Modification of hemicellulose content by antisense down-regulation of UDP-glucuronate decarboxylase in tobacco and its consequences for cellulose extractability

Extractability and recovery of cellulose from cell walls influences many industrial processes and also the utilisation of biomass for energy purposes. The utility of genetic manipulation of lignin has proven potential for optimising such processes and is also advantageous for the environment. Hemicelluloses, particularly secondary wall xylans, also influence the extractability of cellulose. UDP-glucuronate decarboxylase produces UDP-xylose, the precursor for xylans and the effect of its down-regulation on cell wall structure and cellulose extractability in transgenic tobacco has been investigated. Since there are a number of potential UDP-glucuronate decarboxylase genes, a 490 bp sequence of high similarity between members of the family, was chosen for general alteration of the expression of the gene family. Sense and antisense transgenic lines were analysed for enzyme activity using a modified and optimised electrophoretic assay, for enzyme levels by western blotting and for secondary cell wall composition. Some of the down-regulated antisense plants showed high glucose to xylose ratios in xylem walls due to less xylose-containing polymers, while arabinose and uronic acid contents, which could also have been affected by any change in UDP-xylose provision, were unchanged. The overall morphology and stem lignin content of the modified lines remained little changed compared with wild-type. However, there were some changes in vascular organisation and reduction of xylans in the secondary walls was confirmed by immunocytochemistry. Pulping analysis showed a decreased pulp yield and a higher Kappa number in some lines compared with controls, indicating that they were less delignified, although the level of residual alkali was reduced. Such traits probably indicate that lignin was less available for removal in a reduced background of xylans. However, the viscosity was higher in most antisense lines, meaning that the cellulose was less broken-down during the pulping process. This is one of the first studies of a directed manipulation of hemicellulose content on cellulose extractability and shows both positive and negative outcomes.

Modification of hemicellulose content by antisense down-regulation of UDP-glucuronate decarboxylase in tobacco and its conscequence for cellulose extractability

Extractability and recovery of cellulose from cell walls influences many industrial processes and also the utilisation of biomass for energy purposes. The utility of genetic manipulation of lignin has proven potential for optimising such processes and is also advantageous for the environment. Hemicelluloses, particularly secondary wall xylans, also influence the extractability of cellulose. UDP-glucuronate decarboxylase produces UDP-xylose, the precursor for xylans and the effect of its down-regulation on cell wall structure and cellulose extractability in transgenic tobacco has been investigated. Since there are a number of potential UDP-glucuronate decarboxylase genes, a 490 bp sequence of high similarity between members of the family, was chosen for general alteration of the expression of the gene family. Sense and antisense transgenic lines were analysed for enzyme activity using a modified and optimised electrophoretic assay, for enzyme levels by western blotting and for secondary cell wall composition. Some of the down-regulated antisense plants showed high glucose to xylose ratios in xylem walls due to less xylose-containing polymers, while arabinose and uronic acid contents, which could also have been affected by any change in UDP-xylose provision, were unchanged. The overall morphology and stem lignin content of the modified lines remained little changed compared with wild-type. However, there were some changes in vascular organisation and reduction of xylans in the secondary walls was confirmed by immunocytochemistry. Pulping analysis showed a decreased pulp yield and a higher Kappa number in some lines compared with controls, indicating that they were less delignified, although the level of residual alkali was reduced. Such traits probably indicate that lignin was less available for removal in a reduced background of xylans. However, the viscosity was higher in most antisense lines, meaning that the cellulose was less broken-down during the pulping process. This is one of the first studies of a directed manipulation of hemicellulose content on cellulose extractability and shows both positive and negative outcomes.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Cybernetics – the modern science of systems

This article has been written in memory of Norbert Wiener and is dedicated to him. Takes a look at how cybernetics provides an extremely useful framework for the control and operation of real-world systems. With the true advent of computers and simple communications, many more processes can and will be viewed from a systems standpoint. Examples are given of how cybernetics can be applied to industrial processes and how it is seen as an important, integral part of future systems science.

Optimal control of nonlinear differential algebraic equation systems

A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

Predicting fault inflow in iterative software development processes: an industrial evaluation

This paper addresses the need for accurate predictions on the fault inflow, i.e. the number of faults found in the consecutive project weeks, in highly iterative processes. In such processes, in contrast to waterfall-like processes, fault repair and development of new features run almost in parallel. Given accurate predictions on fault inflow, managers could dynamically re-allocate resources between these different tasks in a more adequate way. Furthermore, managers could react with process improvements when the expected fault inflow is higher than desired. This study suggests software reliability growth models (SRGMs) for predicting fault inflow. Originally developed for traditional processes, the performance of these models in highly iterative processes is investigated. Additionally, a simple linear model is developed and compared to the SRGMs. The paper provides results from applying these models on fault data from three different industrial projects. One of the key findings of this study is that some SRGMs are applicable for predicting fault inflow in highly iterative processes. Moreover, the results show that the simple linear model represents a valid alternative to the SRGMs, as it provides reasonably accurate predictions and performs better in many cases.

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

On the Convergence of Two-Stage Iterative Processes for Solving Linear Equations

This paper considers two-stage iterative processes for solving the linear system $Af = b$. The outer iteration is defined by $Mf^{k + 1} = Nf^k + b$, where $M$ is a nonsingular matrix such that $M - N = A$. At each stage $f^{k + 1} $ is computed approximately using an inner iteration process to solve $Mv = Nf^k + b$ for $v$. At the $k$th outer iteration, $p_k $ inner iterations are performed. It is shown that this procedure converges if $p_k \geqq P$ for some $P$ provided that the inner iteration is convergent and that the outer process would converge if $f^{k + 1} $ were determined exactly at every step. Convergence is also proved under more specialized conditions, and for the procedure where $p_k = p$ for all $k$, an estimate for $p$ is obtained which optimizes the convergence rate. Examples are given for systems arising from the numerical solution of elliptic partial differential equations and numerical results are presented.

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop-soil system: validation and application

Models for water transfer in the crop-soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop-soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop-soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. (c) 2009 Elsevier B.V. All rights reserved.

Change escalation processes and complex adaptive systems: from incremental reconfigurations to discontinuous restructuring

This study examines when “incremental” change is likely to trigger “discontinuous” change, using the lens of complex adaptive systems theory. Going beyond the simulations and case studies through which complex adaptive systems have been approached so far, we study the relationship between incremental organizational reconfigurations and discontinuous organizational restructurings using a large-scale database of U.S. Fortune 50 industrial corporations. We develop two types of escalation process in organizations: accumulation and perturbation. Under ordinary conditions, it is perturbation rather than the accumulation that is more likely to trigger subsequent discontinuous change. Consistent with complex adaptive systems theory, organizations are more sensitive to both accumulation and perturbation in conditions of heightened disequilibrium. Contrary to expectations, highly interconnected organizations are not more liable to discontinuous change. We conclude with implications for further research, especially the need to attend to the potential role of managerial design and coping when transferring complex adaptive systems theory from natural systems to organizational systems.

Effect of impurities in biodiesel-derived waste glycerol on the performance and feasibility of biotechnological processes

The rapid development of biodiesel production technology has led to the generation of tremendous quantities of glycerol wastes, as the main by-product of the process. Stoichiometrically, it has been calculated that for every 100 kg of biodiesel, 10 kg of glycerol are produced. Based on the technology imposed by various biodiesel plants, glycerol wastes may contain numerous kinds of impurities such as methanol, salts, soaps, heavy metals and residual fatty acids. This fact often renders biodiesel-derived glycerol unprofitable for further purification. Therefore, the utilization of crude glycerol though biotechnological means represents a promising alternative for the effective management of this industrial waste. This review summarizes the effect of various impurities-contaminants that are found in biodiesel-derived crude glycerol upon its conversion by microbial strains in biotechnological processes. Insights are given concerning the technologies that are currently applied in biodiesel production, with emphasis to the impurities that are added in the composition of crude glycerol, through each step of the production process. Moreover, extensive discussion is made in relation with the impact of the nature of impurities upon the performances of prokaryotic and eukaryotic microorganisms, during crude glycerol bioconversions into a variety of high added-value metabolic products. Finally, aspects concerning ways of crude glycerol treatment for the removal of inhibitory contaminants as reported in the literature are given and comprehensively discussed