Xiaofang Kang^1,2,*, Qiwen Huang¹, Zongqin Wu¹, Jianjun Tang¹, Xueqin Jiang¹, Shancheng Lei³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2361-2398, 2024, DOI:10.32604/cmes.2023.043936

Abstract Tuned mass damper inerter (TMDI) is a device that couples traditional tuned mass dampers (TMD) with an inertial device. The inertial device produces resistance proportional to the relative acceleration at its two ends through its “inertial” constant. Due to its unique mechanical properties, TMDI has received widespread attention and application in the past twenty years. As different configurations are required in different practical situations, TMDI is still active in the research on vibration control and energy harvesting in structures. This paper provides a comprehensive review of the research status of TMDI. This work first examines the generation and important vibration… More >

Ming Liu¹, Pinghua Zhu^2,*, Xiancui Yan², Haichao Li², Xintong Chen²

Journal of Renewable Materials, Vol.12, No.2, pp. 329-347, 2024, DOI:10.32604/jrm.2023.045381

Abstract As socioeconomic development continues, the issue of building energy consumption has attracted significant attention, and improving the thermal insulation performance of buildings has become a crucial strategic measure. Simultaneously, the application of solid waste in insulation materials has also become a hot topic. This paper reviews the sources and classifications of solid waste, focusing on research progress in its application as insulation materials in the domains of daily life, agriculture, and industry. The research shows that incorporating household solid waste materials, such as waste glass, paper, and clothing scraps into cementitious thermal insulation can significantly reduce the thermal conductivity of… More >

Xinlong Diao, Xiao Wang^*, Junkang Qin, Qinmu Wu, Zhiqin He, Xinghong Fan

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2617-2665, 2024, DOI:10.32604/cmc.2024.047377

Abstract In recent years, Artificial Intelligence (AI) has revolutionized people’s lives. AI has long made breakthrough progress in the field of surgery. However, the research on the application of AI in orthopedics is still in the exploratory stage. The paper first introduces the background of AI and orthopedic diseases, addresses the shortcomings of traditional methods in the detection of fractures and orthopedic diseases, draws out the advantages of deep learning and machine learning in image detection, and reviews the latest results of deep learning and machine learning applied to orthopedic image detection in recent years, describing the contributions, strengths and weaknesses,… More >

Asma Hassan Alshehri^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2767-2786, 2024, DOI:10.32604/cmc.2023.046838

Abstract Online review platforms are becoming increasingly popular, encouraging dishonest merchants and service providers to deceive customers by creating fake reviews for their goods or services. Using Sybil accounts, bot farms, and real account purchases, immoral actors demonize rivals and advertise their goods. Most academic and industry efforts have been aimed at detecting fake/fraudulent product or service evaluations for years. The primary hurdle to identifying fraudulent reviews is the lack of a reliable means to distinguish fraudulent reviews from real ones. This paper adopts a semi-supervised machine learning method to detect fake reviews on any website, among other things. Online reviews… More >

Paramjeet Kaur¹, Krishna Teerth Chaturvedi¹, Mohan Lal Kolhe^2,*

Energy Engineering, Vol.121, No.3, pp. 557-579, 2024, DOI:10.32604/ee.2024.043159

Abstract In the increasingly decentralized energy environment, economical power dispatching from distributed generations (DGs) is crucial to minimizing operating costs, optimizing resource utilization, and guaranteeing a consistent and sustainable supply of electricity. A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability. The choice of optimization technique for economic power dispatching from DGs depends on a number of factors, such as the size and complexity of the power system, the availability of computational resources, and the specific requirements of the… More >

ELHAM AMJAD¹, RAFFAELE PEZZANI^2,3,*, BABAK SOKOUTI^1,*

Oncology Research, Vol.32, No.3, pp. 439-461, 2024, DOI:10.32604/or.2023.044473

Abstract Noncoding RNAs instruct the Cas9 nuclease to site-specifically cleave DNA in the CRISPR/Cas9 system. Despite the high incidence of hepatocellular carcinoma (HCC), the patient’s outcome is poor. As a result of the emergence of therapeutic resistance in HCC patients, clinicians have faced difficulties in treating such tumor. In addition, CRISPR/Cas9 screens were used to identify genes that improve the clinical response of HCC patients. It is the objective of this article to summarize the current understanding of the use of the CRISPR/Cas9 system for the treatment of cancer, with a particular emphasis on HCC as part of the current state… More >

XIN MENG^*, YAN LIU, SHUJUN XU, LIANRONG YANG, RUI YIN

BIOCELL, Vol.48, No.1, pp. 65-78, 2024, DOI:10.32604/biocell.2023.045986

Abstract Over the past decade, the swift advancement of metabolomics can be credited to significant progress in technologies such as mass spectrometry, nuclear magnetic resonance, and multivariate statistics. Currently, metabolomics garners widespread application across diverse fields including drug research and development, early disease detection, toxicology, food and nutrition science, biology, prescription, and chinmedomics, among others. Metabolomics serves as an effective characterization technique, offering insights into physiological process alterations in vivo. These changes may result from various exogenous factors like environmental conditions, stress, medications, as well as endogenous elements including genetic and protein-based influences. The potential scientific outcomes gleaned from these insights… More > Graphic Abstract

YANG LI^1,2, JIAN LIU^1,3,*, YUEDI HU^1,2, CHENGZHI CONG^1,2, YIMING CHEN^1,2, QIAO ZHOU^1,2

BIOCELL, Vol.48, No.1, pp. 9-19, 2024, DOI:10.32604/biocell.2023.045862

Abstract Rheumatoid arthritis (RA) is a prevalent autoimmune disease whose main features include chronic synovial inflammation, bone destruction, and joint degeneration. Neutrophils are often considered to be the first responders to inflammation and are a key presence in the inflammatory milieu of RA. Neutrophil extracellular traps (NETs), a meshwork of DNA-histone complexes and proteins released by activated neutrophils, are widely involved in the pathophysiology of autoimmune diseases, especially RA, in addition to playing a key role in the neutrophil innate immune response. NETs have been found to be an important source of citrullinated autoantigen antibodies and inflammatory factor release, which can… More > Graphic Abstract

Sunil Kumar¹, Dilip Kumar¹, Ramraj Dangi², Gaurav Choudhary³, Nicola Dragoni⁴, Ilsun You^5,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 31-63, 2024, DOI:10.32604/cmc.2023.047084

Abstract The widespread and growing interest in the Internet of Things (IoT) may be attributed to its usefulness in many different fields. Physical settings are probed for data, which is then transferred via linked networks. There are several hurdles to overcome when putting IoT into practice, from managing server infrastructure to coordinating the use of tiny sensors. When it comes to deploying IoT, everyone agrees that security is the biggest issue. This is due to the fact that a large number of IoT devices exist in the physical world and that many of them have constrained resources such as electricity, memory,… More >

Xiaozhong Yu^1,2,*, Jinhua Zheng^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 197-225, 2024, DOI:10.32604/cmc.2023.043943

Abstract In rice production, the prevention and management of pests and diseases have always received special attention. Traditional methods require human experts, which is costly and time-consuming. Due to the complexity of the structure of rice diseases and pests, quickly and reliably recognizing and locating them is difficult. Recently, deep learning technology has been employed to detect and identify rice diseases and pests. This paper introduces common publicly available datasets; summarizes the applications on rice diseases and pests from the aspects of image recognition, object detection, image segmentation, attention mechanism, and few-shot learning methods according to the network structure differences; and… More >