Relationship between cooling rate and microsegregation in bottom-chilled directionally solidified ductile irons

This study explores the relationship between cooling rate and microsegregation of directionally solidified ductile iron. The unidirectional heat transfer system used in this research is made up of a copper mold kept chilled by circulating water and embedded in the bottom of Furan sand mold. Thermocouples are connected to the computer measuring system to record the cooling curves of the castings at a distance of 0, 30, 60 and 90 mm from the chilled copper mold surface. Alloys including Mn, Cr, Cu, Ni and Ti were added to the specimens. Electron microprobe analysis (EPMA) was employed to examine distribution of elements between the dendrite arms and nodular graphite. Results show that unidirectional heat transfer affects directly the solidification mode and microstructure of the casting. The cooling curves reveal that local solidification time increases with increasing distance from the chilled copper mold surface. Different solidification rates with corresponding microstructure and element segregation were observed in the same unidirectionally solidified casting. Local solidification time was closely related to element segregation. The effective segregation coefficient (Keff) calculated using the Scheil equation was found to vary, according to the stage of solidification. The actual segregation characteristics of complex alloys generally follow the Scheil equation

Bayesian Semi-parametric Expected Shortfall Forecasting in Financial Markets

Bayesian semi-parametric estimation has proven effective for quantile estimation in general and specifically in financial Value at Risk forecasting. Expected short-fall is a competing tail risk measure, involving a conditional expectation beyond a quantile, that has recently been semi-parametrically estimated via asymmetric least squares and so-called expectiles. An asymmetric Gaussian density is proposed allowing a likelihood to be developed that leads to Bayesian semi-parametric estimation and forecasts of expectiles and expected shortfall. Further, the conditional autoregressive expectile class of model is generalised to two fully nonlinear families. Adaptive Markov chain Monte Carlo sampling schemes are employed for estimation in these families. The proposed models are clearly favoured in an empirical study forecasting eleven financial return series: clear evidence of more accurate expected shortfall forecasting, compared to a range of competing methods is found. Further, the most favoured models are those estimated by Bayesian methods

Bayesian Assessment of Dynamic Quantile Forecasts

Methods for Bayesian testing and assessment of dynamic quantile forecasts are proposed. Specifically, Bayes factor analogues of popular frequentist tests for independence of violations from, and for correct coverage of a time series of, quantile forecasts are developed. To evaluate the relevant marginal likelihoods involved, analytic integration methods are utilised when possible, otherwise multivariate adaptive quadrature methods are employed to estimate the required quantities. The usual Bayesian interval estimate for a proportion is also examined in this context. The size and power properties of the proposed methods are examined via a simulation study, illustrating favourable comparisons both overall and with their frequentist counterparts. An empirical study employs the proposed methods, in comparison with standard tests, to assess the adequacy of a range of forecasting models for Value at Risk (VaR) in several financial market data series

Chorea as a First Manifestation in Young Patients with Systemic Lupus Erythematosus Who Was Initially Diagnosed With Rheumatic Fever

Chorea is a rare manifestation of systemic lupus erythematosus (SLE). We report on a young patient with chorea who was diagnosed initially with rheumatic fever. Follow up and further evaluation confirmed the diagnosis of SLE and anti-phospholipid syndrome. Of special interest were the negative antiphospholipid (aPL) antibodies and the initial diagnosis of rheumatic fever which is still not uncommon problem in our region. The rarity of such presentation with joint and non specific increase of antistreptolysin O (ASO) titer might be the factors that led to an incorrect diagnosis. Early diagnosis and treatment of SLE and anti-phospholipid syndrome are very crucial and should be considered with such presentation

Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis

Value-at-Risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models are compared, including standard, threshold nonlinear and Markov switching GARCH specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student-t, skewed-t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia-Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models out-performed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre-crisis; while at the 1% level during and post-crisis, for a 1 day horizon, models with skewed-t errors ranked best, while IGARCH models were favoured at the 5% level; (iii) all models forecasted VaR less accurately and anti-conservatively post-crisi

Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis

Value-at-Risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models are compared, including standard, threshold nonlinear and Markov switching GARCH specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student-t, skewed-t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia-Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models out-performed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre-crisis; while at the 1% level during and post-crisis, for a 1 day horizon, models with skewed-t errors ranked best, while IGARCH models were favoured at the 5% level; (iii) all models forecasted VaR less accurately and anti-conservatively post-crisi

Search for TeV Scale Physics in Heavy Flavour Decays

The subject of heavy flavour decays as probes for physics beyond the TeV scale is covered from the experimental perspective. Emphasis is placed on the more traditional Beyond the Standard Model topics that have potential for impact in the short term, with the physics explained. We do unabashedly promote our own phemonenology work.Comment: 10 pages, 9 figures (now fixed); Submitted for the SUSY07 proceeding

A quantum field-theoretical perspective on scale anomalies in 1D systems with three-body interactions

We analyze, from a canonical quantum field theory (QFT) perspective, the problem of one-dimensional particles with three-body attractive interactions, which was recently shown to exhibit a scale anomaly identical to that observed in two-dimensional (2D) systems with two-body interactions. We study in detail the properties of the scattering amplitude including both bound and scattering states, using cutoff and dimensional regularization, and clarify the connection between the scale anomaly derived from thermodynamics to the nonvanishing non-relativistic trace of the energy-momentum tensor

Quantum Anomaly and Thermodynamics of One-Dimensional Fermions with Three-Body Interactions

We show that a system of three species of one-dimensional fermions, with an attractive three-body contact interaction, features a scale anomaly directly related to the anomaly of two-dimensional fermions with two-body contact forces. We show, furthermore, that those two cases (and their multispecies generalizations) are the only nonrelativistic systems with contact interactions that display a scale anomaly. While the two-dimensional case is well known and has been under study both experimentally and theoretically for years, the one-dimensional case presented here has remained unexplored. For the latter, we calculate the impact of the anomaly on the equation of state, which appears through the generalization of Tan's contact for three-body forces, and determine the pressure at finite temperature. In addition, we show that the third-order virial coefficient is proportional to the second-order coefficient of the two-dimensional two-body case