miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

Improving the outcomes of foot and ankle surgery through the audit cycle : a case study

The direct costs of managing adverse outcomes from Australian health care are estimated to be $2 billion. The audit cycle is considered an important tool to assist in the preventive management of adverse outcomes.Australian guidelines for audit cycle design allow for comparison of data sets derived from similar surgical specialities. However a lack of data set standardisation inhibits meaningful comparisons of foot and ankle surgical audits. This research will assist development of a best practice model for auditing foot and ankle surgery. Data derived from this model will improve the safety and quality of foot and ankle surgery. The preliminary phase of this process is to identify and understand the attitudes and behaviours of how and why surgeons participate in the audit cycle. A descriptive embedded multiple case study research design is planned to provide an intense focus on a single phenomenon (the audit cycle) within its real life context (clinical governance). The measures to be included in the case study have been identified by the Balanced Patient Safety Measurement Framework. These include: audit and peer review activity, provider attitudes to patient safety, safety learning, action and performance. A purposive sample of 6 to 8 surgeons (units of analysis) from 3 to 4 specialities (cases) will undergo semi-structured interview. This will investigate: current audit tools and processes; attitudes; and behaviours of surgeons to the audit cycle. Similarities in and differences between the units of analysis will indicate which identified measures function as barriers or enablers of the audit cycle. Reliability and validity (external and construct) will be assessed using established methods for case studies. The descriptive embedded multiple case study will reveal how and why foot and ankle surgeons participate in the audit cycle. This will inform further research to improve the outcomes of foot and ankle surgery through development of an audit tool.

Data mining the relationship between road crash and skid resistance

Road asset managers are seeking analysis of the whole road network to supplement statistical analyses of small subsets of homogeneous roadway. This study outlines the use of data mining capable of analyzing the wide range of situations found on the network, with a focus on the role of skid resistance in the cause of crashes. Results from the analyses show that on non-crash-prone roads with low crash rates, skid resistance contributes only in a minor way, whereas on high-crash roadways, skid resistance often contributes significantly in the calculation of the crash rate. The results provide evidence supporting a causal relationship between skid resistance and crashes and highlight the importance of the role of skid resistance in decision making in road asset management.

Performance Measurement in Perspective: An exploratory study of Australian foundations’ approaches to performance measurement

Performance measurement in Australian philanthropic foundations is a hot topic. Foundation staff and board members are concerned with striking the right balance between their need for information with which to assess the effectiveness of their grant-making programs, and the costs in both time and money for grantees. Influenced by normative pressures, the increasing size and professionalism of the Australian philanthropic sector, and trends from the U.S.A and the U.K, foundations are talking amongst themselves, seeking expert advice and training, consulting with grantees and trying different approaches. Many resources examine methods of data collection, measurement or analysis. Our study instead treads into less charted but important territory: the motivations and values that are shaping the debate about performance measurement. In a series of 40 interviews with foundations from Queensland, New South Wales, Victoria and South Australia, we asked whether they felt under pressure to measure performance and if so, why. We queried whether everyone in the foundation shared the same views on the purposes of performance measurement; and the ways in which the act of performance measurement changed their grant-making, their attitude to risk, their relationship with grantees and their collaborations with other funders. Unsurprisingly, a very diverse set of approaches to performance measurement were revealed.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

Public policy on corporate audit committees : case study evidence of current practice

Corporate failures and malpractices have led to an increasing emphasis on the governance role of audit committees. The Smith report Audit Committee Combined Code Guidance and the Higgs Review of the Role and Effectiveness of Non-Executive Directors (now incorporated in a Revised Combined Code) represent further attempts to strengthen corporate accountability in the UK. Although the regulatory focus on audit committees indicates confidence in their role as part of the solution to governance failures, questions remain about their efficacy in practice. Against the background of the publication of the Smith report and the wider reliance on audit committees in several countries to help improve corporate accountability, this paper provides research evidence, drawn from an ACCA-sponsored project, on the processes and effects of the audit committees in three UK companies. This study complements other research on audit committees by adopting a case study approach, in order to reflect the importance of investigating audit committee operations from within the organisation and to develop a closer understanding of audit committee impact than is available from generally observable data. The empirical evidence for the case studies was obtained from semi-structured interviews with personnel involved in the audit committee process, internal documents made available by the companies, and publicly available information, including annual reports.

An observational analysis of the impact of board dynamics and directors’ participation on perceived board effectiveness

This study addresses calls for closer examination of board dynamics by offering an inside view of director interactions. Video-observations of three board meetings at each of two Australian corporations matched with director interviews and secondary data reveal distinct patterns of director interactions, their sources of variation and impact on perceived board effectiveness. Our data reveal that director interactions are multi-dimensional and dynamic: while group interactions across agenda items are similar, with a few directors leading the discussion, the contributing directors change across items. Moreover, directors’ inclusiveness and evenness of participation are associated with higher perceptions of board effectiveness. Last, we find that director interactions change with the nature of the items, board climate and board meeting arrangements. The study contributes to the literature by moving beyond the individual-level analysis of directors’ skills or independence, and offering a detailed view of how the joint group and individual dimensions of board dynamics affect board functioning.

Synthesizing form and data : developing practices for student engagement and learning

We explore the relationship between form and data as a design agenda and learning strategy for novice visual information designers. Our students are university seniors in digital, visual design but novices to information design, manipulation and interpretation. We describe design strategies developed to scaffold sophisticated aesthetic and conceptual engagement despite limited understanding of the domain of designing with information. These revolve around an open-ended design project where students created a physical design from data of their choosing and research. The accompanying learning strategies concern this relationship between data and form to investigate it materially, formally and through ideation. Exemplifying student works that cross media and design domains are described.

Dataset validation within big data security architecture

In recent years, increasing focus has been made on making good business decisions utilizing the product of data analysis. With the advent of the Big Data phenomenon, this is even more apparent than ever before. But the question is how can organizations trust decisions made on the basis of results obtained from analysis of untrusted data? Assurances and trust that data and datasets that inform these decisions have not been tainted by outside agency. This study will propose enabling the authentication of datasets specifically by the extension of the RESTful architectural scheme to include authentication parameters while operating within a larger holistic security framework architecture or model compliant to legislation.