A. NOEL GRAVINA^1,2, NOELIA D´ELÍA^1,2, LUCIANO A. BENEDINI^2,3,*, PAULA MESSINA^1,2

BIOCELL, Vol.48, No.11, pp. 1517-1520, 2024, DOI:10.32604/biocell.2024.055513 - 07 November 2024

Abstract This article navigates the relationship between biomaterials and osteogenic cell adhesion, highlighting the importance of mimicking the physiological response for bone tissue regeneration. Within this spirit is an initial description of the interaction between osteoblasts and osteoprogenitor cells with the extracellular matrix, explaining the leading role of integrins and cadherins in cell adhesion, and the intracellular signaling pathways elicited. Additionally, there is a focus on the strategies of advanced biomaterials that foster osteogenesis by replicating the native environment, taking advantage of these known specific signaling pathways. The final remarks lay on the need for careful More >

Yu Gong^1,*, Jianyu Zhang¹, Libin Zhao², Ning Hu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011451

Abstract Advanced carbon fiber reinforced composite materials are increasingly being used in aerospace and other fields. Composite laminate structure is one of the commonly used configurations, but due to weak interlayer performance, interlayer delamination is prone to occur [1]. The occurrence and growth of delamination will seriously affect the overall integrity and safety of composite structures, making it a focus of attention in the design of laminated structures. Accurately characterizing the delamination mechanical properties of composite laminates and simulating delamination propagation behavior is the basis for damage tolerance design and analysis of composite structures with delamination… More >

Lizheng Zhang^1,2, Jimin Chen^1,2,*, Yong Zeng^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011127

Abstract In laser powder bed fusion (LPBF), the unmelted powder recovered from the powder bed is degraded due to particle-laser interaction during continuous processing. The sensitivity of LPBF performance and molding quality to powder properties, waste powder is usually discarded after several molding cycles, which increases the cost of raw materials. At the same time, the low laser absorption rate and high thermal conductivity of copper and copper alloys inhibit the complete melting of copper powder prepared by LPBF. Therefore, it is challenging to fabricate copper alloy components with full high density and high conductivity through… More >

Chentong Zhao¹, Jiming Zhou^1,2,*, Xujiang Chao^1,3, Su Wang¹, Lehua Qi^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2453-2469, 2024, DOI:10.32604/cmes.2024.052723 - 31 October 2024

Abstract The mechanical properties of graphene reinforced composites are often hampered by challenges related to the dispersion and aggregation of graphene within the matrix. This paper explores the mechanism of cooling rate, process temperature, and process pressure’s influence on the agglomeration behavior of graphene and the tensile response of composites from a computer simulation technology, namely molecular dynamics. Our findings reveal that the cooling rate exerts minimal influence on the tensile response of composites. Conversely, processing temperature significantly affects the degree of graphene aggregation, with higher temperatures leading to the formation of larger-sized graphene clusters. In More >

Run Yang^1,2,3, Yanping Chen^1,2,3,*, Jiaxin Yan^1,2,3, Yongbin Qin^1,2,3

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4129-4147, 2024, DOI:10.32604/cmc.2024.051675 - 12 September 2024

Abstract The relation is a semantic expression relevant to two named entities in a sentence. Since a sentence usually contains several named entities, it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities. In related work, graph convolutional neural networks are widely adopted to learn semantic dependencies, where a dependency tree initializes the adjacency matrix. However, this approach has two main issues. First, parsing a sentence heavily relies on external toolkits, which can be error-prone. Second, the dependency tree only encodes the syntactical structure of a sentence,… More >

R. Mahaveerakannan¹, Thanarajan Tamilvizhi^2,*, Sonia Jenifer Rayen³, Osamah Ibrahim Khalaf⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3945-3966, 2024, DOI:10.32604/cmc.2024.051611 - 12 September 2024

Abstract The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content. In light of the data-centric aspect of contemporary communication, the information-centric network (ICN) paradigm offers hope for a solution by emphasizing content retrieval by name instead of location. If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things (IoT) devices, then effective caching solutions will be required to maximize network throughput and minimize the use of resources. Hence, an ICN-based Cooperative Caching (ICN-CoC) technique has been used to select… More >

Ahmed Mustaffa Saleem, Abdullah A. Badr, Bahjat Hassan Alyas, Omar Rafae Alomar^*

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1231-1244, 2024, DOI:10.32604/fhmt.2024.053770 - 30 August 2024

Abstract This study numerically involves the performance of thermal insulation of different types of composite walls and roofs to demonstrate the best model that can be used for energy-efficient building construction in Iraq. The mathematical model is solved by building its code using the Transmission Matrix Method in MATLAB software. The weather data of 21st July 2022 in Baghdad City/Iraq is selected as a test day. The wall types are selected: the first type consists of cement mortar, brick, and gypsum, the second type consists of cement mortar, brick, gypsum, and plaster and the third type… More >

Jing Zhang^*, Guangli Wu, Shanshan Song

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1947-1965, 2024, DOI:10.32604/cmc.2024.051781 - 15 August 2024

Abstract Video summarization aims to select key frames or key shots to create summaries for fast retrieval, compression, and efficient browsing of videos. Graph neural networks efficiently capture information about graph nodes and their neighbors, but ignore the dynamic dependencies between nodes. To address this challenge, we propose an innovative Adaptive Graph Convolutional Adjacency Matrix Network (TAMGCN), leveraging the attention mechanism to dynamically adjust dependencies between graph nodes. Specifically, we first segment shots and extract features of each frame, then compute the representative features of each shot. Subsequently, we utilize the attention mechanism to dynamically adjust More >

Jieren Cheng^1,3, Jimei Li^1,3,*, Faqiang Zeng^1,3, Zhicong Tao^1,3, Yue Yang^2,3

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 281-298, 2024, DOI:10.32604/cmc.2024.051816 - 18 July 2024

Abstract Contrastive learning is a significant research direction in the field of deep learning. However, existing data augmentation methods often lead to issues such as semantic drift in generated views while the complexity of model pre-training limits further improvement in the performance of existing methods. To address these challenges, we propose the Efficient Clustering Network based on Matrix Factorization (ECN-MF). Specifically, we design a batched low-rank Singular Value Decomposition (SVD) algorithm for data augmentation to eliminate redundant information and uncover major patterns of variation and key information in the data. Additionally, we design a Mutual Information-Enhanced More >

MINGYUE HUANG^1,#, JUNFEI DAI^1,#, XIANLIANG ZHONG², JIN WANG², JIANZHONG XU², BO DU^2,*

BIOCELL, Vol.48, No.6, pp. 889-896, 2024, DOI:10.32604/biocell.2024.050097 - 10 June 2024

Abstract Chronic subdural hematoma (CSDH) is a disease characterized by capsuled blood products that progressively occupy the intracranial space, causing intracranial hypertension and compression in the brain. CSDH frequently occurs in all demographics, especially in the elderly, but the pathogenesis of CSDH remains unclear. In this review, we discuss the origin, development, and current treatment strategies of CSDH. For the first time, we analyzed the cellular and molecular compositions of hematoma membranes with a focus on neomembrane formation, a complex early-stage interactive event in hematoma pathogenesis. We hypothesize that in patients with CSDH, dural border cells… More >