Ahmed Abdel-Wahab¹, Mohammad Alkhatib^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-34, 2026, DOI:10.32604/cmc.2025.070010 - 09 December 2025

Abstract Deepfake is a sort of fake media made by advanced AI methods like Generative Adversarial Networks (GANs). Deepfake technology has many useful uses in education and entertainment, but it also raises a lot of ethical, social, and security issues, such as identity theft, the dissemination of false information, and privacy violations. This study seeks to provide a comprehensive analysis of several methods for identifying and circumventing Deepfakes, with a particular focus on image-based Deepfakes. There are three main types of detection methods: classical, machine learning (ML) and deep learning (DL)-based, and hybrid methods. There are… More >

Guo-Zhi Li¹, Hua-Ping Wang^1,2,*, Si-Kai Wang¹, Jing-Cheng Zhou¹, Ping Xiang^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3165-3195, 2025, DOI:10.32604/cmes.2025.072750 - 23 December 2025

Abstract Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity. A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential, as it offers intuitive insights into parametric influences and facilitates enhanced structural performance. This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures. By establishing a two-dimensional composite pavement model, it investigates load transfer characteristics and validates the accuracy through finite element simulation. The proposed method offers a straightforward analytical approach… More >

Jiunn-Wei Wang^1,2,3, Wen-Hung Hsu^2,3,4, Fang-Jung Yu^2,3, Fu-Chen Kuo⁵, Chung-Jung Liu^3,6, Chao-Hung Kuo^1,2,3, Jaw-Yuan Wang^7,8, Ming-Hong Lin^9,*, Deng-Chyang Wu^1,2,3,*

Oncology Research, Vol.33, No.12, pp. 3907-3922, 2025, DOI:10.32604/or.2025.070432 - 27 November 2025

Abstract Objectives: Colorectal adenomatous polyps frequently recur after removal and are precursors to colorectal cancer, highlighting the need for effective preventive strategies. This study evaluated the efficacy of probiotic Clostridium butyricum MIYAIRI 588 (CBM588) in preventing colorectal adenoma recurrence in high-risk patients. Methods: We conducted a randomized, single-blind, two-year crossover trial in patients with a history of adenomatous polyps. Participants received CBM588 in either the first or second year, with the alternate year as observation, and underwent annual surveillance colonoscopies. Outcomes (adenoma recurrence and polyp counts) were analyzed by intention-to-treat (ITT) and per-protocol (PP) approaches. Results: A total… More >

David Amilo^1,*, Khadijeh Sadri¹, Evren Hincal^1,2, Mohamed Hafez^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2189-2222, 2025, DOI:10.32604/cmes.2025.070298 - 26 November 2025

Abstract Breast cancer’s heterogeneous progression demands innovative tools for accurate prediction. We present a hybrid framework that integrates machine learning (ML) and fractional-order dynamics to predict tumor growth across diagnostic and temporal scales. On the Wisconsin Diagnostic Breast Cancer dataset, seven ML algorithms were evaluated, with deep neural networks (DNNs) achieving the highest accuracy (97.72%). Key morphological features (area, radius, texture, and concavity) were identified as top malignancy predictors, aligning with clinical intuition. Beyond static classification, we developed a fractional-order dynamical model using Caputo derivatives to capture memory-driven tumor progression. The model revealed clinically interpretable patterns: More >

Ayaz Hussain¹, Asad Hayat², Muhammad Hasnain^1,*

Journal on Artificial Intelligence, Vol.7, pp. 485-498, 2025, DOI:10.32604/jai.2025.071933 - 17 November 2025

Abstract Violent hate speech and scapegoating people against one another have emerged as a rising worldwide issue. But identifying and combating such content is crucial to create safer and more inclusive societies. The current study conducted research using Machine Learning models to classify hate speech and overcome the limitations posed in the existing detection techniques. Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbour (KNN) and Decision Tree were used on top of a publicly available hate speech dataset. The data was preprocessed by cleaning the text and tokenization and using normalization techniques to efficiently train the… More >

Si-Kai Wang¹, Ti-Cai Wang¹, Di-Fei Yi², Jia Rui³, Peng-Fei Cao⁴, Hua-Ping Wang^1,5,*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1411-1432, 2025, DOI:10.32604/sdhm.2025.070034 - 17 November 2025

Abstract As a key storage facility, the structural safety of large oil tanks is directly related to the stable operation of the energy system. The static pressure caused by the change of liquid level is one of the main loads in the service process of storage tanks, which determines the structural deformation and damage risk. To explore the structural deformation properties under the change of liquid levels and provide a theoretical basis for the prevention and control of damage risk, this paper systematically analyzes the mechanical response of storage tanks under the pressures induced by different… More > Graphic Abstract

Xiaobo Jiang, Hongchao Zheng^*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1695-1716, 2025, DOI:10.32604/sdhm.2025.063890 - 17 November 2025

Abstract Construction failures caused by unforeseen circumstances, such as natural disasters, environmental degradation, and structural weaknesses, present significant challenges in achieving durability, safety, and sustainability. This research addresses these challenges through the development of advanced emergency rescue systems incorporating wood-derived nanomaterials and IoT-enabled Structural Health Monitoring (SHM) technologies. The use of nanocellulose which demonstrates outstanding mechanical capabilities and biodegradability alongside high resilience allowed developers to design modular rescue systems that function effectively even under challenging conditions while providing real-time failure protection. Experimental data from testing showed that the replacement system strengthened load-bearing limits by 20% while… More >

Nurlan Zhangabay^1,*, Marco Bonopera^2,*, Konstantin Avramov³, Maryna Chernobryvko³, Svetlana Buganova⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 241-261, 2025, DOI:10.32604/cmes.2025.069544 - 30 October 2025

Abstract This research extends ongoing efforts to develop methods for reinforcing damaged main gas pipelines to prevent catastrophic failure. This study establishes the use of scaled-down experimental models for assessing the dynamic strength of damaged pipeline sections reinforced with wire wrapping or composite sleeves. A generalized dynamic model is introduced for numerical simulation to evaluate the effectiveness of reinforcement techniques. The model incorporates the elastoplastic behavior of pipe and wire materials, the influence of temperature on mechanical properties, the contact interaction between the pipe and the reinforcement components (including pretensioning), and local material failure under transient… More >

Zhengzheng Cao^1,2,3, Fangxu Guo¹, Wenqiang Wang^2,3,4,*, Feng Du^2,3,4, Zhenhua Li^2,3,4, Shuaiyang Zhang¹, Qixuan Wang¹, Yongzhi Zhai¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.10, pp. 2419-2442, 2025, DOI:10.32604/fdmp.2025.070624 - 30 October 2025

Abstract With the depletion of shallow mineral resources, mining operations are extending to greater depths and larger scales, increasing the risk of water inrush disasters, particularly from confined aquifers intersected by faults. This paper reviews the current state of research on fault-induced water inrushes in mining faces, examining the damage characteristics and permeability of fractured floor rock, the mechanical behavior of faults under mining stress, and the mechanisms driving water inrush. Advances in prevention technologies, risk assessment, and prediction methods are also summarized. Research shows that damage evolution in fractured floor rock, coupled with fluid-solid interactions,… More > Graphic Abstract

Tao Lin^1,*, Chengdai Chen¹, Liyao Chen¹, Fengqin Han¹, Guanghui He²

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1661-1680, 2025, DOI:10.32604/fhmt.2025.070787 - 31 October 2025

Abstract Targeting spontaneous coal combustion during stacking, we developed an efficient heat dissipation & self-supplied wireless temperature measurement system (SPWTM) with gravity heat pipe-thermoelectric integration for dual safety. The heat transfer characteristics and temperature measurement optimization of the system are experimentally investigated and verified in practical applications. The results show that, firstly, the effects of coal pile heat production power and burial depth, along with heat pipe startup and heat transfer characteristics. At 60 cm burial depth, the condensation section dissipates 98% coal pile heat via natural convection. Secondly, for the temperature measurement error caused by… More >