Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells

Delays are an important feature in temporal models of genetic regulation due to slow biochemical processes, such as transcription and translation. In this paper, we show how to model intrinsic noise effects in a delayed setting by either using a delay stochastic simulation algorithm (DSSA) or, for larger and more complex systems, a generalized Binomial τ-leap method (Bτ-DSSA). As a particular application, we apply these ideas to modeling somite segmentation in zebra fish across a number of cells in which two linked oscillatory genes (her1 and her7) are synchronized via Notch signaling between the cells.

Evolving noisy oscillatory dynamics in genetic regulatory networks

We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.

Mussel-inspired porous SiO2 scaffolds with improved mineralization and cytocompatibility for drug delivery and bone tissue engineering

Porous SiO2 scaffolds with mesopore structure (named as MS scaffolds) have been proposed as suitable for bone tissue engineering due to their excellent drug-delivery ability; however, the mineralization and cytocompatibility of MS scaffolds are far from optimal for bone tissue engineering, and it is also unclear how the delivery of drugs from MS scaffolds affects osteoblastic cells. The aims of the present study were to improve the mineralization and cytocompatibility of MS scaffolds by coating mussel-inspired polydopamine on the pore walls of scaffolds. The effects of polydopamine modification on MS scaffolds was investigated with respect to apatite mineralization and the attachment, proliferation and differentiation of bone marrow stromal cells (BMSCs), as was the release profile of the drug dexamethasone (DEX). Our results show that polydopamine can readily coat the pore walls of MS scaffolds and that polydopamine-modified MS scaffolds have a significantly improved apatite-mineralization ability as well as better attachment and proliferation of BMSCs in the scaffolds, compared to controls. Polydopamine modification did not alter the release profile of DEX from MS scaffolds but the sustained delivery of DEX significantly improved alkaline phosphatase (ALP) activity of BMSCs in the scaffolds. These results suggest that polydopamine modification is a viable option to enhance the bioactivity of bone tissue engineering scaffolds and, further, that DEX-loaded polydopamine MS scaffolds have potential uses as a release system to enhance the osteogenic properties of bone tissue engineering applications.

Preliminary development of a sewerage infrastructure buffer assessment tool for engineering risk and strategic land use planning

Urban expansion continues to encroach on once isolated sewerage infrastructure. In this context,legislation and guidelines provide limited direction to the amenity allocation of appropriate buffer distances for land use planners and infrastructure providers. Topography, wind speed and direction,temperature, humidity, existing land uses and vegetation profiles are some of the factors that require investigation in analytically determining a basis for buffer separations. This paper discusses the compilation and analysis of six years of Logan sewerage odour complaint data. Graphically,relationships between the complaints, topographical features and meteorological data are presented. Application of a buffer sizing process could assist planners and infrastructure designers alike, whilst automatically providing extra green spaces. Establishing a justifiable criterion for buffer zone allocations can only assist in promoting manageable growth for healthier and more sustainable communities.

Population genetic structure and patterns of dispersal in the Giant Long-Armed Prawn, Macrobrachium lar (Fabricius, 1798) (Decapoda : Palaemonidae)

The Giant Long-Armed Prawn, Macrobrachium lar is a freshwater species native to the Indo-Pacific. M. lar has a long-lived, passive, pelagic marine larval stage where larvae need to colonise freshwater within three months to complete their development. Dispersal is likely to be influenced by the extensive distances larvae must transit between small oceanic islands to find suitable freshwater habitat, and by prevailing east to west wind and ocean currents in the southern Pacific Ocean. Thus, both intrinsic and extrinsic factors are likely to influence wild population structure in this species. The present study sought to define the contemporary broad and fine-scale population genetic structure of Macrobrachium lar in the south-western Pacific Ocean. Three polymorphic microsatellite loci were used to assess patterns of genetic variation within and among 19 wild adult sample sites. Statistical procedures that partition variation implied that at both spatial scales, essentially all variation was present within sample sites and differentiation among sites was low. Any differentiation observed also was not correlated with geographical distance. Statistical approaches that measure genetic distance, at the broad-scale, showed that all south-western Pacific Islands were essentially homogeneous, with the exception of a well supported divergent Cook Islands group. These findings are likely the result of some combination of factors that may include the potential for allelic homoplasy, through to the effects of sampling regime. Based on the findings, there is most likely a divergent M. lar Cook Islands clade in the south-western Pacific Ocean, resulting from prevailing ocean currents. Confirmation of this pattern will require a more detailed analysis of nDNA variation using a larger number of loci and, where possible, use of larger population sizes.

A mathematical model for genetic regulation of the lactose operon

In this paper we construct a mathematical model for the genetic regulatory network of the lactose operon. This mathematical model contains transcription and translation of the lactose permease (LacY) and a reporter gene GFP. The probability of transcription of LacY is determined by 14 binding states out of all 50 possible binding states of the lactose operon based on the quasi-steady-state assumption for the binding reactions, while we calculate the probability of transcription for the reporter gene GFP based on 5 binding states out of 19 possible binding states because the binding site O2 is missing for this reporter gene. We have tested different mechanisms for the transport of thio-methylgalactoside (TMG) and the effect of different Hill coefficients on the simulated LacY expression levels. Using this mathematical model we have realized one of the experimental results with different LacY concentrations, which are induced by different concentrations of TMG.

Nanostructured mesoporous bioglass coated zirconia scaffolds for bone tissue engineering

For the filling and reconstruction of non-healing bone defects, the application of porous ceramic scaffold as bone substitutes is considered to be a reasonable choice. In bone tissue engineering, an ideal scaffold must satisfy several criterias such as open porosity, having high compressive strength (it depends where in body, and if external fixatures are used) and the practicability for cell migration. Many researchers have focused on enhancing the mechanical properties of hydroxyapatite scaffolds by combining it with other biomaterials, such as bioglass and polymers. Nevertheless, there is still a lack of suitable scaffolds based on porous biomaterials. In this study, zirconia scaffolds from two different templates (polyurethane (PU) and Acrylonitrile Butadiene Styrene (ABS) templates) were successfully fabricated with dissimilar fabrication techniques. The scaffold surfaces were further modified with mesoporous bioglass for the purpose of bone tissue engineering. In the study of PU template scaffold, high porosity (~88%) sol-gel derived yttria-stabilized zirconia (YSZ) scaffold was prepared by a polyurethane (PU) foam replica method using sol-gel derived zirconia for the first time, and double coated with Mesoporous Bioglass (MBGs) coating. For the ABS template scaffold, two types of templates (cube and cylinder) with different strut spacings were used and fabricated by a 3D Rapid Prototyper. Subsequently, zirconia scaffolds with low porosity (63±2.8% to 68±2.5%) were fabricated by embedding the zirconia powder slurry into the ABS templates and burning out the ABS to produce a uniform porous structure. The zirconia scaffolds were double coated with mesoporous bioglass by dip coating for the first time. The porosities of the scaffolds were calculated before and after coating. The microstructures were then examined using scanning electron microscopy and the mechanical properties were evaluated using compressive test. Accordingly, relationships between microstructure, processing and mechanical behaviour of the porous zirconia was discussed. Scaffold biocompatibility and bioactivity was also evaluated using a bone marrow stromal cell (BMSC) proliferation test and a simulated body fluid test.

Preparation and characterisation of tri-calcium phosphate scaffolds with tunnel-like macro-pores for bone tissue engineering

Calcium Phosphate ceramics have been widely used in tissue engineering due to their excellent biocompatibility and biodegradability. In the physiological environment, they are able to gradually degrade, absorbed and promote bone growth. Ultimately, they are capable of replacing damaged bone with new tissue. However, their low mechanical properties limit calcium phosphate ceramics in load-bearing applications. To obtain sufficient mechanical properties as well as high biocompatibility is one of the main focuses in biomaterials research. Therefore, the current project focuses on the preparation and characterization of porous tri-calcium phosphate (TCP) ceramic scaffolds. Hydroxapatite (HA) was used as the raw material, and normal calcium phosphate bioglass was added to adjust the ratio between calcium and phosphate. It was found that when 20% bioglass was added to HA and sintered at 1400oC for 3 hours, the TCP scaffold was obtained and this was confirmed by X-ray diffraction (XRD) analysis. Test results have shown that by applying this method, TCP scaffolds have significantly higher compressive strength (9.98MPa) than those made via TCP powder (<3MPa). Moreover, in order to further increase the compressive strength of TCP scaffolds, the samples were then coated with bioglass. For normal bioglass coated TCP scaffold, compressive strength was 16.69±0.5MPa; the compressive strength for single layer mesoporous bioglass coated scaffolds was 15.03±0.63MPa. In addition, this project has also concentrated on sizes and shapes effects; it was found that the cylinder scaffolds have more mechanical property than the club ones. In addition, this project performed cell culture within scaffold to assess biocompatibility. The cells were well distributed in the scaffold, and the cytotoxicity test was performed by 3-(4,5)-dimethylthiahiazo(-z-y1)-3,5-di- phenytetrazoliumromide (MTT) assay. The Alkaline Phosphatase (Alp) activity of human bone marrow mesenchymal stem cell system (hBMSCs) seeded on scaffold expressed higher in vitro than that in the positive control groups in osteogenic medium, which indicated that the scaffolds were both osteoconductive and osteoinductive, showing potential value in bone tissue engineering.

An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation

This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.

Teaching motor racing engineering through real-life projects: benefits and challenges

Project-based learning (PBL) is widely used in engineering courses. The closer to real-life the project, the greater the relevance and depth of learning experienced by students. Formula Society of Automotive Engineering (FSAE) is a fine example of a team-based project modelled on real-life problems whereby each student team designs and builds a small race car for competitive evaluation. Queensland University of Technology (QUT) has participated in FSAE-Australia since 2004. Based on the success of the project, QUT has gone the additional step of introducing a motor-racing specialization (second major) to complement its mechanical engineering degree. In this paper, the benefits of teaching motor-racing engineering through real-life projects are presented together with a discussion of the challenges faced and how they have been addressed. In order to validate the authors' observations on the teaching approaches used, student feedback was solicited through QUT's online learning experience survey (LEX), as well as a customized paper-based survey. The results of the surveys are analysed and discussed in this paper.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Management and engineering of process aware information systems : introduction to the special issue

In this editorial letter, we provide the readers of Information Systems with a birds-eye introduction to Process-aware Information Systems (PAIS) – a sub-field of Information Systems that has drawn growing attention in the past two decades, both as an engineering and as a management discipline. Against this backdrop, we briefly discuss how the papers included in this special issue contribute to extending the body of knowledge in this field.

QoS-aware web service composition using genetic algorithms

Web service technology is increasingly being used to build various e-Applications, in domains such as e-Business and e-Science. Characteristic benefits of web service technology are its inter-operability, decoupling and just-in-time integration. Using web service technology, an e-Application can be implemented by web service composition — by composing existing individual web services in accordance with the business process of the application. This means the application is provided to customers in the form of a value-added composite web service. An important and challenging issue of web service composition, is how to meet Quality-of-Service (QoS) requirements. This includes customer focused elements such as response time, price, throughput and reliability as well as how to best provide QoS results for the composites. This in turn best fulfils customers’ expectations and achieves their satisfaction. Fulfilling these QoS requirements or addressing the QoS-aware web service composition problem is the focus of this project. From a computational point of view, QoS-aware web service composition can be transformed into diverse optimisation problems. These problems are characterised as complex, large-scale, highly constrained and multi-objective problems. We therefore use genetic algorithms (GAs) to address QoS-based service composition problems. More precisely, this study addresses three important subproblems of QoS-aware web service composition; QoS-based web service selection for a composite web service accommodating constraints on inter-service dependence and conflict, QoS-based resource allocation and scheduling for multiple composite services on hybrid clouds, and performance-driven composite service partitioning for decentralised execution. Based on operations research theory, we model the three problems as a constrained optimisation problem, a resource allocation and scheduling problem, and a graph partitioning problem, respectively. Then, we present novel GAs to address these problems. We also conduct experiments to evaluate the performance of the new GAs. Finally, verification experiments are performed to show the correctness of the GAs. The major outcomes from the first problem are three novel GAs: a penaltybased GA, a min-conflict hill-climbing repairing GA, and a hybrid GA. These GAs adopt different constraint handling strategies to handle constraints on interservice dependence and conflict. This is an important factor that has been largely ignored by existing algorithms that might lead to the generation of infeasible composite services. Experimental results demonstrate the effectiveness of our GAs for handling the QoS-based web service selection problem with constraints on inter-service dependence and conflict, as well as their better scalability than the existing integer programming-based method for large scale web service selection problems. The major outcomes from the second problem has resulted in two GAs; a random-key GA and a cooperative coevolutionary GA (CCGA). Experiments demonstrate the good scalability of the two algorithms. In particular, the CCGA scales well as the number of composite services involved in a problem increases, while no other algorithms demonstrate this ability. The findings from the third problem result in a novel GA for composite service partitioning for decentralised execution. Compared with existing heuristic algorithms, the new GA is more suitable for a large-scale composite web service program partitioning problems. In addition, the GA outperforms existing heuristic algorithms, generating a better deployment topology for a composite web service for decentralised execution. These effective and scalable GAs can be integrated into QoS-based management tools to facilitate the delivery of feasible, reliable and high quality composite web services.

Planning of distribution networks for medium voltage and low voltage

Determination of the placement and rating of transformers and feeders are the main objective of the basic distribution network planning. The bus voltage and the feeder current are two constraints which should be maintained within their standard range. The distribution network planning is hardened when the planning area is located far from the sources of power generation and the infrastructure. This is mainly as a consequence of the voltage drop, line loss and system reliability. Long distance to supply loads causes a significant amount of voltage drop across the distribution lines. Capacitors and Voltage Regulators (VRs) can be installed to decrease the voltage drop. This long distance also increases the probability of occurrence of a failure. This high probability leads the network reliability to be low. Cross-Connections (CC) and Distributed Generators (DGs) are devices which can be employed for improving system reliability. Another main factor which should be considered in planning of distribution networks (in both rural and urban areas) is load growth. For supporting this factor, transformers and feeders are conventionally upgraded which applies a large cost. Installation of DGs and capacitors in a distribution network can alleviate this issue while the other benefits are gained. In this research, a comprehensive planning is presented for the distribution networks. Since the distribution network is composed of low and medium voltage networks, both are included in this procedure. However, the main focus of this research is on the medium voltage network planning. The main objective is to minimize the investment cost, the line loss, and the reliability indices for a study timeframe and to support load growth. The investment cost is related to the distribution network elements such as the transformers, feeders, capacitors, VRs, CCs, and DGs. The voltage drop and the feeder current as the constraints are maintained within their standard range. In addition to minimizing the reliability and line loss costs, the planned network should support a continual growth of loads, which is an essential concern in planning distribution networks. In this thesis, a novel segmentation-based strategy is proposed for including this factor. Using this strategy, the computation time is significantly reduced compared with the exhaustive search method as the accuracy is still acceptable. In addition to being applicable for considering the load growth, this strategy is appropriate for inclusion of practical load characteristic (dynamic), as demonstrated in this thesis. The allocation and sizing problem has a discrete nature with several local minima. This highlights the importance of selecting a proper optimization method. Modified discrete particle swarm optimization as a heuristic method is introduced in this research to solve this complex planning problem. Discrete nonlinear programming and genetic algorithm as an analytical and a heuristic method respectively are also applied to this problem to evaluate the proposed optimization method.