草酸二甲酯与苯酚酯交换反应产物的高效液相色谱法定量分析

采用高效液相色谱,建立了一种新的定量分析草酸二甲酯与苯酚酯交换反应产物的方法。采用HP1100型高效液相色谱,配以紫外检测器、ZORBAXEclipseXDB-C18(150mm×4.6mm,5μm)型色谱分离柱。绘制目的产物DPO百分含量与峰面积的线性回归曲线,相关系数为0.9999。实验表明,该方法具有精密度高、重复性好的特点,可准确高效地对反应产物进行定量分析,DPO检测限为1.75×10-4mg/mL,回收率为98.3%~100.7%。     

我国传统粮食科学技术的量化考察与分析

本文对我国古代粮食科学技术分别从粮食储藏、粮食加工、食品加工和造曲酿酒等四方面进行了量化考察，并作了综合分析，确认量化程度由高到低的序列为：造曲酿酒——食品加工——粮食加工——粮食储藏。在量化考察分析的基础上，得出古代粮食科学技术在发展中的重要教训是，在已取得辉煌成就的基础上，没有从“数量化”的高度进行归纳总结，因而没有得出有意义的结论，使得已有的科学技术成就无法突破并继续提高。文章最后指出了古代粮食科学技术未能实现数学化的三条主要原因。     

Rapid Determination of Icing Inhibitor (Ethyl Glycol) in Aviation Fuel by Near-infrared Spectroscopy

Abstract

A method for determination of ethyl glycol in aviation fuel by near-infrared spectroscopy is presented. The near-infrared signal of ethyl glycol was analyzed and the wavelength range from 960 to 980 nm and a signal processing method were chosen. A calibration model for ethyl glycol was established by partial least squares regression. The calibration model was satisfactory with parameters of R ² = 0.9719, predictive residual error sum of squares equal to 0.007, and standard error of calibration equal to 0.010%. Statistical t-tests (α = 0.05) verified that there was no significant difference between the near-infrared model and the reference method using refraction analysis according to ASTM D5006. Repeatability testing showed that the near-infrared model has precision equivalent to that of the reference method. The study indicates that near-infrared spectroscopy represents a simpler, more rapid, and highly effective test for ethyl glycol in aviation fuel than conventional quantitative analysis.     

Quantification of significant volatile components of pacharán

 Pacharán is a traditional drink from Navarra (Spain). This liqueur is obtained by maceration of sloe berries (Prunus spinosa L.) with aqueous ethanol and subsequent addition of sugar and essential oils of anise (Pimpinella anisum L. or Illicium verum H.). The following volatile components of pacharán were identified and quantified: cis-anethol; trans-anethol; anisaldehyde; benzaldehyde; benzyl alcohol; γ-butyrolactone; 1,1-diethoxyethane; ethyl benzoate; ethyl lactate; diethyl malate (hydroxybutanedioic acid diethyl ester); estragol (methyl chavicol); eugenol [2-methoxy-4-(2-propenyl)-phenol]; 2-furaldehyde; linalool; cis-3-hexen-1-ol; (4-methoxyphenyl)propanone; 2-phenylethanol and vanillin. Received: 3 November 1997 / Revised version: 29 December 1997     

A hybrid multi-level optimization approach for the dynamic synthesis/design and operation/control under uncertainty of a fuel cell system

During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer’s objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies.To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.     

柴达木盆地西部南区第三系原油成熟度特征

原油成熟度特征是原油地球化学研究的重要组成部分。通过对柴达木盆地西部南区第三系原油的色谱-质谱分析,在饱和烃和芳烃成熟度参数、生物标志物绝对浓度和热不稳定化合物的定量与定性分析基础上,详细剖析了该区原油的成熟度特征。研究结果表明:柴达木盆地西部南区第三系原油主体为未熟-低熟油,不存在混源造成未熟-低熟假象的可能性。成熟原油仅出现在花土沟、狮子沟和砂西地区。柴达木盆地西部南区有效烃源岩的发育特征,佐证了大量未熟-低熟原油存在的可能性。     

颜色不变量的自适应聚类网络量化方法

给出了颜色不变量的自适应聚类网络量化算法。这种方法采用一组图象能自适应地影响量化矢量。把这种算法和均匀量化算法应用于CBIR系统中，并对它们的检索结果和时间复杂度进行比较，结果表明，该算法在检索的正确率时间的复杂度上均优于均匀量化方法。因而颜色不变量的自适应聚类网络量化方法是一种很好的矢量量化算法。     

基于自然影响因子的长江口港口岸线资源评价

港口航运的发展是关系着上海市能否成为世界物流中心的关键,港口岸线是上海市航运发展的宝贵资源。在分析评价的过程中,将上海市岸线分为河口岸线、海岸线和滩涂岸线,利用近年来的实测自然环境数据并结合社会影响因素,选取了岸前水深、潮差、岸线稳定性、坡度、工程地质、生态环境、海域通航、陆域纵深和交通便捷度共9个主要影响因子进行了研究讨论。根据研讨结果,对上海市港口岸线资源进行了综合评价,并对上海市四大滩涂的建港适宜性分别进行了分析,从而确定了上海市五大主要港口岸线资源,包括河口岸线上海市北岸新陆村-川沙新镇段、长兴岛南沿石沙村-庆丰村段及崇明岛南沿城桥村-奚东沙段;海岸线杭州湾渔业村-芦潮港段;滩涂岸线横沙东滩段。研究结果可为上海市未来港口规划和土地利用提供导向性建议。     

塔里木盆地志留系碎屑岩孔隙成因类型定量分析——以顺9井柯坪塔格组为例

碎屑岩储层孔隙主要成因类型鉴别,影响到进一步勘探时对储层预测方向的判断。塔里木盆地志留系储层大多为原生-次生复合孔和微孔,仅仅根据铸体薄片观察统计往往难以正确鉴别其主要孔隙成因类型。以顺9井志留系储层为例,在铸体薄片观察统计的基础上,根据相似岩性在相似埋藏条件下,原生孔隙受压实衰减程度相近,其残余原生孔含量相近的原理,综合分析埋深相近层段储层岩石学特征和实测孔隙度,定量化分析该储层段不同成因类型孔隙的含量。统计表明,顺9井志留系储层中原生残余粒间孔含量小于4.6%(实测孔隙度3.2%~14.6%);现今发育的中-低孔储层,主要是叠加了次生溶蚀孔形成的,孔隙度相对较高的储层以次生孔为主。该定量化分析方法可正确判别储层孔隙类型。     

Determination of aflatoxins in walnut sujuk and Turkish delight by HPLC-FLD method

This study aims to assess the risk of aflatoxins (AFs) in traditional confectionery products (walnut sujuk and Turkish delight) of Turkey. A high performance liquid chromatography coupled with fluorescence detection (HPLC-FLD) method was used for the determination of AFs. Evaluation of the method showed good selectivity, linearity, recovery and precision. The limit of quantification (LOQ) ranged from 0.106 to 0.374 μg kg⁻¹. The expanded measurement uncertainty was less than 40% for all target analytes. The validated method was successfully applied to the determination of AFs in 112 traditional confectionery products containing nuts (hazelnuts and walnuts). AFs were detected in 43.8% of walnuts and 60.9% of hazelnuts used as ingredients in walnut sujuk and Turkish delight and at levels ranging from 0.58 to 15.2 μg kg⁻¹ and 0.43–63.4 μg kg⁻¹, respectively. This means that AFs levels in walnut sujuk and Turkish delight were up to levels of 6.1 and 9.5 μg kg⁻¹, respectively. Six walnut samples and twenty-one hazelnut samples were above the EU maximum limits (MLs) of 2 and 5 μg kg⁻¹ for aflatoxin B₁ (AFB₁), respectively.