JIWEI SUN^1,2,#, LIANG XU^1,#, YESEN ZHANG², HAORAN LI¹, JIE FENG², XUEFENG LU², JUN DONG^1,*

BIOCELL, Vol.47, No.12, pp. 2721-2733, 2023, DOI:10.32604/biocell.2023.043869

Abstract Objective: This investigation aimed to unveil new prospective diagnosis-related biomarkers together with treatment targets against glioblastoma. Methods: The expression levels of long non-coding RNA (lncRNA) DPP10-AS1 were assessed using real-time quantitative polymerase chain reaction (RT-qPCR) within both the patient tissue specimens and glioblastoma cell lines. The relationship between lncRNA DPP10-AS1 expression in glioblastoma and patient prognosis was investigated. Cell Counting Kit-8 (CCK-8), transwell, and clonogenic experiments were utilized to assess tumor cells’ proliferation, invasiveness, and migratory potentials after lncRNA DPP10-AS1 expression was up or down-regulated. Using an online bioinformatics prediction tool, the intracellular localization of lncRNA DPP10-AS1 and its target… More >

Bah Mamoudou^*

Journal on Artificial Intelligence, Vol.5, pp. 163-180, 2023, DOI:10.32604/jai.2023.045324

Abstract It has become an annual tradition for Convolutional Neural Networks (CNNs) to continuously improve their performance in image classification and other applications. These advancements are often attributed to the adoption of more intricate network architectures, such as modules and skip connections, as well as the practice of stacking additional layers to create increasingly complex networks. However, the quest to identify the most optimized model is a daunting task, given that state of the art Convolutional Neural Network (CNN) models are manually engineered. In this research paper, we leveraged a conventional Genetic Algorithm (GA) to craft optimized Convolutional Neural Network (CNN)… More >

Gul Nawaz¹, Muhammad Junaid¹, Adnan Akhunzada², Abdullah Gani^2,*, Shamyla Nawazish³, Asim Yaqub³, Adeel Ahmed¹, Huma Ajab⁴

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2157-2178, 2023, DOI:10.32604/cmc.2023.026952

Abstract Distributed denial of service (DDoS) attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user. We proposed a deep neural network (DNN) model for the detection of DDoS attacks in the Software-Defined Networking (SDN) paradigm. SDN centralizes the control plane and separates it from the data plane. It simplifies a network and eliminates vendor specification of a device. Because of this open nature and centralized control, SDN can easily become a victim of DDoS attacks. We proposed a supervised Developed Deep Neural Network (DDNN) model that can classify the DDoS attack traffic… More >

Rizwan Iqbal^1,*, Rashid Hussain², Sheeraz Arif³, Nadia Mustaqim Ansari⁴, Tayyab Ahmed Shaikh²

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1575-1598, 2023, DOI:10.32604/cmc.2023.042432

Abstract Software-Defined Networking (SDN) is a new network technology that uses programming to complement the data plane with a control plane. To enable safe connection, however, numerous security challenges must be addressed. Flooding attacks have been one of the most prominent risks on the internet for decades, and they are now becoming challenging difficulties in SDN networks. To solve these challenges, we proposed a unique firewall application built on multiple levels of packet filtering to provide a flooding attack prevention system and a layer-based packet detection system. This study offers a systematic strategy for wrapping up the examination of SDN operations.… More >

Laila M. Halman, Mohammed J. F. Alenazi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1469-1483, 2024, DOI:10.32604/cmes.2023.028077

Abstract The healthcare sector holds valuable and sensitive data. The amount of this data and the need to handle, exchange, and protect it, has been increasing at a fast pace. Due to their nature, software-defined networks (SDNs) are widely used in healthcare systems, as they ensure effective resource utilization, safety, great network management, and monitoring. In this sector, due to the value of the data, SDNs face a major challenge posed by a wide range of attacks, such as distributed denial of service (DDoS) and probe attacks. These attacks reduce network performance, causing the degradation of different key performance indicators (KPIs)… More > Graphic Abstract

Tengda Li, Gang Wang, Qiang Fu^*, Xiangke Guo, Minrui Zhao, Xiangyu Liu

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3499-3522, 2023, DOI:10.32604/cmc.2023.041253

Abstract Aiming at the problems of traditional dynamic weapon-target assignment algorithms in command decision-making, such as large computational amount, slow solution speed, and low calculation accuracy, combined with deep reinforcement learning theory, an improved Deep Deterministic Policy Gradient algorithm with dual noise and prioritized experience replay is proposed, which uses a double noise mechanism to expand the search range of the action, and introduces a priority experience playback mechanism to effectively achieve data utilization. Finally, the algorithm is simulated and validated on the ground-to-air countermeasures digital battlefield. The results of the experiment show that, under the framework of the deep neural… More >

Jingshan Huang, Bin Yao^*, Qixin Lan, Zhirong Pan

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 525-550, 2024, DOI:10.32604/cmes.2023.029675

Abstract Friction and wear phenomenon is a complex nonlinear system, and it is also a significant problem in the process of metal cutting. In order to systematically analyze the friction and wear process of tool material-workpiece material friction pair in the cutting process of high hardness alloy steel under different lubrication conditions, the chaotic characteristics of friction process between high hardness alloy steel and cemented carbide under the lubrication C60 nano-particles fluid are studied based on the chaos theory. Firstly, the friction and wear experiments of the friction pair between high hardness alloy steel and cemented carbide tool are carried out… More >

MUNEEBA MALIK¹, MAMOONA MAQBOOL², TOOBA NISAR³, TAZEEM AKHTER⁴, JAVED AHMED UJAN^5,6, ALANOOD S. ALGARNI⁷, FAKHRIA A. AL JOUFI⁸, SULTAN SHAFI K. ALANAZI⁹, MOHAMMAD HADI ALMOTARED¹⁰, MOUNIR M. SALEM BEKHIT¹¹, MUHAMMAD JAMIL^12,*

Oncology Research, Vol.31, No.6, pp. 899-916, 2023, DOI:10.32604/or.2023.030760

Abstract The low survival rate of Kidney renal clear cell carcinoma (KIRC) patients is largely attributed to cisplatin resistance. Rather than focusing solely on individual proteins, exploring protein-protein interactions could offer greater insight into drug resistance. To this end, a series of in silico and in vitro experiments were conducted to identify hub genes in the intricate network of cisplatin resistance-related genes in KIRC chemotherapy. The genes involved in cisplatin resistance across KIRC were retrieved from the National Center for Biotechnology Information (NCBI) database using search terms as “Kidney renal clear cell carcinoma” and “Cisplatin resistance”. The genes retrieved were analyzed… More >

Dongyun Bie^1,#, Hongbai Wang^1,#, Chaobin Zhang², Chunrong Wang³, Yuan Jia¹, Su Yuan¹, Sheng Shi¹, Jiangshan Huang¹, Jianhui Wang^1,*, Fuxia Yan^1,*

Congenital Heart Disease, Vol.18, No.4, pp. 475-488, 2023, DOI:10.32604/chd.2023.028017

Abstract Purpose: This study sought to explore the effect of intraoperative mean blood glucose levels and variability on postoperative acute kidney injury (AKI) in children undergoing congenital cardiac surgery. Methods: We conducted a prospective nested case-control study in children (age < 18 years) undergoing congenital heart surgery with cardiopulmonary bypass (CPB) at the Fuwai Hospital between April 01, 2022 and July 30, 2022. Cases were individuals who developed AKI within the first postoperative 7 days (AKI group) and controls were those without AKI (Non-AKI group) according to KDIGO criteria. AKI and Non-AKI groups unmatched and 1:1 matched by age, sex, and baseline serum… More > Graphic Abstract

FU-MING TSAI¹, PING-HSUN LU^2,3, LU-KAI WANG⁴, CHAN-YEN KUO¹, MAO-LIANG CHEN¹, CHUN-HUA WANG^5,6,*

BIOCELL, Vol.47, No.8, pp. 1793-1802, 2023, DOI:10.32604/biocell.2023.030093

Abstract Background: Cisplatin is a chemotherapeutic agent commonly used clinically for the treatment of various human cancers. Patients often reduce the use of cisplatin due to its side effects, which in turn affects its treatment. This study explored the mechanism of action of safflower extract as an adjuvant traditional Chinese medicine for chemotherapy. Methods: Primary human follicle dermal papilla cells (HFDPCs) were used as target cells for cisplatin-induced damage to hair cells. Western blotting was used to investigate the molecular targets of cisplatin and safflower extract in causing HFDPCs damage. Cell survival and cell cycle were analyzed by mitochondrial staining reagent… More >