Supercritical Fluid Carbon Dioxide in the Extraction of Lanolin and Its Alcohol

The use of supercritical fluid carbon dioxide (SF-CO_2) in extraction of lanolin and its alcohol issuperior to the conventional solvent extractionmethod. Its distinctive advantages include highextractive ratio, nontoxic and nonflammablesolvents, and minimal by-product pollution. The     

Environmental Friendly Route and Wool Shrink Proofing

The shrink proofing on wool with treatment of protease named Argaenzyme STL was studied. The various pretreating auxiliaries, different parameters for protease treating process and the effect of stabilizer were discussed in detail. The varieties of some properties before and after protease treatment were also investigated.     

Permutation Analysis of Track and Column Braiding

Introduction Trackandcolumnbraidingisanavailable3D braidingmethod[1～3],whichperformsbraidingprocessbymovingbraidingcarriersalongroworcolumndirection alternatively.LiandDing[4]examinethebraidingmethod andconcentratetheirstudyonthemovementofbraiding carriersonthebraidingplatform,onwhichthebraiding tracksarelocated.Accordingtothebraidingprinciple,a studyofbraidingprocessisactuallyastudyofthemovingpatternofyarnendsonthebraidingplatform.Intheiranotherpaper[6],thepositionsofbraidingcarriersare r…     

关于地方高等师范院校如何稳住基础性研究的思考

“稳住一头，放开一片”是我国近期科技工作的方针，对于有着基础研究优势的地方高等师范院校来说，稳住基础研究，对提高学校的学术水平，更好地培养专门人才有着重要的现实意义。本文系统阐述了地方高师稳住基础性研究的认识前提，关键措施和根本保证。     

碳酸钙热分解反应动力学的不同方法研究

因比较法和主曲线法在求算热分解动力学"三因子"时基本原理和处理方法不同,为此而探讨了2种方法处理的结果是否一致.利用热重分析(TGA)技术研究了碳酸钙热分解过程,通过这2种方法分别求算了碳酸钙热分解反应动力学"三因子".比较法结果:活化能Ea为174.00kJ·mol-1,指前因子A为9.63×106s-1,机理函数微分形式和积分形式分别为f(α)=2(1-α)1/2和g(α)=1-(1-α)1/2;主曲线法结果:活化能Eα=169.81 kJ/mol,指前因子A=3.84×106s-1,机理函数微分表达式为f(α)=2(1-α)1/1.57,积分表达式为g(α)=1-(1-α)1/1.57,2种方法所得结果基本吻合,说明这2种方法判定动力学"三因子"的一致性和可靠性.     

紫外分光光度法同时测定复方甲硝唑片中甲硝唑和维生素B6的含量

建立了一种简单、快速、能同时测定复方甲硝唑片中甲硝唑与维生素B6的方法.采用0.100 mol/L NaOH和2.0%的四硼酸钠溶液为介质,测定波长为288和320 nm.维生素B6的存在不干扰甲硝唑的直接测定.赋形剂对该测定方法不干扰.甲硝唑的回收率为96.6% ～ 102.0%,RSD为1.6% ～ 3.8%;维生素B6的回收率为95.2% ～ 106.3%,RSD为5.4%～8.1%.该方法简单、成本低、易于操作.     

Emergent Property in Macromolecular Motion

In this paper, the model of inverse cascade fractal super-blocks along one direction (in the positive or negative) in the 3-dimensional space is developed to describe the self-similar motion in macromolecular system. Microscopically the cohesive and dispersed states of the motion blocks are co- existent states with vastly different probability of occurrence. Experimental results and theoretical analysis show that the microscopic cohesive state energy and dispersed state energy of each motion block are respectively equal to the macroscopic glassy state energy kTg and molten state energy kTm of the system. This singularity unveils topologically the non-integrability, mathematically the anholonomy, and macroscopically the emergent property. This singularity also reveals that the glass, viscoelastic and melt states are three distinct emergent properties of macromolecular motion from a macroscopic viewpoint. The fractal concept of excluded volume is introduced to depict the random motion at various scales in     

Computer Data Processing of the Hydrogen Peroxide Decomposition Reaction

Two methods of computer data processing, linear fitting and nonlinear fitting, are applied to compute the rate constant for hydrogen peroxide decomposition reaction. The results indicate that not only the new methods work with no necessity to measure the final oxygen volume, but also the fitting errors decrease evidently.     

Ratio K: a New Way of Metering and Evaluating the Risk and Return of Stock Investment

Although widely used, both the Markowitz model and VAR (Value at Risk) model have some limitations in evaluating the risk and return of stock investment. By the analysis of the conceptions of risk and return, together with the three hypotheses of technological analysis, a novelty model of metering and evaluating the risk and return of stock investment is established. The major indicator of this model , risk-return ratio K, combines the characteristic indicators of risk and return. Regardless of the form of the risk-return probability density functions, this indicator K can always reflect the risk-return performances of the invested stocks clearly and accurately. How to use the model to make optimum investment and how to make portfolio combined with clustering analysis is also explained.