Xiaoyang Shen¹, Xiaojing Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.28, No.1, pp. 1-3, 2023, DOI:10.32604/icces.2023.010519

Abstract 1 General Introduction
Reliable structural health monitoring with high detection probability is very important [1]. Therefore, the method of finite element simulation was adopted. Based on the basic equation of material mechanics and stiffness degradation theory, to detect the damage of composite laminates, and further improves the intelligence of the detection process through the method of visual detection neural network.

2 Theoretical derivation and simulation
2.1 Equations for buckling
In the stratified damage area, each layer bears the load independently, and the bearing capacity is determined by the stiffness there: the larger the axial stiffness, the stronger the bearing capacity… More >

Hao Luo¹, Haibo Deng¹, Honglin Xiao¹, Shaoyang Geng^2,*, Fu Hou¹, Gang Luo¹, Yaqi Li²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 641-659, 2024, DOI:10.32604/fdmp.2023.043565

Abstract Almost all sandstone reservoirs contain interlayers. The identification and characterization of these interlayers is critical for minimizing the uncertainty associated with oilfield development and improving oil and gas recovery. Identifying interlayers outside wells using identification methods based on logging data and machine learning is difficult and seismic-based identification techniques are expensive. Herein, a numerical model based on seepage and well-testing theories is introduced to identify interlayers using transient pressure data. The proposed model relies on the open-source MATLAB Reservoir Simulation Toolbox. The effects of the interlayer thickness, position, and width on the pressure response are thoroughly investigated. A procedure for… More >

HENG ZHANG^1,#, WENJING CHENG^2,#, HAIBO ZHAO², WEIDONG CHEN², QIUJIE ZHANG^2,*, QING-QING YU^2,*

Oncology Research, Vol.32, No.2, pp. 297-308, 2024, DOI:10.32604/or.2023.043138

Abstract Background: Colorectal cancer (CRC) belongs to the class of significantly malignant tumors found in humans. Recently, dysregulated fatty acid metabolism (FAM) has been a topic of attention due to its modulation in cancer, specifically CRC. However, the regulatory FAM pathways in CRC require comprehensive elucidation. Methods: The clinical and gene expression data of 175 fatty acid metabolic genes (FAMGs) linked with colon adenocarcinoma (COAD) and normal cornerstone genes were gathered through The Cancer Genome Atlas (TCGA)-COAD corroborating with the Molecular Signature Database v7.2 (MSigDB). Initially, crucial prognostic genes were selected by uni- and multi-variate Cox proportional regression analyses; then, depending… More >

JIE ZHAO^1,#, XUANTAO YANG^2,#, HAIXI ZHANG¹, XUEZHONG GU^1,*

Oncology Research, Vol.32, No.2, pp. 325-337, 2024, DOI:10.32604/or.2023.030770

Abstract Multiple myeloma (MM) is a hematological tumor with high mortality and recurrence rate. Carfilzomib is a new-generation proteasome inhibitor that is used as the first-line therapy for MM. However, the development of drug resistance is a pervasive obstacle to treating MM. Therefore, elucidating the drug resistance mechanisms is conducive to the formulation of novel therapeutic therapies. To elucidate the mechanisms of carfilzomib resistance, we retrieved the GSE78069 microarray dataset containing carfilzomib-resistant LP-1 MM cells and parental MM cells. Differential gene expression analyses revealed major alterations in the major histocompatibility complex (MHC) and cell adhesion molecules. The upregulation of the tumor… More >

Zheng Shi, Wanru Song^*, Junhao Shan, Feng Liu

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3467-3488, 2023, DOI:10.32604/cmc.2023.045849

Abstract Visible-infrared Cross-modality Person Re-identification (VI-ReID) is a critical technology in smart public facilities such as cities, campuses and libraries. It aims to match pedestrians in visible light and infrared images for video surveillance, which poses a challenge in exploring cross-modal shared information accurately and efficiently. Therefore, multi-granularity feature learning methods have been applied in VI-ReID to extract potential multi-granularity semantic information related to pedestrian body structure attributes. However, existing research mainly uses traditional dual-stream fusion networks and overlooks the core of cross-modal learning networks, the fusion module. This paper introduces a novel network called the Augmented Deep Multi-Granularity Pose-Aware Feature… More >

Manjur Kolhar^*, Sultan Mesfer Aldossary

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2857-2879, 2023, DOI:10.32604/cmc.2023.042726

Abstract In many commercial and public sectors, the Internet of Things (IoT) is deeply embedded. Cyber security threats aimed at compromising the security, reliability, or accessibility of data are a serious concern for the IoT. Due to the collection of data from several IoT devices, the IoT presents unique challenges for detecting anomalous behavior. It is the responsibility of an Intrusion Detection System (IDS) to ensure the security of a network by reporting any suspicious activity. By identifying failed and successful attacks, IDS provides a more comprehensive security capability. A reliable and efficient anomaly detection system is essential for IoT-driven decision-making.… More >

KUAILU LIN^1,2, QIANYU GU², XIXI LAI^2,3,*

BIOCELL, Vol.47, No.12, pp. 2681-2696, 2023, DOI:10.32604/biocell.2023.043298

Abstract Objectives: Triple-negative breast cancer (TNBC) poses a significant challenge due to the lack of reliable prognostic gene signatures and an understanding of its immune behavior. Methods: We analyzed clinical information and mRNA expression data from 162 TNBC patients in TCGA-BRCA and 320 patients in METABRIC-BRCA. Utilizing weighted gene coexpression network analysis, we pinpointed 34 TNBC immune genes linked to survival. The least absolute shrinkage and selection operator Cox regression method identified key TNBC immune candidates for prognosis prediction. We calculated chemotherapy sensitivity scores using the “pRRophetic” package in R software and assessed immunotherapy response using the Tumor Immune Dysfunction and… More >

Cuihong Li¹, Qiuwei Yang^2,3,*, Xi Peng^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2769-2791, 2024, DOI:10.32604/cmes.2023.030908

Abstract Shear-type structures are common structural forms in industrial and civil buildings, such as concrete and steel frame structures. Fault diagnosis of shear-type structures is an important topic to ensure the normal use of structures. The main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage assessment. However, for many shear-type structures, it is difficult to obtain accurate FEM. In order to avoid finite element modeling, a model-free method for diagnosing shear structure defects is developed in this paper. This method only needs to measure a few low-order vibration modes of the structure.… More >

Nasser Alalwan^1,*, Ahmed I. Taloba², Amr Abozeid³, Ahmed Ibrahim Alzahrani¹, Ali H. Al-Bayatti⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2497-2517, 2024, DOI:10.32604/cmes.2023.029910

Abstract An illness known as pneumonia causes inflammation in the lungs. Since there is so much information available from various X-ray images, diagnosing pneumonia has typically proven challenging. To improve image quality and speed up the diagnosis of pneumonia, numerous approaches have been devised. To date, several methods have been employed to identify pneumonia. The Convolutional Neural Network (CNN) has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and radiology. However, these methods are complex, inefficient, and imprecise to analyze a big number of datasets. In this paper, a new hybrid method for the automatic classification… More >

Xiaoqi Xin^*, Dezhi Han, Mingming Cui

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2407-2425, 2023, DOI:10.32604/cmc.2023.042308

Abstract Person Search is a task involving pedestrian detection and person re-identification, aiming to retrieve person images matching a given objective attribute from a large-scale image library. The Person Search models need to understand and capture the detailed features and context information of smaller objects in the image more accurately and comprehensively. The current popular Person Search models, whether end-to-end or two-step, are based on anchor boxes. However, due to the limitations of the anchor itself, the model inevitably has some disadvantages, such as unbalance of positive and negative samples and redundant calculation, which will affect the performance of models. To… More >