Yue Ma^1,2, Douwen Qin^1,2, Weiqiang Liu^1,2, Xiuting Ju^1,2,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3527-3538, 2025, DOI:10.32604/phyton.2025.069643 - 01 December 2025

Abstract Comprehensive evaluation based on mineral element content is one of the effective methods for the exploration and utilization of wild tulip germplasm resources. In this study, Tulipa iliensis, Tulipa tianschanica and Tulipa heterophylla distributed in China were used as the research objects. The contents of 10 mineral elements (N, K, P, S, Ca, Mg, Cu, Zn, Fe, Mn) in roots, bulbs and leaves were determined, and the three wild tulips were comprehensively evaluated by correlation analysis, principal component analysis and cluster analysis. The results showed distinct variations in mineral element content among different organs of T. iliensis, T. tianschanica and T.… More >

Amina Mahreen¹, Fateh Mebarek-Oudina^2,3,4,*, Amna Ashfaq¹, Jawad Raza¹, Sami Ullah Khan⁵, Hanumesh Vaidya⁶

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2829-2853, 2025, DOI:10.32604/fdmp.2025.072492 - 01 December 2025

Abstract Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems. This study investigates the magnetohydrodynamic (MHD) thermosolutal convection of a Casson fluid within an inclined, porous microchannel subjected to convective boundary conditions. The nonlinear, coupled equations governing momentum, energy, and species transport are solved numerically using the MATLAB bvp4c solver, ensuring high numerical accuracy and stability. To identify the dominant parameters influencing flow behavior and to optimize transport performance, a comprehensive hybrid optimization framework—combining a modified Taguchi design, Grey… More >

Nguyen Dong Phuong¹, Nanthakumar Srivilliputtur Subbiah¹, Yabin Jin², Xiaoying Zhuang^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 263-303, 2025, DOI:10.32604/cmes.2025.067100 - 30 October 2025

Abstract Traditional inverse neural network (INN) approaches for inverse design typically require auxiliary feedforward networks, leading to increased computational complexity and architectural dependencies. This study introduces a standalone INN methodology that eliminates the need for feedforward networks while maintaining high reconstruction accuracy. The approach integrates Principal Component Analysis (PCA) and Partial Least Squares (PLS) for optimized feature space learning, enabling the standalone INN to effectively capture bidirectional mappings between geometric parameters and mechanical properties. Validation using established numerical datasets demonstrates that the standalone INN architecture achieves reconstruction accuracy equal or better than traditional tandem approaches while More >

Kofi Bonsu^*, Olivier Bonin

Revue Internationale de Géomatique, Vol.34, pp. 639-654, 2025, DOI:10.32604/rig.2025.067000 - 11 August 2025

Abstract This study analyzes the spatial accessibility of key services in Caen, France, focusing on how different transport modes (car, bicycle, and public transit) influence access to essential services across the urban and suburban landscape. Indeed, the introduction of traffic restrictions in towns with low emission zones encourages a detailed study, on a fine spatial scale, of the differences in accessibility between different modes of transport, for different services and for different journey times. Using spatial analysis techniques, we examine accessibility patterns in relation to services such as shops, healthcare, education, and tourism, highlighting significant disparities… More >

Dang Hung Tran, Van Tinh Nguyen^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4679-4698, 2025, DOI:10.32604/cmc.2025.063228 - 19 May 2025

Abstract It is known that long non-coding RNAs (lncRNAs) play vital roles in biological processes and contribute to the progression, development, and treatment of various diseases. Obviously, understanding associations between diseases and lncRNAs significantly enhances our ability to interpret disease mechanisms. Nevertheless, the process of determining lncRNA-disease associations is costly, labor-intensive, and time-consuming. Hence, it is expected to foster computational strategies to uncover lncRNA-disease relationships for further verification to save time and resources. In this study, a collaborative filtering and graph attention network-based LncRNA-Disease Association (CFGANLDA) method was nominated to expose potential lncRNA-disease associations. First, it… More >

Eman Alhomaidi¹, Aisha Umar^2,*, Mustansar Mubeen³, Laurent Dufossé⁴, Yasir Iftikhar^3,*, Arpita Das⁵, Soumya Ghosh⁶, Muhammad Sibt-e-Abbas⁷

Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 407-420, 2025, DOI:10.32604/phyton.2025.058035 - 06 March 2025

Abstract Aspergillus species produce aflatoxins and raise concerns about food safety in departmental stores and manufacturing mills. To address the risks posed by aflatoxins, and to advise the public on the highest quality rice that serves as a nutritious food source, an inquiry following the guidelines outlined in both local and international standards of food safety for the presence of aflatoxins is an essential requirement. Therefore, 16 white rice samples were selected randomly from low/high socio-economic departmental stores from 16 different localities. Grind powdered rice filtrate was extracted using chloroform. The filtrate applied on TLC plates and… More > Graphic Abstract

Yao Jin^1,2,*, Jie Zhao^1,2, Xiaozhe Tan^1,2, Linghou Miao^1,2, Wenxing Yu^1,2

Digital Engineering and Digital Twin, Vol.2, pp. 131-144, 2024, DOI:10.32604/dedt.2024.048142 - 31 December 2024

Abstract Substation siting is an important foundation and a key task in power system planning. The article is based on a three-dimensional GIS platform combined with an improved BP neural network algorithm and proposes a substation siting method that is more efficient, accurate and provides a better user experience. Firstly, the BP algorithm is enhanced to improve its convergence speed and computational efficiency for a more accurate and reasonable calculation of optimal site selection. Then, a 24-item selection index system with 7 categories is proposed, which provides quantifiable data support and an evaluation basis for substation… More >

Yanxue Ma¹, Xiaoling Liu^1,*, Bing Wang², Ying Liu¹

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 871-889, 2024, DOI:10.32604/sdhm.2024.052683 - 20 September 2024

Abstract In the bridge technical condition assessment standards, the evaluation of bridge conditions primarily relies on the defects identified through manual inspections, which are determined using the comprehensive hierarchical analysis method. However, the relationship between the defects and the technical condition of the bridges warrants further exploration. To address this situation, this paper proposes a machine learning-based intelligent diagnosis model for the technical condition of highway bridges. Firstly, collect the inspection records of highway bridges in a certain region of China, then standardize the severity of diverse defects in accordance with relevant specifications. Secondly, in order… More >

Guangbing Xiao^*, Ruijie Gu, Ning Sun, Yong Zhang

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1329-1348, 2024, DOI:10.32604/csse.2024.050817 - 13 September 2024

Abstract In response to the challenges posed by insufficient real-time performance and suboptimal matching accuracy of traditional feature matching algorithms within automotive panoramic surround view systems, this paper has proposed a high-performance dimension reduction parallel matching algorithm that integrates Principal Component Analysis (PCA) and Dual-Heap Filtering (DHF). The algorithm employs PCA to map the feature points into the lower-dimensional space and employs the square of Euclidean distance for feature matching, which significantly reduces computational complexity. To ensure the accuracy of feature matching, the algorithm utilizes Dual-Heap Filtering to filter and refine matched point pairs. To further More >

Wei Chen^1,*, Xiaogang Wei^2,*, Hongxu Zhang², Wenpeng He²

Journal on Artificial Intelligence, Vol.6, pp. 225-240, 2024, DOI:10.32604/jai.2024.052366 - 16 August 2024

Abstract The Head-Related Transfer Function (HRTF) describes the effects of sound reflection and scattering caused by the environment and the human body when sound signals are transmitted from a source to the human ear. It contains a significant amount of auditory cue information used for sound localization. Consequently, HRTF renders 3D audio accurately in numerous immersive multimedia applications. Because HRTF is high-dimensional, complex, and nonlinear, it is a relatively large and intricate dataset, typically consisting of hundreds of thousands of samples. Storing HRTF requires a significant amount of storage space in practical applications. Based on this, More >