655 research outputs found

    Mixed convection dissipative viscous fluid flow over a rotating cone by way of variable viscosity and thermal conductivity

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    AbstractThe effects of temperature-dependent viscosity and thermal conductivity on the flow and heat transfer characteristics of a viscous fluid over a rotating vertical cone are premeditated. The properties of the fluid are assumed to be constant except for the density difference with the temperature. Also, the effect of viscous dissipation is considered in the energy equation. The highly nonlinear unsteady equations are converted into a system of nonlinear ordinary differential equations which is solved by using Homotopy analysis method. The interesting findings for different pertinent parameters on momentum, energy, skin friction coefficient and local Nusselt number are demonstrated in the form of graphs and tables. A comparison has been made with literature as a limiting case of the well-chosen unsteady problem

    Substation system simulation models for transformer risk assessment analysis

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    This paper comprises a study which is carried out to investigate and evaluate the effect of lightning stresses on the 132 kV substation in the way to improve its reliability in the event of active lightning activities. The paper also detailed the modelling parameters of substation for this transient analysis in order to evaluate the performance and to recommend such configuration to optimize its design to be not only to withstand the stresses but to be more cost effective. The modelling and simulation are carried out using one of the most powerful power system simulations tools that is PSCAD-EMTDC and the substation layout design is adapted from 132/11 kV Simpang Renggam -- Ayer Hitam substation, courtesy of TNB. The model is based on single phase line model as it was suggested by the IEEE to be adequate to represent the substation in transient analysis simulation. The outcome of this paper would be the results of lightning stresses in term of voltage level measured at particular points in substation. The results are then compared with the suggested BIL for assessment of transformer failure

    Breast cancer image classification using pattern-based Hyper Conceptual Sampling method

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    The increase in biomedical data has given rise to the need for developing data sampling techniques. With the emergence of big data and the rise of popularity of data science, sampling or reduction techniques have been assistive to significantly hasten the data analytics process. Intuitively, without sampling techniques, it would be difficult to efficiently extract useful patterns from a large dataset. However, by using sampling techniques, data analysis can effectively be performed on huge datasets, to produce a relatively small portion of data, which extracts the most representative objects from the original dataset. However, to reach effective conclusions and predictions, the samples should preserve the data behavior. In this paper, we propose a unique data sampling technique which exploits the notion of formal concept analysis. Machine learning experiments are performed on the resulting sample to evaluate quality, and the performance of our method is compared with another sampling technique proposed in the literature. The results demonstrate the effectiveness and competitiveness of the proposed approach in terms of sample size and quality, as determined by accuracy and the F1-measure. 2018This contribution was made possible by NPRP-07-794-1-145 grant from the Qatar National Research Fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the authors.Scopu

    Cannabinoid Receptor 2 Agonist JWH-015 Inhibits Interleukin-1β-Induced Inflammation in Rheumatoid Arthritis Synovial Fibroblasts and in Adjuvant Induced Arthritis Rat via Glucocorticoid Receptor

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    Management of pain in the treatment of rheumatoid arthritis (RA) is a priority that is not fully addressed by the conventional therapies. In the present study, we evaluated the efficacy of cannabinoid receptor 2 (CB2) agonist JWH-015 using RA synovial fibroblasts (RASFs) obtained from patients diagnosed with RA and in a rat adjuvant-induced arthritis (AIA) model of RA. Pretreatment of human RASFs with JWH-015 (10–20 μM) markedly inhibited the ability of pro-inflammatory cytokine interleukin-1β (IL-1β) to induce production of IL-6 and IL-8 and cellular expression of inflammatory cyclooxygenase-2 (COX-2). JWH-015 was effective in reducing IL-1β-induced phosphorylation of TAK1 (Thr184/187) and JNK/SAPK in human RASFs. While the knockdown of CB2 in RASFs using siRNA method reduced IL-1β-induced inflammation, JWH-015 was still effective in eliciting its anti-inflammatory effects despite the absence of CB2, suggesting the role of non-canonical or an off-target receptor. Computational studies using molecular docking and molecular dynamics simulations showed that JWH-105 favorably binds to glucocorticoid receptor (GR) with the binding pose and interactions similar to its well-known ligand dexamethasone. Furthermore, knockdown of GR using siRNA abrogated JWH-015's ability to reduce IL-1β-induced IL-6 and IL-8 production. In vivo, administration of JWH-015 (5 mg/kg, daily i.p. for 7 days at the onset of arthritis) significantly ameliorated AIA in rats. Pain assessment studies using von Frey method showed a marked antinociception in AIA rats treated with JWH-015. In addition, JWH-015 treatment inhibited bone destruction as evident from micro-CT scanning and bone analysis on the harvested joints and modulated serum RANKL and OPG levels. Overall, our findings suggest that CB2 agonist JWH-015 elicits anti-inflammatory effects partly through GR. This compound could further be tested as an adjunct therapy for the management of pain and tissue destruction as a non-opioid for RA
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