BMS Derivatives C7-Linked to β-Cyclodextrin and Hyperbranched Polyglycerol Retain Activity against R5-HIV-1NLAD8 Isolates and Can Be Deemed Potential Microbicides

Amides from indole-3-glyoxylic acid and 4-benzoyl-2-methylpiperazine, which are related to entry inhibitors developed by Bristol-Myers Squibb (BMS), have been synthesized with aliphatic chains located at the C7 position of the indole ring. These spacers contain an azido group suitable for the well-known Cu(I)-catalyzed (3+2)-cycloaddition or an activated triple bond for the nucleophilic addition of thiols under physiological conditions. Reaction with polyols (β-cyclodextrin and hyperbranched polyglycerol) decorated with complementary click partners has afforded polyol-BMS-like conjugates that are not cytotoxic (TZM.bl cells) and retain the activity against R5-HIV-1_NLAD8 isolates. Thus, potential vaginal microbicides based on entry inhibitors, which can be called of 4^th generation, are reported here for the first time.     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

基于PBFT区块链技术的电网企业仓储系统

提出了一种基于实用拜占庭容错(PBFT)算法的区块链技术,首先对传统的实用拜占庭容错算法原理进行了阐述,该传统算法包含前期、需求、预准备、准备、确认、答复6个阶段,但传统算法具有实时性差、缺乏惩罚机制、带宽高的缺点。针对出现的这些问题,又对传统算法进行了改进,具体涉及记账节点、共识过程以及视图切换过程。通过测试进一步证明了该改进算法的实用性,并将该算法应用于电网企业中,构建的虚拟仓库实现了联储联备,降低了库存资金的耗费,并且提高了电网企业库存管理的效率。     

Stable power supply of an independent power source for a remote island using a Hybrid Energy Storage System composed of electric and hydrogen energy storage systems

We propose a self-sustaining power supply system consisting of a “Hybrid Energy Storage System (HESS)” and renewable energy sources to ensure a stable supply of high-quality power in remote islands. The configuration of the self-sustaining power supply system that can utilize renewable energy sources effectively on remote islands where the installation area is limited is investigated. It is found that it is important to select renewable energy sources whose output power curve is close to the load curve to improve the efficiency of the system. The operation methods that can increase the cost-effectiveness of the self-sustaining power supply system are also investigated. It is clarified that it is important for increasing the cost effectiveness of the self-sustaining power supply system to operate the HESS with a smaller capacity of its components by setting upper limits on the output power of the renewable energy sources and cutting the infrequent generated power.     

Protection and confinement effect of carbon on Co/CoxOy nano-catalyst for efficient NaBH4 hydrolysis

The hydrolysis of sodium borohydride (NaBH₄) over catalysts is a promising method to produce hydrogen. Although Co-based catalysts exhibit high activity for NaBH₄ hydrolysis, they are still far from satisfying practical applications, especially their poor durability in alkaline media. Herein, a carbon shell structure was designed and synthesized to improve the stability of the mixture of Co⁰ and Co_xO_y nanofilms (Co/Co_xO_y@C) during NaBH₄ hydrolysis via a facile polymerization-pyrolysis strategy with Co/Co_xO_y nanofilms as the precursor. As a result, the Co/Co_xO_y@C catalyst can achieve a remarkable H₂ generation rate of 4348.6 mL min^?1 g_Co^?1 with a low activation energy of 43.6 kJ mol^?1, which is superior to most previously reported catalysts. Moreover, the catalyst shows high stability with an H₂ generation-specific rate of 79% after five cycles. The excellent performance of carbon substrate can well prevent the agglomeration of Co-based nanoparticle and improve the corrosion resistance of the active Co to BO₂^? and OH^?. This work would widen the road for the preparation of nanoconfined catalysts, which has prospective application potentials for H₂ production from NaBH₄ hydrolysis.     

Entropy analysis of unsteady MHD three-dimensional flow of Williamson nanofluid over a convectively heated stretching sheet

This article addresses an investigation of the entropy analysis of Williamson nanofluid flow in the presence of gyrotactic microorganisms by considering variable viscosity and thermal conductivity over a convectively heated bidirectionally stretchable surface. Heat and mass transfer phenomena have been incorporated by taking into account the thermal radiation, heat source or sink, viscous dissipation, Brownian motion, and thermophoretic effects. The representing equations are nonlinear coupled partial differential equations and these equations are shaped into a set of ordinary differential equations via a suitable similarity transformation. The arising set of ordinary differential equations was then worked out by adopting a well-known scheme, namely the shooting method along with the Runge-Kutta-Felberge integration technique. The effects of flow and heat transfer controlling parameters on the solution variables are depicted and analyzed through the graphical presentation. The survey finds that magnifying viscosity parameter, Weissenberg number representing the non-Newtonian Williamson parameter cause to retard the velocity field in both the directions and thermal conductivity parameter causes to reduce fluid temperature. The study also recognizes that enhancing magnetic parameters and thermal conductivity parameters slow down the heat transfer rate. The entropy production of the system is estimated through the Bejan number. It is noticeable that the Bejan number is eminently dependent on the heat generation parameter, thermal radiation parameter, viscosity parameter, thermal conductivity parameter, and Biot number. The skillful accomplishment of the present heat and mass transfer system is achieved through the exteriorized choice of the pertinent parameters.     

Parameter characterization of HTPEMFC using numerical simulation and genetic algorithms

This paper develops a novel approach to the parameterisation of high temperature exchange membrane fuel cells (HTPEMFC) with limited and non-invasive measurements. The proposed method allows an effective identification of electrochemical parameters for three-dimensional fuel cell models by combining computational simulation tools and genetic algorithms. To avoid each evaluation undertaken by the optimisation method involving a complete computational simulation of the 3D model, a strategy has been designed that, thanks to an iterative process, makes it possible to decouple the fluid dynamic resolution from the electrochemistry one.Two electrochemical models have been incorporated into these tools to describe the behaviour of the catalyst layer, Butler-Volmer and spherical aggregate. For each one, a case study has been carried out to validate the results by comparing them with empirical data in the first model and with data generated by numerical simulation in the second. Results show that, from a set of measured operating conditions, it is possible to identify a unique set of electrochemical parameters that fits the 3D model to the target polarisation curve. The extension of this framework can be used to systematically estimate any model parameter in order to reduce the uncertainty in 3D simulation predictions.