Hauwau Kaoje^1,2, Adekunle Adeleke^2,3,*, Esther Anosike-Francis^2,3, Seun Jesuloluwa^2,3, Temitayo Ogedengbe^2,3, Hauwa Rasheed², Jude Okolie⁴

Journal of Renewable Materials, Vol.13, No.12, pp. 2375-2430, 2025, DOI:10.32604/jrm.2025.02025-0109 - 23 December 2025

Abstract The increasing need for sustainable energy and the environmental impacts of reliance on fossil fuels have sparked greater interest in biomass as a renewable energy source. This review provides an in-depth assessment of bio-oil and biochar generation through the pyrolysis of sawdust, a significant variety of lignocellulosic biomass. The paper investigates different thermochemical conversion methods, including fast, slow, catalytic, flash, and co-pyrolysis, while emphasizing their operational parameters, reactor designs, and effects on product yields. The influence of temperature, heating rate, and catalysts on enhancing the quality and quantity of bio-oil and biochar is thoroughly analyzed. More > Graphic Abstract

Qi Chen^1,2, Yizhuo Du¹, Yingsheng Liu¹, Yue Li¹, Chuang Li¹, Zhelun Xu^1,3, Congyan Wang^1,4,5,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2873-2891, 2025, DOI:10.32604/phyton.2025.065970 - 30 September 2025

Abstract The leaves of multiple invasive plants can coexist and intermingle within the same environment. As species number of invasive plants increases, variations may occur in decomposition processes of invasive plants, soil nutrient contents, soil enzyme activities, and soil microbial community structure. Existing progress have predominantly focused on the ecological effects of one species of invasive plant compared to native species, with limited attention paid to the ecological effects of multiple invasive plants compared to one species of invasive plant. This study aimed to determine the differences in the effects of mono- and co-decomposition of four… More >

Seungmin Lee¹, Beomseong Kim², Heesung Lee^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1397-1415, 2025, DOI:10.32604/cmc.2025.066152 - 09 June 2025

Abstract This study proposes an advanced vision-based technology for detecting glass products and identifying defects in a smart glass factory production environment. Leveraging artificial intelligence (AI) and computer vision, the research aims to automate glass detection processes and maximize production efficiency. The primary focus is on developing a precise glass detection and quality management system tailored to smart manufacturing environments. The proposed system utilizes the various YOLO (You Only Look Once) models for glass detection, comparing their performance to identify the most effective architecture. Input images are preprocessed using a Gaussian Mixture Model (GMM) to remove… More >

Pu Yang^1,*, Wanning Yan¹, Rong Li¹, Lei Chen², Lijie Guo²

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 699-725, 2025, DOI:10.32604/cmc.2025.064947 - 09 June 2025

Abstract Lithium-ion batteries (LIBs) have been widely used in mobile energy storage systems because of their high energy density, long life, and strong environmental adaptability. Accurately estimating the state of health (SOH) for LIBs is promising and has been extensively studied for many years. However, the current prediction methods are susceptible to noise interference, and the estimation accuracy has room for improvement. Motivated by this, this paper proposes a novel battery SOH estimation method, the Beluga Whale Optimization (BWO) and Noise-Input Gaussian Process (NIGP) Stacked Model (BGNSM). This method integrates the BWO-optimized Gaussian Process Regression (GPR)… More >

Sirawit Makaew, Yupaporn Areepong^*, Saowanit Sukparungsee

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1617-1634, 2025, DOI:10.32604/cmes.2025.063459 - 30 May 2025

Abstract This study aims to examine the explicit solution for calculating the Average Run Length (ARL) on the triple exponentially weighted moving average (TEWMA) control chart applied to autoregressive model (AR(p)), where AR(p) is an autoregressive model of order p, representing a time series with dependencies on its p previous values. Additionally, the study evaluates the accuracy of both explicit and numerical integral equation (NIE) solutions for AR(p) using the TEWMA control chart, focusing on the absolute percentage relative error. The results indicate that the explicit and approximate solutions are in close agreement. Furthermore, the study More >

Lianqiang Wu, Deming Lei^*, Yutong Cai

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1771-1789, 2025, DOI:10.32604/cmc.2025.063944 - 16 April 2025

Abstract Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines (BPM). In this study, the parallel BPM scheduling problem with machine eligibility in fabric dyeing is considered, and an adaptive cooperated shuffled frog-leaping algorithm (ACSFLA) is proposed to minimize makespan and total tardiness simultaneously. ACSFLA determines the search times for each memeplex based on its quality, with more searches in high-quality memeplexes. An adaptive cooperated and diversified search mechanism is applied, dynamically adjusting search strategies for each memeplex based on their dominance relationships and quality. During the… More >

Liang Zhou¹, Qiyao Hu^1,2,3,*, Xianlin Peng^4,5, Qianlong Liu⁶

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2375-2401, 2025, DOI:10.32604/cmc.2025.061894 - 16 April 2025

Abstract Over 1.3 million people die annually in traffic accidents, and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems. In modern industrial and technological applications and collaborative edge intelligence, control systems are crucial for ensuring efficiency and safety. However, deficiencies in these systems can lead to significant operational risks. This paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control, particularly the limitations of traditional Proportional-Integral-Derivative (PID) controllers in managing nonlinear and time-varying dynamics, such as varying road conditions… More >

AUGUSTO FUSCO¹, STEFANO BONOMI^2,*, LUCA PADUA^1,2

BIOCELL, Vol.49, No.1, pp. 1-5, 2025, DOI:10.32604/biocell.2024.058418 - 24 January 2025

Abstract Connective tissue is a dynamic structure that reacts to environmental cues to maintain homeostasis, including mechanical properties. Mechanical load influences extracellular matrix (ECM)—cell interactions and modulates cellular behavior. Mechano-regulation processes involve matrix modification and cell activation to preserve tissue function. The ECM remodeling is crucial for force transmission. Cytoskeleton components are involved in force sensing and transmission, affecting cellular adhesion, motility, and gene expression. Proper mechanical loading helps to maintain tissue health, while imbalances may lead to pathological processes. Active and passive movement, including manual mobilization, improves connective tissue elasticity, promotes ECM-cell homeostasis, and More > Graphic Abstract

Verónica C. Tapia^1,2,*, Carlos M. Gaona²

Computer Systems Science and Engineering, Vol.49, pp. 1-17, 2025, DOI:10.32604/csse.2024.056979 - 03 January 2025

Abstract In recent years, automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market. The integration of artificial intelligence (AI) tools, particularly those using natural language processing (NLP) like ChatGPT, has opened new possibilities for automating various stages of the development lifecycle. The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development. An artificial intelligence (AI) tool was developed using the OpenAI—Application Programming Interface (API), incorporating two key functionalities: 1) generating user stories based on case or process… More >

Jie Lin^*, Hongchi Shen, Tingting Pei, Yan Wu

Energy Engineering, Vol.122, No.1, pp. 331-347, 2025, DOI:10.32604/ee.2024.055611 - 27 December 2024

Abstract Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unit power generation costs. The service life of these modules directly affects these costs. Over time, the performance of PV modules gradually declines due to internal degradation and external environmental factors. This cumulative degradation impacts the overall reliability of photovoltaic power generation. This study addresses the complex degradation process of PV modules by developing a two-stage Wiener process model. This approach accounts for the distinct phases of degradation resulting from module aging and environmental influences. A power degradation model based on the More > Graphic Abstract