一种新型润滑油添加剂的质谱研究

采用独特的分离方法和途径，综合使用多种质谱分析技术，如电子轰击谱（ＥＩ／ＭＳ）、场解吸谱（ＦＤ／ＭＳ）、快速原子轰击谱（ＦＡＢ／ＭＳ）、色／质联用等，对高档齿轮油的主剂－含磷极压剂的结构组成进行了较为详尽的分析研究，提出了复酯胺盐的结构组成。     

药用明胶标准的探讨

明胶系列的国家标准和行业标准自批准实施以来已经过了3～6年,对我国明胶工业的发展作出了贡献。在实施过程中也揭示出若干问题。有鉴于此,明胶协会正在蕴酿标准修订工作,欢迎明胶界同仁将自己在标准的实施过程中获得的经验与体会在本刊上进行交流,以便使修订的标准更能适应形势发展的需要,更能体现与国际标准接轨,更好地结合我国国情。     

铸造铝合金轮毂T6热处理工艺的优化研究

研究了固溶时间、淬火停留时间及涂装烘烤工艺对A356合金铸造轮毂性能的影响规律并优化了T6热处理工艺，将淬火停留时间缩短到2h。研究表明：未涂装时优化工艺使合金抗拉强度达到240MPa，屈服强度达到181MPa。伸长率达到8％；涂装后抗拉强度达到262MPa，屈服强度达到179MPa，伸长率达到9％，接近并达到目前国内T6工艺的强度性能，超过了国内轮毂行业的强度性能标准，具有一定的生产实际意义。     

基于云基础设施的服务部署优化问题建模

目前典型的云基础设施提供商所提供的虚拟机资源都是有限的规格类型,当同一个服务部署在不同配置的虚拟机上时,会体现出不同的性能。通过对基于云基础设施的SaaS层服务部署情况进行研究和分析,提出对服务部署策略进行优化的必要性,并将该服务部署优化问题抽象为多目标组合优化问题,对其进行数学建模;然后利用排队论,得出优化指标的计算方法,并进行实验验证。     

Ultrafast measurement of transient electroosmotic flow in microfluidics

We present a non-intrusive molecular dye based method, i.e., laser-induced fluorescence photobleaching anemometer (LIFPA), to significantly increase temporal resolution (TR) for velocity measurement of fast transient electrokinetic flows. To our knowledge, the TR has been for the first time achieved to 5–10 μs, about 100 times better than that published from state-of-the-art micro particle image velocimetry (μPIV), which is currently the most widely used velocimetry in the microfluidics community. The new method provides us with new opportunities to study experimentally the fundamental phenomena of unsteady electrokinetics (EK) and to validate relevant theoretical models. One application of the new method is demonstrated by measuring the rise time of DC electroosmotic flows (EOFs) in a microcapillary of 10 μm in diameter.     

Application of VPRS model with enhanced threshold parameter selection mechanism to automatic stock market forecasting and portfolio selection

This study proposes a technique based upon Fuzzy C-Means (FCM) classification theory and related fuzzy theories for choosing an appropriate value of the Variable Precision Rough Set (VPRS) threshold parameter (β) when applied to the classification of continuous information systems. The VPRS model is then combined with a moving Average Autoregressive Exogenous (ARX) prediction model and Grey Systems theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed mechanism, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data are then reduced using a GM(1, N) model, classified using a FCM clustering algorithm, and then supplied to a VPRS classification module which selects appropriate investment stocks in accordance with a pre-determined set of decision-making rules. Finally, a grey relational analysis technique is employed to weight the selected stocks in such a way as to maximize the rate of return of the stock portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The portfolio results obtained using the proposed hybrid model are compared with those obtained using a Rough Set (RS) selection model. The effects of the number of attributes of the RS lower approximation set and VPRS β-lower approximation set on the classification are systematically examined and compared. Overall, the results show that the proposed stock forecasting and stock selection mechanism not only yields a greater number of selected stocks in the β-lower approximation set than in the RS approximation set, but also yields a greater rate of return.