KAIWEN TIAN^#, HANZHONG CHEN^#, QIANQIAN WANG, FENGLIAN JIANG, CHUNXIANG FENG, TENG LI, XIAOYONG PU, YANLIN TANG^*, JIUMIN LIU^*

BIOCELL, Vol.48, No.5, pp. 817-834, 2024, DOI:10.32604/biocell.2024.048737

Abstract Background: The incidence of clear cell renal cell carcinoma (ccRCC) is globally high; however, despite the introduction of innovative drug therapies, there remains a lack of effective biomarkers for evaluating treatment response. Recently, Caspase recruiting domain-containing protein 11 (CARD11) has garnered attention due to its significant association with tumor development and the immune system. Methods: The expression of CARD11 mRNA and protein in ccRCC were analyzed by public database and immunohistochemistry. The focus of this study is on the epigenomic modifications of CARD11, its expression of ccRCC immunophenotype, and its correlation with response to immunotherapy… More > Graphic Abstract

Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction… More >

Mohammed Alatiyyah^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 875-907, 2024, DOI:10.32604/cmc.2024.047790

Abstract In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable… More >

ZHEN LIU^1,#, LIANGWANG YANG^2,#, ZHENGXING XIE¹, HUI YU³, TIANYI GU³, DAOMING SHI⁴, NING CAI^1,*, SHENGHUA ZHUO^2,*

Oncology Research, Vol.32, No.5, pp. 965-981, 2024, DOI:10.32604/or.2024.045769

Abstract Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid… More >

Farhad Mortezapour Shiri^1,*, Ehsan Ahmadi², Mohammadreza Rezaee¹, Thinagaran Perumal¹

Journal on Artificial Intelligence, Vol.6, pp. 85-103, 2024, DOI:10.32604/jai.2024.048911

Abstract Automatic detection of student engagement levels from videos, which is a spatio-temporal classification problem is crucial for enhancing the quality of online education. This paper addresses this challenge by proposing four novel hybrid end-to-end deep learning models designed for the automatic detection of student engagement levels in e-learning videos. The evaluation of these models utilizes the DAiSEE dataset, a public repository capturing student affective states in e-learning scenarios. The initial model integrates EfficientNetV2-L with Gated Recurrent Unit (GRU) and attains an accuracy of 61.45%. Subsequently, the second model combines EfficientNetV2-L with bidirectional GRU (Bi-GRU), yielding More >

M. VASUMATHI^1,a,*, VELA MURALI^2,b, S. RASHIA BEGUM^1,c, N. RAJENDRAN^2,d

Journal of Polymer Materials, Vol.36, No.1, pp. 1-11, 2019, DOI:10.32381/JPM.2019.36.01.1

Abstract In the Fibre Metal Laminate (FML), Carbon Reinforced Aluminium laminate (CARALL), aluminium is placed next to carbon fibres. The potential difference between the aluminium and carbon is larger, leads to galvanic corrosion, which tries to bring down the durability of the FML. To bring down the effect of corrosion, a material layer is introduced between fibres and aluminium so as to separate them thus lowering the possibility of occurrence of corrosion. Another approach is to coat the surfaces of aluminium with different proportions of aluminium oxide nano particles prior to fabrication of the FML. For More >

THIRUMALAISAMY SURYAPRABHA^A, CHUNGHYUN CHOI^A, ZUBAIR AHMED CHANDIO^B, LAWRENCE ROBERT MSALILWA^B, TAEGWANG YUN^C,*, JUN YOUNG CHEONG^B,*, BYUNGIL HWANG^A,*

Journal of Polymer Materials, Vol.40, No.3-4, pp. 191-204, 2023, DOI:10.32381/JPM.2023.40.3-4.5

Abstract Magnetorheological fluids (MRFs) is a smart fluid system that exhibits swift and reversible alterations in their rheological characteristics when exposed to an external magnetic field. MRFs are used for applications in various areas, including automotive systems, robotics, aerospace, and civil engineering. The performance of MRFs depends on the behavior of the dispersed magnetic particles, necessitating thoughtful consideration of particle traits to optimize fluid performance. Carbonyl Iron Powders (CIPs), high purity iron (>98%) reduced from penta carbonyl iron, are widely employed in MRFs due to their exceptional magnetic characteristics. Nevertheless, the innate surfaces of CIPs tend… More >

ARCHNA RANI

Journal of Polymer Materials, Vol.39, No.1-2, pp. 17-35, 2022, DOI:10.32381/JPM.2022.39.1-2.2

Abstract Accumulation of Microplastics (MPs) in diverse ecosystems is a growing global problem of our time. These are entering into the environment directly (micro-sized plastics manufactured purposefully) and by degradation of plastic products. Due to a diverse range of polymers and additives used to manufacture plastic products, the MPs of different chemical compositions are abundant in the environment. A detailed literature survey revealed that MPs -environment interaction is largely governed by these chemicals and other intrinsic properties of MPs viz. shape, size, density, surface charge, etc. The current investigation primarily aims to review different chemical and More >

CONGHUI XU, ZHEQING GONG, XIAOLONG CHEN, LIJUN CHEN^*

Journal of Polymer Materials, Vol.40, No.1-2, pp. 47-58, 2023, DOI:10.32381/JPM.2023.40.1-2.4

Abstract The self-crosslinking polyacrylate latex was prepared via the semi-continuous seed emulsion polymerization technology that methyl methacrylate(MMA) and butyl acrylate (BA)were used as the main monomers and hexafluorobutyl methacrylate (HFMA) and monobutylitaconate (MBI) were used as the modified monomers and glycidyl methacrylate (GMA) was used as the crosslinked monomer which were emulsified with the environmentally friendly mixed surfactant of the isomeric triethylene (9) ether (E-1309) and the lauryl polyoxyethylene ether sulfosuccinate disodium salt (MES-30). The resultant latex and its film is characterized by Fourier transform infrared spectroscopy (FTIR), differential scanning calorimeter (DSC), laser particle sizer, contact More >

Bin Wu^1,2, Xianyi Chen³, Jinzhou Huang^4,*, Caicai Zhang⁵, Jing Wang⁶, Jing Yu^1,2, Zhiqiang Zhao⁷, Zhuolin Mei^1,2

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3177-3194, 2024, DOI:10.32604/cmc.2023.047147

Abstract In a cloud environment, outsourced graph data is widely used in companies, enterprises, medical institutions, and so on. Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers. Servers on cloud platforms usually have some subjective or objective attacks, which make the outsourced graph data in an insecure state. The issue of privacy data protection has become an important obstacle to data sharing and usage. How to query outsourcing graph data safely and effectively has become the focus of research. Adjacency query is a basic… More >