Polar exploration (University Focus) Research into Smart Materials Continues at the University of Dublin with the Development of Methods to Record and Present Data to Demonstrate the Magnetorheological Effect When a Magnetic Field is Applied to a MR Elastomer Sample

Research into methods to record and present data to demonstrate the Magnetorheological effect when a magnetic field is applied to a Magnetorheological Elastomer sample. By Dave Gorman, Niall Murphy and Ray Ekins, Technological University Dublin, Republic of Ireland A Magnetorheological Elastomer (MRE) is an example of a smart material as it undergoes a change in its physical properties when in the presece of an external magnetic field. This change in properties is known as the Magnetorheological (MR) effect and the manner in which it is achieved and reported, is of critical importance to the future development of MRE-based components. To gain a full understanding of the MR effect, detailed information on the applied magnetic field is required (Gorman et al. 2016) as well as the physical strain applied to the MRE sample (Gorman et al. 2017)

The Evaluation of the Effect of Strain Limits on the Physical Properties of Magnetorheological Elastomers Subjected to Uniaxial and Biaxial Cyclic Testing.

Magnetorheological Elastomers (MREs) are “smart” materials whose physical properties are altered by the application of magnetic fields. In a previous study by the authors [1], variations in the physical properties of MREs have been evaluated when subjected to a range of magnetic field strengths for both uniaxial and biaxial cyclic tests. By applying the same magnetic field to similar samples, this paper investigates the effect of both the upper strain limit and the strain amplitude on the properties of MREs subjected to cyclic fatigue testing. As the magnetorheological (MR) effect is due to the dipole-dipole interactions of the magnetic particles in an MRE [2], it is expected that the larger the upper strain limit, the lower the overall MR effect will be. This is investigated by varying the upper strain limit between tests while keeping the magnetic field applied during testing at selected cycles constant between tests. To investigate if the MR effect is only dependent on the upper strain limit and the magnitude of the applied magnetic field during cyclic testing, the tests are repeated with the same upper strain limits and applied fields but with reduced strain amplitude

The Equi-Biaxial Fatigue Characteristics of EPDM under True (Cauchy) Stress Control Conditions

ABSTRACT: Strain amplitude control is most often employed when carrying out fatigue testing of rubber components. Often the design engineer requires fatigue test data that is based on load amplitude control. This is analogous to engineering or nominal stress amplitude control. This usually makes it easy to maintain the load within the specified test limits during extended testing. Values of true stress and strain can be obtained from this approach, but the magnitudes of the maximum true stresses in these tests increase with accumulated cycles, whereas the equivalent maximum engineering stress values remain constant. This is easily demonstrated in the uniaxial case; however the nature of the applied load in equi-biaxial testing adds complexity. The effect in the equi-biaxial case is amplified as the principal stretch ratios have a more pronounced influence on both true stress and strain than in the uniaxial case. Engineering stress-strain data is particularly useful when representing the fatigue behaviour of elastic materials; however it does not represent reality in the case of rubber samples subjected to repeated high strains. True stress control testing can provide data to verify viscoelastic models used to describe elastomeric behaviour under bi-axial fatigue conditions. A test programme has been devised to examine the effect on fatigue life and stress strain relationships of a material tested under conditions of maximum biaxial true stress. This paper compares the difference in fatigue test predictions when using engineering stress and true stress amplitudes as the control parameters. The Experiments are in the form of equi-biaxial bubble inflation fatigue tests employing the DYNAMET system as described in previous CER publications

Equi-biaxial fatigue testing of EPM utilising bubble inflation

This paper describes an equi-biaxial tension fatigue test system which utilises the bubble inflation method to subject elastomers to equi-biaxial fatigue loading between user-defined limits of pressure, volume, stretch ratio or stress. The test system integrates a hydraulic inflation system, a high speed vision system and a control system. The high-speed vision system allows the stretch ratio and stress acting on the test specimen to be evaluated in real-time during testing. This in turn allows either stretch ratio or stress to be used as a direct control limit. In this research, constant maximum engineering stress control tests have been carried out to evaluate the suitability of the developed dynamic bubble inflation system for equi-biaxial fatigue testing of elastomers. The resulting test data was used to produce Wöhler (S/N) curves and stress/stretch ratio plots for ethylene-propylene rubber (EPM)

Analysis of Alzheimer's disease severity across brain regions by topological analysis of gene co-expression networks

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is a progressive neurodegenerative disorder involving variations in the transcriptome of many genes. AD does not affect all brain regions simultaneously. Identifying the differences among the affected regions may shed more light onto the disease progression. We developed a novel method involving the differential topology of gene coexpression networks to understand the association among affected regions and disease severity.</p> <p>Methods</p> <p>We analysed microarray data of four regions - entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC) and middle temporal gyrus (MTG) from AD affected and normal subjects. A coexpression network was built for each region and the topological overlap between them was examined. Genes with zero topological overlap between two region-specific networks were used to characterise the differences between the two regions.</p> <p>Results and conclusion</p> <p>Results indicate that MTG shows early AD pathology compared to the other regions. We postulate that if the MTG gets affected later in the disease, post-mortem analyses of individuals with end-stage AD will show signs of early AD in the MTG, while the EC, HIP and PCC will have severe pathology. Such knowledge is useful for data collection in clinical studies where sample selection is a limiting factor as well as highlighting the underlying biology of disease progression.</p

Automatic Filtering and Substantiation of Drug Safety Signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions