Zihao Song, Yan Zhou^*, Wei Cheng, Futai Liang, Chenhao Zhang

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3349-3376, 2024, DOI:10.32604/cmc.2024.047034

Abstract The frequent missing values in radar-derived time-series tracks of aerial targets (RTT-AT) lead to significant challenges in subsequent data-driven tasks. However, the majority of imputation research focuses on random missing (RM) that differs significantly from common missing patterns of RTT-AT. The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation. Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss. In this paper, a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed. Our model consists of two… More >

PEI QIN^#, MIAO LIU^#, XIN WANG, JIANHUA MA^*

BIOCELL, Vol.48, No.3, pp. 513-523, 2024, DOI:10.32604/biocell.2023.045640

Abstract Background: L-dopa (Levodopa) is well known for managing PD (Parkinson’s disease); however, its prolonged use caused dyskinesia (LID). Due to the varied presentation of LID, effective treatment options are scarce. Flavonoids reported their neuroprotective activity by ameliorating acetylcholinesterase, monoamine oxidase, and neuroinflammation. Kaempferol is another flavonoid bearing these potentials. Aim: To evaluate neuroprotective activity of kaempferol in dyskinetic rats. Methods: PD was developed in Sprague-Dawley rats by injecting combination of L-ascorbic acid (10 µL) + 6-OHDA (12 µg) in medial forebrain bundle to induce neuronal damage in substantial nigra (SNr). LID was induced by administrating combination of L-dopa (20 mg/kg)… More > Graphic Abstract

Muhammad Suleman¹, Faizan Ullah¹, Ghadah Aldehim^2,*, Dilawar Shah¹, Mohammad Abrar^1,3, Asma Irshad⁴, Sarra Ayouni²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3533-3549, 2023, DOI:10.32604/cmc.2023.042365

Abstract The early detection of skin cancer, particularly melanoma, presents a substantial risk to human health. This study aims to examine the necessity of implementing efficient early detection systems through the utilization of deep learning techniques. Nevertheless, the existing methods exhibit certain constraints in terms of accessibility, diagnostic precision, data availability, and scalability. To address these obstacles, we put out a lightweight model known as Smart MobiNet, which is derived from MobileNet and incorporates additional distinctive attributes. The model utilizes a multi-scale feature extraction methodology by using various convolutional layers. The ISIC 2019 dataset, sourced from the International Skin Imaging Collaboration,… More >

QINGQING GUO^1,2, JIAYUE QI^1,2, XIAOQIANG LIANG², ZIGANG ZHAO², JIA BAI², FANG XIE^2,#,*, CHENGXIN LI^1,2,#,*

BIOCELL, Vol.47, No.11, pp. 2435-2443, 2023, DOI:10.32604/biocell.2023.043126

Abstract Introduction: Verruca vulgaris is one of the most common low-risk HPV infections and is characterized by excessive proliferation of keratinocytes. Currently, very little genetic information is available regarding verruca vulgaris in the Chinese population. This study aimed to obtain comprehensive transcript information of verruca vulgaris by RNA sequencing. Methods: High-throughput sequencing was performed on three fresh verruca vulgaris samples and adjacent normal skin on the Illumina sequencing platform. The transcriptomes were analyzed using bioinformatics and the differentially expressed genes (DEGs) were verified by immunohistochemistry. Verruca vulgaris exhibited a unique molecular signature. Results: In total, 1,643 DEGs were identified in verruca… More >

Ahmad Alassaf^*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2773-2789, 2023, DOI:10.32604/csse.2023.035899

Abstract Intelligent diagnosis approaches with shallow architectural models play an essential role in healthcare. Deep Learning (DL) models with unsupervised learning concepts have been proposed because high-quality feature extraction and adequate labelled details significantly influence shallow models. On the other hand, skin lesion-based segregation and disintegration procedures play an essential role in earlier skin cancer detection. However, artefacts, an unclear boundary, poor contrast, and different lesion sizes make detection difficult. To address the issues in skin lesion diagnosis, this study creates the UDLS-DDOA model, an intelligent Unsupervised Deep Learning-based Stacked Auto-encoder (UDLS) optimized by Dynamic Differential Annealed Optimization (DDOA). Pre-processing, segregation,… More >

PAVITHRA SUBRAMANI^1,2, RAUNAK KUMAR DAS^1,*

BIOCELL, Vol.47, No.10, pp. 2195-2205, 2023, DOI:10.32604/biocell.2023.030383

Abstract Solar ultraviolet B (UVB) radiation is a major skin cancer-causing agent. Initiation, promotion, and progression are the diverse phases of UVB-induced carcinogenesis. Exposure to UVB causes abnormalities in a series of biochemical and molecular pathways: thymine dimer formation, DNA damage, oxidative stress, inflammatory responses, and altered cell signaling, eventually resulting in tumor formation. The increased skin cancer rates urge researchers to develop more efficient drugs, but synthetic chemotherapeutic drugs have more contrary effects and drug resistance issues, which have been reported recently. The current review focuses on the relationship between microbes and cancer. Human skin acts as a barrier against… More > Graphic Abstract

C. S. S. Anupama¹, Saud Yonbawi², G. Jose Moses³, E. Laxmi Lydia⁴, Seifedine Kadry^5,6,7, Jungeun Kim^8,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2079-2095, 2023, DOI:10.32604/csse.2023.038322

Abstract Skin cancer is one of the most dangerous cancer. Because of the high melanoma death rate, skin cancer is divided into non-melanoma and melanoma. The dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin lesions. Sometimes, pathology and biopsy examinations are required for cancer diagnosis. Earlier studies have formulated computer-based systems for detecting skin cancer from skin lesion images. With recent advancements in hardware and software technologies, deep learning (DL) has developed as a potential technique for feature learning. Therefore, this study develops a new sand cat swarm optimization with a deep transfer learning method for… More >

M. Bouraoui^a, M. S. Rouabah^a, A. Abidi-Saad^b,c,d,*, A. Korichi^e, C. Popa^b , G. Polidori^b

Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-6, 2017, DOI:10.5098/hmt.8.18

Abstract Study concerning a double skin flow with secondary ventilation was conducted numerically, in order to understand the basic mechanisms of the free convection in an open channel asymmetrically heated with uniform heat flux density (510 W/m² ). The vertical channel corresponds to a double skin façade, which was immersed in a tank filled with water. The tank corresponds to the environment which allows us to overcome pressure conditions at the inlet and the outlet of the channel. The use of water allows neglecting radiation effect. The mass conservation equations of momentum and energy are solved using the finite volume method… More >

P. R. Sharma^a , Sushila Choudhary^a,* , O. D. Makinde^b

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-7, 2017, DOI:10.5098/hmt.9.18

Abstract Steady two dimensional laminar magnetohydrodynamic (MHD) slip flow and heat transfer of a viscous incompressible and electrically conducting fluid past over a flat exponentially non-conducting stretching porous sheet embedded in a porous medium with non uniform permeability in the presence of non uniform heat source is investigated. The governing equations of velocity and temperature distributions are solved numerically and the effects of different physical parameters are shown through graphs. The rate of shear stress and the rate of heat transfer at the sheet are derived, discussed numerically and their numerical values for various values of physical parameters are presented through… More >

A. Subba Rao^a,* , V. Ramachandra Prasad^a , P. Rajendra^a , M. Sasikala^a , O. Anwar Beg^b

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-9, 2017, DOI:10.5098/hmt.9.2

Abstract In this article, we investigate the nonlinear steady state boundary layer flow and heat transfer of an incompressible Jeffery non-Newtonian fluid from a permeable horizontal isothermal cylinder. The transformed conservation equations are solved numerically subject to physically appropriate boundary conditions using a versatile, implicit, finite-difference technique. The numerical code is validated with previous studies. The influence of a number of emerging non-dimensional parameters, namely with Deborah number (De), surface suction parameter (S), Prandtl number (Pr), ratio of relaxation to retardation times (λ) and dimensionless tangential coordinate (ξ) on velocity and temperature evolution in the boundary layer regime are examined in… More >