Characterization,pretreatment and saccharification of spent seaweed biomass for bioethanol production using baker's yeast

Seaweeds are marine macroalgae found abundantly and viewed as potential source of phycocolloids to produce biofuel. In this study, seaweed spent biomass obtained from alginate production industry and biomass obtained after pigment extraction were found to contain a considerable amount of phycocolloids. These two spent biomasses were investigated for the production of ethanol. In this study, the red seaweed spent biomass of Gracilaria corticata var corticata showed higher content of polysaccharide (190.71 ± 30.67 mg g⁻¹ dry weight) than brown seaweed spent biomass (industrial) (136.28 ± 30.09 mg g⁻¹ dry weight). Hydrolysis of spent biomasses with different concentrations of sulfuric acid (0.1%, 0.5% and 1%) was also investigated. Brown seaweed spent biomass and red seaweed spent biomass exhibited high amount of sugar in 0.5% and 1% sulfuric acid treatment, respectively. Proximate and ultimate composition of seaweed spent biomasses were analysed for energy value. The FT-Raman spectra exhibited similar stretches for both acid hydrolysed spent biomasses with their respective standards. Ethanol produced through a fermentation process using spent hydrolysates with baker's yeast at pH 5.3 was found to be significant. The ethanol yield from brown seaweed spent biomass and red seaweed spent biomass was observed to be 0.011 g g⁻¹ and 0.02 ± 0.003 g g⁻¹ respectively, when compared with YPD (0.42 ± 0.03 g g⁻¹) and d-galactose (0.37 ± 0.04 g g⁻¹) as standard on day 4. The present study revealed the possibility of effective utilization of spent biomass from seaweed industry for ethanol production.     

基于CAE技术的单体液压支柱油缸部件分析

在介绍了DW型单体液压支柱的结构和工作原理的基础上,通过Pro/E软件平台实现了DW16-300/100单体液压支柱的参数化设计,并对其油缸部件进行了局部的受力分析。针对单体液压支柱在不同的工况情况下,利用ANSYS11.0对油缸进行强度有限元分析,得出油缸的结构位移和应力分布变形情况。结果表明,有限元分析结果和力学计算结果基本保持一致,通过对比分析,可为单体液压支柱油缸的优化设计和研究提供理论依据。     

Determination of falcarinol in carrot (Daucus carota L.) genotypes using liquid chromatography/mass spectrometry

A new analytical method for the determination of falcarinol [(Z)-heptadeca-1,9-diene-4,6-diyn-3-ol] in carrot root samples has been developed and validated. The method consists of accelerated solvent extraction (ASE) of lyophilised carrot root samples with ethyl acetate and LC–MS analysis of the extracts. Falcarinol was determined by extracting the main ion species generated in the ESI positive mode, m/z 268 [M+H–H₂O+MeCN]⁺, from the full MS chromatogram. Quantitation was performed using a falcarinol calibration curve (correlation coefficient 0.9975) as an external standard and pelargonic acid vanillylamide as an internal standard. The method showed good precision with interday and intraday variation of less than 4% and high recovery (average recovery rate 97.9%). LOD (S/N = 3) and LOQ (S/N = 10) were 2.5 and 7 ng, respectively. Using this method, 27 different carrot genotypes grown and harvested under the same conditions were analyzed, and falcarinol contents ranging from 0.70 to 4.06 mg/100 g fresh weight were determined.     

GW4-40.5DW型隔离刀闸改造

为了消除GW4-40.5DW型隔离刀闸频繁发热问题,同时本着安全可靠,降低费用的原则,根据隔离刀闸的工作条件、设计原理制作加工件来固定接地刀闸的静触头,从而保证了GW4-40.5DW型隔离刀闸安全、稳定运行。     

DW中一种基于本体的语义集成方法研究

文中介绍了数据仓库领域一种基于本体的语义集成方法。首先建立领域本体和数据源的局部本体,然后通过局部本体对应的概念树间的映射算法得到数据源全局本体,再和领域本体映射,得到映射关系。最后通过本体推理,得出隐含的语义关系,用最终的语义关系来指导数据抽取、转换和加载过程,实现数据仓库语义程度上的数据集成。     

THERMUS—A thermal model package for ROOT

THERMUS is a package of C++ classes and functions allowing statistical-thermal model analyses of particle production in relativistic heavy-ion collisions to be performed within the ROOT framework of analysis. Calculations are possible within three statistical ensembles; a grand-canonical treatment of the conserved charges B, S and Q, a fully canonical treatment of the conserved charges, and a mixed-canonical ensemble combining a canonical treatment of strangeness with a grand-canonical treatment of baryon number and electric charge. THERMUS allows for the assignment of decay chains and detector efficiencies specific to each particle yield, which enables sensible fitting of model parameters to experimental data.

Program summary

Program title: THERMUS, version 2.1Catalogue identifier: AEBW_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBW_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 17 152No. of bytes in distributed program, including test data, etc.: 93 581Distribution format: tar.gzProgramming language: C++Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent)Operating system: Linux: FEDORA, RedHat, etc.Classification: 17.7External routines: Numerical Recipes in C [1], ROOT [2]Nature of problem: Statistical-thermal model analyses of heavy-ion collision data require the calculation of both primordial particle densities and contributions from resonance decay. A set of thermal parameters (the number depending on the particular model imposed) and a set of thermalized particles, with their decays specified, is required as input to these models. The output is then a complete set of primordial thermal quantities for each particle, together with the contributions to the final particle yields from resonance decay. In many applications of statistical-thermal models it is required to fit experimental particle multiplicities or particle ratios. In such analyses, the input is a set of experimental yields and ratios, a set of particles comprising the assumed hadron resonance gas formed in the collision and the constraints to be placed on the system. The thermal model parameters consistent with the specified constraints leading to the best-fit to the experimental data are then output.Solution method: THERMUS is a package designed for incorporation into the ROOT [2] framework, used extensively by the heavy-ion community. As such, it utilizes a great deal of ROOT's functionality in its operation. ROOT features used in THERMUS include its containers, the wrapper TMinuit implementing the MINUIT fitting package, and the TMath class of mathematical functions and routines. Arguably the most useful feature is the utilization of CINT as the control language, which allows interactive access to the THERMUS objects. Three distinct statistical ensembles are included in THERMUS, while additional options to include quantum statistics, resonance width and excluded volume corrections are also available. THERMUS provides a default particle list including all mesons (up to the (2045)) and baryons (up to the Ω⁻) listed in the July 2002 Particle Physics Booklet [3]. For each typically unstable particle in this list, THERMUS includes a text-file listing its decays. With thermal parameters specified, THERMUS calculates primordial thermal densities either by performing numerical integrations or else, in the case of the Boltzmann approximation without resonance width in the grand-canonical ensemble, by evaluating Bessel functions. Particle decay chains are then used to evaluate experimental observables (i.e. particle yields following resonance decay). Additional detector efficiency factors allow fine-tuning of the model predictions to a specific detector arrangement. When parameters are required to be constrained, use is made of the ‘Numerical Recipes in C’ [1] function which applies the Broyden globally convergent secant method of solving nonlinear systems of equations. Since the NRC software is not freely-available, it has to be purchased by the user. THERMUS provides the means of imposing a large number of constraints on the chosen model (amongst others, THERMUS can fix the baryon-to-charge ratio of the system, the strangeness density of the system and the primordial energy per hadron). Fits to experimental data are accomplished in THERMUS by using the ROOT TMinuit class. In its default operation, the standard χ² function is minimized, yielding the set of best-fit thermal parameters. THERMUS allows the assignment of separate decay chains to each experimental input. In this way, the model is able to match the specific feed-down corrections of a particular data set.Running time: Depending on the analysis required, run-times vary from seconds (for the evaluation of particle multiplicities given a set of parameters) to several minutes (for fits to experimental data subject to constraints).References:

[1]

W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C: The Art of Scientific Computing, Cambridge University Press, Cambridge, 2002.

[2]

R. Brun, F. Rademakers, Nucl. Inst. Meth. Phys. Res. A 389 (1997) 81. See also http://root.cern.ch/.

[3]

K. Hagiwara et al., Phys. Rev. D 66 (2002) 010001.

     

数据仓库技术在教学管理信息系统中的应用研究

在现有信息系统基础上建立数据仓库应用是信息系统开发面临的新课题。文章介绍了数据仓库的基本概念和系统结构,针对教学管理信息系统中的数据特性,探讨了数据仓库中的数据组织的基本方法。     

Periodic peristalsis enhancing the high solids enzymatic hydrolysis performance of steam exploded corn stover biomass

Enzymatic hydrolysis beyond 15% solid loading offers many advantages such as increased sugar and ethanol concentrations and decreased capital cost. However, difficult mixing and handling limited its industrialized application. A novel intensification method, periodic peristalsis, had been exploited to improve the high solids enzymatic hydrolysis performance of steam exploded corn stover (SECS). The optimal steam explosion conditions were 200 °C and 8 min, under which glucan and xylan recovery was 94.3% and 64.8%, respectively. Glucan and xylan conversions in periodic peristalsis enzymatic hydrolysis (PPEH) were 28.0–38.5% and 25.0–36.0% higher than those in static state enzymatic hydrolysis with solid loading increasing from 1% to 30%, respectively, while they were 1.0–11.2% and 3.0–9.2% higher than those in incubator shaker enzymatic hydrolysis (ISEH). Glucan and xylan conversion in PPEH at 21% solid loading reached 71.2% and 70.3%, respectively. Periodic peristalsis also facilitated fed-batch enzymatic hydrolysis of which SECS was added completely before transition point. Results presented that PPEH shortened the transition point time from solid state to slurry state, decreased the viscosity of hydrolysis mixture, and reduced the denaturation effect of enzymes compared with ISEH, and hence improve the high solids enzymatic hydrolysis efficiency.     

露天矿卡车调度系统数据处理技术的研究

利用数据仓库DW(Data Warehouse)、联机分析处理OLAP(On—Line Analytical Processing)、数据挖掘DM(Data Mining)等技术对露天矿卡车调度系统存有的大量数据,提出分析处理的思路和方法。     

面向数据仓库技术的财务决策支持系统研究

以数据仓库技术为核心,结合联机分析处理技术和数据挖掘技术的基础上,构建了财务决策支持系统,通过使用数据仓库的联机分析技术和数据挖掘技术强化了DSS的智能功能,为企业财务决策提供服务。