Microstructure and electromagnetic properties of LiFe5O8 ferrite ceramics prepared from wet- and dry-milled powders

The effect of dry and wet ball milling of LiFe₅O₈ ferrite powder on the microstructure and electromagnetic properties of ferrite ceramics was studied using XRD analysis, scanning electron microscopy, dilatometry, thermogravimetry, calorimetry, and measurement of specific magnetization and electrical resistance. The sintering temperature was 1050 °C; the sintering time was 2 h. It was found that ferrite fabricated from dry-milled powder exhibits an ordered α-LiFe₅O₈ phase with bulk density of 91%. Its saturation magnetization and Curie temperature are 55 emu/g and 628°С, respectively. Specific electrical resistance is 4?10⁶ Ω cm. Wet milling in isopropyl alcohol causes formation of a disordered β-LiFe₅O₈ phase. Ceramics produced by this method shows higher bulk density (97%) and low porosity, and an order of magnitude lower resistivity. Its saturation magnetization and Curie temperature are 51 emu/g and 607°С, respectively.     

High dielectric constant of NiFe2O4–LaFeO3 nanocomposite: Interfacial conduction and dielectric loss

Materials exhibiting colossal dielectric constant are the most sought-after materials due to their variety of applications in various electronics industries. NiFe₂O₄ and LaFeO₃ belonging to the spinel and perovskite structures, respectively, were coupled into a nanocomposite by adapting a one-pot sol-gel synthesis. The ratio of NiFe₂O₄:LaFeO₃ was varied and the synthesized materials were studied for their dielectric behaviors. Interestingly, among the samples studied, the nanocomposite with the ratio of 1:2 of NiFe₂O₄–LaFeO₃ exhibited a high dielectric constant value of 10390 at a frequency of 1 kHz with a several-fold increase in conductivity. The high conductivity resulted in a high dielectric loss. The origin of such a high dielectric constant and loss have been attributed to the Maxwell-Wagner type space charge polarization arising from the microstructure that consists of large and continuous grain boundaries, and the conducting phase at the interface, respectively.     

Synthesis,Anticancer Activity,Structure-Activity Relationship and Mechanistic Investigations of Falcarindiol Analogues

Forty samples of optically active falcarindiol analogues are synthesized by using the easily available C2 symmetric (R)- and (S)-1,1’-binaphth-2-ol (BINOL) in combination with Ti(OⁱPr)₄, Zn powder and EtI. Their anticancer activities on Hccc-9810, HepG2, MDA-MB-231, Hela, MG-63 and H460 cells are assayed to elucidate their structure-activity relationships. These results showed that the falcarindiol analogue (3R,8S)- 2 i with the terminal double bond has the most potent anti-proliferation effect on Hccc-9810 cells with IC₅₀ value of 0.46 μM. The falcarindiol analogue (3R,8S)- 2 i can induce obvious Hccc-9810 cell apoptosis in a concentration-dependent manner by Hoechst staining and flow cytometry analysis. The proposed mechanism suggests that the falcarindiol analogue (3R,8S)- 2 i increases LDH release and MDA content, and reduces the levels of SOD activity, which lead to the accumulation of oxidative stress and induce apoptosis in Hccc-9810 cells.     

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。     

Preliminary Structural Data Revealed That the SARS-CoV-2 B.1.617 Variant's RBD Binds to ACE2 Receptor Stronger Than the Wild Type to Enhance the Infectivity

The evolution of new SARS-CoV-2 variants around the globe has made the COVID-19 pandemic more worrisome, further pressuring the health care system and immunity. Novel variations that are unique to the receptor-binding motif (RBM) of the receptor-binding domain (RBD) spike glycoprotein, i. e. L452R-E484Q, may play a different role in the B.1.617 (also known as G/452R.V3) variant's pathogenicity and better survival compared to the wild type. Therefore, a thorough analysis is needed to understand the impact of these mutations on binding with host receptor (RBD) and to guide new therapeutics development. In this study, we used structural and biomolecular simulation techniques to explore the impact of specific mutations (L452R-E484Q) in the B.1.617 variant on the binding of RBD to the host receptor ACE2. Our analysis revealed that the B.1.617 variant possesses different dynamic behaviours by altering dynamic-stability, residual flexibility and structural compactness. Moreover, the new variant had altered the bonding network and structural-dynamics properties significantly. MM/GBSA technique was used, which further established the binding differences between the wild type and B.1.617 variant. In conclusion, this study provides a strong impetus to develop novel drugs against the new SARS-CoV-2 variants.     

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。     

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.