Antioxidant Activities of Plumbagin and Its Cu (II) Complex

Plumbagin and its Cu (II) complex [Cu (plumbagin)2]·H2O have been synthesized, and their antioxidant activities towards the inhibitory effect on DPPH free radical, reducing power, total antioxidant capacity, and inhibition on lipid peroxidation were investigated. Plumbagin and its Cu (II) complex were found to exhibit scavenging activities on DPPH radical with the inhibitory rate of 41% and 24%, respectively. The reducing power of plumbagin was outstanding at the concentrations of 1.0, 1.5, and 2.0 mg/mL, compared to Cu (II) complex and synthetic antioxidant 2,6-di-ter-butyl-4-methylphenol (BHT); the highest level reached 1.333 for plumbagin and 0.581 for Cu (II) complex. Also, the inhibition on lipid peroxidation of plumbagin was higher than that of Cu (II) complex and BHT, 46.4% for plumbagin and 24.5% for Cu (II) complex. The results give a strong impact for designing anticancer drugs, combined with their potential cytotoxic and antioxidant activities, which can be targeted selectively against cancer cells and increase their therapeutic index and additional advantages over other anticancer drugs

SIMULATION OF MICROBUBBLE RESISTANCE REDUCTION ON A SUBOFF MODEL

This paper presents a mixture-model based computational fluid dynamics (CFD) simulation on the two-phase microbubble flow over the hull of a SUBOFF model, aimed at assessing the roles of air-injection-to-freestream velocity ratio and air volume fraction in microbubble resistance reduction. The numerical framework consists of the Reynolds-average Navier-Stokes (RANS) equations and the standard turbulence model with standard wall function treatment, which is validated, without microbubbles, by existing experimental data of the same SUBOFF model. The effect of velocity ratio is then investigated by comparing different types of the resistance reduction at various water speeds, and the effect of air volume fraction on the friction resistance reduction is also studied with various air injection velocities. This study confirms that both the velocity ratio and air volume fraction play important roles in the microbubble resistance reduction phenomenon

A Novel Approach for Enhancing Thermal Performance of Battery Modules Based on Finite Element Modeling and Predictive Modeling Mechanism

Electric vehicles (EVs) are estimated as the most sustainable solutions for future transportation requirements. However, there are various problems related to the battery pack module and one such problem is invariable high-temperature differences across the battery pack module due to the discharging and charging of batteries under operating conditions of EVs. High-temperature differences across the battery module contribute to the degradation of maximum charge storage and capacity of Li-ion batteries which ultimately affects the performance of EVs. To address this problem, a finite element modeling (FEM) based automated neural network search (ANS) approach is proposed. The research methodology constitutes of four stages: design of air-cooled battery pack module, setup of the FEM constraints and thermal equations, formulating the predictive model on generated data using ANS, and lastly performing multi-objective response optimization of the best fit predictive model to formulate optimum design constraints for the air-cooled battery module. For efficient thermal management of the battery module, an empirical model is formulated using the mentioned methodology for minimizing the maximum temperature differences, standard deviation of temperature across the battery pack module, and battery pack volume. The results obtained are as follows: (1) the battery pack module volume is reduced from 0.003279 m3 to 0.002321 m3 by 29.21%, (2) the maximum temperature differences across the eight cells of battery pack module declines from 6.81 K to 4.38 K by 35.66%, and (3) the standard deviation of temperature across battery pack decreases from 4.38 K to 0.93 K by 78.69%. Thus, the predictive empirical model enhances the thermal management and safety factor of battery module

A Factored Similarity Model with Trust and Social Influence for Top-N Recommendation

Many trust-aware recommendation systems have emerged to overcome the problem of data sparsity, which bottlenecks the performance of traditional Collaborative Filtering (CF) recommendation algorithms. However, these systems most rely on the binary social network information, failing to consider the variety of trust values between users. To make up for the defect, this paper designs a novel Top-N recommendation model based on trust and social influence, in which the most influential users are determined by the Improved Structural Holes (ISH) method. Specifically, the features in Matrix Factorization (MF) were configured by deep learning rather than random initialization, which has a negative impact on prediction of item rating. In addition, a trust measurement model was created to quantify the strength of implicit trust. The experimental result shows that our approach can solve the adverse impacts of data sparsity and enhance the recommendation accuracy

OGR1/GPR68 Modulates the Severity of Experimental Autoimmune Encephalomyelitis and Regulates Nitric Oxide Production by Macrophages.

Ovarian cancer G protein-coupled receptor 1 (OGR1) is a proton-sensing molecule that can detect decreases in extracellular pH that occur during inflammation. Although OGR1 has been shown to have pro-inflammatory functions in various diseases, its role in autoimmunity has not been examined. We therefore sought to determine whether OGR1 has a role in the development of T cell autoimmunity by contrasting the development of experimental autoimmune encephalomyelitis between wild type and OGR1-knockout mice. OGR1-knockout mice showed a drastically attenuated clinical course of disease that was associated with a profound reduction in the expansion of myelin oligodendrocyte glycoprotein 35-55-reactive T helper 1 (Th1) and Th17 cells in the periphery and a reduced accumulation of Th1 and Th17 effectors in the central nervous system. We determined that these impaired T cell responses in OGR1-knockout mice associated with a reduced frequency and number of dendritic cells in draining lymph nodes during EAE and a higher production of nitric oxide by macrophages. Our studies suggest that OGR1 plays a key role in regulating T cell responses during autoimmunity

CFD-Based Analysis of Wedges Water Entry under Impact Loads

1053-1056The impact on a falling wedge upon water entry is numerically investigated in this paper. After verified by experimental data, the numerical framework is applied for parametric studies on wedges of different drop heights and different deadrise angles to reveal the interaction behaviour between the wedge and water during impact. Pressure distribution on the wedge surface during the water entry shows that the pressure peak moves up along the surface as impact time increases. It is found that the force peak decrease with the increase of drop height and decrease of deadrise angle of the wedge. The peak positions move positively along the timeline as the increase of deadrise angle while the peak force appears just in a small impact time range for a wedge