Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Corporate fraud and misconduct : investigative and regulatory priorities

This article investigates the profile of the companies that have been investigated for corporate fraud and misconduct. Our definition of fraud includes financial statement fraud, market misconduct fraud such as insider trading or false disclosures, and managerial fraud. The particular evidence presented relates to those instances of corporate fraud and misconduct investigated by the Australian corporate regulatory, Australian Securities and Investments Commission (ASIC), and relates to sanctions for fraud, misconduct or compliance breaches. Using data compiled from the public announcements in the ASIC reports over the period 2004-2008, we categorise the type of fraud and misconduct breaches ASIC chooses to report and investigate.

Selective reductions using visible light photocatalysts of supported gold nanoparticles

Photocatalytic synthesis using visible light is a desirable chemical process because of its potential to utilize sunlight. Supported gold nanoparticles (Au-NPs) were found to be efficient photocatalysts and the effects of the supports were identified including CeO2, TiO2, ZrO2, Al2O3, and zeolite Y. In particular Au/CeO2 exhibited the high catalytic activity to reduce nitroaromatics to azo compounds, hydrogenate azobenzene to hydroazobenzene, reduce ketones to alcohols, and deoxygenate epoxides to alkenes at ambient temperatures, under irradiation of visible light (or simulated sunlight). The reac-tive efficiency depends on two primary factors: one is the light adsorption of catalysts and another is the driving ability of catalysts corresponding to the reactants. The light absorption by Au-NPs is due to surface plasmon resonance effect or inter-band electron transition; this is related to the reduction ability of the photocatalysts. Irradiation with shorter wavelengths can excite the conduction electrons in Au-NPs to higher energy levels and as a result, induce reduction with more negative reduction potentials. It is known when irradiated with light the Au-NPs can abstract hydrogen from isopropanol forming Au-H species on the Au-NP surface. Hence, we proposed that the active Au-H species will react with the N=O, N=N, C=O double bonds or epoxide bonds, which are weakened by the interaction with the excited electrons in the Au-NPs, and yield the final reductive products. The reacting power of the Au-H species depends on the energy of the excited electrons in Au-NPs: the higher the electronic energy, the stronger the reduction ability of the Au-H species. This finding demonstrates that we can tune the reduction ability of the photocatalysts by manipulating the irradiation wavelength.

Hybrid light-emitting diodes based on ZnO nanowires

ZnO is a wide band-gap semiconductor that has several desirable properties for optoelectronic devices. With its large exciton binding energy of ~60 meV, ZnO is a promising candidate for high stability, room-temperature luminescent and lasing devices [1]. Ultraviolet light-emitting diodes (LEDs) based on ZnO homojunctions had been reported [2,3], while preparing stable p-type ZnO is still a challenge. An alternative way is to use other p-type semiconductors, ether inorganic or organic, to form heterojunctions with the naturally n-type ZnO. The crystal structure of wurtzite ZnO can be described as Zn and O atomic layers alternately stacked along the [0001] direction. Because of the fastest growth rate over the polar (0001) facet, ZnO crystals tend to grow into one-dimensional structures, such as nanowires and nanobelts. Since the first report of ZnO nanobelts in 2001 [4], ZnO nanostructures have been particularly studied for their potential applications in nano-sized devices. Various growth methods have been developed for growing ZnO nanostructures, such as chemical vapor deposition (CVD), Metal-organic CVD (MOCVD), aqueous growth and electrodeposition [5]. Based on the successful synthesis of ZnO nanowires/nanorods, various types of hybrid light-emitting diodes (LEDs) were made. Inorganic p-type semiconductors, such as GaN, Si and SiC, have been used as substrates to grown ZnO nanorods/nanowires for making LEDs. GaN is an ideal material that matches ZnO not only in the crystal structure but also in the energy band levels. However, to prepare Mg-doped p-GaN films via epitaxial growth is still costly. In comparison, the organic semiconductors are inexpensive and have many options to select, for a large variety of p-type polymer or small-molecule semiconductors are now commercially available. The organic semiconductor has the limitation of durability and environmental stability. Many polymer semiconductors are susceptible to damage by humidity or mere exposure to oxygen in the air. Also the carrier mobilities of polymer semiconductors are generally lower than the inorganic semiconductors. However, the combination of polymer semiconductors and ZnO nanostructures opens the way for making flexible LEDs. There are few reports on the hybrid LEDs based on ZnO/polymer heterojunctions, some of them showed the characteristic UV electroluminescence (EL) of ZnO. This chapter reports recent progress of the hybrid LEDs based on ZnO nanowires and other inorganic/organic semiconductors. We provide an overview of the ZnO-nanowire-based hybrid LEDs from the perspectives of the device configuration, growth methods of ZnO nanowires and the selection of p-type semiconductors. Also the device performances and remaining issues are presented.

Supply chain benefits expectation management framework

Organizations invest heavily in Supply Chain Management Systems expecting the benefits promised by the software vendors and the implementation partners. However, both academic and industry reports suggest that there is growing dissatisfaction among client organizations due to an increasing gap in benefits purported by the software vendors and benefits realised by the client. In order to better manage expectations of the client organization, this study proposes a Benefit Expectation Management Framework for Supply Chain Management Systems, based on Expectation-Confirmation Theory. This study derives 60 expected benefits of Supply Chain Management Systems through 41 vendor-reported customer stories and academic papers. Through comparing those benefits with the received benefits by a case organization that has implemented SAP Supply Chain Management Systems for seven years, two salient factors – long timetable and multiple stakeholders – have been identified as the controlling factors affecting the confirmation level of Supply Chain Management System expectations and further impacting the satisfaction of a client organization. The case study also highlights the likely causes for realized benefits and enduring issues in relation to the Supply Chain Management Systems.

Examination of distracted driving and yellow light running : analysis of simulator data

Driving on an approach to a signalized intersection while distracted is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. Given the prevalence and importance of this particular scenario, the decisions and actions of distracted drivers during the onset of yellow lights are the focus of this study. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of Iowa - National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examination has been conducted from a traditional regression-based approach, which does not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that novice (16-17 years) and young drivers’ (18-25 years) have heightened yellow light running risk while distracted by a cell phone conversation. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Overall, distracted drivers across most tested groups tend to reduce the propensity of yellow light running as the distance to stop line increases, exhibiting risk compensation on a critical driving situation.

Regulating journalists? The Finkelstein Review, the Convergence Review, and News Media Regulation in Australia

This paper identifies two major forces driving change in media policy worldwide: media convergence, and renewed concerns about media ethics, with the latter seen in the U.K. Leveson Inquiry. It focuses on two major public inquiries in Australia during 2011-2012 – the Independent Media Inquiry (Finkelstein Review) and the Convergence Review – and the issues raised about future regulation of journalism and news standards. Drawing upon perspectives from media theory, it observes the strong influence of social responsibility theories of the media in the Finkelstein Review, and the adverse reaction these received from those arguing from Fourth Estate/free press perspectives, which were also consistent with the longstanding opposition of Australian newspaper proprietors to government regulation. It also discusses the approaches taken in the Convergence Review to regulating for news standards, in light of the complexities arising from media convergence. The paper concludes with consideration of the fast-changing environment in which such proposals to transform media regulation are being considered, including the crisis of news media organisation business models, as seen in Australia with major layoffs of journalists from the leading print media publications.

A framework of promoting stakeholder mutual benefits for sustainable housing implementation

Strong regulatory pressure and rising public awareness on environmental issues will continue to influence the market demand for sustainable housing for years to come. Despite this potential, the voluntary uptake rate of sustainable practices is not as high as expected within the new built housing industry. This is in contrast to the influx of emerging building technologies, new materials and innovative designs as showcased in office buildings and exemplar homes worldwide. One of the possible reasons for this under-performance is that key stakeholders such as developers, builders and consumers do not fully understand and appreciate the related challenges, risks and opportunities of pursuing sustainability. Therefore, in their professional and business activities, they may not be able to see the tangible and mutual benefits that sustainable housing may bring. This research investigates the multiple challenges to achieving benefits (CABs) from sustainable housing development, and links these factors to the characteristics of key stakeholders in the housing supply chain. It begins with a comparative survey study among seven stakeholder groups in the Australian housing industry, in order to examine the importance and interrelationships of CABs. In-depth interviews then further explore the survey findings with a focus on stakeholder diversity, which leads to the identification of 12 critical mutual-benefit factors and their interrelationship. Based on such a platform, a mutual-benefit framework is developed with the aid of Interpretive Structure Modelling, to identify the patterns of stakeholder benefit materialisation, suggest the priority of critical factors and provide related stakeholder-specific action guidelines for sustainable housing implementation. The study concludes with a case study of two real-life housing projects to test the application of the mutual-benefit framework for improvement. This framework will lead to a shared value of sustainability among stakeholders and improved stakeholder collaboration, which in turn help to break the "circle of blame" for the current under-performance of sustainable housing implementation.

Detection of banana bunchy top virus in virus-infected plants using polymerase chain reaction

Polymerase chain reaction (PCR) was developed for the detection of Banana bunchy top virus (BBTV) at maximum after 210 min and at minimum after 90 min using Pc-1 and Pc-2, respectively. PCR detection of BBTV in crude sap indicated that the freezing of banana tissue in liquid nitrogen (LN2) before extraction was more effective than using sand as the extraction technique. BBTV was also detected using PCR assay in 69 healthy and diseased plants using Na-PO4 buffer containing 1 % SDS. PCR detection of BBTV in nucleic acid extracts using seven different extraction buffers to adapt the use of PCR in routine detection in the field was studied. Results proved that BBTV was detected with high sensitivity in nucleic acid extracts more than in infectious sap. The results also suggested the common aetiology for the BBTV by the PCR reactions of BBTV in nucleic acid extracts from Australia, Burundi, Egypt, France, Gabon, Philippines and Taiwan. Results also proved a positive relation between the Egyptian-BBTV isolate and abaca bunchy top isolate from the Philippines, but there no relation was found with the Cucumber mosaic cucumovirus (CMV) isolates from Egypt and Philippines and Banana bract mosaic virus (BBMV) were found.

Engine performance characteristics for biodiesels of different degrees of saturation and carbon chain lengths

This experimental study examines the effect on performance and emission outputs of a compression ignition engine operating on biodiesels of varying carbon chain length and the degree of unsaturation. A well-instrumented, heavy-duty, multi-cylinder, common-rail, turbo-charged diesel engine was used to ensure that the results contribute in a realistic way to the ongoing debate about the impact of biofuels. Comparative measurements are reported for engine performance as well as the emissions of NOx, particle number and size distribution, and the concentration of the reactive oxygen species (which provide a measure of the toxicity of emitted particles). It is shown that the biodiesels used in this study produce lower mean effective pressure, somewhat proportionally with their lower calorific values; however, the molecular structure has been shown to have little impact on the performance of the engine. The peak in-cylinder pressure is lower for the biodiesels that produce a smaller number of emitted particles, compared to fossil diesel, but the concentration of the reactive oxygen species is significantly higher because of oxygen in the fuels. The differences in the physicochemical properties amongst the biofuels and the fossil diesel significantly affect the engine combustion and emission characteristics. Saturated short chain length fatty acid methyl esters are found to enhance combustion efficiency, reduce NOx and particle number concentration, but results in high levels of fuel consumption.

Hybrid graphene and graphitic carbon nitride nanocomposite : gap opening, electron–hole puddle, interfacial charge transfer, and enhanced visible light response

Opening up a band gap and finding a suitable substrate material are two big challenges for building graphene-based nanodevices. Using state-of-the-art hybrid density functional theory incorporating long range dispersion corrections, we investigate the interface between optically active graphitic carbon nitride (g-C3N4) and electronically active graphene. We find an inhomogeneous planar substrate (g-C3N4) promotes electronrich and hole-rich regions, i.e., forming a well-defined electron−hole puddle, on the supported graphene layer. The composite displays significant charge transfer from graphene to the g-C3N4 substrate, which alters the electronic properties of both components. In particular, the strong electronic coupling at the graphene/g-C3N4 interface opens a 70 meV gap in g-C3N4-supported graphene, a feature that can potentially allow overcoming the graphene’s band gap hurdle in constructing field effect transistors. Additionally, the 2-D planar structure of g-C3N4 is free of dangling bonds, providing an ideal substrate for graphene to sit on. Furthermore, when compared to a pure g-C3N4 monolayer, the hybrid graphene/g-C3N4 complex displays an enhanced optical absorption in the visible region, a promising feature for novel photovoltaic and photocatalytic applications.

Hybrid graphene/titania nanocomposite : interface charge transfer, hole doping, and sensitization for visible light response

We demonstrated for the first time by large-scale ab initio calculations that a graphene/titania interface in the ground electronic state forms a charge-transfer complex due to the large difference of work functions between graphene and titania, leading to substantial hole doping in graphene. Interestingly, electrons in the upper valence band can be directly excited from graphene to the conduction band, that is, the 3d orbitals of titania, under visible light irradiation. This should yield well-separated electron−hole pairs, with potentially high photocatalytic or photovoltaic performance in hybrid graphene and titania nanocomposites. Experimental wavelength-dependent photocurrent generation of the graphene/titania photoanode demonstrated noticeable visible light response and evidently verified our ab initio prediction.

The key regulatory roles of the PI3K/Akt signalling pathway in the functionalities of mesenchymal stem cells and applications in tissue regeneration

Mesenchymal stem cells (MSCs) are multi-potent cells that can differentiate into various cell types and have been used widely in tissue engineering application. In tissue engineering, a scaffold, MSCs and growth factors are used as essential components and their interactions have been regarded to be important for regeneration of tissues. A critical problem for MSCs in tissue engineering is their low survival ability and functionality. Most MSCs are going to be apoptotic after transplantation. Therefore, increasing MSC survival ability and functionalities is the key for potential applications of MSCs. Several approaches have been studied to increase MSC tissue forming capacity including application of growth factors, overexpression of stem cell regulatory genes and improvement of biomaterials for scaffolds. The effects of these approaches on MSCs have been associated with the activation of the PI3K/Akt signaling pathway. The pathway plays central regulatory roles in MSC survival, proliferation, migration, angiogenesis, cytokine production and differentiation. In this review, we summarize and discuss the literatures related to the roles of the PI3K/Akt pathway in the functionalities of MSCs and the involvement of the pathway in biomaterials-increased MSC functinalities. Biomaterials have been modified in their properties, surface structure and loaded with growth factors to increase MSC functionalities. Several studies demonstrated that the biomaterials-increased MSC functionalities are mediated by the activation of the PI3K/Akt pathway.

Synthesis of discrete allyl-functional polyethylene glycol for efficient hydrophilization of dihydr (polydimethylsiloxane)

Amphiphilic poly(ethylene glycol)-block-pol (dimethylsiloxane)-block-poly(ethylene glycol)(PEG-block-PDMS block-PEG) triblock copolymers have been successfully prepared via hydrosilylation using discrete and polydisperse PEG of various chain lengths. Facile synthesis of discrete PEG (dPEG) is achieved via systematic tosylation and etherification of lower glycols. Amphiphilicity of the dPEG block-PDMS-block-dPEG triblock copolymer is illustrated by dynamic light scattering (DLS) and measurement of the critical micelle concentration (CMC).