Exploring second life as a learning environment for computer programming

Computer programming can be challenging for beginners because of the need to understand abstract programming concepts. In this paper, we study the use of the Second Life (SL) virtual world for learning computer programming concepts. We conduct an empirical study for learning computer programming in SL by addressing affordances of SL for experiential problem-based learning pedagogies. We present preliminary findings, the promises and the limitations of Second Life as an environment for learning computer programming.

Exploring the fantastic: new critical frameworks in an evolving genre

This thesis (creative practice/exegesis) argues that fantasy fiction can function as a progressive socio-political literature. Using the Marxist theory of the Frankfurt School it explores the relationship between fantasy and science fiction via utopian/dystopian representation. Through this dialogue a new understanding of the genre is voiced.

Emerging theoretical frameworks for global health governance

The shift from an international to a global world order has substantially transformed how health is produced at the global level and, consequently, how health can be regulated at the global level. This entails that analysts concerned with global health need new sets of theoretical tools to analyse global health governance. This chapter presents three different case studies (Framework Convention on Tobacco Control, trade agreement on intellectual property rights in relation to access to medicines and national policies on global health) analyzing major governance issues through different theoretical perspectives (implementation theories, a critical discourse analysis, theories on the formulation and circulation of policy ideas). This chapter ends with a tentative way to make sense of global health governance research that accommodates different research questions and theoretical perspectives.

Occupational light-vehicle use and OHS legislative frameworks : an Australian example

Occupational light vehicle (OLV) use and associated exposures and hazards in the Australian context are described. Available insurance data indicate that the OLV injury burden, which is greater than that of other work–road users, is growing asOLV use changes incidental, to workers', primary occupations and work patterns. Legislation that affects OLV users is reviewed and the shifting of the burden of responsibility for injured or killed OLV users between workers' compensation, motor accident insurance and public health systems is described. Changes to OHS regulatory frameworks are proposed to better address OLV-relevant policy and practice. These issues are relevant for many international jurisdictions.

Fetal programming of schizophrenia: select mechanisms

Mounting evidence indicates that schizophrenia is associated with adverse intrauterine experiences. An adverse or suboptimal fetal environment can cause irreversible changes in brain that can subsequently exert long-lasting effects through resetting a diverse array of biological systems including endocrine, immune and nervous. It is evident from animal and imaging studies that subtle variations in the intrauterine environment can cause recognizable differences in brain structure and cognitive functions in the offspring. A wide variety of environmental factors may play a role in precipitating the emergent developmental dysregulation and the consequent evolution of psychiatric traits in early adulthood by inducing inflammatory, oxidative and nitrosative stress (IO&NS) pathways, mitochondrial dysfunction, apoptosis, and epigenetic dysregulation. However, the precise mechanisms behind such relationships and the specificity of the risk factors for schizophrenia remain exploratory. Considering the paucity of knowledge on fetal programming of schizophrenia, it is timely to consolidate the recent advances in the field and put forward an integrated overview of the mechanisms associated with fetal origin of schizophrenia.

Sulfur-doped porous reduced graphene oxide hollow nanosphere frameworks as metal-free electrocatalysts for oxygen reduction reaction and as supercapacitor electrode materials.

Chemical doping with foreign atoms is an effective approach to significantly enhance the electrochemical performance of the carbon materials. Herein, sulfur-doped three-dimensional (3D) porous reduced graphene oxide (RGO) hollow nanosphere frameworks (S-PGHS) are fabricated by directly annealing graphene oxide (GO)-encapsulated amino-modified SiO2 nanoparticles with dibenzyl disulfide (DBDS), followed by hydrofluoric acid etching. The XPS and Raman spectra confirmed that sulfur atoms were successfully introduced into the PGHS framework via covalent bonds. The as-prepared S-PGHS has been demonstrated to be an efficient metal-free electrocatalyst for oxygen reduction reaction (ORR) with the activity comparable to that of commercial Pt/C (40%) and much better methanol tolerance and durability, and to be a supercapacitor electrode material with a high specific capacitance of 343 F g(-1), good rate capability and excellent cycling stability in aqueous electrolytes. The impressive performance for ORR and supercapacitors is believed to be due to the synergistic effect caused by sulfur-doping enhancing the electrochemical activity and 3D porous hollow nanosphere framework structures facilitating ion diffusion and electronic transfer.

A survey of approaches and frameworks to carry out genomic data analysis on the cloud

High Performance Computing (HPC) clouds have started to change the way how research in science, in particular medicine and genomics (bioinformatics) is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. However, most HPC clouds are provided at an Infrastructure as a Service (IaaS) level, users are presented with a set of virtual servers which need to be put together to form HPC environments via time consuming resource management and software configuration tasks, which make them practically unusable by discipline, non-computing specialists. In response, there is a new trend to expose cloud applications as services to simplify access and execution on clouds. This paper firstly examines commonly used cloud-based genomic analysis services (Tuxedo Suite, Galaxy and Cloud Bio Linux). As a follow up, we propose two new solutions (HPCaaS and Uncinus), which aim to automate aspects of the service development and deployment process. By comparing and contrasting these five solutions, we identify key mechanisms of service creation, execution and access that are required to support genomic research on the SaaS cloud, in particular by discipline specialists. © 2014 IEEE.

From ranking fuzzy numbers to solving fuzzy linear programming: a comprehensive review

Solving fuzzy linear programming (FLP) requires the employment of a consistent ranking of fuzzy numbers. Ineffective fuzzy number ranking would lead to a flawed and erroneous solving approach. This paper presents a comprehensive and extensive review on fuzzy number ranking methods. Ranking techniques are categorised into six classes based on their characteristics. They include centroid methods, distance methods, area methods, lexicographical methods, methods based on decision maker's viewpoint, and methods based on left and right spreads. A survey on solving approaches to FLP is also reported. We then point out errors in several existing methods that are relevant to the ranking of fuzzy numbers and thence suggest an effective method to solve FLP. Consequently, FLP problems are converted into non-fuzzy single (or multiple) objective linear programming based on a consistent centroid-based ranking of fuzzy numbers. Solutions of FLP are then obtained by solving corresponding crisp single (or multiple) objective programming problems by conventional methods.

Solving fuzzy programming with a consistent fuzzy number ranking

 Some illustrative examples are provided to identify the ineffective and unrealistic characteristics of existing approaches to solving fuzzy linear programming (FLP) problems (with single or multiple objectives). We point out the error in existing methods concerning the ranking of fuzzy numbers and thence suggest an effective method to solve the FLP. Based on the consistent centroid-based ranking of fuzzy numbers, the FLP problems are transformed into non-fuzzy single (or multiple) objective linear programming. Solutions of FLP are then crisp single or multiple objective programming problems, which can respectively be obtained by conventional methods.

Extending scheduling algorithms to minimise the impact of bounded uncertainty using interval programming

 This research proposed a new methodology to extend algorithms to accept interval-based uncertain parameters. The methodology is applied on scheduling algorithms, including heuristic and meta-heuristic algorithms and produced optimal results with higher accuracy. The research outcomes are effective for decision making process using uncertain or predicted data.

Impact of Assurance of Learning (AOL) in programming course for novices

One of the aims of any higher education institution is to align its curriculum with program learning goals. Programs which ensure proper learning have positive effects on students, instructors, departments and also on the higher education institution itself. This paper discusses the implementation and effects of Assurance Of Learning (AOL) processes on introductory programming (IP) courses. It elaborates five stages of AOL to align program learning goals with IP curriculum. Then, it discusses how the AOL process identifies shortcomings in the assessment methods of IP courses. Furthermore, it enlightens how the assessment findings, as a result of the AOL process, provide mechanisms to address the drawbacks during the delivery of such courses. Feedback on