Dan Wang, Jihuan Song, Qiyuan Wang, Chenmeng Cui, Ying Yang^*

Journal of Renewable Materials, Vol.13, No.1, pp. 49-78, 2025, DOI:10.32604/jrm.2024.056644 - 20 January 2025

Abstract Upgrading of abundant cellulosic biomass to isosorbide can reduce the dependence on limited fossil resources and provide a sustainable way to produce isosorbide, utilized for polymers, medicine and health care product synthesis. This review comprehensively examines the key steps and catalytic systems involved in the conversion of cellulose to isosorbide. Initially, the reaction pathway from cellulose to isosorbide is elucidated, emphasizing three critical steps: cellulose hydrolysis, glucose hydrogenation, and the two-step dehydration of sorbitol to produce isosorbide. Additionally, the activation energy and acidic sites during cellulose hydrolysis, the impact of metal particle size and catalyst More >

Ghulam E Mustafa Abro^1,*, Ayman M Abdallah^1,2, Faizan Zahid³, Saleem Ahmed⁴

Intelligent Automation & Soft Computing, Vol.40, pp. 99-123, 2025, DOI:10.32604/iasc.2025.060364 - 23 January 2025

Abstract This review synthesises and assesses the most recent developments in Unmanned Aerial Vehicles (UAVs) and swarm robotics, with a specific emphasis on optimisation strategies, path planning, and formation control. The study identifies key methodologies that are driving progress in the field by conducting a comprehensive analysis of seven critical publications. The following are included: sensor-based platforms that facilitate effective obstacle avoidance, cluster-based hierarchical path planning for efficient navigation, and adaptive hybrid controllers for dynamic environments. The review emphasises the substantial contribution of optimisation techniques, including Max-Min Ant Colony Optimisation (MMACO), to the improvement of convergence… More >

MARTA SANTOS¹, DIANA MARTINS^1,2,3,4, FERNANDO MENDES^1,2,3,4,5,*

Oncology Research, Vol.33, No.2, pp. 263-281, 2025, DOI:10.32604/or.2024.052207 - 16 January 2025

Abstract Background: Gastric Cancer (GC) is the 5th most prevalent and 4th most deadly neoplasm globally. Immunotherapy has emerged as a promising treatment approach in GC, potentially improving positive clinical outcomes while addressing the limitations of conventional therapies. GC immunotherapy modalities consist of adoptive cell therapy (ACT), cancer vaccines, and immune checkpoint inhibitors (ICI). Objectives: This systematic review aims to provide an overview of the advances in immune-based therapeutic approaches in GC, highlighting the potential of this therapy as a strategy for GC treatment. Methods: Key studies investigating several immunotherapeutic agents and combination therapies were searched in… More > Graphic Abstract

Chengquan Wang^1,2, Lei Xu³, Xinquan Wang¹, Yun Zou^3,*, Kangyu Wang⁴, Boyan Ping⁵, Xiao Li¹

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 233-263, 2025, DOI:10.32604/sdhm.2024.055096 - 15 January 2025

Abstract Kinked rebar is a special type of steel material, which is installed in beam column nodes and frame beams. It effectively enhances the blast resilience, seismic collapse resistance, and progressive collapse resistance of reinforced concrete (RC) structures without imposing substantial cost burdens, thereby emerging as a focal point of recent research endeavors. On the basis of explaining the working principle of kinked rebars, this paper reviews the research status of kinked rebars at home and abroad from three core domains: the tensile mechanical properties of kinked rebars, beam column nodes with kinked rebars, and concrete… More >

Prabal Shrestha¹, Onur Avci^1,*, Sahabeddin Rifai¹, Feras Abla¹, Michael Seek², Karl Barth¹, Udaya Halabe³

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 193-231, 2025, DOI:10.32604/sdhm.2024.049530 - 15 January 2025

Abstract Civil infrastructure is continuously subject to aging and deterioration due to multiple factors, which lead to a decline in performance and impact structural health. Accumulated damage on structures increases operational costs and poses significant risks to public safety. Effective maintenance, repair, and rehabilitation strategies are needed to ensure civil infrastructure’s overall safety and reliability. Non-Destructive Evaluation (NDE) methods are utilized to assess latent damage and provide decision-makers with real-time information for mitigating hazards. Within the last decade, there has been a significant increase in the research and development of innovative NDE techniques to improve data… More >

Nahed Alsaleh^1,2, Reem Alnanih^1,*, Nahed Alowidi¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 949-976, 2025, DOI:10.32604/cmc.2024.059351 - 03 January 2025

Abstract App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products. Automating the analysis of these reviews is vital for efficient review management. While traditional machine learning (ML) models rely on basic word-based feature extraction, deep learning (DL) methods, enhanced with advanced word embeddings, have shown superior performance. This research introduces a novel aspect-based sentiment analysis (ABSA) framework to classify app reviews based on key non-functional requirements, focusing on usability factors: effectiveness, efficiency, and satisfaction. We propose a hybrid DL model, combining BERT (Bidirectional Encoder Representations from Transformers) More >

Jinlong Wang^1,2,*, Zhenyu Liu¹, Xingtao Yang¹, Min Li¹, Zhihan Lyu³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1-39, 2025, DOI:10.32604/cmc.2024.058926 - 03 January 2025

Abstract With the rapid development of artificial intelligence, the Internet of Things (IoT) can deploy various machine learning algorithms for network and application management. In the IoT environment, many sensors and devices generate massive data, but data security and privacy protection have become a serious challenge. Federated learning (FL) can achieve many intelligent IoT applications by training models on local devices and allowing AI training on distributed IoT devices without data sharing. This review aims to deeply explore the combination of FL and the IoT, and analyze the application of federated learning in the IoT from More >

Amjad Rehman¹, Muhammad Mujahid¹, Alex Elyassih¹, Bayan AlGhofaily¹, Saeed Ali Omer Bahaj^2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 41-72, 2025, DOI:10.32604/cmc.2024.058036 - 03 January 2025

Abstract In computer vision and artificial intelligence, automatic facial expression-based emotion identification of humans has become a popular research and industry problem. Recent demonstrations and applications in several fields, including computer games, smart homes, expression analysis, gesture recognition, surveillance films, depression therapy, patient monitoring, anxiety, and others, have brought attention to its significant academic and commercial importance. This study emphasizes research that has only employed facial images for face expression recognition (FER), because facial expressions are a basic way that people communicate meaning to each other. The immense achievement of deep learning has resulted in a… More >

Hassan Saeed¹, Imran Shafi¹, Jamil Ahmad², Adnan Ahmed Khan³, Tahir Khurshaid^4,*, Imran Ashraf^5,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 139-172, 2025, DOI:10.32604/cmc.2024.057587 - 03 January 2025

Abstract Software-related security aspects are a growing and legitimate concern, especially with 5G data available just at our palms. To conduct research in this field, periodic comparative analysis is needed with the new techniques coming up rapidly. The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle (SDLC) by analyzing the articles published in the last two decades and to propose a way forward. This review follows Kitchenham’s review protocol. The review has been divided into three main stages including planning, execution, and analysis.… More >

Millenium Wong¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, Vol.122, No.1, pp. 1-39, 2025, DOI:10.32604/ee.2024.056707 - 27 December 2024

Abstract A hydrogen energy storage system (HESS) is one of the many rising modern green innovations, using excess energy to generate hydrogen and storing it for various purposes. With that, there have been many discussions about commercializing HESS and improving it further. However, the design and sizing process can be overwhelming to comprehend with various sources to examine, and understanding optimal design methodologies is crucial to optimize a HESS design. With that, this review aims to collect and analyse a wide range of HESS studies to summarise recent studies. Two different collections of studies are studied,… More >