CHUCHU ZHANG^1,#, YING LIU^2,#, ZEHUI CHEN¹, YI LIU³, QIYUAN MAO⁴, GE ZHANG⁵, HONGSHENG LIN⁴, JIABIN ZHENG^6,*, HAIYAN LI^1,*

Oncology Research, Vol.33, No.6, pp. 1437-1458, 2025, DOI:10.32604/or.2025.059290 - 29 May 2025

Abstract Objectives: Decades of clinical and fundamental research advancements in oncology have led to significant breakthroughs such as early screening, targeted therapies, and immunotherapy, contributing to reduced mortality rates in cancer patients. Despite these achievements, cancer continues to be a major public health challenge. This study employs bibliometric techniques to visually analyze the English literature on cancer prevention, screening, diagnosis, treatment, and rehabilitation. Methods: We systematically reviewed publications from 01 March 2014, to 01 March 2024, indexed in the Web of Science core collection. Tools such as VOSviewer Version 1.6.20 is characterized by its core idea… More > Graphic Abstract

Ali Batouche¹, Souham Meshoul^2,*, Hadil Shaiba³, Mohamed Batouche^2,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1727-1752, 2025, DOI:10.32604/cmc.2025.063227 - 16 April 2025

Abstract The field of biometric identification has seen significant advancements over the years, with research focusing on enhancing the accuracy and security of these systems. One of the key developments is the integration of deep learning techniques in biometric systems. However, despite these advancements, certain challenges persist. One of the most significant challenges is scalability over growing complexity. Traditional methods either require maintaining and securing a growing database, introducing serious security challenges, or relying on retraining the entire model when new data is introduced—a process that can be computationally expensive and complex. This challenge underscores the… More >

Jiming Lan¹, Bo Zeng^1,*, Suiqun Li¹, Weihan Zhang¹, Xinyi Shi²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2865-2888, 2025, DOI:10.32604/cmc.2025.060260 - 16 April 2025

Abstract The Quadric Error Metrics (QEM) algorithm is a widely used method for mesh simplification; however, it often struggles to preserve high-frequency geometric details, leading to the loss of salient features. To address this limitation, we propose the Salient Feature Sampling Points-based QEM (SFSP-QEM)—also referred to as the Deep Learning-Based Salient Feature-Preserving Algorithm for Mesh Simplification—which incorporates a Salient Feature-Preserving Point Sampler (SFSP). This module leverages deep learning techniques to prioritize the preservation of key geometric features during simplification. Experimental results demonstrate that SFSP-QEM significantly outperforms traditional QEM in preserving geometric details. Specifically, for general models… More >

Chen Chen^#,*, Chunli Li^#, Tengfei Li, Qianhong Li, Luyao Li, Fengqin Liu

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 793-807, 2025, DOI:10.32604/phyton.2025.063549 - 31 March 2025

Abstract Lycium ruthenicum Murray, a plant widely cultivated in northwestern China, is integral to traditional Chinese medicine, with applications in treating menstrual disorders, cardiovascular diseases, and menopausal symptoms. Despite its recognized medicinal value and use as a functional food, comprehensive knowledge of its metabolites and their pharmacological effects remains limited. This study presents an innovative approach using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC–QTOF/MS) to conduct a detailed analysis of both wild and cultivated L. ruthenicum samples. A total of 62 peaks were detected in the total ion current profile, with 59 metabolites identified based… More >

Manjit Singh, Sunil Kumar Singla^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3003-3029, 2025, DOI:10.32604/cmes.2025.060863 - 03 March 2025

Abstract Deep Learning-based systems for Finger vein recognition have gained rising attention in recent years due to improved efficiency and enhanced security. The performance of existing CNN-based methods is limited by the puny generalization of learned features and deficiency of the finger vein image training data. Considering the concerns of existing methods, in this work, a simplified deep transfer learning-based framework for finger-vein recognition is developed using an EfficientNet model of deep learning with a self-attention mechanism. Data augmentation using various geometrical methods is employed to address the problem of training data shortage required for a… More > Graphic Abstract

Mariam A. Alotaibi^1,2,*, Sami S. Alwakeel^1,*, Aasem N. Alyahya¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3467-3497, 2025, DOI:10.32604/cmc.2025.060599 - 17 February 2025

Abstract The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics… 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 >

Buchi Reddy Ramakantha Reddy, Ramasamy Lokesh Kumar^*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4081-4107, 2024, DOI:10.32604/cmc.2024.057071 - 19 December 2024

Abstract Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products, leading to suboptimal user experiences. To address this, our study presents a Personalized Adaptive Multi-Product Recommendation System (PAMR) leveraging transfer learning and Bi-GRU (Bidirectional Gated Recurrent Units). Using a large dataset of user reviews from Amazon and Flipkart, we employ transfer learning with pre-trained models (AlexNet, GoogleNet, ResNet-50) to extract high-level attributes from product data, ensuring effective feature representation even with limited data. Bi-GRU captures both spatial and sequential dependencies in user-item interactions. The innovation of this study lies… More >

Yu-Ting Huang^1,#, Daniel Kwasi Ahorsu^2,#, Emma Sethina Adjaottor^3,*, Frimpong-Manso Addo³, Mark D. Griffiths⁴, Amir H. Pakpour⁵, Chung-Ying Lin^1,6,7,8,*

International Journal of Mental Health Promotion, Vol.26, No.11, pp. 875-885, 2024, DOI:10.32604/ijmhp.2024.057049 - 28 November 2024

Abstract Background: The present study evaluated the psychometric properties of Problematic Internet Use (PIU) instruments and their correlation with psychological distress and time spent on Internet activities among university students in Ghana. Methods: In the present cross-sectional survey design study, 520 participants (35.96% female) were recruited with a mean age of 19.55 years (SD = 1.94) from several university departments (i.e., Behavioral Sciences, Materials Engineering, Nursing and Midwifery, and Biochemistry and Biotechnology) of Kwame Nkrumah University of Science and Technology (KNUST) between 19 July and 04 August, 2023. Participants completed a survey that included the following… More >

Petrayuna Dian Omega¹, Joniarto Parung^1,*, Listyo Yuwanto¹, Yuh-Shan Ho^2,*

International Journal of Mental Health Promotion, Vol.26, No.10, pp. 817-836, 2024, DOI:10.32604/ijmhp.2024.056501 - 31 October 2024

Abstract Background: This study aimed to conduct a bibliometric analysis of positive mental health, focusing on citation performance, article title, abstract, author keywords, Keyword Plus, and their development trends. The novelty of this study is a pioneer within the field of positive mental health. Therefore, it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years. Methods: The data were retrieved on 30 April 2024 from the Social Sciences Citation Index (SSCI) of Clarivate Analytics’ Web of… More >