Manisha Choudhari¹, Shantanu Damle², Rajat Vashist¹, Ranendra Narayan Saha³, Sunil Kumar Dubey⁴, Gautam Singhvi^1,*

Journal of Polymer Materials, Vol.42, No.4, pp. 1199-1229, 2025, DOI:10.32604/jpm.2025.072987 - 26 December 2025

Abstract Abiraterone acetate (ABTA) was approved by the USFDA in 2011 for treating metastatic castration-resistant prostate cancer (mCRPC). ABTA exhibits poor aqueous solubility, inadequate dissolution, low oral bioavailability (<10%), and significant positive food effects. To overcome these limitations, in the present work, ABTA solid dispersions (SDs) were developed by using hot melt extrusion technology (HME) with various grades of hydroxypropyl methylcellulose HME (HPMC HME 15LV and 100LV) at different extrusion temperatures. HPMC HME demonstrated the ability to prevent drug precipitation for up to 120 min compared to the free drug (10 min), sustaining the supersaturation state… More > Graphic Abstract

Yi Guan¹, Pengpeng Zhi^2,3,*, Zhonglai Wang^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3343-3368, 2025, DOI:10.32604/cmes.2025.069515 - 30 September 2025

Abstract Variable-fidelity (VF) surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity (HF) simulations with reduced computational power. A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity (LF) and/or HF samples. The additional samples must enhance the model accuracy while maximizing the computational efficiency. We propose ISMA-VFEEI, a global optimization framework that integrates an Improved Slime-Mould Algorithm (ISMA) and a Variable-Fidelity Expected Extension Improvement (VFEEI) learning function to construct a VF surrogate model efficiently. First, A cost-aware VFEEI More >

Imene Tatar Caliskan^1,2, George Dzorgbenya Ametefe³, Aziz Caliskan⁴, Su-Ee Lau^1,5, Yvonne Jing Mei Liew⁶, Nur Kusaira Khairul Ikram⁵, Boon Chin Tan^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2229-2254, 2025, DOI:10.32604/phyton.2025.067225 - 29 August 2025

Abstract Myeloblastosis (MYB) transcription factors (TFs) are evolutionarily conserved regulatory proteins that are crucial for plant growth, development, secondary metabolism, and stress adaptation. Recent studies have highlighted their crucial role in coordinating growth–defense trade-offs through transcriptional regulation of key biosynthetic and stress-response genes. Despite extensive functional characterization in model plants such as Arabidopsis thaliana, systematically evaluating the broader functional landscape of MYB TFs across diverse species and contexts remains necessary. This systematic review integrates results from 24 peer-reviewed studies sourced from Scopus and Web of Science, focusing on the functional diversity of MYB TFs, particularly in relation… More >

Xiaoqin Li, Yongfu Zhang^*, Zhen Ren, Jiao Chen, Zuqin Qiao, Xingmei Tao, Xuan Yi, Kai Wang, Zhao Liu

Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2529-2550, 2025, DOI:10.32604/phyton.2025.066894 - 29 August 2025

Abstract Soil salinization is a major abiotic stress that hampers plant development and significantly reduces agricultural productivity, posing a serious challenge to global food security. Akebia trifoliata (Thunb.) Koidz, a species within the genus Akebia Decne., is valued for its use in food, traditional medicine, oil production, and as an ornamental plant. Curcumin, widely recognized for its pharmacological properties including anti-cancer, anti-neuroinflammatory, and anti-fibrotic effects, has recently drawn interest for its potential roles in plant stress responses. However, its impact on plant tolerance to saline-alkali stress remains poorly understood. In this study, the effects of curcumin on… More >

Da-Chun Wu^*, Bing-Han Sie

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 535-580, 2025, DOI:10.32604/cmes.2025.067239 - 31 July 2025

Abstract Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect. In data hiding methods based on image interpolation, the image size is reduced and then enlarged through interpolation, followed by the embedding of secret data into the newly generated pixels. A general improving approach for embedding secret messages is proposed. The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods. This enhancement is achieved by expanding the range of pixel values… More >

Hanbo Zheng, Yue Peng, Enpeng Qin, Yi Li^*

Journal of Polymer Materials, Vol.42, No.2, pp. 549-568, 2025, DOI:10.32604/jpm.2025.064866 - 14 July 2025

Abstract Fluorination is a critical surface modification technique for enhancing the electrical performance of composite insulators. This study employs molecular simulations to examine the microstructure and space charge behavior of fluorinated and non-fluorinated silicone rubber under an electric field, with experimental validation. The results show that fluorinated silicone rubber exhibits lower total energy, higher polarization, and stronger dipole moments compared to its non-fluorinated counterpart, shifting the material from an insulating to a conductive state. Under lower electric field strengths, the carbon-silicon bonds in fluorinated silicone rubber are longer, but it maintains geometric stability under higher fields.… More > Graphic Abstract

Nisa Nacar Çıkan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3279-3327, 2025, DOI:10.32604/cmes.2025.065442 - 30 June 2025

Abstract This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks (UPDNs), focusing on the complex 123-Bus test system. Three scenarios are investigated: (1) simultaneous power loss reduction and voltage profile improvement, (2) minimization of voltage and current unbalance indices under various operational cases, and (3) multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index, active power loss, and current unbalance index. Unlike previous research that oftensimplified system components, this work maintains all equipment, including capacitor banks, transformers, and voltage regulators, to ensure realistic results. The study evaluates twelve metaheuristic More >

Rongwei Yu¹, Jie Yin^1,*, Jingyi Xiang¹, Qiyun Shao², Lina Wang¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 365-391, 2025, DOI:10.32604/cmc.2025.064438 - 09 June 2025

Abstract With the emergence of new attack techniques, traffic classifiers usually fail to maintain the expected performance in real-world network environments. In order to have sufficient generalizability to deal with unknown malicious samples, they require a large number of new samples for retraining. Considering the cost of data collection and labeling, data augmentation is an ideal solution. We propose an optimized noise-based traffic data augmentation system, ONTDAS. The system uses a gradient-based searching algorithm and an improved Bayesian optimizer to obtain optimized noise. The noise is injected into the original samples for data augmentation. Then, an More >

Zhenfu Zhang¹, Haiyan Yin², Liudong Zuo³, Pan Lai^1,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 919-936, 2025, DOI:10.32604/cmc.2025.062980 - 09 June 2025

Abstract The knapsack problem is a classical combinatorial optimization problem widely encountered in areas such as logistics, resource allocation, and portfolio optimization. Traditional methods, including dynamic programming (DP) and greedy algorithms, have been effective in solving small problem instances but often struggle with scalability and efficiency as the problem size increases. DP, for instance, has exponential time complexity and can become computationally prohibitive for large problem instances. On the other hand, greedy algorithms offer faster solutions but may not always yield the optimal results, especially when the problem involves complex constraints or large numbers of items.… More >

Vicky Anand¹, Priyadarshani Rajput¹, Tatiana Minkina¹, Saglara Mandzhieva¹, Santosh Kumar², Avnish Chauhan³, Vishnu D. Rajput^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1339-1365, 2025, DOI:10.32604/phyton.2025.063927 - 29 May 2025

Abstract The digital revolution in agriculture has introduced data-driven decision-making, where artificial intelligence, especially machine learning (ML), helps analyze large and varied data sources to improve soil quality and crop growth indices. Thus, a thorough evaluation of scientific publications from 2007 to 2024 was conducted via the Scopus and Web of Science databases with the PRISMA guidelines to determine the realistic role of ML in soil health and crop improvement under the SDGs. In addition, the present review focused to identify and analyze the trends, challenges, and opportunities associated with the successful implementation of ML in… More >