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.     

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。     

Adaptive response and tolerance to weak acids in Saccharomyces cerevisiae boulardii: a metabolomics approach

Weak acids inhibit the growth of probiotics, such as Saccharomyces boulardii. We explored the tolerance of S. boulardii to different weak acids. S. boulardii had better fermentation ability under lactic acid conditions compared with acetic and butyric acid conditions; however, the budding of S. boulardii was significantly stronger than that of Saccharomyces cerevisiae under acetic acid conditions. Although the surface structure of S. boulardii was destroyed, it produced more daughter cells. S. boulardii metabolites were also significantly different from S. cerevisiae under acidic stress. The growth of S. boulardii under weak acid conditions differed significantly from that of S. cerevisiae. S. boulardii-mediated fingerprints under weak acid conditions were identified as latent biomarkers, related to fructose and mannose metabolism, tricarboxylic acid cycle, and the glycolysis pathway. Identified biomarkers will aid in the genetic engineering of S. boulardii and other Saccharomyces strains for improved acid resistance and biomass yield.     

FPGA互连测试中的反馈桥接故障覆盖问题

现场可编程门阵列(FPGA)内部资源众多,其中互连资源出现故障的概率远远高于片内其他资源,而在以往许多互连测试研究中,所生成的测试配置存在无法覆盖反馈桥接故障的难题,所以较难有测试配置实现故障列表的100%覆盖。因此通过约束桥接故障只发生在单个查找表(LUT)内的信号线上,并结合单项函数,对反馈桥接故障模型进行优化改进,从根本上解决难题；然后对优化后的反馈桥接故障设置相应的约束条件,再使用布尔可满足性理论(SAT)生成满足约束条件的测试配置。采用优化后的故障模型对ISCAS"89基准电路进行了测试配置生成实验,结果表明生成的测试向量解决了反馈桥接故障的覆盖难题,并且在实现故障列表的100%覆盖下,优化后的故障模型所需要的测试配置数最少。     

Double emulsion (W/O/W) gel stabilised by polyglycerol polyricinoleate and calcium caseinate as mangiferin carrier: insights on formulation and stability properties

Mangiferin (MGF) is a phenolic compound isolated from mango, but its poor solubility significantly limits its use. In this study, MGF was embedded into the inner aqueous phase of W₁/O/W₂ emulsions. Firstly, the dissolution method of MGF was determined. MGF remained stable in solution with pH 13 at 30 min, and its solubility reached 10 mg mL⁻¹. When the pH of MGF solutions was adjusted from pH 13 to pH 6, MGF did not immediately crystallise, providing sufficient time to construct the MGF-loaded W₁/O/W₂ emulsions. Subsequently, the MGF-loaded W₁/O/W₂ emulsions were constructed using polyglycerol polyricinoleate (PGPR) and calcium caseinate (CAS). The formation and stability of the W₁/O/W₂ emulsions were investigated. The MGF-loaded W₁/O/W₂ emulsions stabilised with 1% PGPR and 1% – 3% CAS exhibited a low viscosity, limited loading capacity, and poor stability. Conversely, the MGF-loaded W₁/O/W₂ emulsions stabilised by 3%PGPR–3%CAS exhibited optimal loading capacity (encapsulation efficiency = 95.31% and loading efficiency = 0.91%) and stability, which was attributed to the fact that high viscosity and gel state retarded the migration of inner aqueous phase. These results indicated that the W₁/O/W₂ emulsions stabilised by PGPR and CAS may be a potential alternative for encapsulating mangiferin.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

用于电弧检测的电力专用SoC设计

针对传统的电弧电路故障检测结果不准确的问题,设计用于电弧检测的SoC系统,并且在55nm工艺下进行流片验证。采用包含两种结构的模数转换器的片上电压源,设计了锁相环以及复位电路,精度最高可达8.67 bit。验证结果表明,本设计可提高电弧检测的准确性。