Kai Wang¹, Biao He^2,*, Pijush Samui³, Jian Zhou⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569

Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset, which serves… More >

LEI ZHANG^*, YUAN ZHANG, HUIJUAN GAO, XIN LI, PEIFENG LI^*

Oncology Research, Vol.31, No.4, pp. 449-462, 2023, DOI:10.32604/or.2023.029062

Abstract Glioblastoma (GBM) is the most malignant form of glioma and is difficult to diagnose, leading to high mortality rates. Circular RNAs (circRNAs) are noncoding RNAs with a covalently closed loop structure. CircRNAs are involved in various pathological processes and have been revealed to be important regulators of GBM pathogenesis. CircRNAs exert their biological effects by 4 different mechanisms: serving as sponges of microRNAs (miRNAs), serving as sponges of RNA binding proteins (RBPs), modulating parental gene transcription, and encoding functional proteins. Among the 4 mechanisms, sponging miRNAs is predominant. Their good stability, broad distribution and high specificity make circRNAs promising biomarkers… More > Graphic Abstract

Turke Althobaiti^1,2, Yousef Sanjalawe^3,*, Naeem Ramzan⁴

Computer Systems Science and Engineering, Vol.47, No.1, pp. 453-469, 2023, DOI:10.32604/csse.2023.039207

Abstract Flash Crowd attacks are a form of Distributed Denial of Service (DDoS) attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing (CC). Botnets are often used by attackers to perform a wide range of DDoS attacks. With advancements in technology, bots are now able to simulate DDoS attacks as flash crowd events, making them difficult to detect. When it comes to application layer DDoS attacks, the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate issue. This is mainly because it can imitate… More >

Sesikala Bapatla¹, J. Harikiran^2,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 597-617, 2023, DOI:10.32604/csse.2023.034998

Abstract Diabetes problems can lead to an eye disease called Diabetic Retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated early, DR becomes a significant reason for blindness. To identify the DR and determine the stages, medical tests are very labor-intensive, expensive, and time-consuming. To address the issue, a hybrid deep and machine learning technique-based autonomous diagnostic system is provided in this paper. Our proposal is based on lesion segmentation of the fundus images based on the LuNet network. Then a Refined Attention Pyramid Network (RAPNet) is used for extracting global and local features. To increase… More >

Abdulaziz Almazyad, Laila Halman, Alaa Alsaeed^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4769-4784, 2023, DOI:10.32604/cmc.2023.033382

Abstract The novel Software Defined Networking (SDN) architecture potentially resolves specific challenges arising from rapid internet growth of and the static nature of conventional networks to manage organizational business requirements with distinctive features. Nevertheless, such benefits lead to a more adverse environment entailing network breakdown, systems paralysis, and online banking fraudulence and robbery. As one of the most common and dangerous threats in SDN, probe attack occurs when the attacker scans SDN devices to collect the necessary knowledge on system susceptibilities, which is then manipulated to undermine the entire system. Precision, high performance, and real-time systems prove pivotal in successful goal… More >

S. Priya^1,*, N. K. Karthikeyan¹, D. Palanikkumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2673-2685, 2023, DOI:10.32604/iasc.2023.028599

Abstract In recent years, cervical cancer is one of the most common diseases which occur in any woman regardless of any age. This is the deadliest disease since there were no symptoms shown till it is diagnosed to be the last stage. For women at a certain age, it is better to have a proper screening for cervical cancer. In most underdeveloped nations, it is very difficult to have frequent scanning for cervical cancer. Data Mining and machine learning methodologies help widely in finding the important causes for cervical cancer. The proposed work describes a multi-class classification approach is implemented for… More >

Yongtao Li^*, Fanyu Chen^*, Jiancheng Chu^*, Chao Wu^*, Yuan Li^†, Heng Li^†, Hongxin Ma^*

Oncology Research, Vol.27, No.8, pp. 911-921, 2019, DOI:10.3727/096504019X15516966905337

Abstract To date, miR-148-3p and DNMT1–recombinant human runt-related transcription factor 3 (RUNX3) axis have been linked to cell proliferation, migration, and invasion; however, their roles and relationships in human glioblastoma multiforme (GBM) are still not clear. Here we found that the expression of miR-148-3p in glioma tissues was decreased compared with adjacent nontumor tissues and correlated with WHO grade, tumor size, and prognosis as well as DNMT1 and RUNX3 expressions. Compared with NHA cells, the expression of miR- 148-3p in U87 and U251 cells was also downregulated and accompanied with upregulation of DNMT1 and hypermethylation level of RUNX3 promoter region. miR-148-3p… More >

Jie Xu^*1, Zhongzhou Su^*1, Qiuping Ding^†, Liang Shen^*, Xiaohu Nie^*, Xuyan Pan^*, Ai Yan^*, Renfu Yan^*, Yue Zhou^*, Liqin Li^‡, Bin Lu^*

Oncology Research, Vol.27, No.7, pp. 819-826, 2019, DOI:10.3727/096504018X15478559215014

Abstract Human glioblastoma multiforme (GBM) accounts for the majority of human brain gliomas. Several TMEM proteins, such as TMEM 45A, TMEM 97, and TMEM 140, are implicated in human brain gliomas. However, the roles of TMEM168 in human GBM remain poorly understood. Herein we found that mRNA levels of TMEM168 were overexpressed in GBM patients (n=85) when compared with healthy people (n=10), which was also supported by data from The Cancer Genome Atlas (TCGA). Kaplan–Meier analysis of Gene Expression Omnibus dataset GSE16011 suggested that enhanced TMEM168 expression was associated with shorter survival time. To investigate whether and how TMEM168 functioned in… More >

Yan Gao, Yongchuan Xu, Jue Wang, Xue Yang, Lulu Wen, Juan Feng

Oncology Research, Vol.27, No.3, pp. 341-347, 2019, DOI:10.3727/096504018X15228909735079

Abstract Long noncoding RNAs (lncRNAs) have been acknowledged as important regulators in various human cancers. lncRNA MNX1-AS1 has been shown to be an oncogene in epithelial ovarian cancer. However, the function of MNX1-AS1 in glioblastoma (GBM) remains largely unknown. Here we found that the expression of MNX1-AS1 was significantly upregulated in GBM tissues and cell lines. Knockdown of MNX1-AS1 significantly inhibited the proliferation, migration, and invasion of GBM cells. In terms of mechanism, we found that MNX1-AS1 could bind to miR-4443 in GBM cells. Overexpression of miR-4443 significantly inhibited the expression of MNX1-AS1 and vice versa. Moreover, there was an inverse… More >

Hengzhou Lin, Dahui Zuo, Jiabin He, Tao Ji, Jianzhong Wang, Taipeng Jiang

Oncology Research, Vol.28, No.6, pp. 591-603, 2020, DOI:10.3727/096504020X15982623243955

Abstract The long noncoding RNA WEE2 antisense RNA 1 (WEE2-AS1) plays an oncogenic role in hepatocellular carcinoma and triple negative breast cancer progression. In this study, we investigated the expression and roles of WEE2-AS1 in glioblastoma (GBM). Furthermore, the molecular mechanisms behind the oncogenic actions of WEE2-AS1 in GBM cells were explored in detail. WEE2-AS1 expression was detected using quantitative real-time polymerase chain reaction. The roles of WEE2-AS1 in GBM cells were evaluated by the cell counting kit-8 assay, flow cytometric analysis, Transwell cell migration and invasion assays, and tumor xenograft experiments. WEE2-AS1 expression was evidently enhanced in GBM tissues and… More >