Metabolic and ecological study of environmental pentose utilizing bacteria (E-PUB)

Lignocellulosic materials, such as sugar cane bagasse, a waste product of the sugarcane processing industry, agricultural residues and herbaceous crops, may serve as an abundant and comparatively cheap feedstock for largescale industrial fermentation, resulting in the production of marketable end-products. However, the complex structure of lignocellulosic materials, the presence of various hexose and pentose sugars in the hemicellulose component, and the presence of various compounds that inhibit the organisms selected for the fermentation process, all constitute barriers that add to the production costs and make full scale industrial production economically less feasible. The work presented in this thesis was conducted in order to screen microorganisms for ability to utilize pentose sugars derived from the sugar mill industrial waste. A large number of individual bacterial strains were investigated from hemi-cellulose rich material collected at the Proserpine and Maryborough sugar mills, notably soil samples from the mill sites. The research conducted to isolation of six pentose-capable Gram-positive organisms from the actinomycetes group by using pentose as a sole carbon source in the cultivation process. The isolates were identified as Corynebacterium glutamicum, Actinomyces odontolyticus, Nocardia elegans, and Propionibacterium freudenreichii all of which were isolated from the hemicellulose-enriched soil. Pentose degrading microbes are very rare in the environment, so this was a significant discovery. Previous research indicated that microbes could degrade pentose after genetic modification but the microbes discovered in this research were able to naturally utilize pentose. Six isolates, identified as four different genera, were investigated for their ability to utilize single sugars as substrates (glucose, xylose, arabinose or ribose), and also dual sugars as substrates (a hexose plus a pentose). The results demonstrated that C. glutamicum, A. odontolyticus, N. elegans, and P. freudenreichii were pentose-capable (able to grow using xylose or other pentose sugar), and also showed diauxie growth characteristics during the dual-sugar (glucose, in combination with xylose, arabinose or ribose) carbon source tests. In addition, it was shown that the isolates displayed very small differences in growth rates when grown on dual sugars as compared to single sugars, whether pentose or hexose in nature. The anabolic characteristics of C. glutamicum, A. odontolyticus, N. elegans and P. freudenreichii were subsequently investigated by qualitative analysis of their end-products, using high performance liquid chromatography (HPLC). All of the organisms produced arginine and cysteine after utilization of the pentose substrates alone. In addition, P. freudenreichii produced alanine and glycine. The end-product profile arising from culture with dual carbon sources was also tested. Interestingly, this time the product was different. All of them produced the amino acid glycine, when grown on a combination substrate-mix of glucose with xylose, and also glucose with arabinose. Only N. elegans was able to break down ribose, either singly or in combination with glucose, and the end-product of metabolism of the glucose plus ribose substrate combination was glutamic acid. The ecological analysis of microbial abundance in sugar mill waste was performed using denaturing gradient gel electrophoresis (DGGE) and also the metagenomic microarray PhyloChip method. Eleven solid samples and seven liquid samples were investigated. A very complex bacterial ecosystem was demonstrated in the seven liquid samples after testing with the PhyloChip method. It was also shown that bagasse leachate was the most different, compared to all of the other samples, by virtue of its richness in variety of taxa and the complexity of its bacterial community. The bacterial community in solid samples from Proserpine, Mackay and Maryborough sugar mills showed huge diversity. The information found from 16S rDNA sequencing results was that the bacterial genera Brevibacillus, Rhodospirillaceae, Bacillus, Vibrio and Pseudomonas were present in greatest abundance. In addition, Corynebacterium was also found in the soil samples. The metagenomic studies of the sugar mill samples demonstrate two important outcomes: firstly that the bagasse leachate, as potentially the most pentose-rich sample tested, had the most complex and diverse bacterial community; and secondly that the pentose-capable isolates that were initially discovered at the beginning of this study, were not amongst the most abundant taxonomic groups discovered in the sugar mill samples, and in fact were, as suspected, very rare. As a bioprospecting exercise, therefore, the study has discovered organisms that are naturally present, but in very small numbers, in the appropriate natural environment. This has implications for the industrial application of E-PUB, in that a seeding process using a starter culture will be necessary for industrial purposes, rather than simply assuming that natural fermentation might occur.

First steps towards modeling a multi-scale Earth system

Recent advances in computational geodynamics are applied to explore the link between Earth’s heat, its chemistry and its mechanical behavior. Computational thermal-mechanical solutions are now allowing us to understand Earth patterns by solving the basic physics of heat transfer. This approach is currently used to solve basic convection patterns of terrestrial planets. Applying the same methodology to smaller scales delivers promising similarities between observed and predicted structures which are often the site of mineral deposits. The new approach involves a fully coupled solution to the energy, momentum and continuity equations of the system at all scales, allowing the prediction of fractures, shear zones and other typical geological patterns out of a randomly perturbed initial state. The results of this approach are linking a global geodynamic mechanical framework over regional-scale mineral deposits down to the underlying micro-scale processes. Ongoing work includes the challenge of incorporating chemistry into the formulation.

How collaborative technology supports cognitive processes in collaborative process modeling : a capabilities-gains-outcome model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.

Construct Redundancy in Process Modeling Grammars: Improving the Explanatory Power of Ontological Analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature.

Deposition of hydrocarbon molecules on diamond (001) surfaces : atomic scale modeling

The impact induced chemisorption of hydrocarbon molecules (CH3 and CH2) on H-terminated diamond (001)-(2x1) surface was investigated by molecular dynamics simulation using the many-body Brenner potential. The deposition dynamics of the CH3 radical at impact energies of 0.1-50 eV per molecule was studied and the energy threshold for chemisorption was calculated. The impact-induced decomposition of hydrogen atoms and the dimer opening mechanism on the surface was investigated. Furthermore, the probability for dimer opening event induced by chemisorption of CH, was simulated by randomly varying the impact position as well as the orientation of the molecule relative to the surface. Finally, the energetic hydrocarbons were modeled, slowing down one after the other to simulate the initial fabrication of diamond-like carbon (DLC) films. The structure characteristic in synthesized films with different hydrogen flux was studied. Our results indicate that CH3, CH2 and H are highly reactive and important species in diamond growth. Especially, the fraction of C-atoms in the film having sp(3) hybridization will be enhanced in the presence of H atoms, which is in good agreement with experimental observations. (C) 2002 Elsevier Science B.V. All rights reserved.

The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

Computer modeling of diffusion in biological tissues

Molecular-level computer simulations of restricted water diffusion can be used to develop models for relating diffusion tensor imaging measurements of anisotropic tissue to microstructural tissue characteristics. The diffusion tensors resulting from these simulations can then be analyzed in terms of their relationship to the structural anisotropy of the model used. As the translational motion of water molecules is essentially random, their dynamics can be effectively simulated using computers. In addition to modeling water dynamics and water-tissue interactions, the simulation software of the present study was developed to automatically generate collagen fiber networks from user-defined parameters. This flexibility provides the opportunity for further investigations of the relationship between the diffusion tensor of water and morphologically different models representing different anisotropic tissues.

Business process variability modeling : A survey

It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

Modeling obligations with event-calculus

Time plays an important role in norms. In this paper we start from our previously proposed classification of obligations, and point out some shortcomings of Event Calculus (EC) to represent obligations. We proposed an extension of EC that avoids such shortcomings and we show how to use it to model the various types of obligations.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

An ecological approach towards building knowledge cities

Purpose A knowledge-based urban development needs to be sustainable and, therefore, requires ecological planning strategies to ensure a better quality of its services. The purpose of this paper is to present an innovative approach for monitoring the sustainability of urban services and help the policy-making authorities to revise the current planning and development practices for more effective solutions. The paper introduces a new assessment tool–Micro-level Urban-ecosystem Sustainability IndeX (MUSIX) – that provides a quantitative measure of urban sustainability in a local context. Design/methodology/approach A multi-method research approach was employed in the construction of the MUSIX. A qualitative research was conducted through an interpretive and critical literature review in developing a theoretical framework and indicator selection. A quantitative research was conducted through statistical and spatial analyses in data collection, processing and model application. Findings/results MUSIX was tested in a pilot study site and provided information referring to the main environmental impacts arising from rapid urban development and population growth. Related to that, some key ecological planning strategies were recommended to guide the preparation and assessment of development and local area plans. Research limitations/implications This study provided fundamental information that assists developers, planners and policy-makers to investigate the multidimensional nature of sustainability at the local level by capturing the environmental pressures and their driving forces in highly developed urban areas. Originality/value This study measures the sustainability of urban development plans through providing data analysis and interpretation of results in a new spatial data unit.

Improving ecological performance of industrialized building systems in Malaysia

For construction stakeholders to fully embrace sustainability, its long-term benefits and associated risks need to be identified through holistic approaches. Consensus among key stakeholders is very important to the improvement of the ecological performance of industrialized building systems (IBS), a building construction method gaining momentum in Malaysia. A questionnaire survey examines the relative significance of 16 potentially important sustainability factors for IBS applications. To present possible solutions,semi-structured interviews solicit views from experienced IBS practitioners, representing the professions involved. Three most critical factors agreed by key stakeholders are material consumption, waste generation and waste disposal. Using SWOT analysis, the positive and negative aspects of these factors are investigated, with action plans formulated for IBS design practitioners. The SWOT analysis based guidelines have the potential to become part of IBS design briefing documents against which sustainability solutions are contemplated, selected and implemented. Existing knowledge on ecological performance issues is extended by considering the unique characteristics of IBS and identifying not only the benefits, but also the potential risks and challenges of pursuing sustainability. This is largely missing in previous research efforts. Findings to date focus on providing much-needed assistance to IBS designers, who are at the forefront of decision-making with a significant level of project influence. Ongoing work will be directed towards other project development phases and consider the inherent linkage between design decisions and subsequent sustainability deliverables in the project life cycle.

Heparan sulfate proteoglycans, tumour progression and the cancer stem cell niche

The cancer stem cell hypothesis states that tumours arise from cells with the ability to self-renew and differentiate into multiple cell types, and that these cells persist in tumors as a distinct population that can cause disease relapse and hence metastasis. The crux of this hypothesis is that these cells are the only cells capable of, by themselves, giving rise to new tumours. What proportion of a tumour consists of these stem cells, where are they localised, how are they regulated, and how can we identify them? The stromal cells embedded within the extracellular matrix (ECM) not only provide a scaffold but also produce ECM constituents for use by stem cells. Heparan sulfate proteoglycans (HSPGs) are ubiquitous to this cell niche and interact with a large number of ligands including growth factors, their receptors, and ECM structural components. It is still unclear whether ECM degradation and subsequent metastasis is a result of proteases produced by the tumour cells themselves or by cells within the stromal compartment. The identification of the cellular origin of cancer stem cells along with microenvironmental changes involved in the initiation, progression and the malignant conversion of all cancers is critical to the development of targeted therapeutics. As ubiquitous members of the ECM microenvironment and hence the cancer cell niche, HSPGs are candidates for a central role in these processes.

Modeling electricity price events as point processes

Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

Understanding the actualization of affordances: A study in the process modeling context

The affordances concept describes the possibilities for goal-oriented action that technical objects offer to specified users. This notion has received growing attention from IS researchers. However, few studies have gone beyond contextualizing parts of the concept to a specific setting – the tip of the iceberg. In this research-in-progress paper, we report on our efforts to further develop the IS discipline’s understanding of affordances from informational objects. Specifically, we seek to extend extant theory on the origin and actualization of affordances. We develop a model that describes the process by which affordances are perceived and actualized and their dependence on information and actualization effort. We illustrate our emergent theory in the context of conceptual process models used by analysts for purposes of information systems analysis and design. We offer suggestions for operationalizing and testing this model empirically, and provide details about our design of a mixed-methods study currently in progress.