苯-环己烷体系萃取精馏溶剂的计算机筛选

为了对苯-环己烷体系进行萃取精馏溶剂的计算机筛选,采用了基于UNIFAC分子设计方法并结合Aspen数据库进行了萃取精馏溶剂的初步筛选。利用全塔模拟筛选法对初选溶剂做了进一步的筛选,获得了效果较好的一组溶剂为：含氮杂环化合物-NMP、酰胺类-DMF、醇类-四甘醇、三甘醇等。得出结论酯类和酸类分离效果一般,酯类化合物中分...     

浆态床合成二甲醚宏观动力学模拟

采用宏观动力学,对以合成气为原料的浆态床液相法合成二甲醚反应进行模拟研究,通过物料恒算建立一组常微分方程组,计算过程采用四阶精度的Runge-Kutta法并结合C++编程求解.通过模拟计算,讨论了压力、温度、空速、催化剂浓度、CO2浓度对反应转化率、收率以及DME的选择性的影响,从而寻找合适的反应器参数,为实际的工业生产提供参考.     

浆态床法合成二甲醚的模拟研究

对于直接以合成气作为原料，使用Cu-Zn-Al和γ-Al2O3构成的双重催化剂、采用浆态床法合成二甲醚的反应体系，使用全混流反应器模型结合化学反应动力学进行模拟。组分方程使用超松弛迭代方法并结合C 编程进行求解，编制了计算机程序。通过模拟计算，讨论了压力、温度、空速、催化剂配比、反应气中不同氢碳比以及CO2含量对反应收率、DME选择性的影响，并讨论了在不同氢碳比下对CO转化率和CO与H2总转化率的影响，从而寻找合适的反应条件，为工业化生产提供参考。     

Microwave assisted fast synthesis of various ZnO morphologies for selective detection of CO, CH4 and ethanol

ZnO nanocrystals with various morphologies were synthesized via a fast and facile microwave assisted method using zinc acetate as starting material, guanidinium and acetyl acetone as structure directing agents, and water as solvent. Reaction conditions, templates and pH of the reaction medium were adjusted in order to achieve nanorod, nanoparticle, and flower-like morphologies. As synthesized ZnO samples were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), and nitrogen adsorption analysis (BET). Response and selectivity of the samples to CO, CH₄ and ethanol were measured in a flow system. It is shown that different morphologies of ZnO nanoparticles exhibit different responses and selectivities. Flower-like morphology is highly selective to CO, while nanorods and nanoparticles are selective to methane and ethanol, respectively. Moreover, in a wide range of temperatures, response of ZnO nanorods and nanoparticles towards CO is temperature independent.     

Novel e-nose for the discrimination of volatile organic biomarkers with an array of carbon nanotubes (CNT) conductive polymer nanocomposites (CPC) sensors

We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters.     

Towards a suite of quality metrics for KADS-domain knowledge

In this paper, the quality metrics suite for object oriented (OO) design is partially used as an initial concept to develop metrics for statically measuring quality of KADS-domain knowledge bases. KADS-domain knowledge bases have common characteristics with OO, and other distinct features that limit the usage of some OO quality metrics. Therefore, new sets of domain knowledge quality metrics are proposed. The proposed matrices are enriched with an automatic tool used to measure quality of real world expert systems. In order to assess the effectiveness of these proposed quality metrics, these metrics were applied on a sample of real world agriculture application domains developed by CLAES (The Central Laboratory of Agriculture Expert System). Finally, complete analysis of the results obtained due to applying these metrics is presented.     

Application of Evolutionary Neural Networks on Optimization Design of Mobile Phone Based on User's Emotional Needs

Taking users’ emotional needs into consideration, this research aims to propose a new method to present product design features exactly and completely. On the basis of genetic algorithm integrated with back‐propagation (BP) neural networks, taking the mobile phone as research object, an optimization design algorithm was finally designed. First, the continuous and discrete design variables that describe mobile phones were screened with methods of dimensions, coordinate label, and morphological analysis. Forty three‐dimensional (3D) mobile phone models were designed by using 3D design software PROE. Accordingly, 12 representative mobile phones were selected through multidimensional scaling analysis and cluster analysis. Fourteen pairwise Kansei image words were obtained by collecting, screening, surveys, and statistical analysis method. Second, a BP neural networks model between design variables and user preference along with Kansei image words was established and verified with questionnaire survey data. Finally, the optimization design model for mobile phones was established considering design requirements and users’ emotional needs. A genetic algorithm integrated with BP neural networks was used to optimize mobile phone design. The results show that the optimization scheme is superior to others, and this paper will provide design suggestion for mobile phone designers.     

Dealing With The Data Deluge In High Throughput Screening

Numerical taxonomy and pattern recognition analysis offer powerful tools that can greatly reduce the information burden of multiple-assay screening programs. These methods can be used to rationally design prescreens, identify assays with similar chemical response patterns, select reporter assays for chemical response groups, evaluate drug selectivity, and predict a drug's likely mechanism of action. When combined with assays designed to identify lead compounds with characteristics likely to cause failure at a later and more expensive stage of development, a simple 3-stage primary discovery process consisting of a rational prescreen, reporters, and clinical failure assay can reduce the number of required culture wells by more than 20-fold and can eliminate all but 1–2 drugs per 1,000 tested as leads for further evaluation and development.     

Methods for compound selection focused on hits and application in drug discovery

In the context of virtual screening calculations, a multiple fingerprint-based metric is applied to generate focused compound libraries by database searching. Different fingerprints are used to facilitate a similarity step for database mining, followed by a diversity step to assemble the final library. The method is applied, for example, to build libraries of limited size for hit-to-lead development efforts. In studies designed to inhibit a therapeutically relevant protein–protein interaction, small molecular hits were initially obtained by combined fingerprint- and structure-based virtual screening and used for the design of focused libraries. We review the applied virtual screening approach and report the statistics and results of screening as well as focused library design. While the structures of lead compounds cannot be disclosed, the analysis is thought to provide an example of the interplay of different methods applied in practical lead identification.     

主动规则可终止性的动态分析方法

判定主动规则集合的执行情况是相当困难的,尤其是在主动规则支持复合事件时,提出了一种利用确定型多带图灵机对主动数据库进行动态分析的模型,归结出主动规则可终止的充分必要条件,并进一步提出了利用动态分析模型进行主动规则可终止性判定的算法,该模型易于实现,能有效描述规则集合的动态特性,可以作为分析主动规则集合行为的理论基础,还可以用于对主动规则的辅助设计和验证。     

石脑油裂解过程中一次反应选择性系数的调整方法研究

在分析石脑油裂解炉辐射段的Kumar分子反应动力学模型的基础上,提出了一种应用数据融合技术对Kumar模型一次反应选择性系数进行在线调整的方法。首先,利用进化的遗传算法,以改进的石脑油裂解模型计算出的产率与实际工况产率的误差作为目标函数,对选择性系数进行离线调整,进而建立原料性质与选择性系数相匹配的标准样本数据库。其次,利用数据融合技术中的Dempeter-Shafer证据理论建立模型,计算待估物料与标准样本数据库中样本物料的匹配度,进而对待估原料的一次反应选择性系数进行估算。研究结果表明,利用估算出的一次反应选择性系数建立的裂解工艺模型具有较高精度,将仿真结果与实际工况产率进行对比,证实了该方法的有效性和可行性。     

"MDZY型，冲压模方案设计专家系统的设计与实现

作为一种先进的金属零件加工方法,冲压生产在工业领域中已经得到了广泛的应用,但其生产效率的进一步提高却由于冲压模具设计的复杂性和耗时性而受到了较大程度制。CAD技术的引入虽然简化了图形的绘制和处理工作,但对冲模设计当中普遍存在的推理、判断等非数值问题却无能为力。文中利用人工智能技术,在Visual C 5．0环境下实现了一个冲压模方案设计专家系统,用来帮助设计者在模具设计前期完成合理的方案设计。系统在执行设计任务时采用了实例匹配和归纳推理两种不同手段,系统中的设计知识分别采用了数据库记录、链表以及集成了框架、规则和方法的对象等多种形式来表示,各类知识的学习和修改采用了包括神经网络在内的多种机制。     

Dexter: A guide to selecting the best design for an industrial screening experiment

As a means of increasing the quality and productivity of R&D efforts, we provide an integrated collection of experimental design tools for use by researchers at the Becton Dickinson Research Center. The bases for these tools are a set of well-accepted guidelines for experimental procedures and a tabulation of practical experimental designs. The designs themselves are provided to researchers in an easy-to-use personal computer (PC) spreadsheet format. The data can then be easily exported to a commercial PC statistics package. A PC based expert system, called Dexter, assists researchers in following the guidelines for selecting which of the tabulated designs should be used for a given experiment.Dexter incorporates the expertise of a consulting statistician in helping a user select a design from among 35 designs for industrial screening experiments. The designs considered include from three to eleven experimental factors with a maximum sample size of 32 runs. The evaluation is based on the calculation of design scores which model guidelines for selecting experimental designs. A graph isomorphism algorithm is used to match particular design characteristics such as estimable two-factor interactions. Smart search techniques and precomputing of graph representations minimize run times and make the PC platform practical. The window-oriented, menu-driven interface is intuitive and easy-to use.     

Development of a receptor model for efficient in silico screening of HIV-1 integrase inhibitors

Integrase (IN) is a key viral enzyme for the replication of the type-1 human immunodeficiency virus (HIV-1), and as such constitutes a relevant therapeutic target for the development of anti-HIV agents. However, the lack of crystallographic data of HIV IN complexed with the corresponding viral DNA has historically hindered the application of modern structure-based drug design techniques to the discovery of new potent IN inhibitors (INIs). Consequently, the development and validation of reliable HIV IN structural models that may be useful for the screening of large databases of chemical compounds is of particular interest. In this study, four HIV-1 IN homology models were evaluated respect to their capability to predict the inhibition potency of a training set comprising 36 previously reported INIs with IC₅₀ values in the low nanomolar to the high micromolar range. Also, 9 inactive structurally related compounds were included in this training set. In addition, a crystallographic structure of the IN-DNA complex corresponding to the prototype foamy virus (PFV) was also evaluated as structural model for the screening of inhibitors. The applicability of high throughput screening techniques, such as blind and ligand-guided exhaustive rigid docking was assessed. The receptor models were also refined by molecular dynamics and clustering techniques to assess protein sidechain flexibility and solvent effect on inhibitor binding. Among the studied models, we conclude that the one derived from the X-ray structure of the PFV integrase exhibited the best performance to rank the potencies of the compounds in the training set, with the predictive power being further improved by explicitly modeling five water molecules within the catalytic side of IN. Also, accounting for protein sidechain flexibility enhanced the prediction of inhibition potencies among the studied compounds. Finally, an interaction fingerprint pattern was established for the fast identification of potent IN inhibitors. In conclusion, we report an exhaustively validated receptor model if IN that is useful for the efficient screening of large chemical compounds databases in the search of potent HIV-1 IN inhibitors.     

A comprehensive comparison of two variable importance analysis techniques in high dimensions: Application to an environmental multi-indicators system

Permutation variable importance measure (PVIM) based on random forest and Morris' screening design are two effective techniques for measuring the variable importance in high dimensions. The former technique is developed in the machine learning discipline and widely used in bioinformatics, while the latter technique is popular in scientific computing. We present three main contributions to variable importance analysis (VIA). First, through theoretical derivation, we show that the PVIM converges to double the non-standardized Sobol' total effect index. This observation indicates that the PVIM is especially useful for variable screening as it captures both the individual and interaction effects. Second, three numerical examples with different types of model behavior are presented for comparing the performances of these two techniques. The main conclusions are as follows. For high-dimensional additive or approximately additive models, the PVIM is much more efficient than Morris' screening design when used for both variable importance ranking and variable screening. For high-dimensional models mainly governed by interaction effects, the performance of PVIM degrades, but it is still a competitive technique. Finally, the two techniques are applied to an environmental multi-indicators system for improving the robustness of the partial order structure of this system.     

一个面向智能电话的移动可信平台设计

由于手机病毒或设备失窃,导致手机上的私密数据面临泄漏的危险。为了满足移动平台的安全需求,TCG的MPWG提出移动可信平台规范。然而MPWG并没有明确规定特定的技术方法来实现移动可信模块(MTM),现有研究中没有整体的可实际部署于智能手机环境的MTM平台框架性设计,对可信软件栈(TSS)也没有可以实施的详细的部署方案。设计了一个面向智能手机的移动可信平台服务模型,它将基于TrustZone的纯软件MTM实现与基于Java Card的智能卡MTM实现结合起来构建两个可信引擎。提出其中可信构建块的部署流程并对其安全性进行了分析。     

无标记金纳米传感测定四氯苯醌

活体内五氯苯酚(PCP)的检测,往往是通过检测其代谢产物实现。四氯苯醌(TCBQ)作为PCP的一种主要代谢产物,发展其检测方法具有重要意义。该文基于TCBQ与ssDNA的G碱基发生特异性化学反应,破坏ssDNA的结构,从而破坏ssDNA对金纳米粒子的保护作用,导致金纳米粒子在盐诱导下聚沉发生颜色改变。通过测定ssDNA保护的金纳米粒子溶液颜色的改变,实现TCBQ的定量检测。该检测方法线性范围宽(9.3nmol/L～0.93mmol/L),检测限达到了3nmol/L。干扰实验表明该方法选择性高。     

一种多小波滤波器在医学图像融合中的应用

医学图像融合为临床诊断、手术设计与效果评估等提供不同模态影像互补信息。构造具有3阶消失矩的双正交多小波滤波器,其以高斯函数一次泰勒规范展开正交化后得到的完备二次单位正交基作为尺度函数。利用构造的多小波滤波器,分别对CT、MRI医学图像进行分解,使用基于多小波分解改进的局部能量加权规则融合图像。结果表明改进规则融合了源图像主要信息,优于常用的融合规则。应用构造的多小波滤波器可有效地融合医学图像,略优于DGHM多小波。     

An expert system for aided design of ship systems automation

The paper presents a structure and functions of an expert system for aided design of ship systems automation. The system was developed on basis of a detailed analysis of the design process of ship systems automation. The system includes: knowledge bases regarding methods and procedures of ship systems automation design, databases of automated objects, control devices and elements, requirements of classification societies, and a subsystem for simulation investigations co-operating with the Matlab Simulink package and a knowledge base. In the creation of the system the shell expert system Exsys Developer was used. This system is characterised by a rule-oriented representation of knowledge, backward and forward chaining inference methods, various confidence modes to handle uncertain reasoning including fuzzy logic, and possibility of co-operation with other software and databases. The databases were made using the MS Access software.     

An effective HIV-1 integrase inhibitor screening platform: Rationality validation of drug screening,conformational mobility and molecular recognition analysis for PFV integrase complex with viral DNA

As an important target for the development of novel anti-AIDS drugs, HIV-1 integrase (IN) has been widely concerned. However, the lack of a complete accurate crystal structure of HIV-1 IN greatly blocks the discovery of novel inhibitors. In this work, an effective HIV-1 IN inhibitor screening platform, namely PFV IN, was filtered from all species of INs. Next, the 40.8% similarity with HIV-1 IN, as well as the high efficiency of virtual screening and the good agreement between calculated binding free energies and experimental ones all proved PFV IN is a promising screening platform for HIV-1 IN inhibitors. Then, the molecular recognition mechanism of PFV IN by its substrate viral DNA and six naphthyridine derivatives (NRDs) inhibitors was investigated through molecular docking, molecular dynamics simulations and water-mediated interactions analyses. The functional partition of NRDs IN inhibitors could be divided into hydrophobic and hydrophilic ones, and the Mg²⁺ ions, water molecules and conserved DDE motif residues all interacted with the hydrophilic partition, while the bases in viral DNA and residues like Tyr212, Pro214 interacted with the hydrophobic one. Finally, the free energy landscape (FEL) and cluster analyses were performed to explore the molecular motion of PFV IN-DNA system. It is found that the association with NRDs inhibitors would obviously decrease the motion amplitude of PFV IN-DNA, which may be one of the most potential mechanisms of IN inhibitors. This work will provide a theoretical basis for the inhibitor design based on the structure of HIV-1 IN.