Moein Tosan^1,*, Vahid Nourani^2,3, Ozgur Kisi^4,5,6, Yongqiang Zhang⁷, Sameh A. Kantoush⁸, Mekonnen Gebremichael⁹, Ruhollah Taghizadeh-Mehrjardi¹⁰, Jinhui Jeanne Huang¹¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074768 - 29 January 2026

Abstract The integration of machine learning (ML) into geohazard assessment has successfully instigated a paradigm shift, leading to the production of models that possess a level of predictive accuracy previously considered unattainable. However, the black-box nature of these systems presents a significant barrier, hindering their operational adoption, regulatory approval, and full scientific validation. This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence (XAI) as applied to geohazard science (GeoXAI), a domain that aims to resolve the long-standing trade-off between model performance and interpretability. A rigorous synthesis of 87 foundational… More >

Urszula Częścik^1,2,#, Martyna Gryglas³, Arkadiusz Szterk⁴, Sylwia Flis^3,#,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.067449 - 19 January 2026

Abstract Colorectal cancer (CRC) is the third most common malignancy worldwide and the second leading cause of cancer-related deaths, accounting for approximately 10% of all cancer cases. By 2050, CRC incidence is expected to rise substantially, driven by population aging and greater exposure to risk factors in developing countries. Despite advances in medicine and pharmacy, the effectiveness of available treatments remains limited, underscoring the urgent need for innovative therapeutic strategies. This review summarizes and critically evaluates currently available CRC therapies and explores new emerging directions. Particular attention is given to the role of immunotherapy, targeted therapies,… More >

Leyu Zheng¹, Mingming Xiao^1,*, Yi Ren², Ke Li¹, Chang Sun¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072036 - 12 January 2026

Abstract In a wide range of engineering applications, complex constrained multi-objective optimization problems (CMOPs) present significant challenges, as the complexity of constraints often hampers algorithmic convergence and reduces population diversity. To address these challenges, we propose a novel algorithm named Constraint Intensity-Driven Evolutionary Multitasking (CIDEMT), which employs a two-stage, tri-task framework to dynamically integrates problem structure and knowledge transfer. In the first stage, three cooperative tasks are designed to explore the Constrained Pareto Front (CPF), the Unconstrained Pareto Front (UPF), and the ε-relaxed constraint boundary, respectively. A CPF-UPF relationship classifier is employed to construct a problem-type-aware… More >

Yuntian Wang^1,2, Taohua Liang^1,2, Yuan Zhou^1,2, Weimei Shi^1,2, Lijuan Huang^1,2, Yuzhu Guo^3,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-26, 2026, DOI:10.32604/cmc.2025.071624 - 09 December 2025

Abstract This investigation utilizes non-equilibrium molecular dynamics (NEMD) simulations to explore shock-induced spallation in single-crystal tantalum across shock velocities of 0.75–4 km/s and initial temperatures from 300 to 2000 K. Two spallation modes emerge: classical spallation for shock velocity below 1.5 km/s, with solid-state reversible Body-Centered Cubic (BCC) to Face-Centered Cubic (FCC) or Hexagonal Close-Packed (HCP) phase transformations and discrete void nucleation-coalescence; micro-spallation for shock velocity above 3.0 km/s, featuring complete shock-induced melting and fragmentation, with a transitional regime (2.0–2.5 km/s) of partial melting. Spall strength decreases monotonically with temperature due to thermal softening. Elevated temperatures More >

Siwen Xu¹, Hanning Chen², Rui Ni¹, Maowei He², Zhaodi Ge³, Xiaodan Liang^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-25, 2026, DOI:10.32604/cmc.2025.071398 - 09 December 2025

Abstract Selective Laser Melting (SLM), an advanced metal additive manufacturing technology, offers high precision and personalized customization advantages. However, selecting reasonable SLM parameters is challenging due to complex relationships. This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm. JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones, but it is prone to premature convergence thus leading to insufficient global search. To overcome limitations, this research proposes a Differential Evolution-framed JAYA algorithm (DEJAYA). DEJAYA incorporates four key enhancements More >

Malvinder Singh Bali¹, Weiwei Jiang^2,*, Saurav Verma³, Kanwalpreet Kour⁴, Ashwini Rao³

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070866 - 09 December 2025

Abstract In recent years, Blockchain Technology has become a paradigm shift, providing Transparent, Secure, and Decentralized platforms for diverse applications, ranging from Cryptocurrency to supply chain management. Nevertheless, the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency, scalability, and energy consumption. This study proposes an innovative approach to Blockchain network optimization, drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms. Specifically, we explore the application of genetic algorithms, particle swarm optimization, and related evolutionary techniques to enhance the performance of blockchain networks. The proposed methodologies More >

Muhammad Waqar Khan^1,*, Adnan Ahmed Siddiqui¹, Syed Sajjad Hussain Rizvi²

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-15, 2026, DOI:10.32604/cmc.2025.070858 - 09 December 2025

Abstract The multi-objective optimization problems, especially in constrained environments such as power distribution planning, demand robust strategies for discovering effective solutions. This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization (MCCMO) Algorithm, termed Adaptive Diversity Preservation (ADP). This enhancement is primarily focused on the improvement of constraint handling strategies, local search integration, hybrid selection approaches, and adaptive parameter control. The improved variant was experimented on with the RWMOP50 power distribution system planning benchmark. As per the findings, the improved variant outperformed the original MCCMO across the eleven performance metrics, particularly in terms… More >

Asal Jameel Khudhair^#, Amenah Dahim Abbood^#,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.068553 - 10 November 2025

Abstract Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities. Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can. Therefore, we utilized two objective functions… More >

Mustansar Mubeen¹, Yasir Iftikhar^1,*, Ganesan Vadamalai^2,3, Muhammad Aasim⁴, Muhammad Faiq⁵, Uthman Balgith Algopishi⁶, Ahmed Ezzat Ahmed^6,7

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3827-3843, 2025, DOI:10.32604/phyton.2025.071555 - 29 December 2025

Abstract Citrus viroids are small non-coding RNA pathogens that pose a significant threat to global citrus production by reducing fruit yield, quality, and tree longevity. Several viroids, including Citrus exocortis viroid (CEVd), Hop stunt viroid (HSVd), Citrus bent leaf viroid (CBLVd), and newly identified members such as Citrus Viroid VI (CVd-VI) and Citrus Viroid VII (CVd-VII) have been reported from diverse citrus-growing regions. These pathogens are transmitted mainly through vegetative propagation, contaminated tools, and occasionally via seed or pollen, making their management complex. This review synthesizes current knowledge on the biology, structural diversity, transmission, symptomatology, detection,… More >

Md. Injamum-Ul-Hoque^1,2, Md. Mahfuzur Rahman², Nayan Chandra Howlader³, Soosan Tavakoli⁴, Md. Mezanur Rahman⁵, Shahin Imran⁶, Mallesham Bulle⁷, S. M. Ahsan^2,4,*, Hyong Woo Choi^4,8,*

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 3805-3826, 2025, DOI:10.32604/phyton.2025.069827 - 29 December 2025

Abstract Cannabis sativa is highly valued for its use in fiber production, medicine, and recreational products. Its secondary metabolites (SM) are renowned for their wide range of health benefits and psychoactive properties. While much of the existing research has focused on cannabinoid production in the plant’s aerial parts, particularly the leaves and flowers, the root system remains understudied in terms of its SM profile. One promising in vitro approach for metabolite production involves the use of ‘hairy roots (HRs)’. These roots mimic the phytochemical profile of native roots but grow more efficiently and yield higher quantities of metabolites.… More >