Flow-graph techniques for epicyclic gear train analysis

Flow-graph techniques are applied in this article for the analysis of an epicyclic gear train. A gear system based on this is designed and constructed for use in Numerical Control Systems.

Bayesian synthetic likelihood

Having the ability to work with complex models can be highly beneficial, but the computational cost of doing so is often large. Complex models often have intractable likelihoods, so methods that directly use the likelihood function are infeasible. In these situations, the benefits of working with likelihood-free methods become apparent. Likelihood-free methods, such as parametric Bayesian indirect likelihood that uses the likelihood of an alternative parametric auxiliary model, have been explored throughout the literature as a good alternative when the model of interest is complex. One of these methods is called the synthetic likelihood (SL), which assumes a multivariate normal approximation to the likelihood of a summary statistic of interest. This paper explores the accuracy and computational efficiency of the Bayesian version of the synthetic likelihood (BSL) approach in comparison to a competitor known as approximate Bayesian computation (ABC) and its sensitivity to its tuning parameters and assumptions. We relate BSL to pseudo-marginal methods and propose to use an alternative SL that uses an unbiased estimator of the exact working normal likelihood when the summary statistic has a multivariate normal distribution. Several applications of varying complexity are considered to illustrate the findings of this paper.

Achieving a national sample of nursing homes: Balancing probability techniques and practicalities

Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

Computational Techniques for Haplotype Inference and for Local Alignment Significance

This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.

Harmonic Analysis of Advanced Bus-Clamping PWM Techniques

Special switching sequences can be employed in space-vector-based generation of pulsewidth-modulated (PWM) waveforms for voltage-source inverters. These sequences involve switching a phase twice, switching the second phase once, and clamping the third phase in a subcycle. Advanced bus-clamping PWM (ABCPWM) techniques have been proposed recently that employ such switching sequences. This letter studies the spectral properties of the waveforms produced by these PWM techniques. Further, analytical closed-form expressions are derived for the total rms harmonic distortion due to these techniques. It is shown that the ABCPWM techniques lead to lower distortion than conventional space vector PWM and discontinuous PWM at higher modulation indexes. The findings are validated on a 2.2-kW constant $V/f$ induction motor drive and also on a 100-kW motor drive.

Feature selection and the concept of immediate neighborhood in the context of clustering techniques

The concept of feature selection in a nonparametric unsupervised learning environment is practically undeveloped because no true measure for the effectiveness of a feature exists in such an environment. The lack of a feature selection phase preceding the clustering process seriously affects the reliability of such learning. New concepts such as significant features, level of significance of features, and immediate neighborhood are introduced which result in meeting implicitly the need for feature slection in the context of clustering techniques.

Rapid synthetic routes to prepare LiNi1/3Mn1/3Co1/3O2 as a high voltage, high-capacity Li-ion battery cathode material

LiNi1/3Mn1/3Co1/3O2, a high voltage and high-capacity cathode material for Li-ion batteries, has been synthesized by three different rapid synthetic methods. viz. nitrate-melt decomposition, combustion and sol-gel methods. The first two methods are ultra rapid and a time period as small as 15 min is sufficient to prepare nano-crystalline LiNi1/3Mn1/3Co1/3O2. The processing parameters in obtaining the best performing materials are optimized for each process and their electrochemical performance is evaluated in Li-ion cells. The combustion-derived LiNi1/3Mn1/3Co1/3O2 sample exhibits large extent of cation mixing (10%) while the other two methods yield LiNi1/3Mn1/3Co1/3O2 with cation mixing <5%. LiNi1/3Mn1/3Co1/3O2 prepared by nitrate-melt decomposition method exhibits superior performance as Li-ion battery cathode material.

Review of continuum, finite element and hybrid techniques in the analysis of stress concentrations in structures

When a uniform flow of any nature is interrupted, the readjustment of the flow results in concentrations and rare-factions, so that the peak value of the flow parameter will be higher than that which an elementary computation would suggest. When stress flow in a structure is interrupted, there are stress concentrations. These are generally localized and often large, in relation to the values indicated by simple equilibrium calculations. With the advent of the industrial revolution, dynamic and repeated loading of materials had become commonplace in engine parts and fast moving vehicles of locomotion. This led to serious fatigue failures arising from stress concentrations. Also, many metal forming processes, fabrication techniques and weak-link type safety systems benefit substantially from the intelligent use or avoidance, as appropriate, of stress concentrations. As a result, in the last 80 years, the study and and evaluation of stress concentrations has been a primary objective in the study of solid mechanics. Exact mathematical analysis of stress concentrations in finite bodies presents considerable difficulty for all but a few problems of infinite fields, concentric annuli and the like, treated under the presumption of small deformation, linear elasticity. A whole series of techniques have been developed to deal with different classes of shapes and domains, causes and sources of concentration, material behaviour, phenomenological formulation, etc. These include real and complex functions, conformal mapping, transform techniques, integral equations, finite differences and relaxation, and, more recently, the finite element methods. With the advent of large high speed computers, development of finite element concepts and a good understanding of functional analysis, it is now, in principle, possible to obtain with economy satisfactory solutions to a whole range of concentration problems by intelligently combining theory and computer application. An example is the hybridization of continuum concepts with computer based finite element formulations. This new situation also makes possible a more direct approach to the problem of design which is the primary purpose of most engineering analyses. The trend would appear to be clear: the computer will shape the theory, analysis and design.

Harvest: A biotextile future

- Description of the work Harvest: A biotextile future consists of four bags constructed from kombucha, each utilizing a different approach to this material. The kombucha material is a byproduct of the fermented green tea, kombucha, and is comprised of a symbiotic culture of bacteria and yeast (SCOBY) that forms a fast growing curd or pellicle on the surface of the tea. This pellicle is harvested, washed, and dried to make a material with characteristics that can range between leather and paper in handle. The pellicle is one hundred per cent cellulose, with the individual fibres growing together to produce a durable and strong non-woven textile. Techniques explored with the dry kombucha material include folding, stitching, and laser etching. The final bags were designed with reference to classic tropes of fashion accessories: the briefcase, the clutch, the valise and the handbag. The valise included three jars in which the kombucha was displayed as ‘growing’ within the bag. - Research Background This work sits within an emerging field of practice in which fashion design intersects with biotechnology. Designers such as Suzanne Lee have explored constructing garments from bacteria byproducts, and bio-artists Oron Catts and Ionat Zurr have created ‘victimless leather’ grown from cultured cells. Although still speculative, these collaborations between science and design point to new material applications for fashion. Our work contributes to this area through testing both the growing of the textile and its application to construct durable fashion artefacts. - Research Contribution Harvest: A biotextile future makes two contributions to new knowledge in the area of design for sustainability within fashion. The first contribution lies in extending the technical experimentation required to grow and manipulate the textile. For the briefcase, the pattern shape was ‘grown’ into the required shape, using a shaped container. Other techniques used in the bags included weaving, folding and laser etching the material to extend its functional and decorative properties. Experimentation with the growing and drying of the material led to the production of a wide range of physical properties, in which the material was more brittle or flexible as required. The second research contribution lies in the proposal of this material for use in durable fashion accessories. The material is still speculative and small-scale in production, however the four bags illustrate the potential for kombucha as a biodegradable alternative to leather or synthetic materials. - Research Significance This interplay of science and design research opens up an exploration for a speculative future of sustainable, biodegradable textiles using live bacteria to enable ‘homegrown’ vegan apparel. The collaborators on this project include scientist Peter Musk and fashion designers Alice Payne and Dean Brough. Harvest: A biotextile future was exhibited at the State Library of Queensland’s Asia Pacific Design Library, 1-5 November 2015, as part of The International Association of Societies of Design Research’s (IASDR) biannual design conference. The work was chosen for display by a panel of experts, based on the criteria of design innovation and contribution to new knowledge in design.

Self-image (autoidolon) techniques for the realisation of optical computing type operations

Abstract is not available.

Synthetic polypeptide with antifreeze activity

MUCH information has been gathered in recent years on the so-called 'antifreeze' proteins which lower the freezing point of the serum of certain marine fishes living in sub-zero water temperatures1−4. The proteins from the Antarctic fish Trematomus borchgrevinki are glycoproteins with a repeating alanyl-alanyl-threonyl tripeptide sequence, the threonyl residue being linked to a disaccharide1,2. In contrast, the antifreeze protein from the winter flounder Pseudopleuronectus americanus in the North American Atlantic coastal region is made up of eight ammo acids with no apparent repeating sequence of the residues and no sugar moiety (ref. 4 and unpublished work of C. L. Hew, C. C. Yip & G. Fletcher). The antifreeze activity of these proteins is not compatible with the known colligative properties of solutes in solution and the mechanism of their action is not yet fully understood. But a common feature of both types of the antifreeze proteins is the preponderance of alanine which accounts for over 60% of the total amino residues. This fact, together with the absence of the carbohydrate in the protein from the winter flounder, prompted us to attempt the synthesis of polypeptide analogues having comparable proportions of alanine in them along with suitable other amino acids. As a first step, we made use of the lack of any obvious periodicity in the distribution of the alanyl residues in the flounder's protein and attempted the synthesis of a random copolypeptide containing about 65 mol % of alanine and 35 mol % of aspartic acid. The choice of aspartic acid was made on the basis of its being the next major amino acid in the flounder's protein3,4 and on the expectation that its polar character will help the water-solubility of the alanine-rich copolypeptide, as in other studies on alanine-containing random copolymers. In addition, Duman and DeVries4 have earlier indicated the involvement of carboxyl groups on the antifreeze activity by chemical modification studies. We report here the synthesis of this polypeptide and show that it possesses antifreeze activity.