Sahar Arooj¹, Muhammad Farhan Khan², Tariq Shahzad³, Muhammad Adnan Khan^4,5,6, Muhammad Umar Nasir⁷, Muhammad Zubair¹, Atta-ur-Rahman⁸, Khmaies Ouahada^3,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043013

Abstract Breast cancer (BC) is the most widespread tumor in females worldwide and is a severe public health issue. BC is the leading reason of death affecting females between the ages of 20 to 59 around the world. Early detection and therapy can help women receive effective treatment and, as a result, decrease the rate of breast cancer disease. The cancer tumor develops when cells grow improperly and attack the healthy tissue in the human body. Tumors are classified as benign or malignant, and the absence of cancer in the breast is considered normal. Deep learning, machine learning, and transfer learning… More >

JINJIN FU^1,#, XIAOYUE FENG^2,#, JUAN WEI², XIANG GENG¹, YU GONG¹, FENGDONG LI¹, SHAOHUA ZHUANG¹, JIN HUANG¹, FANGYU WANG^2,*

BIOCELL, Vol., , DOI:10.32604/biocell.2023.042586

Abstract Background: This study aimed to elucidate the potential mechanisms through which bone marrow-derived mesenchymal stem cells (BM-MSCs) may be effective in alleviating experimental colitis induced by treatment with 2,4,6-trinitrobenzene-sulfonate acid (TNBS), specifically through autophagy modulation. Methods: BM-MSCs were collected from BALB/c mice for subsequent experiments. The study employed cell counting kits (CCK-8) to investigate the impact of the MSC-conditioned medium (M medium) on the proliferation of RAW264.7 macrophages. The GFP-mRFP-LC3 adenovirus was transfected into RAW264.7 to detect autophagic flux. The gene expression of cytokines was assessed through quantitative reverse transcription polymerase chain reaction (qRT-PCR). Western blot analysis was employed to… More >

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

FDMP-Fluid Dynamics & Materials Processing, Vol., , 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 >

Yi Song¹, Zheyu Hu^2,*, Cheng Shen¹, Lan Ren², Xingwu Guo¹, Ran Lin², Kun Wang³, Zhiyong Zhao⁴

FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.030521

Abstract Deep shale gas reserves that have been fractured typically have many relatively close perforation holes. Due to the proximity of each fracture during the formation of the fracture network, there is significant stress interference, which results in uneven fracture propagation. It is common practice to use “balls” to temporarily plug fracture openings in order to lessen liquid intake and achieve uniform propagation in each cluster. In this study, a diameter optimization model is introduced for these plugging balls based on a multi-cluster fracture propagation model and a perforation dynamic abrasion model. This approach relies on proper consideration of the multiphase… More >

Abdul Qadir Khan¹, Guangmin Sun^1,*, Yu Li¹, Anas Bilal², Malik Abdul Manan¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043239

Abstract In the emerging field of image segmentation, Fully Convolutional Networks (FCNs) have recently become prominent. However, their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters, which can often be a cumbersome manual task. The main aim of this study is to propose a more efficient, less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images. To this end, our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network (FCEDN). The optimization is handled by a novel Genetic Grey Wolf Optimization (G-GWO) algorithm. This algorithm employs the Genetic Algorithm (GA) to generate a diverse set of… More >

Yi Shi, Fangfang Shangguan^*, Jing Xiao^*

International Journal of Mental Health Promotion, Vol., , DOI:10.32604/ijmhp.2023.030516

Abstract Background: Social support is related to depression, but the gender differences and related factors that contribute to low social support among adolescents with subthreshold depression remain to be elucidated. This study explores the relationship between social support and depression, in addition to the gender difference in the incidence of low social support among adolescents with subthreshold depression and its related factors. Methods: A total of 371 Chinese adolescents with subthreshold depression were recruited. All subjects were rated on the Social Support Scale for Adolescents, the Response Style Scale, the Self-Perception Profile for Children, the Individualism-collectivism scale. Results: Binary logistic regression… More >

Pudhari Srilatha¹, Ahmed M. Hassan², B. Shankar Goud^3,*, E. Ranjit Kumar⁴

Frontiers in Heat and Mass Transfer, Vol., , DOI:10.32604/fhmt.2023.043023

Abstract The purpose of this research is to investigate the influence that slip boundary conditions have on the rate of heat and mass transfer by examining the behavior of micropolar MHD flow across a porous stretching sheet. In addition to this, the impacts of thermal radiation and viscous dissipation are taken into account. With the use of various computing strategies, numerical results have been produced. Similarity transformation was utilized in order to convert the partial differential equations (PDEs) that regulated energy, rotational momentum, concentration, and momentum into ordinary differential equations (ODEs). As compared to earlier published research, MATLAB inbuilt solver solution… More >

Lifeng Liu¹, Menghe Shi², Jianhui Wang³, Wendong Wang^2,*, Yuliang Su², Xinyu Zhuang²

FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.041962

Abstract Ultra-low permeability reservoirs are characterized by small pore throats and poor physical properties, which are at the root of well-known problems related to injection and production. In this study, a gas injection flooding approach is analyzed in the framework of numerical simulations. In particular, the sequence and timing of fracture channeling and the related impact on production are considered for horizontal wells with different fracture morphologies. Useful data and information are provided about the regulation of gas channeling and possible strategies to delay gas channeling and optimize the gas injection volume and fracture parameters. It is shown that in order… More >

Rui Qiao, Shi Dong^*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043476

Abstract Effectively identifying and preventing the threat of Byzantine nodes to the security of distributed systems is a challenge in applying consortium chains. Therefore, this paper proposes a new consortium chain generation model, deeply analyzes the vulnerability of the consortium chain consensus based on the behavior of the nodes, and points out the effects of Byzantine node proportion and node state verification on the consensus process and system security. Furthermore, the normalized verification node aggregation index that represents the consensus ability of the consortium organization and the trust evaluation function of the verification node set is derived. When either of the… More >

Muhammad Tahir^1,2,*, Mingchu Li^1,2, Irfan Khan^1,2, Salman A. Al Qahtani³, Rubia Fatima⁴, Javed Ali Khan⁵, Muhammad Shahid Anwar⁶

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042403

Abstract Real-time health data monitoring is pivotal for bolstering road services’ safety, intelligence, and efficiency within the Internet of Health Things (IoHT) framework. Yet, delays in data retrieval can markedly hinder the efficacy of big data awareness detection systems. We advocate for a collaborative caching approach involving edge devices and cloud networks to combat this. This strategy is devised to streamline the data retrieval path, subsequently diminishing network strain. Crafting an adept cache processing scheme poses its own set of challenges, especially given the transient nature of monitoring data and the imperative for swift data transmission, intertwined with resource allocation tactics.… More >