Jiamin Huang^1,2, Ping Wu^2,*, Wangxin Li³, Jun Zhang², Yidong Xu²

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 577-598, 2024, DOI:10.32604/sdhm.2024.050338

Abstract With the advent of the big data era and the rise of Industrial Revolution 4.0, digital twins (DTs) have gained significant attention in various industries. DTs offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering industry. In this paper, 605 documents obtained from the search were first analysed using CiteSpace for literature visualisation, and an author co-occurrence network, a keyword co-occurrence network, and a keyword clustering set were obtained. Next, through a literature review of 86 papers, this paper summarises the current status of DT More >

S. F. Ismael^1,2,*, A. H. Alias¹, N. A. Haron¹, B. B. Zaidan³, Abdulrahman M. Abdulghani⁴

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 525-551, 2024, DOI:10.32604/sdhm.2024.050088

Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

Yaqiong He, Jinlin Fan^*, Huaiguang Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 995-1032, 2024, DOI:10.32604/cmc.2024.052887

Abstract With the rise of blockchain technology, the security issues of smart contracts have become increasingly critical. Despite the availability of numerous smart contract vulnerability detection tools, many face challenges such as slow updates, usability issues, and limited installation methods. These challenges hinder the adoption and practicality of these tools. This paper examines smart contract vulnerability detection tools from 2016 to 2023, sourced from the Web of Science (WOS) and Google Scholar. By systematically collecting, screening, and synthesizing relevant research, 38 open-source tools that provide installation methods were selected for further investigation. From a developer’s perspective,… More >

Jiawen Li^1,2, Yuesheng Huang¹, Yayi Lu¹, Leijun Wang^1,*, Yongqi Ren¹, Rongjun Chen¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1581-1599, 2024, DOI:10.32604/cmc.2024.052666

Abstract In the context of the accelerated pace of daily life and the development of e-commerce, online shopping is a mainstream way for consumers to access products and services. To understand their emotional expressions in facing different shopping experience scenarios, this paper presents a sentiment analysis method that combines the e-commerce review keyword-generated image with a hybrid machine learning-based model, in which the Word2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence (AI). Subsequently, a hybrid Convolutional Neural Network and Support Vector Machine (CNN-SVM) model… More >

Nidhi Parashar¹, Prashant Johri¹, Arfat Ahmad Khan⁵, Nitin Gaur¹, Seifedine Kadry^2,3,4,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 389-425, 2024, DOI:10.32604/cmc.2024.050240

Abstract The growing global requirement for food and the need for sustainable farming in an era of a changing climate and scarce resources have inspired substantial crop yield prediction research. Deep learning (DL) and machine learning (ML) models effectively deal with such challenges. This research paper comprehensively analyses recent advancements in crop yield prediction from January 2016 to March 2024. In addition, it analyses the effectiveness of various input parameters considered in crop yield prediction models. We conducted an in-depth search and gathered studies that employed crop modeling and AI-based methods to predict crop yield. The… More >

Adelya Khayrova^*, Sergey Lopatin, Valery Varlamov

Journal of Renewable Materials, Vol.12, No.5, pp. 923-950, 2024, DOI:10.32604/jrm.2024.050033

Abstract Due to the expected rise in the world population, an increase in the requirements for quality and safety of food and feed is expected, which leads to the growing demand for new sources of sustainable and renewable protein. Insect protein is gaining importance as a renewable material for several reasons, reflecting its potential contributions to sustainability, resource efficiency, and environmental conservation. Some insect species are known to be able to efficiently convert organic waste into high-value products such as protein, requiring less land and water compared to traditional livestock. In addition, insect farming produces fewer… More > Graphic Abstract

DIMITRA P. VAGELI^1,2,*, PANAGIOTIS G. DOUKAS³, KERASIA GOUPOU², ANTONIOS D. BENOS², KYRIAKI ASTARA^2,4, KONSTANTINA ZACHAROULI², SOTIRIS SOTIRIOU⁵, MARIA IOANNOU²

Oncology Research, Vol.32, No.8, pp. 1239-1256, 2024, DOI:10.32604/or.2024.052130

Abstract Glioblastoma multiforme (GBM) is an aggressive primary brain tumor characterized by extensive heterogeneity and vascular proliferation. Hypoxic conditions in the tissue microenvironment are considered a pivotal player leading tumor progression. Specifically, hypoxia is known to activate inducible factors, such as hypoxia-inducible factor 1alpha (HIF-1α), which in turn can stimulate tumor neo-angiogenesis through activation of various downward mediators, such as the vascular endothelial growth factor (VEGF). Here, we aimed to explore the role of HIF-1α/VEGF immunophenotypes alone and in combination with other prognostic markers or clinical and image analysis data, as potential biomarkers of GBM prognosis… More >

ANA S. CVETANOVIC^1,2,*, MATTEO LAMBERTINI^3,4, KEVIN PUNIE⁵, GORANA G. MATOVINA BRKO⁶, NIKOLA D. ZIVKOVIC^7,8, MAJA J. POPOVIC^6,9, MARIJANA M. MILOVIC KOVACEVIC¹⁰, LAZAR S. POPOVIC^6,9

Oncology Research, Vol.32, No.8, pp. 1309-1322, 2024, DOI:10.32604/or.2024.049743

Abstract Oncofertility is an extremely significant topic that is increasingly being discussed owing to increased evidence indicating that fertility preservation does not affect the treatment outcomes of patients with cancer but significantly contributes to preserving life quality. The effect of chemotherapy can range from minimal effects to complete ovarian atrophy. Limited data are available on the effects of monoclonal antibodies and targeted therapies on the ovaries and fertility. Temporary ovarian suppression by administering a gonadotropin-releasing hormone agonist (GnRHa) during chemotherapy decreases the gonadotoxic effect of chemotherapy, thereby diminishing the chance of developing premature ovarian insufficiency (POI).… More > Graphic Abstract

Qasem Abu Al-Haija^1,*, Sara Othman Al-Salameen²

Computer Systems Science and Engineering, Vol.48, No.4, pp. 897-914, 2024, DOI:10.32604/csse.2024.050846

Abstract The paper discusses the importance of biometric verification systems in mobile environments and highlights the challenges and strategies used to overcome them in order to ensure the security of mobile devices. Emphasis is placed on evaluating the impact of illumination on the performance of biometric verification techniques and how to address this challenge using image processing techniques. The importance of accurate and reliable data collection to ensure the accuracy of verification processes is also discussed. The paper also highlights the importance of improving biometric verification techniques and directing research toward developing models aimed at reducing More >

Tahir Abbas^1,*, Ali Haider Khan², Khadija Kanwal³, Ali Daud^4,*, Muhammad Irfan⁵, Amal Bukhari⁶, Riad Alharbey⁶

Computer Systems Science and Engineering, Vol.48, No.4, pp. 871-895, 2024, DOI:10.32604/csse.2024.049026

Abstract The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The More >