Morphology changes and mechanistic aspects of the electrochemically-induced reversible solid-solid transformation of microcrystalline TCNQ into Co TCNQ 2-based materials (TCNQ= 7, 7, 8, 8-Tetracyanoquinodimethane)

The chemically reversible solid−solid phase transformation of a TCNQ-modified glassy carbon, indium tin oxide, or metal electrode into Co\[TCNQ]2(H2O)2 material in the presence of Co2+(aq) containing electrolytes has been induced and monitored electrochemically. Voltammetric data reveal that the TCNQ/Co\[TCNQ]2(H2O)2 interconversion process is independent of electrode material and identity of cobalt electrolyte anion. However, a marked dependence on electrolyte concentration, scan rate, and method of electrode modification (drop casting or mechanical attachment) is found. Cyclic voltammetric and double potential step chronoamperometric measurements confirm that formation of Co\[TCNQ]2(H2O)2 occurs through a rate-determining nucleation and growth process that initially involves incorporation of Co2+(aq) ions into the reduced TCNQ crystal lattice at the TCNQ|electrode|electrolyte interface. Similarly, the reverse (oxidation) process, which involves transformation of solid Co\[TCNQ]2(H2O)2 back to parent TCNQ crystals, also is controlled by nucleation−growth kinetics. The overall chemically reversible process that represents this transformation is described by the reaction:  2TCNQ0(s) + 2e- + Co2+(aq) + 2H2O \[Co(TCNQ)2(H2O)2](s). Ex situ SEM images illustrated that this reversible TCNQ/Co\[TCNQ]2(H2O)2 conversion process is accompanied by drastic size and morphology changes in the parent solid TCNQ. In addition, different sizes of needle-shaped nanorod/nanowire crystals of Co\[TCNQ]2(H2O)2 are formed depending on the method of surface immobilization.

Investigation of genetic diversity and development of vaccine for Chlamydia pecorum infections in koala (Phascolarctos cinereus)

Many wild koala populations in Australia continue to experience serious declines due to factors such as disease caused by Chlamydia. This thesis is the first of its kind to investigate diversity of the chlamydial infections in wild koala populations across Australia and has made significant progress towards the development of a vaccine for koalas. The findings in this study have demonstrated that it is feasible to develop a safe and effective recombinant vaccine against Chlamydia in both disease free as well as severely diseased koalas. Most importantly, this study is also first of its kind to evaluate a multi-component vaccine that should be effective against the range of Chlamydia pecorum strains circulating in both captive as well as wild koala populations.

Infectious in vitro transcripts from a cloned cDNA of barley yellow dwarf virus

A full-length cDNA clone of barley yellow dwarf virus (BYDV-PAV serotype) has been constructed and fused to the bacteriophage T7 RNA polymerase promoter. RNA transcripts produced in vitro, either capped or uncapped, were infectious in Triticum monococcum protoplasts. Protoplasts inoculated with in vitro-transcribed BYDV RNA accumulated coat protein, synthesized new viral RNAs, and produced virus particles. Aphid feeding on extracts from protoplasts inoculated with in vitro RNA transcripts can be used to transfer the virus progeny to whole plants. Introduction of mutations which interrupt specific BYDV-PAV open reading frames (ORFs) V and VI eliminated infectivity while an ORF I mutant remained infectious. Infectious RNA transcripts derived from BYDV cDNA clones will facilitate analysis of the molecular aspects of BYDV infection and further enhance our understanding of this economically important virus.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Mathematical investigation of the interactions between the inflammatory response and mechanical aspects of dermal wound repair

Dermal wound repair involves complex interactions between cells, cytokines and mechanics to close injuries to the skin. In particular, we investigate the contribution of fibroblasts, myofibroblasts, TGFβ, collagen and local tissue mechanics to wound repair in the human dermis. We develop a morphoelastic model where a realistic representation of tissue mechanics is key, and a fibrocontractive model that involves a reasonable approximation to the true kinetics of the important bioactive species. We use each of these descriptions to elucidate the mechanisms that generate pathologies such as hypertrophic scars, contractures and keloids. We find that for hypertrophic scar and contracture development, factors regulating the myofibroblast phenotype are critical, with heightened myofibroblast activation, reduced myofibroblast apoptosis or prolonged inflammation all predicted as mediators for scar hypertrophy and contractures. Prevention of these pathologies is predicted when myofibroblast apoptosis is induced, myofibroblast activation is blocked or TGFβ is neutralised. To investigate keloid invasion, we develop a caricature representation of the fibrocontractive model and find that TGFβ spread is the driving factor behind keloid growth. Blocking activation of TGFβ is found to cause keloid regression. Thus, we recommend myofibroblasts and TGFβ as targets for clinicians when developing intervention strategies for prevention and cure of fibrotic scars.

QUT Library advances the use of open public tools to navigate genetic inventions and builds research networks

Many emerging economies are dangling the patent system to stimulate bio-technological innovations with the ultimate premise that these will improve their economic and social growth. The patent system mandates full disclosure of the patented invention in exchange of a temporary exclusive patent right. Recently, however, patent offices have fallen short of complying with such a mandate, especially for genetic inventions. Most patent offices provide only static information about disclosed patent sequences and even some do not keep track of the sequence listing data in their own database. The successful partnership of QUT Library and Cambia exemplifies advocacy in Open Access, Open Innovation and User Participation. The library extends its services to various departments within the university, builds and encourages research networks to complement skills needed to make a contribution in the real world.

Whole-genome sequencing reveals untapped genetic potential in Africa’s indigenous cereal crop sorghum

Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16–45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

Genetic analysis of GRIA2 and GRIA4 genes in migraine

Background Migraine is a brain disorder affecting ∼12% of the Caucasian population. Genes involved in neurological, vascular, and hormonal pathways have all been implicated in predisposing individuals to developing migraine. The migraineur presents with disabling head pain and varying symptoms of nausea, emesis, photophobia, phonophobia, and occasionally visual sensory disturbances. Biochemical and genetic studies have demonstrated dysfunction of neurotransmitters: serotonin, dopamine, and glutamate in migraine susceptibility. Glutamate mediates the transmission of excitatory signals in the mammalian central nervous system that affect normal brain function including cognition, memory and learning. The aim of this study was to investigate polymorphisms in the GRIA2 and GRIA4 genes, which encode subunits of the ionotropic AMPA receptor for association in an Australian Caucasian population. Methods Genotypes for each polymorphism were determined using high resolution melt analysis and the RFLP method. Results Statistical analysis showed no association between migraine and the GRIA2 and GRIA4 polymorphisms investigated. Conclusions Although the results of this study showed no significant association between the tested GRIA gene variants and migraine in our Australian Caucasian population further investigation of other components of the glutamatergic system may help to elucidate if there is a relationship between glutamatergic dysfunction and migraine.

Genetic polymorphisms in miRNAs targeting the estrogen receptor and their effect on breast cancer risk

Breast cancer is the cancer that most commonly affects women worldwide. This type of cancer is genetically complex, but is strongly linked to steroid hormone signalling systems. Because microRNAs act as translational regulators of multiple genes, including the steroid nuclear receptors, single nucleotide polymorphisms (SNPs) in microRNAs genes can have potentially wide-ranging influences on breast cancer development. Thus, this study was conducted to investigate the relationships between six SNPs (rs6977848, rs199981120, rs185641358, rs113054794, rs66461782, and rs12940701) located in four miRNA genes predicted to target the estrogen receptor (miR-148a, miR-221, miR-186, and miR-152) and breast cancer risk in Caucasian Australian women. By using high resolution melt analysis (HRM) and polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), 487 samples including 225 controls and 262 cases were genotyped. Analysis of their genotype and allele frequencies indicated that the differences between case and control populations was not significant for rs6977848, rs66461782, and rs12940701 because their p-values are 0.81, 0.93, 0.1 which are all above the threshold value (p=0.05). Our data thus suggests that these SNPs do not affect breast cancer risk in the tested population. In addition, rs199981120, rs185641358, and rs113054794 could not be found in this population, suggesting that these SNPs do not occur in Caucasian Australians.

BDNF and TNF-α polymorphisms in memory

Here, we investigate the genetic basis of human memory in healthy individuals and the potential role of two polymorphisms, previously implicated in memory function. We have explored aspects of retrospective and prospective memory including semantic, short term, working and long-term memory in conjunction with brain derived neurotrophic factor (BDNF) and tumor necrosis factor-alpha (TNF-alpha). The memory scores for healthy individuals in the population were obtained for each memory type and the population was genotyped via restriction fragment length polymorphism for the BDNF rs6265 (Val66Met) SNP and via pyrosequencing for the TNF-alpha rs113325588 SNP. Using univariate ANOVA, a significant association of the BDNF polymorphism with visual and spatial memory retention and a significant association of the TNF-alpha polymorphism was observed with spatial memory retention. In addition, a significant interactive effect between BDNF and TNF-alpha polymorphisms was observed in spatial memory retention. In practice visual memory involves spatial information and the two memory systems work together, however our data demonstrate that individuals with the Val/Val BDNF genotype have poorer visual memory but higher spatial memory retention, indicating a level of interaction between TNF-alpha and BDNF in spatial memory retention. This is the first study to use genetic analysis to determine the interaction between BDNF and TNF-alpha in relation to memory in normal adults and provides important information regarding the effect of genetic determinants and gene interactions on human memory.

Quantitative genetic parameters for body traits at different ages in a cultured stock of giant freshwater prawn (Macrobrachium rosenbergii) selected for fast growth

The aim of the current study was to estimate heritabilities and correlations for body traits at different ages (Weeks 10 and 18 after stocking) in a giant freshwater prawn (Macrobrachium rosenbergii) population selected for fast growth rate in Vietnam. The dataset consisted of 4650 body records (2432 and 2218 records collected at Weeks 10 and 18, respectively) in the full pedigree comprising a total of 18 387 records. Variance and covariance components were estimated using restricted maximum likelihood fitting a multi-trait animal model. Estimates of heritability for body traits (bodyweight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) were moderate and ranged from 0.06 to 0.11 and from 0.11 to 0.22 at Weeks 10 and 18, respectively. Body-trait heritabilities estimated at Week 10 were not significantly lower than at Week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Our results suggested that selection for high growth rate in GFP can be undertaken successfully before full market size has been reached.

Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

A new grouping genetic algorithm for the MapReduce placement problem in cloud computing

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NPcomplete. Thus, in this paper we propose a new grouping genetic algorithm for the mappers/reducers placement problem in cloud computing. Compared with the original one, our grouping genetic algorithm uses an innovative coding scheme and also eliminates the inversion operator which is an essential operator in the original grouping genetic algorithm. The new grouping genetic algorithm is evaluated by experiments and the experimental results show that it is much more efficient than four popular algorithms for the problem, including the original grouping genetic algorithm.

Composite SaaS scaling in cloud computing using a hybrid genetic algorithm

A Software-as-a-Service or SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. Components in a composite SaaS may need to be scaled – replicated or deleted, to accommodate the user’s load. It may not be necessary to replicate all components of the SaaS, as some components can be shared by other instances. On the other hand, when the load is low, some of the instances may need to be deleted to avoid resource underutilisation. Thus, it is important to determine which components are to be scaled such that the performance of the SaaS is still maintained. Extensive research on the SaaS resource management in Cloud has not yet addressed the challenges of scaling process for composite SaaS. Therefore, a hybrid genetic algorithm is proposed in which it utilises the problem’s knowledge and explores the best combination of scaling plan for the components. Experimental results demonstrate that the proposed algorithm outperforms existing heuristic-based solutions.