通过赝反伽伐尼反应实现金纳米粒子模块替换

通过可控的方式精确调控纳米粒子的结构仍是一个富有挑战性和鼓舞人心的课题.尽管单原子或两、三个金属原子的精细调控已经在金纳米粒子中实现,涉及三个以上金属原子的取代（模块取代）还没有报道.本工作报道了环己硫醇配体保护的Au₄₈（CHT）₂₆的合成及其通过赝反伽伐尼过程的模块取代.单晶结构揭示模块取代的产物与母体团簇共用一个相似的Au₃₁（CHT）₁₂主体,但剩余部分不同（Au₆（CHT）₁₁ vs.Au₁₆（CHT）₁₄）.一个有趣的发现是模块取代抑制了Au₄₈（CHT）₂₆的光热过程,却增强了它的发射,赋予了所合成团簇更好的双（多）功能应用潜力.光热效应的减弱和发射的增强也暗示了这两种作用能够彼此至少部分转化,对于研究这两种效应之间的相互影响也具有重要的启示.     

Anti-inflammatory bibenzyls from the stems of Dendrobium huoshanense via bioassay guided isolation

Abstract

The stems of Dendrobium huoshanense have long been used to prevent various diseases, including inflammatory diseases. This study was aimed to explain the anti-inflammatory effect of D. huoshanense stems in LPS-induced RAW 264.7 macrophages and to discover potential anti-inflammatory compounds. Results exhibited that D. huoshanense stems ethanol extract could significantly inhibit LPS-induced production of NO, TNF-α and IL-1β. Based on bioassay guided strategy, four bibenzyls (1–4) were isolated from D. huoshanense stems for the first time. Anti-inflammatory assay showed 1–4 could remarkably inhibit the production of NO in LPS-induced macrophages. Moreover, quantitative RT-PCR analysis displayed that the mRNA levels of iNOs, TNF-α and IL-1β could also be significantly reduced by 1–4. These results suggested that D. huoshanense stems ethanol extract and bibenzyls 1–4 might be well developed as therapeutic agent to prevent inflammatory diseases.     

On the Variability of Heart Rate Variability—Evidence from Prospective Study of Healthy Young College Students

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).     

Mn（Ⅱ）,Co（Ⅱ）与HSA相互作用的荧光光谱研究

用荧光光谱法研究了生理ｐＨ和等离子点（ｐＨ＝５．３０）时Ｍｎ（Ⅱ）、Ｃｏ（Ⅱ）与ＨＳＡ的相互作用。根据Ｆｏｒｓｔｅ非辐射能量转移理论,得到了不同ｐＨ时Ｍｎ（Ⅱ）、Ｃｏ（Ⅱ）在ＨＳＡ中的第一强结合位置与Ｔｒｐ－２１４残基间的距离。这一结果远大于文献报道值,根据Ｍｎ（Ⅱ）、Ｃｏ（Ⅱ）在ＨＳＡ中的结合部位及ＨＳＡ的畴结构对这一显著差异进行了讨论。     

低能质子在半导体材料Si 和GaAs中的非电离能损研究

非电离能损(NIEL)引起的位移损伤是导致空间辐射环境中新型光电器件失效的主要因素.由于低能时库仑相互作用占主导地位,一般采用Mott-Rutherford微分散射截面,但它没考虑核外电子库仑屏蔽的影响.为此,本文采用解析法和基于Monte-Carlo方法的SRIM程序计算了考虑库仑屏蔽效应后低能质子在半导体材料Si,GaAs中的NIEL,SRIM程序在计算过程中采用薄靶近似法, 并与其他作者的计算数据和实验数据进行了比较.结果表明：用SRIM程序计算NIEL时采用薄靶近似法处理是比较合理的,同时考虑库仑 关键词： 低能质子 非电离能损 硅 砷化镓     

Numerical simulation of transonic limit cycle oscillations using high-order low-diffusion schemes

This paper simulates the NLR7301 airfoil limit cycle oscillation (LCO) caused by fluid–structure interaction (FSI) using Reynolds averaged Navier–Stokes equations (RANS) coupled with Spalart–Allmaras (S–A) one-equation turbulence model. A low diffusion E-CUSP (LDE) scheme with 5th order weighted essentially nonoscillatory scheme (WENO) is employed to calculate the inviscid fluxes. A fully conservative 4th order central differencing is used for the viscous terms. A fully coupled fluid–structural interaction model is employed. For the case computed in this paper, the predicted LCO frequency, amplitudes, averaged lift and moment, all agree excellently with the experiment performed by Schewe et al. The solutions appear to have bifurcation and are dependent on the initial fields or initial perturbation. The developed computational fluid dynamics (CFD)/computational structure dynamics (CSD) simulation is able to capture the LCO with very small amplitudes measured in the experiment. This is attributed to the high order low diffusion schemes, fully coupled FSI model, and the turbulence model used. This research appears to be the first time that a numerical simulation of LCO matches the experiment. The simulation confirms several observations of the experiment.     

Isoperimetric Constants of Infinite Plane Graphs

   Abstract. Let G be an infinite locally finite plane graph with one end and let H be a finite plane subgraph of G . Denote by a(H) the number of finite faces of H and by l(H) the number of the edges of H that are on the boundary of the infinite face or a finite face not in H . Define the isoperimetric constant h (G) to be inf _H l(H) / a(H) and define the isoperimetric constant h (δ) to be inf _G h (G) where the infimum is taken over all infinite locally finite plane graphs G having minimum degree δ and exactly one end. We establish the following bounds on h (δ) for δ ≥ 7 :

Linear low-rank approximation and nonlinear dimensionality reduction

We present our recent work on both linear and nonlinear data reduction methods and algorithms: for the linear case we discuss results on structure analysis of SVD of column-partitioned matrices and sparse low-rank approximation; for the nonlinear case we investigate methods for nonlinear dimensionality reduction and manifold learning. The problems we address have attracted great deal of interest in data mining and machine learning.