DNA sequences of Alu elements indicate a recent replacement of the human autosomal genetic complement.

DNA sequences of neutral nuclear autosomal loci, compared across diverse human populations, provide a previously untapped perspective into the mode and tempo of the emergence of modern humans and a critical comparison with published clonally inherited mitochondrial DNA and Y chromosome measurements of human diversity. We obtained over 55 kilobases of sequence from three autosomal loci encompassing Alu repeats for representatives of diverse human populations as well as orthologous sequences for other hominoid species at one of these loci. Nucleotide diversity was exceedingly low. Most individuals and populations were identical. Only a single nucleotide difference distinguished presumed ancestral alleles from descendants. These results differ from those expected if alleles from divergent archaic populations were maintained through multiregional continuity. The observed virtual lack of sequence polymorphism is the signature of a recent single origin for modern humans, with general replacement of archaic populations.

DANA elements: a family of composite, tRNA-derived short interspersed DNA elements associated with mutational activities in zebrafish (Danio rerio).

DNA is the first SINE isolated from zebrafish (Danio rerio) exhibiting all the hallmarks of these tRNA-derived elements. DANA is unique in its clearly defined substructure of distinct cassettes. In contrast to generic SINE elements, DANA appears to have been assembled by insertions of short sequences into a progenitor, tRNA-derived element. Once associated with each other, these subunits were amplified as a new transposable element with such a remarkable success that DANA-related sequences comprise approximately 10% of the modern zebrafish genome. At least some of the sequences comprised by the full-length element were capable of movement, forming a new group of mobile, composite transposons, one of which caused an insertional mutation in the zebrafish no tail gene. Being present only in the genus Danio, and estimated to be as old as the genus itself, DANA may have played a role in Danio speciation by massive amplification and genome-wide dispersion. There are extensive DNA polymorphisms between zebrafish populations and strains detected by PCR amplification using primers specific to DANA, suggesting that the DANA element will be useful as a molecular tool for genetic and phylogenetic analyses.

Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics

Support vector machines (SVMs) have recently emerged as a powerful technique for solving problems in pattern classification and regression. Best performance is obtained from the SVM its parameters have their values optimally set. In practice, good parameter settings are usually obtained by a lengthy process of trial and error. This paper describes the use of genetic algorithm to evolve these parameter settings for an application in mobile robotics.

Genetic algorithm seeding of idiotypic networks for mobile-robot navigation

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

Comparison of koala LPCoLN and human strains of Chlamydia pneumoniae highlights extended genetic diversity in the species

Background Chlamydia pneumoniae is a widespread pathogen causing upper and lower respiratory tract infections in addition to a range of other diseases in humans and animals. Previous whole genome analyses have focused on four essentially clonal (> 99% identity) C. pneumoniae human genomes (AR39, CWL029, J138 and TW183), providing relatively little insight into strain diversity and evolution of this species. Results We performed individual gene-by-gene comparisons of the recently sequenced C. pneumoniae koala genome and four C. pneumoniae human genomes to identify species-specific genes, and more importantly, to gain an insight into the genetic diversity and evolution of the species. We selected genes dispersed throughout the chromosome, representing genes that were specific to C. pneumoniae, genes with a demonstrated role in chlamydial biology and/or pathogenicity (n = 49), genes encoding nucleotide salvage or amino acid biosynthesis proteins (n = 6), and extrachromosomal elements (9 plasmid and 2 bacteriophage genes). Conclusions We have identified strain-specific differences and targets for detection of C. pneumoniae isolates from both human and animal origin. Such characterisation is necessary for an improved understanding of disease transmission and intervention.

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.

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.

Exploring the opportunities and challenges of using mobile sensing for gamification and achievements

Gamified services delivered on smart phones, such as Foursquare, are able to utilise the sensors on the phone to capture user contexts as a means of triggering game elements. This paper identifies and discusses opportunities and challenges that exist when using mobile sensors as input for game elements. We present initial findings from a field study of a gamified mobile application made to support the university orientation event for new students using game achievements. The study showed that overall the use of context was well received by participants when compared to game elements that required no context to complete. It was also found that using context could help validate that an activity was completed however there were still technical challenges when using sensors that led to exploits in the game elements, or cheating.

Clustering composite SaaS components in cloud computing using a grouping genetic algorithm

Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.

Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.

Compact arrays for mobile platforms : trade-off between size and performance for SDMA and MIMO applications

Smart antenna receiver and transmitter systems consist of multi-port arrays with an individual receiver channel (including ADC) and an individual transmitter channel (including DAC)at every of the M antenna ports, respectively. By means of digital beamforming, an unlimited number of simultaneous complex-valued vector radiation patterns with M-1 degrees of freedom can be formed. Applications of smart antennas in communication systems include space-division multiple access. If both stations of a communication link are equipped with smart antennas (multiple-input-multiple-output, MIMO). multiple independent channels can be formed in a "multi-path-rich" environment. In this article, it will be shown that under certain circumstances, the correlation between signals from adjacent ports of a dense array (M + ΔM elements) can be kept as low as the correlation between signals from adjacent ports of a conventional array (M elements and half-wavelength pacing). This attractive feature is attained by means of a novel approach which employs a RF decoupling network at the array ports in order to form new ports which are decoupled and associated with mutually orthogonal (de-correlated) radiation patterns.

A gamified mobile application for engaging new students at university orientation

The term gamification describes the addition of game elements to non-game contexts as a means to motivate and engage users. This study investigates the design, delivery and pilot evaluation of a gamified, smartphone application built to introduce new students to the campus, services and people at university during their first few weeks. This paper describes changes to the application made after an initial field study was undertaken and provides an evaluation of the impact of the redesign. Survey responses were collected from thirteen students and usage data was captured from 105 students. Results indicate three levels of user engagement and suggest that there is value in adding game elements to the experience in this way. A number of issues are identified and discussed based on game challenges, input, and facilitating game elements in an event setting such as university orientation.

Encouraging learners to drive using game elements and smartphones

Young drivers aged 17-24 years are at a risk of death and injury from road crashes primarily due to their age and inexperience on the road. Our research aims to investigate if a gamified mobile tracking and intervention tool can help to address this issue. We aim to build a smartphone application to support the current process of logging driving hours using a physical logbook and pen in Queensland. This provides an easier way to log driving hours than recording them in a logbook. In an attempt to engage Learners and encourage them to undertake more diverse driving practice we will explore how game elements can be integrated into the experience to motivate Learners. Previous research in other domains has shown that framing tasks as game-like can help engage and motivate users, however the addition of game elements to this space provides some interesting design challenges. This paper presents an overview of the research and presents these challenges for further discussion.

Gamifying everyday activities using mobile sensing

The addition of game design elements to non-game contexts has become known as gamification. Previous research has suggested that framing tedious and non-motivating tasks as game-like can make them enjoyable and motivating (e.g., de Oliveira, et al., 2010; Fujiki, et al., 2007; Chiu, et al., 2009). Smartphone applications lend themselves to being gamified as the underlying mobile technology has the ability to sense user activities and their surrounding environment. These sensed activities can be used to implement and enforce game-like rules based around many physical activities (e.g., exercise, travel, or eating). If researchers wish to investigate this area, they first need an existing gamified application to study. However if an appropriate application does not exist then the researcher may need to create their own gamified prototype to study. Unfortunately, there is little previous research that details or explains the design and integration of game elements to non-game mobile applications. This chapter explores this gap and shares a framework that was used to add videogame-like achievements to an orientation mobile application developed for new university students. The framework proved useful and initial results are discussed from two studies. However, further development of the framework is needed, including further consideration of what makes an effective gamified experience.