A home-based progressive resistance exercise programme for patients with venous leg ulcers : a feasibility study

This study aimed to assess the feasibility of a home-based exercise program and examine the effects on the healing rates of venous leg ulcers. A 12 –week randomised controlled trial was conducted investigating the effects of an exercise intervention compared to a usual care group. Participants in both groups (n = 13) had active venous ulceration and were treated in a metropolitan hospital outpatients clinic in Australia. Data were collected on recruitment from medical records, clinical assessment and questionnaires. Follow-up data on progress in healing and treatments were collected fortnightly for 12 weeks. Calf muscle pump function data were collected at baseline and 12 weeks from recruitment. Range of ankle motion data were collected at baseline, 6 and 12 weeks from recruitment. This pilot study indicated that the intervention was feasible. Clinical significance was observed in the intervention group with a 32% greater decrease in ulcer size (p=0.34) than the control group, and a 10% (p=0.74) improvement in the number of participants healed in the intervention group compared to the control group. Significant differences between groups over time were observed in calf muscle pump function parameters; (ejection fraction [p = 0.05]; residual volume fraction [p = 0.04]) and range of ankle motion (p = 0.01). This pilot study is one of the first studies to examine and measure clinical healing rates for participants involved in a home-based progressive resistance exercise program. Further research is warranted with a larger multi-site study.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Effect of Fe3O4 addition on removal of ammonium by zeolite NaA

Magnetic zeolite NaA with different Fe3O4 loadings was prepared by hydrothermal synthesis based on metakaolin and Fe3O4. The effect of added Fe3O4 on the removal of ammonium by zeolite NaA was investigated by varying the Fe3O4 loading, pH, adsorption temperature, initial concentration, adsorption time. Langmuir, Freundlich, and pseudo-second-order modeling were used to describe the nature and mechanism of ammonium ion exchange using both zeolite and magnetic zeolite. Thermodynamic parameters such as change in Gibbs free energy, enthalpy and entropy were calculated. The results show that all the selected factors affect the ammonium ion exchange by zeolite and magnetic zeolite, however, the added Fe3O4 apparently does not affect the ion exchange performance of zeolite to the ammonium ion. Freundlich model provides a better description of the adsorption process than Langmuir model. Moreover, kinetic analysis indicates the exchange of ammonium on the two materials follows a pseudosecond-order model. Thermodynamic analysis makes it clear that the adsorption process of ammonium is spontaneous and exothermic. Regardless of kinetic or thermodynamic analysis, all the results suggest that no considerable effect on the adsorption of the ammonium ion by zeolite is found after the addition of Fe3O4. According to the results, magnetic zeolite NaA can be used for the removal of ammonium due to the good adsorption performance and easy separation method from aqueous solution.

The effect of surface tension and kinetic undercooling on a radially-symmetric melting problem

The addition of surface tension to the classical Stefan problem for melting a sphere causes the solution to blow up at a finite time before complete melting takes place. This singular behaviour is characterised by the speed of the solid-melt interface and the flux of heat at the interface both becoming unbounded in the blow-up limit. In this paper, we use numerical simulation for a particular energy-conserving one-phase version of the problem to show that kinetic undercooling regularises this blow-up, so that the model with both surface tension and kinetic undercooling has solutions that are regular right up to complete melting. By examining the regime in which the dimensionless kinetic undercooling parameter is small, our results demonstrate how physically realistic solutions to this Stefan problem are consistent with observations of abrupt melting of nanoscaled particles.

Genus Umbravirus

The practical need to partition the world of viruses into distinguishable, universally agreed upon entities is the ultimate justification for developing a virus classification system. The Author of this Book is Andrew MQ King, Elliot Lefkowitz, Eric B. Carstens, Michael J. Adams Since 1971, the International Committee on Taxonomy of Viruses (ICTV) operating on behalf of the world community of virologists has taken on the task of developing a single, universal taxonomic scheme for all viruses infecting animals (vertebrate, invertebrates, and protozoa), plants (higher plants and algae), fungi, bacteria, and archaea.

Carrot mottle mimic virus (CMoMV): A second umbravirus associated with carrot motley dwarf disease recognised by nucleic acid hybridisation

Carrot mottle umbravirus (CMoV) has always been found co-infecting plants with carrot red leaf luteovirus (CRLV) and in carrot (Daucus carota) these co-infections are associated with carrot motley dwarf disease (CMD). CMD occurs wherever carrots are grown. Hence, CMoV was believed to have a corresponding global distribution. However, little or no hybridisation was detected between cDNA generated from the sequenced Australian isolate of CMoV (CMoV-A) and RNA from the much studied Scottish isolate of CMoV (CMoV-S). A weak hybridisation signal was obtained using cDNA to a conserved part of the RNA-dependent RNA polymerase gene of CMoV-A, but when cDNAs to other parts of the CMoV-A genome were used as probes there was no detectable hybridisation with CMoV-S RNA. This lack of hybridisation suggests that the two virus isolates have relatively divergent genomes and that they should be regarded as distinct virus species. Both viruses are transmitted by Cavariella aegopodii, but only with the help of CRLV, and they yield almost identical double-stranded RNA profiles. For these reasons, we propose that the CMoV isolate from Australia be renamed carrot mottle mimic umbravirus (CMoMV). cDNA to CMoMV RNA hybridised with RNA from an isolate from New Zealand, whereas cDNA to CMoV-S RNA hybridised with RNA from isolates from England and Morocco but not to RNA from the isolate from New Zealand. Although preliminary, these data suggest that CMoV and CMoMV may have different global distributions.

Comparison of promoters and selectable marker genes for use in Indica rice transformation

The effectiveness of different promoters for use in Indica rice transformation was compared. Plasmids encoding the Escherichia coli uidA (gus) gene under the control of CaMV 35S, Emu, Act1 or Ubi1 promoters were delivered into cell suspension cultures by particle bombardment. Transient gene expression, 48 h after delivery, was greatest from plasmids utilising the constitutive promoters, Act1 and Ubi1. Gene expression in stably transformed tissue was examined by bombarding embryogenic Indica rice calli with a pUbil-gus plasmid and a plasmid containing either the selectable marker gene, hph, which confers hygromycin resistance, or bar, which confers resistance to the herbicide phosphinothricin (BASTA) each under the control of the CaMV 35S, Emu, Act1 or the Ubi1 promoters. The bombarded calli were placed on the appropriate selection media and stained for GUS activity at 1 day, 3 weeks and 5 weeks after shooting. Callus bombarded with the pUbi1-hph or the pEmu-hph constructs gave a dramatic increase in the size of the GUS staining areas with time. No such increase in the size of GUS staining areas was observed in calli co-bombarded with pUbi1-gus and any of the bar containing constructs. Co-bombardment of calli with either the pEmu-hph or pUbi1-hph construct and a virus minor coat protein (cp) gene construct resulted in many fertile transgenic Indica rice plants, containing one to eight copies of both the hph and cp genes. These genes were stably inherited by the T 1 generation.

Genome segment 5 of rice ragged stunt virus encodes a virion protein

The complete nucleotide sequence of the genome segment 5 (S5) of a Thai isolate of rice ragged stunt virus (RRSV) was determined. The 2682 nucleotide sequence contains a single long open reading frame capable of encoding a polypeptide with a molecular mass of ~91 kDa. Polypeptides encoded by various truncated cDNAs of S5 were expressed using the pGEX fusion protein vector and the highest level of fusion protein was obtained from a construct encoding a hydrophilic region of S5 protein. Antibodies raised against this fusion protein recognized a minor polypeptide, with a molecular mass of ~ 91 kDa, that was present in purified preparations of RRSV particles, infected insect vectors and infected rice plants. This indicates that RRSV S5 encodes a minor structural protein. Comparing the RRSV S5 sequence with sequences of other reo-viruses did not reveal any significant sequence similarities.

The genome organization and affinities of an Australian isolate of carrot mottle umbravirus

The genomic sequence of an Australian isolate of carrot mottle umbravirus (CMoV-A) was determined from cDNA generated from dsRNA. This provides the first data on the genome organization and phylogeny of an umbravirus. The 4201-nucleotide genome contains four major open reading frames (ORFs). Analysis suggests that ORF2 encodes an RNA-dependent RNA polymerase, that ORF4 encodes a movement protein, and that the virus has no coat protein gene. The functions of ORFs 1 and 3 remain unknown. ORF2 is probably translated following ribosomal frameshifting. ORFs 3 and 4 are probably translated from a subgenomic mRNA. Sequence comparisons showed CMoV-A to be closely related to pea enation mosaic RNA2 NA2), but also to have affinities with the Bromoviridae. These findings shed light on the relationships between the luteoviruses, PEMV, and the umbraviruses and on the relationships between the carmo-like viruses and the Bromoviridae.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

The schooling experience of six adolescent boys who have been diagnosed with Attention Deficit/ Hyperactivity Disorder (AD/HD)

This thesis explored the experience of schooling of six adolescent boys diagnosed with AD/HD from the perspectives of the boys, their mothers and their teachers. The study utilised social constructionism as the theoretical orientation and an explanatory theory of AD/HD, the Dynamic Developmental Theory (DDT) of AD/HD as a framework. Findings included the importance of making and managing friendships for young people with AD/HD, the importance of being informed about AD/HD as well classroom strategies that support the learning of students for teachers, and the apparent role that medication in concert with an engaging classroom environment can play in the successful schooling of boys with AD/HD.

A Bayesian regression approach to assess uncertainty in pollutant wash-off modelling

Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.

Rapid, simultaneous activation of thin nanowire growth in low-temperature, low-pressure chemically active plasmas

Multiscale numerical modeling of the species balance and transport in the ionized gas phase and on the nanostructured solid surface complemented by the heat exchange model is used to demonstrate the possibility of minimizing the Gibbs-Thompson effect in low-temperature, low-pressure chemically active plasma-assisted growth of uniform arrays of very thin Si nanowires, impossible otherwise. It is shown that plasma-specific effects drastically shorten and decrease the dispersion of the incubation times for the nucleation of nanowires on non-uniform Au catalyst nanoparticle arrays. The fast nucleation makes it possible to avoid a common problem of small catalyst nanoparticle burying by amorphous silicon. These results explain a multitude of experimental observations on chemically active plasma-assisted Si nanowire growth and can be used for the synthesis of a range of inorganic nanowires for environmental, biomedical, energy conversion, and optoelectronic applications.