The Mechanism of Corrosion of Aluminium Zirconium Silicate (AZS) Material in the Float Glass Furnace Regenerator

Failure mechanisms in AZS materials from the regenerators of two float glass furnaces are presented. Results of a post-mortem examination of materials are used to identify the physical and chemical changes during service. Methods used include bulk density and apparent porosity measurements, optical microscopy, scanning electron microscopy (SEM), elemental dispersive analysis (EDA), x-ray fluorescence spectroscopy (XRF), x-ray diffraction (XRD) and IR spectroscopy. Corrosion was found to be related to oxidising and reducing conditions and temperature. Chemical and physical differences between virgin and three different furnace materials are identified and used to propose a mechanism for corrosion in different zones of the glass furnace regenerator

Hemodynamic predictors of aortic dilatation in bicuspid aortic valve by velocity-encoded cardiovascular magnetic resonance

<p>Abstract</p> <p>Background</p> <p>Congenital Bicuspid Aortic Valve (BAV) is a significant risk factor for serious complications including valve dysfunction, aortic dilatation, dissection, and sudden death. Clinical tools for identification and monitoring of BAV patients at high risk for development of aortic dilatation, an early complication, are not available.</p> <p>Methods</p> <p>This paper reports an investigation in 18 pediatric BAV patients and 10 normal controls of links between abnormal blood flow patterns in the ascending aorta and aortic dilatation using velocity-encoded cardiovascular magnetic resonance. Blood flow patterns were quantitatively expressed in the angle between systolic left ventricular outflow and the aortic root channel axis, and also correlated with known biochemical markers of vessel wall disease.</p> <p>Results</p> <p>The data confirm larger ascending aortas in BAV patients than in controls, and show more angled LV outflow in BAV (17.54 ± 0.87 degrees) than controls (10.01 ± 1.29) (p = 0.01). Significant correlation of systolic LV outflow jet angles with dilatation was found at different levels of the aorta in BAV patients STJ: r = 0.386 (N = 18, p = 0.048), AAO: r = 0.536 (N = 18, p = 0.022), and stronger correlation was found with patients and controls combined into one population: SOV: r = 0.405 (N = 28, p = 0.033), STJ: r = 0.562 (N = 28, p = 0.002), and AAO r = 0.645 (N = 28, p < 0.001). Dilatation and the flow jet angle were also found to correlate with plasma levels of matrix metallo-proteinase 2.</p> <p>Conclusions</p> <p>The results of this study provide new insights into the pathophysiological processes underlying aortic dilatation in BAV patients. These results show a possible path towards the development of clinical risk stratification protocols in order to reduce morbidity and mortality for this common congenital heart defect.</p

Defect detection in reinforced concrete using random neural architectures

Detecting defects within reinforced concrete is vital to the safety and durability of our built infrastructure upon which we heavily rely. In this work a non‐invasive technique, ElectroMagnetic Anomaly Detection (EMAD), is used which provides information into the electromagnetic properties of the reinforcing steel and for which data analysis is currently performed visually: an undesirable process. This article investigates the first use of two neural network approaches to automate the analysis of this data: Echo State Networks (ESNs) and Extreme Learning Machines (ELMs) where fast and efficient training procedures allow networks to be trained and evaluated in less time than traditional neural network approaches. Data collected from real‐world concrete structures have been analyzed using these two approaches as well as using a simple threshold measure and a standard recurrent neural network. The ELM approach offers a significant improvement in performance for a single tendon‐reinforced structure, while two ESN architectures provided best performance for a mesh‐reinforced concrete structure

Where are our patients? Retrospective cohort study of acute medical unit admissions during and prior to the COVID-19 pandemic.

Admissions to hospital have declined markedly during the COVID-19 pandemic in Australia. This may be due to patients not presenting with acute illness or managing their chronic illness at home. We reviewed a cohort admitted to the Acute Medical Unit of the Royal Melbourne Hospital during and before the pandemic and found admissions were more acutely unwell and more comorbid. This may lead to worse outcomes for those not presenting, as well as those presenting late. We recommend a public health campaign to encourage Australians to present to hospital if unwell