Exponential integrators and a dual-scale model for wood drying

For the timber industry, the ability to simulate the drying of wood is invaluable for manufacturing high quality wood products. Mathematically, however, modelling the drying of a wet porous material, such as wood, is a diffcult task due to its heterogeneous and anisotropic nature, and the complex geometry of the underlying pore structure. The well{ developed macroscopic modelling approach involves writing down classical conservation equations at a length scale where physical quantities (e.g., porosity) can be interpreted as averaged values over a small volume (typically containing hundreds or thousands of pores). This averaging procedure produces balance equations that resemble those of a continuum with the exception that effective coeffcients appear in their deffnitions. Exponential integrators are numerical schemes for initial value problems involving a system of ordinary differential equations. These methods differ from popular Newton{Krylov implicit methods (i.e., those based on the backward differentiation formulae (BDF)) in that they do not require the solution of a system of nonlinear equations at each time step but rather they require computation of matrix{vector products involving the exponential of the Jacobian matrix. Although originally appearing in the 1960s, exponential integrators have recently experienced a resurgence in interest due to a greater undertaking of research in Krylov subspace methods for matrix function approximation. One of the simplest examples of an exponential integrator is the exponential Euler method (EEM), which requires, at each time step, approximation of φ(A)b, where φ(z) = (ez - 1)/z, A E Rnxn and b E Rn. For drying in porous media, the most comprehensive macroscopic formulation is TransPore [Perre and Turner, Chem. Eng. J., 86: 117-131, 2002], which features three coupled, nonlinear partial differential equations. The focus of the first part of this thesis is the use of the exponential Euler method (EEM) for performing the time integration of the macroscopic set of equations featured in TransPore. In particular, a new variable{ stepsize algorithm for EEM is presented within a Krylov subspace framework, which allows control of the error during the integration process. The performance of the new algorithm highlights the great potential of exponential integrators not only for drying applications but across all disciplines of transport phenomena. For example, when applied to well{ known benchmark problems involving single{phase liquid ow in heterogeneous soils, the proposed algorithm requires half the number of function evaluations than that required for an equivalent (sophisticated) Newton{Krylov BDF implementation. Furthermore for all drying configurations tested, the new algorithm always produces, in less computational time, a solution of higher accuracy than the existing backward Euler module featured in TransPore. Some new results relating to Krylov subspace approximation of '(A)b are also developed in this thesis. Most notably, an alternative derivation of the approximation error estimate of Hochbruck, Lubich and Selhofer [SIAM J. Sci. Comput., 19(5): 1552{1574, 1998] is provided, which reveals why it performs well in the error control procedure. Two of the main drawbacks of the macroscopic approach outlined above include the effective coefficients must be supplied to the model, and it fails for some drying configurations, where typical dual{scale mechanisms occur. In the second part of this thesis, a new dual{scale approach for simulating wood drying is proposed that couples the porous medium (macroscale) with the underlying pore structure (microscale). The proposed model is applied to the convective drying of softwood at low temperatures and is valid in the so{called hygroscopic range, where hygroscopically held liquid water is present in the solid phase and water exits only as vapour in the pores. Coupling between scales is achieved by imposing the macroscopic gradient on the microscopic field using suitably defined periodic boundary conditions, which allows the macroscopic ux to be defined as an average of the microscopic ux over the unit cell. This formulation provides a first step for moving from the macroscopic formulation featured in TransPore to a comprehensive dual{scale formulation capable of addressing any drying configuration. Simulation results reported for a sample of spruce highlight the potential and flexibility of the new dual{scale approach. In particular, for a given unit cell configuration it is not necessary to supply the effective coefficients prior to each simulation.

Exploring new and emerging models for nonlinear performative works

This dissertation seeks to define and classify potential forms of Nonlinear structure and explore the possibilities they afford for the creation of new musical works. It provides the first comprehensive framework for the discussion of Nonlinear structure in musical works and provides a detailed overview of the rise of nonlinearity in music during the 20th century. Nonlinear events are shown to emerge through significant parametrical discontinuity at the boundaries between regions of relatively strong internal cohesion. The dissertation situates Nonlinear structures in relation to linear structures and unstructured sonic phenomena and provides a means of evaluating Nonlinearity in a musical structure through the consideration of the degree to which the structure is integrated, contingent, compressible and determinate as a whole. It is proposed that Nonlinearity can be classified as a three dimensional space described by three continuums: the temporal continuum, encompassing sequential and multilinear forms of organization, the narrative continuum encompassing processual, game structure and developmental narrative forms and the referential continuum encompassing stylistic allusion, adaptation and quotation. The use of spectrograms of recorded musical works is proposed as a means of evaluating Nonlinearity in a musical work through the visual representation of parametrical divergence in pitch, duration, timbre and dynamic over time. Spectral and structural analysis of repertoire works is undertaken as part of an exploration of musical nonlinearity and the compositional and performative features that characterize it. The contribution of cultural, ideological, scientific and technological shifts to the emergence of Nonlinearity in music is discussed and a range of compositional factors that contributed to the emergence of musical Nonlinearity is examined. The evolution of notational innovations from the mobile score to the screen score is plotted and a novel framework for the discussion of these forms of musical transmission is proposed. A computer coordinated performative model is discussed, in which a computer synchronises screening of notational information, provides temporal coordination of the performers through click-tracks or similar methods and synchronises the audio processing and synthesized elements of the work. It is proposed that such a model constitutes a highly effective means of realizing complex Nonlinear structures. A creative folio comprising 29 original works that explore nonlinearity is presented, discussed and categorised utilising the proposed classifications. Spectrograms of these works are employed where appropriate to illustrate the instantiation of parametrically divergent substructures and examples of structural openness through multiple versioning.

Cost and environmental efficiency of rice farms in South Korea

We examine cost and nutrient use efficiency of farms and determine the cost to move farms to nutrient-efficient operation using Data Envelopment Analysis (DEA) with a dataset of 96 rice farms in Gangwon province of South Korea from 2003 to 2007. Our findings show that improvements in technical efficiency would result in both lower production costs and better environmental performance. It is, however, not costless for farms to move from their current operation to the environmentally efficient operation. On average, this movement would increase production costs by 119% but benefit the water system through an approximately 69% reduction in eutrofying power (EP). The average estimated cost of each EP kg of aggregate nutrient reduction is approximately one thousand two hundred won. For technically efficient farms, there is a trade-off between cost and environmental efficiency. We also find that the environmental performance of farms varies across farms and regions. We suggest that agri-environmental policies should be (re)designed to improve both cost and environmental performance of rice farms.

Thermodynamic modeling of ethanol fumigation in a diesel engine

Due to rapidly diminishing international supplies of fossil fuels, such as petroleum and diesel, the cost of fuel is constantly increasing, leading to higher costs of living, as a result of the significant reliance of many industries on motor vehicles. Many technologies have been developed to replace part or all of a fossil fuel with bio-fuels. One of the dual fuel technologies is fumigation of ethanol in diesel engines, which injects ethanol into the intake air stream of the engine. The advantage of this is that it avoids any costly modification of the engine high pressure diesel injection system, while reducing the volume of diesel required and potentially increasing the power output and efficiency. This paper investigates the performance of a diesel engine, converted to implement ethanol fumigation. The project will use both existing experimental data, along with generating computer modeled results using the program AVL Boost. The data from both experiments and the numerical simulation indicate desirable results for the peak pressure and the indicated mean effective pressure (IMEP). Increase in ethanol substitution resulted in elevated combustion pressure and an increase in the IMEP, while the variation of ethanol injection location resulted in negligible change. These increases in cylinder pressure led to a higher work output and total efficiency in the engine as the ethanol substitution was increased. In comparing the numerical and experimental results, the simulation showed a slight elevation, due to the inaccuracies in the heat release models. Future work is required to improve the combustion model and investigate the effect of the variation of the location of ethanol injection.

Effects of dissolved oxygen availability and culture biomass at induction upon the intracellular expression of monoamine oxidase by recombinant E. coli in fed batch bioprocesses

The effects of oxygen availability and induction culture biomass upon production of an industrially important monoamine oxidase (MAO) were investigated in fed-batch cultures of a recombinant E. coli. For each induction cell biomass 2 different oxygenation methods were used, aeration and oxygen enriched air. Induction at higher biomass levels increased the culture demand for oxygen, leading to fermentative metabolism and accumulation of high levels of acetate in the aerated cultures. Paradoxically, despite an almost eight fold increase in acetate accumulation to levels widely reported to be highly detrimental to protein production, when induction wet cell weight (WCW) rose from 100% to 137.5%, MAO specific activity in these aerated processes showed a 3 fold increase. By contrast, for oxygenated cultures induced at WCW's 100% and 137.5% specific activity levels were broadly similar, but fell rapidly after the maxima were reached. Induction at high biomass levels (WCW 175%) led to very low levels of specific MAO activity relative to induction at lower WCW's in both aerated and oxygenated cultures. Oxygen enrichment of these cultures was a useful strategy for boosting specific growth rates, but did not have positive effects upon specific enzyme activity. Based upon our findings, consideration of the amino acid composition of MAO and previous studies on related enzymes, we propose that this effect is due to oxidative damage to the MAO enzyme itself during these highly aerobic processes. Thus, the optimal process for MAO production is aerated, not oxygenated, and induced at moderate cell density, and clearly represents a compromise between oxygen supply effects on specific growth rate/induction cell density, acetate accumulation, and high specific MAO activity. This work shows that the negative effects of oxygen previously reported in free enzyme preparations, are not limited to these acellular environments but are also discernible in the sheltered environment of the cytosol of E. coli cells.

Stepwise engineering of a Pichia pastoris D-amino acid oxidase whole cell catalyst

Trigonopsis variabilis D-amino acid oxidase (TvDAO) is a well characterized enzyme used for cephalosporin C conversion on industrial scale. However, the demands on the enzyme with respect to activity, operational stability and costs also vary with the field of application. Processes that use the soluble enzyme suffer from fast inactivation of TvDAO while immobilized oxidase preparations raise issues related to expensive carriers and catalyst efficiency. Therefore, oxidase preparations that are more robust and active than those currently available would enable a much broader range of economically viable applications of this enzyme in fine chemical syntheses. A multi-step engineering approach was chosen here to develop a robust and highly active Pichia pastoris TvDAO whole-cell biocatalyst. As compared to the native T. variabilis host, a more than seven-fold enhancement of the intracellular level of oxidase activity was achieved in P. pastoris through expression optimization by codon redesign as well as efficient subcellular targeting of the enzyme to peroxisomes. Multi copy integration further doubled expression and the specific activity of the whole cell catalyst. From a multicopy production strain, about 1.3 x 103 U/g wet cell weight (wcw) were derived by standard induction conditions feeding pure methanol. A fed-batch cultivation protocol using a mixture of methanol and glycerol in the induction phase attenuated the apparent toxicity of the recombinant oxidase to yield final biomass concentrations in the bioreactor of >or= 200 g/L compared to only 117 g/L using the standard methanol feed. Permeabilization of P. pastoris using 10% isopropanol yielded a whole-cell enzyme preparation that showed 49% of the total available intracellular oxidase activity and was notably stabilized (by three times compared to a widely used TvDAO expressing Escherichia coli strain) under conditions of D-methionine conversion using vigorous aeration. Stepwise optimization using a multi-level engineering approach has delivered a new P. pastoris whole cell TvDAO biocatalyst showing substantially enhanced specific activity and stability under operational conditions as compared to previously reported preparations of the enzyme. The production of the oxidase through fed-batch bioreactor culture and subsequent cell permeabilization is high-yielding and efficient. Therefore this P. pastoris catalyst has been evaluated for industrial purposes.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Chemo-enzymatic synthesis of unnatural amino acids

A general chemo-enzymatic process has been developed to prepare enantiomerically pure L- and D-amino acids in high yield by deracemisation of racemic starting materials. The method has been developed from initial academic studies to be a robust, scalable industrial process. Unnatural amino acids, in high optical purity, are a rapidly growing class of intermediates required for pharmaceuticals, agrochemicals and other fine chemical applications. However, no single method has proven sufficiently adaptable to prepare these compounds generally at large scale. Our approach uses an enantioselective oxidase biocatalyst and a non-selective chemical reducing agent to effect the stereoinversion of one enantiomer and can result in an enantiomeric excess of > 99 % from a starting racemate, and product yields over 90 %. The current approach compares very favourably to resolution methods which have a maximum single pass yield of 50 %. Efficient methods have been developed to adapt the biocatalyst used in this process towards new target compounds and to optimise key factors which improve the process efficiency and offer competitive economics at scale.

Genome-wide analysis in a murine Dnmt1 knockdown model identifies epigenetically silenced genes in primary human pituitary tumors

DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.

Recovering Functional Integrity in Pastures Dominated by an Invasive Grass Species

Exotic grasses have been introduced in countries worldwide for pasture improvement, soil stabilisation and ornamental purposes. Some of these introductions have proven successful, but many have not (Cook & Dias 2006). In Australia, the Commonwealth Plant Introduction Scheme was initiated in 1929, and over-time introduced more than 5000 species of grasses, legumes and other forage and browse plants (Cook & Dias 2006). Lonsdale (1994) suggested that, in tropical Australia, 13% of introductions have become a problem, with only 5% being considered useful for agriculture. Low (1997) suggested that 5 out of 18 of Australia's worst tropical environmental weeds were intentionally introduced as pasture grasses. The spread and dominance of invasive grass species that degrade the quality of pastures for production can impact significantly on the livelihoods of small proprietors. Although Livestock grazing contributes only a small percentage to the world's GDP (1.5%), maintaining the long-term stability of this industry is crucial because of the high social and environmental consequence of a collapse. One billion of the world's poor are dependent on livestock grazing for food and income with this industry occupying more than 25% of the world's land base (Steinfeld et al. 2006). The ling-term sustainability of livestock grazing is also crucial for the environment. A recent FAO report attributed livestock production as a major cause of five of the most serious environmental problems: global warming, land degredation, air and water pollution, and the loss of biodiversity (Steinfeld et al. 2006). For these reasons, finding more effective approaches that guide the sustainable management of pastures is urgently needed. In Australia more than 55% of land use is for livestock grazing by sheelp and/or cattle. This land use dominate in the semi-arid and arid regions where rainfall and soil conditions are marginal for production (Commonwealth of Australia 2004). Although the level of agriculture production by conglomerates is increasing, the majority of livestock grazing within Australia remains family owned and operated (Commonwealth of Australia 2004). The sustainability of production from a grazed pasture is dependent on its botanical composition (Kemp & Dowling 1991, Kemp et al. 1996). In a grazed pasture, the dominance of an invasive grass species can impact on the functional integrity of the ecosystem, including production and nutrient cycling; wwhich will in turn, affect the income of proprietors and the ability of the system to recover from disturbance and environmental change. In Australia, $0.3 billion is spent on weed control in livestock production, but despite this substantial investment $1.9 billion is still lost in yield as a result of weeds (Sinden et al. 2004). In this paper, we adaprt a framework proposed for the restoration of degraded rainforest communities (Lamb & Gilmour 2003, Lamb et al. 2005) to compare and contrast options for recovering function integrity (i.e. a diverse set of desirable plant species that maintain key ecological processes necessary for sustainable production and nutrient cycling) within pasture communities dominated by an invasive grass species. To do this, we uase a case-study of the invasion of Eragrostis curvula (Africal lovegrss; hereafter, Lovegrass), a serious concern in Australian agricultural communities (Parsons and Cuthbertson 1992). The spread and dominance of Lovegrass is a problem because its low palatability, low nutritional content and competitiveness affect the livelihood of graziers by reducing the diversity of other plant species. We conclude by suggesting modifications to this framework for pasture ecosystems to help increase the effiency of strategies to protect functional integrity and balance social/economic and biodiversity values.

Organic non-fullerene acceptors for organic photovoltaics

Heterojunction organic photovoltaics have been the subject of intensive academic interest over the past two decades, and significant commercial efforts have been directed towards this area with the vision of developing the next generation of low-cost solar cells. Materials development has played a vital role in the dramatic improvement of organic solar cell performance in recent years, and this is driven primarily by the advancement of p-type semiconductors as donor materials. With the highest performing solar cells today dominated by acceptors based on members of the fullerene family, much less attention has been devoted to other classes of n-type acceptors. In this review, we will provide an overview of the progress in the synthesis, characterization and implementation of the various classes of non-fullerenebased n-type organic acceptors for photovoltaic applications.

Catch limits, capacity utilization and cost reduction in Japanese fishery management

Japan's fishery harvest peaked in the late 1980s. To limit the race for fish, each fisherman could be provided with specific catch limits in the form of individual transferable quotas (ITQs). The market for ITQs would also help remove the most inefficient fishers. In this article we estimate the potential cost reduction associated with catch limits, and find that about 300 billion yen or about 3 billion dollars could be saved through the allocation and trading of individual-specific catch shares.

Valuing the influence of underlying attitudes and the demand for organic milk in Japan

Subjective perceptions about a product affect consumer choice. Accordingly, acquiring the underlying demand characteristics that consumers find desirable is vital for firms planning future marketing strategies. However, the extent to which product-specific perceptions affect consumer choice is poorly understood. New agricultural standards for organic livestock were introduced in Japan in November 2005 and are expected to influence the market significantly. Choice modeling (CM) is used to explore how consumers evaluate the latent demands and conventional attributes (or tangible values) of organic milk. The results suggest that latent demands, along with socioeconomic characteristics and conventional attributes, provide strong incentives for consumers to move from the purchase of conventional milk to organic milk. The analysis indicates that latent demands reflecting the safeness of organic milk, the better taste of organic milk, the image of environmental friendliness in the production process, and the image of the health and comfort of the cows are important factors that influence consumers' purchasing decisions. However, each specific factor has a corresponding conventional tangible attribute that needs to be targeted in marketing strategy.