K. Kaladhar^a,∗, D. Srinivasacharya^b

Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-10, 2016, DOI:10.5098/hmt.7.6

Abstract This present investigation carried out the effects of Hall current, Joule heating and the thermal diffusion on mixed convection flow of electrically conducting couple stress fluid in a vertical channel saturated with porous medium. The final system of ordinary differential equations are obtained from the governing non-linear partial differential equations by using the similarity transformations. Homotopy Analysis Method has been used to solve the non-linear system. The average residue errors of the HAM solutions are presented through graphs. The influence of the emerging parameters (Hall, Soret, magnetic and the couple stress parameters) on velocity, temperature and concentration profiles are presented… More >

ROGHAYEH GHORBANI¹, MAHMOUD GHARBAVI², ALI SHARAFI^3,4, ELHAM RISMANI⁵, HAMED REZAEEJAM⁶, YOUSEF MORTAZAVI^1,*, BEHROOZ JOHARI^3,*

Oncology Research, Vol.32, No.1, pp. 101-125, 2024, DOI:10.32604/or.2023.044741

Abstract In the present study, we investigated the synergistic effects of targeted methotrexate-selenium nanostructure containing Myc decoy oligodeoxynucleotides along with X-irradiation exposure as a combination therapy on LNCaP prostate cancer cells. Myc decoy ODNs were designed based on the promoter of Bcl-2 gene and analyzed by molecular docking and molecular dynamics assays. ODNs were loaded on the synthesized Se@BSA@Chi-MTX nanostructure. The physicochemical characteristics of nanostructures were determined by FTIR, DLS, UV-vis, TEM, EDX, in vitro release, and hemolysis tests. Subsequently, the cytotoxicity properties of them with and without X-irradiation were investigated by uptake, MTT, cell cycle, apoptosis, and scratch assays on… More > Graphic Abstract

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 >

Hachemi Bennaceur, Meznah Almutairy, Norah Alhussain^*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2687-2706, 2023, DOI:10.32604/iasc.2023.038723

Abstract The dimensionality of data is increasing very rapidly, which creates challenges for most of the current mining and learning algorithms, such as large memory requirements and high computational costs. The literature includes much research on feature selection for supervised learning. However, feature selection for unsupervised learning has only recently been studied. Finding the subset of features in unsupervised learning that enhances the performance is challenging since the clusters are indeterminate. This work proposes a hybrid technique for unsupervised feature selection called GAk-MEANS, which combines the genetic algorithm (GA) approach with the classical k-Means algorithm. In the proposed algorithm, a new… More >

Yuhang Wang^1,2, Gaojin Li^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-2, 2023, DOI:10.32604/icces.2023.09895

Abstract The chemically active droplets, which converts the chemical energy into a localized fluid flow at the interfaces by generating a concentration gradients of surfactant, can realize self-propulsion with complex trajectories and have been widely studied to mimic the swimming behavior of micro-organisms. In reality, the motion of chemically active droplets is influenced by a combination of diffusiophoresis and Marangoni effect under concentration gradients of surfactant. However, the interaction between these two effects has been only studied for a drop under the constraint of the axial-symmetric motion. To understand the hydrodynamics of the unconstraint motion, we consider a two-dimensional drop model… More >

Ruifeng Zhao¹, Zhijun Wu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09814

Abstract The combined finite-discrete element method (FDEM) can effectively simulate the continuousdiscontinuous failure process of rocks, and is now widely adopted to investigate the issues related to rock mechanics and engineering. The conventional FDEM requires pre-defines constitutive models to calculate the element stress from element deformations [1]. However, the constitutive model used in conventional FDEM is obtained by empirical fitting of rock mechanics test data, and large amount of rock physical and mechanical information present in the test data, such as the nonlinear properties of rock presented in the initial compaction stage, are lost in the process of fitting test data… More >

S. Ravi Kumar^* , S. K. Abzal

Frontiers in Heat and Mass Transfer, Vol.9, pp. 1-9, 2017, DOI:10.5098/hmt.9.19

Abstract The aim of the present attempt is hall currents and joule heating on peristaltic blood flow in porous medium through a vertical tapered asymmetric channel under the influence of radiation. The Mathematical modeling is investigated by utilizing long wavelength and low Reynolds number assumptions. The indicates an appreciable increase in the axial velocity distribution with increase in hall current parameter and porosity parameter whereas the result in axial velocity distribution diminished by increase in magnetic field parameter. The result in pressure gradient reduces by rise in hall current parameter, porosity parameter and volumetric flow rate. The temperature of the fluid… More >

Nidhal Hnaien^a , Salwa Marzouk^a , Lioua Kolsi^a,b,*, Abdullah A.A.A. Al-Rashed^c , Habib Ben Aissia^a , Jacques Jay^d

Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-11, 2018, DOI:10.5098/hmt.11.8

Abstract The purpose of the present paper is to numerically investigate two plane turbulent parallel jets using CFD model. A parametric study was carried out to evaluate the simultaneous effect of the nozzle spacing and the velocity ratio on the merge point (MP), the combined points (CP) as well as the upper (UVC) and lower (LVC) vortices centers positions. Results show that the velocity ratio significantly affects twin-parallel jets flow structure. In fact, increasing the velocity ratio moves the MP, CP, UVC and LVC further upstream along the longitudinal direction while deflecting toward the stronger jet along the transverse direction. Due… More >

Hong Zhang^1,*, Jiaming Zhou¹, Qi Wang¹, Chengxi Zhu¹, Haijian Shao²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035

Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection algorithms. In the process of scratch identification, it is challenging to… More >

Fulu Wei¹, Xin Li¹, Yongqing Guo^1,*, Zhenyu Wang², Qingyin Li¹, Xueshi Ma³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2001-2018, 2023, DOI:10.32604/iasc.2023.035799

Abstract Traffic flow prediction plays an important role in intelligent transportation systems and is of great significance in the applications of traffic control and urban planning. Due to the complexity of road traffic flow data, traffic flow prediction has been one of the challenging tasks to fully exploit the spatiotemporal characteristics of roads to improve prediction accuracy. In this study, a combined flow direction level traffic flow prediction graph convolutional network (GCN) and long short-term memory (LSTM) model based on spatiotemporal characteristics is proposed. First, a GCN model is employed to capture the topological structure of the data graph and extract… More >