木薯淀粉改性絮凝剂的光谱研究

采用氧化还原引发体系引发木薯淀粉与丙烯酰胺接枝共聚制备出天然木薯淀粉改性絮凝剂,用紫外-可见吸收光谱(UV-Vis)、红外光谱(FTIR)和拉曼光谱(RS)详细对比研究了木薯淀粉、丙烯酰胺和接枝共聚物三者的光谱特征,并据此讨论了接枝共聚机理.     

概率神经网络及FAAS在植物药分类研究中的应用

用火焰原子吸收法（FAAS）测定了植物药中Fe、Mg、Mn、Cu、Zn和Ca元素的含量,采用主成分分析法对所测数据进行预处理,结合概率神经网络模型对中药功效类别进行识别预测研究,取得了较满意的结果。     

酶荧光毛细分析法测定血清中微量丙酮酸

提出了一种用于血清微量丙酮酸（PA）测定的酶荧光毛细分析法（P-LE-FCA）。优选的测定条件为：乳酸脱氢酶和还原型辅酶Ⅰ的浓度分别为100U/L和60μmol/L,反应时间5min。测定PA的线性范围4—80μmol/L,检出限0.73μmol/L,RSD〈1.3%。血清共存物质对PA测定无明显干扰。使用该方法对血清PA进行测定,其回收率在93.0%—106.5%之间;结果与常规紫外分光光度法一致。本方法的样品预处理过程简单、省时,省试剂,灵敏度高,重现性好。     

仪器分析理论课程教学实践与探索

仪器分析是一门实践性较强的专业基础课,其原理抽象、理论性强、内容广泛。在分析了仪器分析课程特点及实践教学中出现的问题的基础上,对该课程的教学模式及观念提出了改革措施,以激发学生学习兴趣,提高课堂教学效率,培养学生创新及实践能力。     

对主成分分析法三个问题的剖析

从主成分分析法的基本原理入手,针对教学过程中学生对主成分分析法感到费解的三个问题进行了逐一剖析:1.为什么主成分系数是经标准差标准化后原始变量的协方差矩阵的特征向量?2.特征向量正负号如何选取?对进一步的研究如计算综合得分和聚类分析有何影响?3.主成分载荷值是如何得来的?同时指出有些教材在计算主成分得分时混淆了主成分载荷和特征向量的概念,以致造成错误的结果.     

PLS分析与RBF神经网络耦合环境模型

鉴于城市大气环境质量受到诸多复杂因素影响,且各因素间存在多重相关性,本文将偏最小二乘(PLS)分析与人工神经网络径向基网络(RBF)耦合,建立偏最小二乘径向基神经网络模型(PLSRBF),应用于贵阳大气环境质量的检验和预测。实例表明:PLSRBF模型可对原多自变量模型进行降维简化,并可有效提取解释变量信息,防止信息丢失,且具有较强的拟合能力。     

On the expected longest length probe sequence for hashing with separate chaining

Hashing is a widely used technique for data organization. Hash tables enable a fast search of the stored data and are used in a variety of applications ranging from software to network equipment and computer hardware. One of the main issues associated with hashing are collisions that cause an increase in the search time. A number of alternatives have been proposed to deal with collisions. One of them is separate chaining, in which for each hash value an independent list of the elements that have that value is stored. In this scenario, the worst case search time is given by the maximum length of that list across all hash values. This worst case is often referred to as Longest Length Probe Sequence (llps) in the literature. Approximations for the expected longest length probe sequence when the hash table is large have been proposed and an exact analytical solution has also been presented in terms of a set of recurring equations. In this paper, a novel analytical formulation of the expected longest length probe sequence is introduced. The new formulation does not require a recursive computation and can be easily implemented in a symbolic computation tool.     

Effect of surfactant additives on nucleate pool boiling heat transfer of refrigerant-based nanofluid

Effect of surfactant additives on nucleate pool boiling heat transfer of refrigerant-based nanofluid was investigated experimentally. Three types of surfactants including Sodium Dodecyl Sulfate (SDS), Cetyltrimethyl Ammonium Bromide (CTAB) and Sorbitan Monooleate (Span-80) were used in the experiments. The refrigerant-based nanofluid was formed from Cu nanoparticles and refrigerant R113. The test surface is horizontal with the average roughness of 1.6 μm. Test conditions include a saturation pressure of 101.3 kPa, heat fluxes from 10 to 80 kW m⁻², surfactant concentrations from 0 to 5000 ppm (parts per million by weight), and nanoparticle concentrations from 0 to 1.0 wt.%. The experimental results indicate that the presence of surfactant enhances the nucleate pool boiling heat transfer of refrigerant-based nanofluid on most conditions, but deteriorates the nucleate pool boiling heat transfer at high surfactant concentrations. The ratio of nucleate pool boiling heat transfer coefficient of refrigerant-based nanofluid with surfactant to that without surfactant (defined as surfactant enhancement ratio, SER) are in the ranges of 1.12-1.67, 0.94-1.39, and 0.85-1.29 for SDS, CTAB and Span-80, respectively, and the values of SER are in the order of SDS > CTAB > Span-80, which is opposite to the order of surfactant density values. The SER increases with the increase of surfactant concentration and then decreases, presenting the maximum values at 2000, 500 and 1000 ppm for SDS, CTAB and Span-80, respectively. At a fixed surfactant concentration, the SER increases with the decrease of nanoparticle concentration. A nucleate pool boiling heat transfer correlation for refrigerant-based nanofluid with surfactant is proposed, and it agrees with 92% of the experimental data within a deviation of ±25%.     

Measurement and correlation of densities and viscosities of pure 1,7-dibromoheptane and 1,7-dibromoheptane in ethanol at temperatures from 288.15 to 323.15 K

The densities and viscosities of pure 1,7-dibromoheptane and 1,7-dibromoheptane in ethanol had been determined from 288.15 to 323.15 K. The relative viscosities were correlated using the Carl L. Yaws equation. The results showed that the model agreed very well with the experimental data.     

An adaptive network based fuzzy inference system–auto regression–analysis of variance algorithm for improvement of oil consumption estimation and policy making: The cases of Canada,United Kingdom,and South Korea

This paper presents an adaptive network based fuzzy inference system (ANFIS)–auto regression (AR)–analysis of variance (ANOVA) algorithm to improve oil consumption estimation and policy making. ANFIS algorithm is developed by different data preprocessing methods and the efficiency of ANFIS is examined against auto regression (AR) in Canada, United Kingdom and South Korea. For this purpose, mean absolute percentage error (MAPE) is used to show the efficiency of ANFIS. The algorithm for calculating ANFIS performance is based on its closed and open simulation abilities. Moreover, it is concluded that ANFIS provides better results than AR in Canada, United Kingdom and South Korea. This is unlike previous expectations that auto regression always provides better estimation for oil consumption estimation. In addition, ANOVA is used to identify policy making strategies with respect to oil consumption. This is the first study that introduces an integrated ANFIS–AR–ANOVA algorithm with preprocessing and post processing modules for improvement of oil consumption estimation in industrialized countries.