Mulberry Ethanol Extract and Rutin Protect Alcohol-Damaged GES-1 Cells by Inhibiting the MAPK Pathway

Mulberry extract has been proven to have the effect of resisting alcohol damage, but its mechanism is still unclear. In this study, the composition of mulberry ethanol extract (MBE) was identified by LC-MS/MS and the main components of MBE were ascertained by measuring. Gastric mucosal epithelial (GES-1) cells were used to elucidate the mechanism of MBE and rutin (the central part of MBE) helped protect against alcohol damage. The results revealed that phenolics accounted for the majority of MBE, accounting for 308.6 mg/g gallic acid equivalents and 108 substances were identified, including 37 flavonoids and 50 non-flavonoids. The treatment of 400 μg/mL MBE and 320 μM rutin reduced early cell apoptosis and the content of intracellular reactive oxygen species, malondialdehyde and increased glutathione. The qPCR results indicated that the MBE inhibits the expression of genes in the mitogen-activated protein kinase (MAPK) pathway, including p38, JNK, ERK and caspase-3; rutin inhibits the expression of p38 and caspase-3. Overall, MBE was able to reduce the oxidative stress of GES-1 cells and regulated apoptosis-related genes of the MAPK pathway. This study provides information for developing anti-ethanol injury drugs or functional foods.     

微光成像系统的阈值探测理论和视距探测方程的研究

研究目前文献中常见的１８种微光成像系统探测方程之间的内在联系和异同之处，分析论证各种阈值探测理论和探测方程存在的问题和不足。在此基础上，从人眼的视觉理论和阈值特性出发，建立微光成像系统新的阈值探测理论模型，并分别导出微光直视系统和微光电视系统的视距探测方程。应用所导出的理论公式计算的数据与各种实际系统的实测数据进行了比较，证明新的阈值探测理论和视距探测方程是正确可靠的，且具有很高的精度。     

Q-正则Loewner空间中的拟对称映射

本文在Q-正则Loewner空间中用环模不等式刻划了拟对称映射.另外,在 Q-维Ahlfors-David正则空间中建立了拟对称映射作用下的Grotzsch-Teichmuller型 模不等式,它是通过伸张系数的积分平均来表示.     

Network-Based Driving Force of National Economic Development: A Social Capital Perspective

Network science has been widely applied in theoretical and empirical studies of global value chain (GVC), and many related articles have emerged, forming many more mature and complete analytical frameworks. Among them, the GVC accounting method based on complex network theory is different from the mainstream economics in both research angle and content. In this paper, we build up global industrial value chain network (GIVCN) models based on World Input–Output Database, introduce the theoretical framework of Social Capital, and define the network-based indicators with economic meanings. Second, we follow the econometric framework to analyze the hypothesis and test whether it is true. Finally, we study how the three types of capital constituted by these indicators interact with each other, and discuss their impact on the social capital (economic development level, i.e., GDP). The results prove that the structural capital (industrial status) has a positive impact on the social capital; the relational capital (industrial correlation) has a positive impact on both social capital and structural capital; the cognitive capital (industrial structure) has a small impact on the social capital, structural capital, and relational capital.     

A modular attachment mechanism for software network evolution

A modular attachment mechanism of software network evolution is presented in this paper. Compared with the previous models, our treatment of object-oriented software system as a network of modularity is inherently more realistic. To acquire incoming and outgoing links in directed networks when new nodes attach to the existing network, a new definition of asymmetric probabilities is given. Based on this, modular attachment instead of single node attachment in the previous models is then adopted. The proposed mechanism is demonstrated to be able to generate networks with features of power-law, small-world, and modularity, which represents more realistic properties of actual software networks. This work therefore contributes to a more accurate understanding of the evolutionary mechanism of software systems. What is more, explorations of the effects of various software development principles on the structure of software systems have been carried out, which are expected to be beneficial to the software engineering practices.     

Diffusion of hydrogen in metals

The present status of our understanding of the diffusion of hydrogen in metals, both experimental and theoretical, is reviewed. Discussions are focused on the mechanism of diffusion of hydrogen isotopes H, D and T in f.c.c. and b.c.c. metals; the positive muon (μ ⁺) is referred to where appropriate. An up-to-date compilation of diffusion data as a function of temperature and isotope mass has been made, and a clear distinction in general diffusion behaviour in f.c.c. and b.c.c. metals is noted. Subsequently, the results obtained from the Gorsky effect, nuclear magnetic resonance and quasi-elastic neutron scattering that provide information on elementary jump processes are discussed.

A conceptual framework of the quantum diffusion of light interstitials in metals is given, including the recent Kondo theory that emphasizes the crucial importance of particle-conduction electron interactions in the diffusion process, especially at low temperatures. It is shown with the help of recent estimates of the tunneling matrix element that the overall feature of diffusion of hydrogen isotopes in b.c.c. metals as well as μ ⁺ in f.c.c. metals can be explained consistently within the frame presented here.

Finally, recent advances in the diffusion studies on hydrogen in b.c.c. metals are described. They include a re-analysis of quench-recovery experiments that manifested nearly athermal diffusion of H, D and T in Ta at low temperatures, and an enormous enhancement of the diffusivity under stress (superdiffusion) observed for H and D in V.     

Preparation and Characterization of Polypyrrole/Ferrospinel Nanocomposite by W/O Microemulsion Pathway

A polypyrrole/ferrospinel(NiFe₂O₄) nanocomposite was prepared by the in situ chemical oxidizing of pyrrole in the presence of NiFe₂O₄ nanoparticles in water-in-oil (w/o) microemulsion. The structural, morphological, and magnetic properties of the as-prepared polypyrrole/NiFe₂O₄ nanocomposite were characterized by X-ray diffraction (XRD), Fourier transform infrared spectra, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and magnetic measurements. XRD and FTIR revealed the presence of NiFe₂O₄ in the nanocomposite. SEM and TEM images illustrated that polypyrrole was coated on the NiFe₂O₄ surface. The electromagnetic parameters, such as conductivity, saturation magnetization, and coercivity of NiFe₂O₄ nanoparticles varied after coating with polypyrrole.     

Low frequency limits of third-order harmonic coefficients for atomic hydrogen in any level of discrete energy spectrum

In this paper the analytical expression is derived for the third-order optical harmonic coefficients x _abcd ^v (,,) of the atomic hydrogen at very low frequencies 0 in many level of the discrete energy spectrum.The author expresses his thank to Prof. Nguyen Van Hieu for suggesting the problem and fruitful discussions.     

A Dynamic Anomaly Detection Approach Based on Permutation Entropy for Predicting Aging-Related Failures

Software aging is a phenomenon referring to the performance degradation of a long-running software system. This phenomenon is an accumulative process during execution, which will gradually lead the system from a normal state to a failure-prone state. It is a crucial challenge for system reliability to predict the Aging-Related Failures (ARFs) accurately. In this paper, permutation entropy (PE) is modified to Multidimensional Multi-scale Permutation Entropy (MMPE) as a novel aging indicator to detect performance anomalies, since MMPE is sensitive to dynamic state changes. An experiment is set on the distributed database system Voldemort, and MMPE is calculated based on the collected performance metrics during execution. Finally, based on MMPE, a failure prediction model using the machine learning method to reveal the anomalies is presented, which can predict failures with high accuracy.