P-deficient tropical soils. However, scientific evidence indicates that inoculation with phosphate-solubilizing bacteria can improve the development, uptake, and P-use efficiency of corn plants. In the present study, two contrasting corn hybrids were investigated for their responsiveness to multiple inoculations of Bacillus subtilis, B. megaterium, B. velezencis, and Pseudomonas fluorescens and application of phosphate fertilizer rates in the sandy soil of the Brazilian Cerrado. Plants from stable (DKB 360… More >

Jialong Zhang¹, Meijuan Yin^2,*, Yang Pei², Fenlin Liu², Chenyu Wang²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2095-2115, 2025, DOI:10.32604/cmc.2025.065679 - 29 August 2025

Abstract Identifying influential users in social networks is of great significance in areas such as public opinion monitoring and commercial promotion. Existing identification methods based on Graph Neural Networks (GNNs) often lead to yield inaccurate features of influential users due to neighborhood aggregation, and require a large substantial amount of labeled data for training, making them difficult and challenging to apply in practice. To address this issue, we propose a semi-supervised contrastive learning method for identifying influential users. First, the proposed method constructs positive and negative samples for contrastive learning based on multiple node centrality metrics… More >

Kexuan Niu, Xiameng Si^*, Xiaojie Qi, Haiyan Kang

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2051-2070, 2025, DOI:10.32604/cmc.2025.065377 - 29 August 2025

Abstract Sarcasm detection is a complex and challenging task, particularly in the context of Chinese social media, where it exhibits strong contextual dependencies and cultural specificity. To address the limitations of existing methods in capturing the implicit semantics and contextual associations in sarcastic expressions, this paper proposes an event-aware model for Chinese sarcasm detection, leveraging a multi-head attention (MHA) mechanism and contrastive learning (CL) strategies. The proposed model employs a dual-path Bidirectional Encoder Representations from Transformers (BERT) encoder to process comment text and event context separately and integrates an MHA mechanism to facilitate deep interactions between More >

Yu-Shiuan Tsai^*, Zhen-Rong Wu, Jian-Zhi Liu

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3431-3457, 2025, DOI:10.32604/cmc.2025.066509 - 03 July 2025

Abstract Few-shot learning has emerged as a crucial technique for coral species classification, addressing the challenge of limited labeled data in underwater environments. This study introduces an optimized few-shot learning model that enhances classification accuracy while minimizing reliance on extensive data collection. The proposed model integrates a hybrid similarity measure combining Euclidean distance and cosine similarity, effectively capturing both feature magnitude and directional relationships. This approach achieves a notable accuracy of 71.8% under a 5-way 5-shot evaluation, outperforming state-of-the-art models such as Prototypical Networks, FEAT, and ESPT by up to 10%. Notably, the model demonstrates high… More >

Manqing Qian^*, Xiyu Chen, Yongming Li

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1353-1377, 2025, DOI:10.32604/fdmp.2025.061652 - 30 June 2025

Abstract Shale reservoirs are characterized by numerous geological discontinuities, such as bedding planes, and exhibit pronounced heterogeneity across rock layers separated by these planes. Bedding planes often possess distinct mechanical properties compared to the surrounding rock matrix, particularly in terms of damage and fracture behavior. Consequently, vertical propagation of hydraulic fractures is influenced by both bedding planes and the heterogeneity. In this study, a numerical investigation into the height growth of hydraulic fractures was conducted using the finite element method, incorporating zero-thickness cohesive elements. The analysis explored the effects of bedding planes, toughness contrasts between layers,… More >