BackgroundD-2,3-butanediol has many industrial applications such as chiral reagents, solvents, anti-freeze agents, and low freezing point fuels. Traditional D-2,3-butanediol producing microorganisms, such as Klebsiella pneumonia and K. xoytoca, are pathogenic and not capable of producing D-2,3-butanediol at high optical purity. Bacillus licheniformis is a potential 2,3-butanediol producer but the wild type strain (WX-02) produces a mix of D- and meso-type isomers. BudC in B. licheniformis is annotated as 2,3-butanediol dehydrogenase or acetoin reductase, but no pervious experiment was performed to verify this hypothesis.ResultsWe developed a genetically modified strain of B. licheniformis (WX-02 ΔbudC) as a D-2,3-butanediol producer with high optimal purity. A marker-less gene deletion protocol based on a temperature sensitive knock-out plasmid T2-Ori was used to knock out the budC gene in B. licheniformis WX-02. The budC knock-out strain successfully abolished meso-2,3-butanediol production with enhanced D-2,3-butanediol production. No meso-BDH activity was detectable in cells of this strain. On the other hand, the complementary strain restored the characteristics of wild strain, and produced meso-2,3-butanediol and possessed meso-BDH activity. All of these data suggested that budC encoded the major meso-BDH catalyzing the reversible reaction from acetoin to meso-2,3-butanediol in B. licheniformis. The budC knock-out strain produced D-2,3-butanediol isomer only with a high yield of 30.76 g/L and a productivity of 1.28 g/L-h.ConclusionsWe confirmed the hypothesis that budC gene is responsible to reversibly transfer acetoin to meso-2,3-butanediol in B. licheniformis. A mutant strain of B. licheniformis with depleted budC gene was successfully developed and produced high level of the D-2,3-butanediol with high optimal purity.

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The energy Internet is a complex multi-grid flow system, which is based on the power system, the Internet and other cutting-edge information technologies, with distributed renewable energy as the main primary energy and closely coupled with natural gas network, transportation network and other systems. The power grid technology has to develop to support the energy Internet construction. This paper discusses the changes and challenges in the asset environment, asset types, asset scope and asset risk under the energy Internet. Then the corresponding implementation methods of power grid technology to supporting energy Internet construction are put forward. The research results can provide reference for power grid companies to implement power technical innovation.

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In recent years, the changing trend and causes of power grid engineering are diversified and complicated. In view of this problem, it is impossible to determine the influencing factors by quantitative analysis. Selection in order to solve this problem, we collect relevant power transmission project data, since 2015. First, we determine the control index system, 20 factors affected substation project, 19 influence factors affected route project, and then use AHP method to establish the new situation under the background of grid engineering control model. Through the MATLAB software, we determine the weight of each influence factor. Finally, the factors that have great influence on power grid engineering control are obtained according to the order of weight. Thus, it lays the foundation for the orderly development of better control grid engineering in the future.

ObjectiveTurn-amplitude clouds were widely used in automatic electromyography (EMG) interference pattern analysis. Earlier works employed the intercept ± 2SD (standard deviation) of the linear regression equation as the upper and lower boundaries of the clouds. The goal of this study was to employ the linear regression method and percentile method to calculate the reference value of turn-amplitude clouds, identify the determining criteria in accordance with the receiver operator characteristic curve (ROC), and analyze the sensitivity and specificity of the linear regression cloud, percentile cloud, and quantitative assessment of the motor unit potential (QMUP).MethodsFirst, we explore what factors affect the number of turns per second and the mean amplitude. Then, their logarithms were taken for the normal test. All muscle data were used to calculate the reference values of percentile clouds. However, the reference values of the linear regression clouds were obtained for the muscles with a bivariate normal distribution, homogeneous variances and a linear correlation. We calculated the prediction interval with the standard errors of the intercept and slope of the linear regression equation, which can determine the upper and lower boundaries of the linear regression clouds. Furthermore, we obtained ROCs of these clouds, which were used as the determining criteria to determine the optimum cut-off values. Finally, our study analyzed the sensitivity and specificity of the linear regression cloud, percentile cloud, and QMUP.ResultsWe here presented the reference values and ROCs of the linear regression clouds and percentile clouds. We suggest the determining criteria be based on ROCs. The areas under the curve (AUC) of both clouds are larger than 0.8, revealing that they have significant diagnostic value. Our results display that the specificities of the linear regression clouds, percentile clouds, and QMUP are almost identical to each other, whereas the sensitivity of percentile cloud is higher than those of QMUP and linear regression clouds.ConclusionAccording to ROCs, the researchers determine the determining criteria of the linear regression clouds and percentile clouds. Our findings suggest that the percentile clouds possess a wide application range and significant diagnostic value, therefore it may be the optimum for automatic EMG interference pattern analysis.

Abstract. Oriented the amounts of the service requests on the user's demand, it is possible to provide the service to the users with the lowest price, the most economical resource and the type of service closest to the users' requests. In order to provide the different resources to the users effectively, the optimization model of the management about the cloud services resources is set up. In the first place, under the guidance of the resources management center, it is best to match the most suitable cloud service resources for the user needs with the grey relational comprehensive evaluation, then according to the time, the price, the data workflow and the service type attribute value. Optimal resource deployment algorithm is established with the target of the best cloud service resources offered to the users. Finally, it is verified the validity and rationality of the method by the simulation.

To meet power cable construction underground in the city, it is necessary to ensure the normal operation of power cable. In this paper, we do the research about the compensation mode of cable line construction in Henan province, that is the difference mode and the construction mode, and analyzed with the actual project. We get the conclusion that difference fee compare to the construction fee is increased the difference between the cable fee and overhead cost. And we analysis the reasons based on "State grid corporation on General cost of transmission and transformation engineering" and the actual engineering. Keywords: Big Data; Power cable; Difference feeAlong with the sustained development of the urbanization of our province, in order to strength the management about urban underground pipeline construction，guarantee the safe operation of the city, and improve the quality of the comprehensive combined load capacity and urbanization development.Planning requirements of electric line cable is put forward around the city and the new urban area [1] .Normal power lines are invested by electricity companies. Because the cable line has characteristics of one-time investment, long recovery period construction cost and high maintenance cost, which is compare to the overhead line. Based on the principle of "who advocates, who pays", Power Company negotiated with the government: the government for the cable line construction pay for the corresponding compensation [2] . Current compensation patterns in Henan province is mainly divided into two kinds: one is the price spread compensation mode provide by government between cable plan and overhead plan. (referred to as "differential mode", costs as price difference). The other is use free of charge that the cable construction is pad by the government (for short " civil construction "). This paper analyzes the two investment modes from the theory and the practical engineering [3] .