Effect of Notoginsenoside-Rg1 on the Expression of Several Proteins in the Striatum of Rat Models with Parkinson＇s Disease

After establishing hemi-Parkinsonian rat models, the relationships between neuron death and the expression of several proteins, such as c-Fos, GFAP, GDNF, NF-κB and some cytokines were determined. Therapeutics experiments with notoginsenoside-Rg1 were carried out. The research results show that the expressions of GFAP, NF-Kκ and c-Fos will obviously increase in the lesion side of the striatum and the expression of GDNF will decrease, which implies that the signal transduction pathway may participate in the apoptosis in neurons. The levels of some cytokines such as TNF-α, IL-1β in the striatum of PD rat models increased compared to those of normal rats. The results of the therapeutics experiments show that notoginsenoside-Rg1 may repress the immune inflammation response and regulate the immune function through the neuro-immune molecular network. Therefore, notoginsenoside-Rg1 can be used as an effective drug for anti-oxidation and anti-inflammation, and can be used in the therapy of Parkinson＇s disease（PD）.     

Temperature effect on deposition rate of silicon nitride films

Temperature effects on deposition rate of silicon nitride films were characterized by building a neural network prediction model. The silicon nitride films were deposited by using a plasma enhanced chemical vapor deposition system and process parameter effects were systematically characterized by 2⁶⁻¹ fractional factorial experiment. The process parameters involved include a radio frequency power, pressure, temperature, SiH₄, N₂, and NH₃ flow rates. The prediction performance of generalized regression neural network was drastically improved by optimizing multi-valued training factors using a genetic algorithm. Several 3D plots were generated to investigate parameter effects at various temperatures. Predicted variations were experimentally validated. The temperature effect on the deposition rate was a complex function of parameters but N₂ flow rate. Larger decreases in the deposition rate with the temperature were only noticed at lower SiH₄ (or higher NH₃) flow rates. Typical effects of SiH₄ or NH₃ flow rate were only observed at higher or lower temperatures. A comparison with the refractive index model facilitated a selective choice of either SiH₄ or NH₃ for process optimization.     

基于Internet/Intranet的大学物理实验系统

利用计算机技术、传感技术和校园网，将现代教育技术引入大学普通物理实验教学中，实现实验数据的自动采集，基于网络的实验预习和实验报告写作、递交、批改及管理等功能．     

Evolution in complex systems

What features characterize complex system dynamics? Power laws and scale invariance of fluctuations are often taken as the hallmarks of complexity, drawing on analogies with equilibrium critical phenomena. Here we argue that slow, directed dynamics, during which the system's properties change significantly, is fundamental. The underlying dynamics is related to a slow, decelerating but spasmodic release of an intrinsic strain or tension. Time series of a number of appropriate observables can be analyzed to confirm this effect. The strain arises from local frustration. As the strain is released through “quakes,” some system variable undergoes record statistics with accompanying log‐Poisson statistics for the quake event times. We demonstrate these phenomena via two very different systems: a model of magnetic relaxation in type II superconductors and the Tangled Nature model of evolutionary ecology and show how quantitative indications of aging can be found. © 2004 Wiley Periodicals, Inc. Complexity 10: 49–56, 2004     

Widrow-cellular neural network and optoelectronic implementation

A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.     

FeCoB-SiO2磁性纳米颗粒膜的微波电磁特性

采用交替沉积磁控溅射工艺制备了超薄多层的FeCoB SiO2 磁性纳米颗粒膜 .利用x射线衍射仪、扫描探针显微镜、透射电子显微镜分析了薄膜的微结构和形貌特征 .采用振动样品磁强计、四探针法、微波矢量分析仪及谐振腔法测量薄膜试样的磁电性能和微波复磁导率 .重点对SiO2 介质相含量、薄膜微结构对电磁性能产生重要影响的机理做了分析和探讨 .结果表明 :这类FeCoB SiO2 磁性纳米颗粒膜具有良好的软磁性能和高频电磁性能 ,2GHz时的磁导率 μ′高于 70 ,可以应用于高频微磁器件或微波吸收材料的设计     

稀土配合物Eu(asprin)_3phen发光特性的研究

将稀土配合物Eu(asprin)_3phen掺杂到导电聚合物PVK中,制成结构分别为ITO/PVK:RE配合物/LiF/AI(1),ITO/PVK:RE配合物/PBD/LiF/AI(2)的电致发光(EL)器件。发现二者的电致发光谱存在着较大的差别:在器件(1)中,来自Eu~(3 )的位于594nm(~5D_0→~7F_1)和614nm(~5D_0→~7F_2)处的发光强度大致相当,而在器件(2)中,EL主要来自Eu~(3 )位于614nm的发光,594nm处的发光很弱,与薄膜状态下的光致发光谱(PL)一致。并针对此现象进行了初步讨论。     

Ti(IV)/BINOL-catalyzed asymmetric aldol reaction of a masked acetoacetic ester: pronounced influence of catalyst concentration on nonlinear effects

Initial concentration of enantioenriched or enantiopure catalysts proved to be an important factor for the achievement of a more pronounced amplification of ee's in the Ti(IV)/BINOL-catalyzed aldol reaction of an O-silyldienolate.     

Networks, Fields and Organizations: Micro-Dynamics, Scale and Cohesive Embeddings

Social action is situated in fields that are simultaneously composed of interpersonal ties and relations among organizations, which are both usefully characterized as social networks. We introduce a novel approach to distinguishing different network macro-structures in terms of cohesive subsets and their overlaps. We develop a vocabulary that relates different forms of network cohesion to field properties as opposed to organizational constraints on ties and structures. We illustrate differences in probabilistic attachment processes in network evolution that link on the one hand to organizational constraints versus field properties and to cohesive network topologies on the other. This allows us to identify a set of important new micro-macro linkages between local behavior in networks and global network properties. The analytic strategy thus puts in place a methodology for Predictive Social Cohesion theory to be developed and tested in the context of informal and formal organizations and organizational fields. We also show how organizations and fields combine at different scales of cohesive depth and cohesive breadth. Operational measures and results are illustrated for three organizational examples, and analysis of these cases suggests that different structures of cohesive subsets and overlaps may be predictive in organizational contexts and similarly for the larger fields in which they are embedded. Useful predictions may also be based on feedback from level of cohesion in the larger field back to organizations, conditioned on the level of multiconnectivity to the field.     

Eigenvalue Spectrum of a Dirac Particle in Static and Spherical Complex Potential

It has been observed that a quantum theory need not be Hermitian to have a real spectrum. We study the non-Hermitian relativistic quantum theories for many complex potentials, and obtain the real relativistic energy eigenvalues and corresponding eigenfunctions of a Dirac-charged particle in complex statically and spherically symmetric potentials. Complex Dirac–Eckart, complex Dirac–Rosen–Morse II, complex Dirac–Scarf and complex Dirac–Poschl–Teller potential are investigated.