Autonomic management of non-functional concerns in distributed & parallel application programming

An approach to the management of non-functional concerns in massively parallel and/or distributed architectures that marries parallel programming patterns with autonomic computing is presented. The necessity and suitability of the adoption of autonomic techniques are evidenced. Issues arising in the implementation of autonomic managers taking care of multiple concerns and of coordination among hierarchies of such autonomic managers are discussed. Experimental results are presented that demonstrate the feasibility of the approach.

Adolescent men’s pregnancy resolution choices in relation to an unintended pregnancy: A comparative analysis of adolescent men in three countries.

This paper investigates adolescent men's pregnancy resolution choices in Australia, Ireland and Italy. It addresses two main gaps in the literature: the lack of research on (adolescent) men's views on unintended pregnancy and pregnancy resolution; and the lack of international comparative case studies on men and reproductive choices. Consistent with theories of the transformation of intimacies in society and the growth of individualization, the results suggest that adolescent men are interested in the effect of an unintended pregnancy on their individual biographies as well as the effect on their girlfriend's health and well-being. However, Australian male adolescents were much more likely to choose abortion than Italian or Irish adolescents, suggesting adolescent males have also internalized country level debates surrounding abortion. Methodologically, the paper demonstrates an innovative approach to data-collection using a computer-based interactive drama to facilitate participants' deliberation and responses. It was shown to engage a large number of adolescent men and is likely to have wider generalisability in developing international comparative research on the topic, as well as applications for health promotion.

CD2AP is associated with end-stage renal disease in patients with type 1 diabetes

CD2-associated protein (CD2AP) is essential for podocyte function. CD2AP mutations have been found in patients with focal segmental glomerulosclerosis, a disease histologically resembling diabetic nephropathy and often progressing to end-stage renal disease (ESRD). We hypothesised that variations in the CD2AP gene may contribute to susceptibility to glomerular injury in diabetes and investigated if single-nucleotide polymorphisms (SNPs) in CD2AP are associated with diabetic nephropathy in patients with type 1 diabetes. The discovery cohort consisted of 2,251 Finnish patients with type 1 diabetes. SNPs were selected from the HapMap database to cover the CD2AP gene. The associations between genotyped SNPs and diabetic nephropathy or ESRD were analysed with the chi-squared test and logistic regression. Three SNPs were selected for replication in cohorts from Denmark, Italy, the United Kingdom and Ireland. None of the 15 successfully genotyped SNPs were associated with diabetic nephropathy when compared to patients with normal albumin excretion rate. However, when genotype frequencies in patients with ESRD were compared with all other patients, two CD2AP SNPs, rs9369717 and rs9349417, were found to be associated with ESRD. The meta-analysis of the original and two additional European cohorts resulted in significant p values

Asset Tracking in Critical Power Communications Infrastructures using Passive Techniques

Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.

The determination of optimal processing conditions for PLA and PLA/CaCO3 in twin screw extrusion using DoE and multivariate analysis

Biodegradable polymers, such as PLA (Polylactide), come from renewable resources like corn starch and if disposed of correctly, degrade and become harmless to the ecosystem making them attractive alternatives to petroleum based polymers. PLA in particular is used in a variety of applications including medical devices, food packaging and waste disposal packaging. However, the industry faces challenges in melt processing of PLA due to its poor thermal stability which is influenced by processing temperatures and shearing.
Identification and control of suitable processing conditions is extremely challenging, usually relying on trial and error, and often sensitive to batch to batch variations. Off-line assessment in a lab environment can result in high scrap rates, long lead times and lengthy and expensive process development. Scrap rates are typically in the region of 25-30% for medical grade PLA costing between €2000-€5000/kg.
Additives are used to enhance material properties such as mechanical properties and may also have a therapeutic role in the case of bioresorbable medical devices, for example the release of calcium from orthopaedic implants such as fixation screws promotes healing. Additives can also reduce the costs involved as less of the polymer resin is required.
This study investigates the scope for monitoring, modelling and optimising processing conditions for twin screw extrusion of PLA and PLA w/calcium carbonate to achieve desired material properties. A DAQ system has been constructed to gather data from a bespoke measurement die comprising melt temperature; pressure drop along the length of the die; and UV-Vis spectral data which is shown to correlate to filler dispersion. Trials were carried out under a range of processing conditions using a Design of Experiments approach and samples were tested for mechanical properties, degradation rate and the release rate of calcium. Relationships between recorded process data and material characterisation results are explored.

Feasibility Assessment of Plug and Play Model Predictive Control for use in DC Grids

Distributed control techniques can allow Transmission System Operators (TSOs) to coordinate their responses via TSO-TSO communication, providing a level of control that lies between that of centralised control and communication free decentralised control of interconnected power systems. Recently the Plug and Play Model Predictive Control (PnPMPC) toolbox has been developed in order to allow practitioners to design distributed controllers based on tube-MPC techniques. In this paper, some initial results using the PnPMPC toolbox for the design of distributed controllers to enhance AGC in AC areas connected to Multi-Terminal HVDC (MTDC) grids, are illustrated, in order to evaluate the feasibility of applying PnPMPC for this purpose.

Synchronous Islanding Control in the Presence of Hydro-electric Generation

This paper introduces a novel load sharing algorithm to enable island synchronization. The system model used for development is based on an actual system for which historical measurement and fault data is available and is used to refine and test the algorithms performance and validity. The electrical system modelled is selected due to its high-level of hydroelectric generation and its history of islanding events. The process of developing the load sharing algorithm includes a number of steps. Firstly, the development of a simulation model to represent the case study accurately - this is validated by way of matching system behavior based on data from historical island events. Next, a generic island simulation is used to develop the load sharing algorithm. The algorithm is then tested against the validated simulation model representing the case study area selected. Finally, a laboratory setup is described which is used as validation method for the novel load sharing algorithm.