Modeling of primary dendrite arm spacing variations in thin-slab casting of low carbon and low alloy steels

Solidification structure of a High Strength Low Alloy (HSLA) steel, in terms of dendrite arm spacing distribution across the shell thickness, is studied in a breakout shell from a thin-slab caster at Tata Steel in IJmuiden. Columnar dendrites were found to be the predominant morphology throughout the shell with size variations across the shell thickness. Primary Dendrite Arm Spacing (PDAS) increases by increasing the distance from meniscus or slab surface. Subsequently, a model is proposed to describe the variation of the PDAS with the shell thickness (the distance from slab surface) under solidifiction conditions experienced in the primary cooling zone of thin-slab casting. The proposed relationship related the PDAS to the shell thickness and, hence, can be used as a tool for predicting solidifcation structure and optimizing the thin-slab casting of low alloy steels

Bayesian clustering of multiple zero-inflated outcomes

Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes. In this context, it is of interest to study the patterns of counts and cluster the subjects accordingly. We introduce a novel Bayesian approach to cluster multiple, possibly related, zero-inflated processes. We propose a joint model for zero-inflated counts, specifying a hurdle model for each process with a shifted Negative Binomial sampling distribution. Conditionally on the model parameters, the different processes are assumed independent, leading to a substantial reduction in the number of parameters as compared with traditional multivariate approaches. The subject-specific probabilities of zero-inflation and the parameters of the sampling distribution are flexibly modelled via an enriched finite mixture with random number of components. This induces a two-level clustering of the subjects based on the zero/non-zero patterns (outer clustering) and on the sampling distribution (inner clustering). Posterior inference is performed through tailored Markov chain Monte Carlo schemes. We demonstrate the proposed approach on an application involving the use of the messaging service WhatsApp. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'

Tuberculosis in Dr Granville's mummy: a molecular re-examination of the earliest known Egyptian mummy to be scientifically examined and given a medical diagnosis

‘Dr Granville's mummy’ was described to the Royal Society of London in 1825 and was the first ancient Egyptian mummy to be subjected to a scientific autopsy. The remains are those of a woman, Irtyersenu, aged about 50, from the necropolis of Thebes and dated to about 600 BC. Augustus Bozzi Granville (1783–1872), an eminent physician and obstetrician, described many organs still in situ and attributed the cause of death to a tumour of the ovary. However, subsequent histological investigations indicate that the tumour is a benign cystadenoma. Histology of the lungs demonstrated a potentially fatal pulmonary exudate and earlier studies attempted to associate this with particular disease conditions. Palaeopathology and ancient DNA analyses show that tuberculosis was widespread in ancient Egypt, so a systematic search for tuberculosis was made, using specific DNA and lipid biomarker analyses. Clear evidence for Mycobacterium tuberculosis complex DNA was obtained in lung tissue and gall bladder samples, based on nested PCR of the IS6110 locus. Lung and femurs were positive for specific M. tuberculosis complex cell-wall mycolic acids, demonstrated by high-performance liquid chromatography of pyrenebutyric acid–pentafluorobenzyl mycolates. Therefore, tuberculosis is likely to have been the major cause of death of Irtyersenu

Questioning the Influence of Sunspots on Amazon Hydrology: Even a Broken Clock Tells the Right Time Twice a Day

It was suggested in a recent article that sunspots drive decadal variation in Amazon River flow. This conclusion was based on a novel time series decomposition method used to extract a decadal signal from the Amazon River record. We have extended this analysis back in time, using a new hydrological proxy record of tree ring oxygen isotopes (δ¹⁸OTR). Consistent with the findings of Antico and Torres, we find a positive correlation between sunspots and the decadal δ¹⁸OTR cycle from 1903 to 2012 (r = 0.60, p < 0.001). However, the relationship does not persist into the preceding century and even becomes weakly negative (r = −0.30, p = 0.11, 1799–1902). This result casts considerable doubt over the mechanism by which sunspots are purported to influence Amazon hydrology