Dynamical systems for discovering protein complexes and functional modules from biological networks

Recent advances in high throughput experiments and annotations via published literature have provided a wealth of interaction maps of several biomolecular networks, including metabolic, protein-protein, and protein-DNA interaction networks. The architecture of these molecular networks reveals important principles of cellular organization and molecular functions. Analyzing such networks, i.e., discovering dense regions in the network, is an important way to identify protein complexes and functional modules. This task has been formulated as the problem of finding heavy subgraphs, the Heaviest k-Subgraph Problem (k-HSP), which itself is NPhard. However, any method based on the k-HSP requires the parameter k and an exact solution of k-HSP may still end up as a “spurious” heavy subgraph, thus reducing its practicability in analyzing large scale biological networks. We proposed a new formulation, called the rank-HSP, and two dynamical systems to approximate its results. In addition, a novel metric, called the Standard deviation and Mean Ratio (SMR), is proposed for use in “spurious” heavy subgraphs to automate the discovery by setting a fixed threshold. Empirical results on both the simulated graphs and biological networks have demonstrated the efficiency and effectiveness of our proposal.

Diverse approaches : a study of Australian journalism educators' use of web-based curriculum modules for reporting cultural difference

The Reporting Diversity website provides four curriculum modules to assist journalism educators to teach students about the issues and practice of reporting on cultural difference. The researchers co-ordinated the second round of trials of these resources in 2009, which involved the participation of academics and students from five Australian universities. A further 30 academics were surveyed to gauge their level of awareness of the materials. This paper reports on the educators’ evaluation of the resources and reveals the innovative ways in which the modules are being used and adapted in different classroom settings. The researchers argue that sharing different teaching approaches to the materials through the Reporting Diversity website would assist other academics to adapt the resources for their own use.

A new fuzzy ratio and its application to the single input rule modules connected fuzzy inference system

The principle of ratios has been applied to many real world problems, e.g. the part-to-part and part-to-whole ratio formulations. As it is difficult for humans to provide an exact ratio in many real situations, we introduce a fuzzy ratio in this paper. We use some notions from fuzzy arithmetic to analyze fuzzy ratios captured from humans. An application of the formulated fuzzy ratio to a Single Input Rule Modules connected Fuzzy Inference System (SIRMs-FIS) is demonstrated. Instead of using a precise weight, fuzzy sets are employed to represent the relative importance of each rule module. The resulting fuzzy weights are explained as a fuzzy ratio on a weight domain. In addition, a new SIRMs-FIS model with fuzzy weights and part-to-whole fuzzy ratio is devised. A simulated example is presented to clarify the proposed SIRM-FIS model.

A simulated annealing global maximum power point tracking approach for PV modules under partial shading conditions

This paper proposes a simulated annealing (SA)-based global maximum power point tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions (PSC). The proposed technique is compared with the common perturb and observe MPPT technique and the particle swarm optimization method for GMPPT. The performance is assessed by considering the time taken to converge and the number of sample cases where the technique converges to the GMPP. Simulation results indicate the improved performance of the SA-based GMPPT algorithm, with arbitrarily selected parameters, in tracking to the global maxima in a multiple module PV system which experiences PSC. Experimental validation of the technique is presented based on PV modules that experience nonuniform environmental conditions. Additionally, studies regarding the influence of the key parameters of the SA-based algorithm are described. Simulation and experimental results verify the effectiveness of the proposed GMPPT method.

Evidence-based learning: Interactive, online EBP modules for first year nursing. A case study

Deakin University Library designed a series of six modules to provide interactive, online learning for a first year nursing unit, Understanding Research Evidence. The modules were developed in response to the changing learning requirements of students in the digital age. Delivered using Smart Sparrow software, the modules were designed to assist students in the development and consolidation of their understandings of evidence-based practice (EBP).The development of the modules represents a shift from unilateral communication to interactive content. Previously, online support had largely consisted of static material that was not presented in the context of curriculum. The Library has now developed integrated content that allows for interactivity, but which may also be customised for other purposes or units across all health disciplines.Feedback and data collected from the modules indicate an encouraging degree of engagement with the content. Data also allows the Library to ensure the continuous improvement of the modules. Library staff have also reported on their improved capacity and confidence in creating learning experiences that integrate core information and digital literacy competencies with students' curriculum. Staff also report improvements in their ability to use technologies to create online learning objects.