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Rhamsan gum is a type of water-soluble exopolysaccharide produced by species of Sphingomonas bacteria. The optimal fermentation medium for rhamsan gum production by Sphingomonas sp. CGMCC 6833 was explored definition. Single-factor experiments indicate that glucose, soybean meal, K(2)HPO(4) and MnSO(4) compose the optimal medium along with and initial pH 7.5. To discover ideal cultural conditions for rhamsan gum production in a shake flask culture, response surface methodology was employed, from which the following optimal ratio was derived: 5.38 g/L soybean meal, 5.71 g/L K(2)HPO(4) and 0.32 g/L MnSO(4). Under ideal fermentation rhamsan gum yield reached 19.58 g/L ± 1.23 g/L, 42.09% higher than that of the initial medium (13.78 g/L ± 1.38 g/L). Optimizing the fermentation medium results in enhanced rhamsan gum production.

The optimal temperature for the microbial polysaccharide fermentation is no higher than 30 °C, which is economically undesirable due to additional cooling cost. To solve this problem in the case of welan gum production, we obtained the high-temperature-tolerant-producing strain, Sphingomonas sp. HT-1 by atmospheric and room-temperature plasma-induced mutation. Using HT-1, we obtained a concentration and 1 % aqueous viscosity of 26.8 ± 0.34 g/L and 3.50 ± 0.05 Pa s at a comparatively higher optimal temperature (37 °C). HT-1 was further characterized to understand the mechanism by which these properties are improved. Results indicated that high yield could be attributed to the following: (1) enhanced intracellular synthesis, demonstrated by an increase in the activities of key enzymes, and (2) accelerated cross-membrane substrate uptake and product secretion, indicated by improved membrane fluidity and permeability. Temperature tolerance could be attributed to the overexpression of the investigated heat shock proteins and oxidative stress proteins.

Breast tumor segmentation is useful to diagnose breast cancer. However, challenges, such as intensity inhomogeneity and shadowing artifacts arise in this task. To address these two issues, this paper proposes a robust ultrasound image segmentation method based on correction learning. At first, a novel idea of correction learning is introduced. In contrast to traditional methods that develop the complex models to obtain accurate segmentation results, correction learning aims to detect the erroneous segmentation in advance and correct this automatically by only using simple method. The proposed correction learning method mainly involves two steps: coarse segmentation and correction learning. First, an active contour model is firstly constructed for coarse segmentation by introducing assumption of bias field and local intensity clustering property. Then, correction learning is developed to address the erroneous segmentation and to improve the segmentation performance. In this paper, correction learning mainly contains Internal Tumor Block Correction (ITBC) and Boundary Block Correction(BBC). In order to correct the erroneous segmentation caused by intensity inhomogeneity, the internal tumor blocks detection model based on Simple Linear Iterative Clustering(SLIC) and Support Vector Machine (SVM) is learned to detect these segmented blocks. Based on the detection result, the incorrect segmented blocks can be corrected. In addition, BBC is proposed to correct the erroneous segmentation of boundary blocks which are caused by shadowing artifacts. Our experiment results on the constructed database demonstrate the effectiveness and robustness of the proposed method.

Porous materials are promising media for designing medical instruments, drug carriers, and bioimplants because of their excellent biocompatibility, ease of design, and large variation of elastic moduli. In this study, a computational strategy using the finite element method is developed to model the porous microstructures and to predict the relevant elastic moduli considering the actual characteristics of the micropores and their distributions. First, an element-based approach is presented to generate pores of different shapes and sizes according to the experimental observations. Then, a computational scheme to evaluate the effective moduli of macroscopically isotropic porous materials based on their micro-mechanics is introduced. Next, the accuracy of our approach is verified with the analytical solutions of the extreme bounds of the elastic isotropic moduli of a simplified model and with the experimental data available in the literature. Finally, the influence of the shape of pores and their distribution modes are assessed.

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Abstract.With the train axle product as the research object, based on analysis of the functional needs of the CAD/CAPP parametric design system of train axle, the overall functional framework of the system is decided, and the Unified Modeling Language (UML) activity diagram of the system is designed. The parametric design methods of the system are discussed, including the shaft shape features and parametric programming, the establishment of feature drawing function. Based on Visual Basic 6.0 programming language and SQL Sever database technology, the CAD/CAPP parametric design system of train axle is developed, and an application example is given. The application result shows that the system is easy to operate and significantly saves the design time of the product. The format of its generated drawings is unified, and accords with the national standard specification. IntroductionAt present, the products of domestic manufacturing enterprises are stable, and the daily product design mode of enterprises is usually to modify the existing similar products according to customer needs [1]. Because of the customers' individual and diversified demand for the train axle product, the modified design based on the basic product involves a lot of tedious drawing design and process design work, and its design efficiency is low and easy to make mistakes. The traditional interactive computer drawing is difficult to meet the needs of custom-made production. It is necessary to use CAD and CAPP parameterized technology to realize the rapid design of the product, in order to shorten the design cycle and improve the efficiency and quality of the design.In order to study the stress field of axle, the visual data checking of axle was carried out in Southwest Jiaotong University [2] based on OpenGL technology, and a parametric modeling system of axle was realized by modularization idea. However, the parameterized modeling function of the system is only for the main parameters of the axle, and lacks the automatic drawing function of the intermediate process in the manufacturing process of the axle.Aiming at the deficiency in reference [2] and the actual demand of a train axle manufacturing enterprise, this paper puts forward the overall functional framework of the CAD/CAPP parametric design system of train axle and the work flow model of the system. Then, this paper focuses on the parametric design methods, including the shaft shape feature and parameter planning, the construction of the feature drawing function and so on. Finally, the CAD/CAPP parameterized design system of train axle is developed, and the parameterized design of train axle and automatic generation of engineering drawings and process drawings are realized.

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