Guiling Xu^1,#, Xiaoxuan You^1,#, Yuehua Feng^1,2,*, Xiaoke Wang¹, Yuqi Gao¹, Hongjun Ren¹, Zhili Han¹, Jiale Li¹

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3251-3268, 2025, DOI:10.32604/phyton.2025.067997 - 29 October 2025

Abstract Nitrogen (N) reduction combined with organic fertilizer has become a highly popular fertilization method, meeting the sustainable development of agriculture. A field experiment was conducted to investigate the effects of N reduction (NR) and combined application of organic fertilizer (OF) on N utilization, yield, and quality of hybrid indica rice in the karst area. Using rice ‘Yixiangyou2115’ as the material, a split-plot design experiment was carried out with OF application rate as the main plots and NR rate as the subplots. The OF application rate had three levels: M0 (0 kg/ha), M1 (low OF, 1673… More >

Chenquan Gan^1,2,*, Xu Liu¹, Yu Tang², Xianrong Yu³, Qingyi Zhu¹, Deepak Kumar Jain⁴

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5399-5421, 2025, DOI:10.32604/cmc.2025.068126 - 23 October 2025

Abstract Multimodal sentiment analysis aims to understand emotions from text, speech, and video data. However, current methods often overlook the dominant role of text and suffer from feature loss during integration. Given the varying importance of each modality across different contexts, a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process. In response to these critical limitations, we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues. In our model, text is… More >

Yibin Mao¹, Dianlong Yu^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.012290

Abstract In modern engineering, situations that require vibration reduction often come with specific pressure requirements. Mechanical metamaterials have the advantages in mechanical loading and low-frequency band gap vibration reduction. To ensure that the structure has a wide and low-frequency band gap while having a pressure resistance, a two-dimensional triangular concave negative Poisson's ratio structure with strong pressure resistance is introduced. The internal structure is designed according to the principle of local resonance. The band structure and intrinsic modes of the two-dimensional triangular concave model are calculated by the finite element method through simulation software. The band… More >

Yinyu Tang^1,2,3,*, Mingzhi Yang^1,2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011292

Abstract Energy efficiency and environmental sustainability in rail transit are key engineering goals. In urban trains, pressure drag plays a more significant role than in high-speed EMUs, primarily due to the blunt shape of the train’s head. The constraints imposed by underground construction and engineering protocols prevent the optimization strategies used in high-speed EMUs from being applied to urban trains. Therefore, aerodynamic drag reduction in blunt-tail urban trains, through active wake flow control, holds promise for improving train aerodynamics.
This study investigates drag reduction on the tail car of blunt urban trains using a hybrid numerical and… More >

Jichao Li, Xuexin Zhu, Cong Zhang, Shiwang Dang, Guang Chen^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2305-2329, 2025, DOI:10.32604/fdmp.2025.067087 - 30 September 2025

Abstract The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution. Beyond the promotion of new energy vehicles, reducing aerodynamic drag remains a critical strategy for improving energy efficiency and lowering emissions. This study investigates the influence of key geometric parameters on the aerodynamic drag of vehicles. A parametric vehicle model was developed, and computational fluid dynamics (CFD) simulations were conducted to analyse variations in the drag coefficient () and pressure distribution across different design configurations. The results reveal that More >

Sunawar Khan¹, Tehseen Mazhar^1,2,*, Naila Sammar Naz¹, Fahed Ahmed¹, Tariq Shahzad³, Atif Ali⁴, Muhammad Adnan Khan^5,*, Habib Hamam^6,7,8,9

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2347-2401, 2025, DOI:10.32604/cmc.2025.066932 - 23 September 2025

Abstract Feature selection (FS) plays a crucial role in medical imaging by reducing dimensionality, improving computational efficiency, and enhancing diagnostic accuracy. Traditional FS techniques, including filter, wrapper, and embedded methods, have been widely used but often struggle with high-dimensional and heterogeneous medical imaging data. Deep learning-based FS methods, particularly Convolutional Neural Networks (CNNs) and autoencoders, have demonstrated superior performance but lack interpretability. Hybrid approaches that combine classical and deep learning techniques have emerged as a promising solution, offering improved accuracy and explainability. Furthermore, integrating multi-modal imaging data (e.g., Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron… More >

Ragava Raja R^1,2,*, Girish Khanna R³

Journal on Artificial Intelligence, Vol.7, pp. 301-327, 2025, DOI:10.32604/jai.2025.069693 - 22 September 2025

Abstract Packaging materials are indispensable in modern industries but also significantly contribute to environmental degradation, resource consumption, and waste generation. This systematic review critically assesses the integration of artificial intelligence (AI), life cycle sustainability assessment (LCSA) following ISO 14040 standards, and circularity mapping to overcome sustainability barriers in packaging. The study identifies environmental, economic, and social hotspots across the life cycle stages of packaging materials by examining real-world case studies such as Coca-Cola’s adoption of recycled PET bottles and Unilever’s commitment to 100% recyclable plastic. AI technologies highlight transformative tools for optimising resource allocation, enhancing waste… More >

Hao Fang^1,2, Hongyun Guo¹, Yinchao Chen³, Hui Shi⁴, Yihan Gan⁵, Lin Li^6,*

International Journal of Mental Health Promotion, Vol.27, No.7, pp. 1051-1069, 2025, DOI:10.32604/ijmhp.2025.066369 - 31 July 2025

Abstract Objectives: Emotional stress is a significant public health challenge. Virtual reality (VR) offers the potential for aiding emotional recovery. This study explores the impact of VR environment design factors on emotional recovery, examining underlying mechanisms through physiological indicators and behavioral responses. Methods: Two experiments were conducted. Experiment 1 employed a 4 [Scene Type: real environment (RE), virtual scenes that restore the RE (VR), virtual scenes that incorporate natural window view design (VR-W), and a no-scene control condition (CTL)] × 3 (Experimental Phase: baseline, emotion arousal, recovery) mixed design (N = 33). Participants viewed a 4-min… More >

Muhammad Sibtain¹, Mehdi Hussain^1,*, Qaiser Riaz¹, Sana Qadir¹, Naveed Riaz¹, Ki-Hyun Jung^2,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5177-5199, 2025, DOI:10.32604/cmc.2025.066198 - 30 July 2025

Abstract Ransomware is malware that encrypts data without permission, demanding payment for access. Detecting ransomware on Android platforms is challenging due to evolving malicious techniques and diverse application behaviors. Traditional methods, such as static and dynamic analysis, suffer from polymorphism, code obfuscation, and high resource demands. This paper introduces a multi-stage approach to enhance behavioral analysis for Android ransomware detection, focusing on a reduced set of distinguishing features. The approach includes ransomware app collection, behavioral profile generation, dataset creation, feature identification, reduction, and classification. Experiments were conducted on ∼3300 Android-based ransomware samples, despite the challenges posed… More >

P. William^1,2, Ved Prakash Mishra¹, Osamah Ibrahim Khalaf^3,*, Arvind Mukundan⁴, Yogeesh N⁵, Riya Karmakar⁶

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5133-5156, 2025, DOI:10.32604/cmc.2025.065840 - 30 July 2025

Abstract Cloud computing has become an essential technology for the management and processing of large datasets, offering scalability, high availability, and fault tolerance. However, optimizing data replication across multiple data centers poses a significant challenge, especially when balancing opposing goals such as latency, storage costs, energy consumption, and network efficiency. This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization (DMGO), designed to enhance data replication efficiency in cloud environments. Unlike traditional static replication systems, DMGO adapts dynamically to variations in network conditions, system demand, and resource availability. The approach utilizes multi-objective optimization More >