Classification using distance nearest neighbours

This paper proposes a new probabilistic classification algorithm using a Markov random field approach. The joint distribution of class labels is explicitly modelled using the distances between feature vectors. Intuitively, a class label should depend more on class labels which are closer in the feature space, than those which are further away. Our approach builds on previous work by Holmes and Adams (2002, 2003) and Cucala et al. (2008). Our work shares many of the advantages of these approaches in providing a probabilistic basis for the statistical inference. In comparison to previous work, we present a more efficient computational algorithm to overcome the intractability of the Markov random field model. The results of our algorithm are encouraging in comparison to the k-nearest neighbour algorithm.Comment: 12 pages, 2 figures. To appear in Statistics and Computin

Bayesian computations and efficient algorithms for computing functions of large, sparse matrices

The need for computing functions of large, sparse matrices arises in Bayesian spatial models where the computations using Gaussian Markov random fields require the evaluation of G -1 and G -1/2 for the precision matrix G and in the geostatistical approach where approximations of R -1 and R 1/2 are needed for the covariance matrix R . In both cases, good approximations to the desired matrix functions are required over a range of probable values of a vector v drawn randomly from a given population, as occurs in simulation techniques for finding posterior distributions such as Markov chain Monte Carlo. Consequently, it is preferable that the complete matrix function approximation be determined rather than for its action on a given v . The aim of this work is to find low degree polynomial approximations p( A ) such that e = ? f( A ) - p( A ) ? 2 is small in some sense on the spectral interval [a,b], where the extreme eigenvalues a and b are calculated using Krylov subspace approximation. Algorithms based on low order near-minimax polynomial approximations are proposed for the required matrix functions for a typical case study in computational Bayesian statistics, where a good balance between accuracy and computationally efficiency is achieved

Loss of MIR15A and MIR16-1 at 13q14 is associated with increased TP53 mRNA, de-repression of BCL2 and adverse outcome in chronic lymphocytic leukaemia.

This study was conducted to investigate the possibility that TP53 mRNA is variably expressed in chronic lymphocytic leukaemia (CLL) and that under-expression is associated with TP53 dysfunction and adverse outcome. Although TP53 mRNA levels did indeed vary among the 104 CLL samples examined, this variability resulted primarily from over-expression of TP53 mRNA in 18 samples, all of which lacked TP53 deletion/mutation. These patients had higher lymphocyte counts and shorter overall and treatment-free survival times compared to cases with low TP53 mRNA expression and no TP53 deletion/mutation. Furthermore, TP53 mRNA levels did not correlate with levels of TP53 protein or its transcriptional target CDKN1A. We speculated that the adverse outcome associated with TP53 mRNA over-expression might reflect variation in levels of MIR15A and MIR16-1, which are encoded on chromosome 13q14 and target TP53 and some oncogenes including BCL2. In keeping with our hypothesis, 13q14 copy number and levels of MIR15A/MIR16-1 correlated positively with one another but negatively with levels of TP53 mRNA and BCL2 mRNA. Our findings support a model in which loss of MIR15A/MIR16-1 at chromosome 13q14 results in adverse outcome due to de-repression of oncogenes such as BCL2, and up-regulation of TP53 mRNA as a bystander effect

A procedure for the change point problem in parametric models based on phi-divergence test-statistics

This paper studies the change point problem for a general parametric, univariate or multivariate family of distributions. An information theoretic procedure is developed which is based on general divergence measures for testing the hypothesis of the existence of a change. For comparing the accuracy of the new test-statistic a simulation study is performed for the special case of a univariate discrete model. Finally, the procedure proposed in this paper is illustrated through a classical change-point example

A Novel Genome-Wide Association Study Approach Using Genotyping by Exome Sequencing Leads to the Identification of a Primary Open Angle Glaucoma Associated Inversion Disrupting ADAMTS17

Closed breeding populations in the dog in conjunction with advances in gene mapping and sequencing techniques facilitate mapping of autosomal recessive diseases and identification of novel disease-causing variants, often using unorthodox experimental designs. In our investigation we demonstrate successful mapping of the locus for primary open angle glaucoma in the Petit Basset Griffon Vendéen dog breed with 12 cases and 12 controls, using a novel genotyping by exome sequencing approach. The resulting genome-wide association signal was followed up by genome sequencing of an individual case, leading to the identification of an inversion with a breakpoint disrupting the ADAMTS17 gene. Genotyping of additional controls and expression analysis provide strong evidence that the inversion is disease causing. Evidence of cryptic splicing resulting in novel exon transcription as a consequence of the inversion in ADAMTS17 is identified through RNAseq experiments. This investigation demonstrates how a novel genotyping by exome sequencing approach can be used to map an autosomal recessive disorder in the dog, with the use of genome sequencing to facilitate identification of a disease-associated variant

Searching for New Physics Through AMO Precision Measurements

We briefly review recent experiments in atomic, molecular, and optical physics using precision measurements to search for physics beyond the Standard Model. We consider three main categories of experiments: searches for changes in fundamental constants, measurements of the anomalous magnetic moment of the electron, and searches for an electric dipole moment of the electron.Comment: Prepared for Comments on AMO Physics at Physica Script

Operating theatre related syncope in medical students: a cross sectional study

<p>Abstract</p> <p>Background</p> <p>Observing surgical procedures is a beneficial educational experience for medical students during their surgical placements. Anecdotal evidence suggests that operating theatre related syncope may have detrimental effects on students' views of this. Our study examines the frequency and causes of such syncope, together with effects on career intentions, and practical steps to avoid its occurrence.</p> <p>Methods</p> <p>All penultimate and final year students at a large UK medical school were surveyed using the University IT system supplemented by personal approach. A 20-item anonymous questionnaire was distributed and results were analysed using the Statistical Package for Social Sciences, version 15.0 (Chicago, Illinois, USA).</p> <p>Results</p> <p>Of the 630 clinical students surveyed, 77 responded with details of at least one near or actual operating theatre syncope (12%). A statistically significant gender difference existed for syncopal/near-syncopal episodes (male 12%; female 88%), p < 0.05. Twenty-two percent of those affected were graduate entry medical course students with the remaining 78% undergraduate. Mean age was 23-years (range 20 – 45). Of the 77 reactors, 44 (57%) reported an intention to pursue a surgical career. Of this group, 7 (9%) reported being discouraged by syncopal episodes in the operating theatre. The most prevalent contributory factors were reported as hot temperature (n = 61, 79%), prolonged standing (n = 56, 73%), wearing a surgical mask (n = 36, 47%) and the smell of diathermy (n = 18, 23%). The most frequently reported measures that students found helpful in reducing the occurrence of syncopal episodes were eating and drinking prior to attending theatre (n = 47, 61%), and moving their legs whilst standing (n = 14, 18%).</p> <p>Conclusion</p> <p>Our study shows that operating theatre related syncope among medical students is common, and we establish useful risk factors and practical steps that have been used to prevent its occurrence. Our study also highlights the detrimental effect of this on the career intentions of medical students interested in surgery. Based on these findings, we recommend that dedicated time should be set aside in surgical teaching to address this issue prior to students attending the operating theatre.</p

The variational Bayesian approach to fitting mixture models to circular wave direction data

The emerging variational Bayesian (VB) technique for approximate Bayesian statistical inference is a nonsimulation- based and time-efficient approach. It provides a useful, practical alternative to other Bayesian statistical approaches such as Markov chain Monte Carlo–based techniques, particularly for applications involving large datasets. This article reviews the increasingly popular VB statistical approach and illustrates how it can be used to fit Gaussian mixture models to circular wave direction data. This is done by taking the straightforward approach of padding the data; this method involves adding a repeat of a complete cycle of the data to the existing dataset to obtain a dataset on the real line. The padded dataset can then be analyzed using the standard VB technique. This results in a practical, efficient approach that is also appropriate for modeling other types of circular, or directional, data such as wind direction