Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry     

对我厂防治加热管内碳酸钙垢的思索

分析了我厂两碱法原卤净化后,加热管内壁结碳酸钙垢的原因,探讨了我厂采取加盐酸、加阻垢剂、用超声波阻垢器的方法,以及对加热管内碳酸钙垢防治的情况和存在的问题.     

大庆蜡油在酸性催化剂上反应机理的研究

以大庆蜡油为原料，采用两种不同类型的催化剂，在流化床反应器实验装鬣上进行催化裂化反应。结果表明，大庆蜡油在酸性催化剂上反应所产生的干气组成与高烯烃催化裂化汽油相同，干气的产生主要是单分子裂化反应所造成的。从干气产率、组成以及液化气组成可以看出，大庆蜡油在不同类型的催化剂上明显地表现出裂化反应类型的差异。     

Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

紫苏中迷迭香酸的乙醇提取优化实验研究

研究了采用乙醇提取法从紫苏中提取迷迭香酸的工艺条件。方法采用正交实验L9（3^4）优化迷迭香酸乙醇浸提法的提取工艺，硫酸亚铁比色法测定迷迭香酸含量。确定了最佳工艺条件为：50％乙醇为提取剂，料液比为1：50（w／v），提取温度为65℃，提取时间为35min，迷迭香酸提取率为1．061％比热水浸提法提高了30．18％。     

2，6-萘二甲酸二甲酯在有机溶剂中溶解度的测定与关联

Solubility of dimethyl-2,6-naphthalene dicarboxylate in acetic acid, N,N-dimethylfonnamide, N,N-dimethyl acetamide, dimethyl sulphoxide, and N-methyl-2-ketopyrrolidine were determined using a dynamic method. The measured systems were correlated by UNIFAC group contribution method. A new main group （aromatic ester, ACCOO） was defined to express the activity coefficients of the aromatic ester. New interaction parameters of the ACCOO group were expressed as the first-order function of temperature and were determined from the experimental data. The calculated results for the new interaction parameters were satisfactory. The measured systems were also correlated with the Wilson and 2-h models, and the results were compared with those of the UNIFAC model.     

Restricted overlapping balancing domain decomposition methods and restricted coarse problems for the Helmholtz problem

Overlapping balancing domain decomposition methods and their combination with restricted additive Schwarz methods are proposed for the Helmholtz equation. These new methods also extend previous work on non-overlapping balancing domain decomposition methods toward simplifying their coarse problems and local solvers. They also extend restricted Schwarz methods, originally designed to overlapping domain decomposition and Dirichlet local solvers, to the case of non-overlapping domain decomposition and/or Neumann and Sommerfeld local solvers. Finally, we introduce coarse spaces based on partitions of unity and planes waves, and show how oblique projection coarse problems can be designed from restricted additive Schwarz methods. Numerical tests are presented.     

Simulation of macroscopic material behavior for uniaxial fiber-matrix composites, using a DAE-approach

The macroscopic deformation behavior of a fiber-reinforced aluminum-boron composite is investigated. Different periodic and random arrangements of the microstructure are considered with macroscopic hardening behavior due to the evolution of plastic zones on the microscale being taken into account.

For the solution of the initial boundary value problem, a non-standard algorithm is applied. It consists of the direct solution of the whole set of equations, treating all variables as global quantities. Together with a higher order time integration method (BDF2), an automatic step size control is used in the FEM calculations.     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

国家粮储库屋面防水APP卷材施工技术

针对国家粮食储备库的特点，就屋面防水APP卷材热熔法施工的施工准备及工艺流程进行了介绍，提出了具体的施工技术要点及质量通病的防治措施，取得了良好的施工效果。