Leprosy and tuberculosis concomitant infection: a poorly understood, age-old relationship

Historically, archaeological evidence, post-mortem findings and retro- spective analysis of leprosy institutions’ data demonstrates a high observed incidence of concomitant infection with leprosy and tuberculosis (TB). However, reports of concomitant infection in the modern literature remain scarce, with estimates of annual new case detection rates of concomitant infection at approximately 0·02 cases per 100,000 population. Whilst the mechanism for this apparent decline in concomitant infections remains unclear, further research on this topic has remained relatively neglected. Modelling of the interaction of the two organisms has suggested that the apparent decline in observations of concomitant infection may be due to the protective effects of cross immunity, whilst more recently others have questioned whether it is a more harmful relationship, predisposing towards increased host mortality. We review recent evidence, comparing it to previously held understanding on the epidemiological relationship and our own experience of concomitant infection. From this discussion, we highlight several under-investigated areas, which may lead to improvements in the future delivery of leprosy management and services, as well as enhance understanding in other fields of infection management. These include, a) highlighting the need for greater understanding of host immunogenetics involved in concomitant infection, b) whether prolonged courses of high dose steroids pre-dispose to TB infection? and, c) whether there is a risk of rifampicin resistance developing in leprosy patients treated in the face of undiagnosed TB and other infections? Longitudinal work is still required to characterise these temporal relationships further and add to the current paucity of literature on this subject matter

Predicting Item Popularity: Analysing Local Clustering Behaviour of Users

Predicting the popularity of items in rating networks is an interesting but challenging problem. This is especially so when an item has first appeared and has received very few ratings. In this paper, we propose a novel approach to predicting the future popularity of new items in rating networks, defining a new bipartite clustering coefficient to predict the popularity of movies and stories in the MovieLens and Digg networks respectively. We show that the clustering behaviour of the first user who rates a new item gives insight into the future popularity of that item. Our method predicts, with a success rate of over 65% for the MovieLens network and over 50% for the Digg network, the future popularity of an item. This is a major improvement on current results.Comment: 25 pages, 11 figure

Identifying Influential Nodes in Bipartite Networks Using the Clustering Coefficient

The identification of influential nodes in complex network can be very challenging. If the network has a community structure, centrality measures may fail to identify the complete set of influential nodes, as the hubs and other central nodes of the network may lie inside only one community. Here we define a bipartite clustering coefficient that, by taking differently structured clusters into account, can find important nodes across communities

The Impact of Orography and Latent Heating on the Location of the Tropical Easterly Jet

The Tropical Easterly Jet (TEJ) is a prominent atmospheric circulation feature observed during the Asian Summer Monsoon. It is generally assumed that Tibet is an essential ingredient in determining the location of the TEJ. However studies have also suggested the importance of latent heating in determining the jet location. The relative importance of Tibetan orography and latent heating is explored through simulations with a general circulation model. The simulation of TEJ by the Community Atmosphere Model, version 3.1 (CAM-3.1) has been discussed in detail. Although the simulated TEJ replicated many observed features of the jet, the jet maximum was located too far to the west when compared to observation. The precipitation in the control simulation was high to the west of India and this caused the TEJ to shift westwards by approximately the same amount. Orography was found to have minimal impact on the simulated TEJ hence indicating that latent heating is the crucial parameter. The primacy of latent heating in determining the jet location was confirmed by additional simulations where the simulated precipitation was brought closer to observations. This made the TEJ to also shift to the correct position.Comment: 14 pages including 7 figures and 1 tabl

Prediction Weighted Maximum Frequency Selection

Shrinkage estimators that possess the ability to produce sparse solutions have become increasingly important to the analysis of today's complex datasets. Examples include the LASSO, the Elastic-Net and their adaptive counterparts. Estimation of penalty parameters still presents difficulties however. While variable selection consistent procedures have been developed, their finite sample performance can often be less than satisfactory. We develop a new strategy for variable selection using the adaptive LASSO and adaptive Elastic-Net estimators with $p_n$ diverging. The basic idea first involves using the trace paths of their LARS solutions to bootstrap estimates of maximum frequency (MF) models conditioned on dimension. Conditioning on dimension effectively mitigates overfitting, however to deal with underfitting, these MFs are then prediction-weighted, and it is shown that not only can consistent model selection be achieved, but that attractive convergence rates can as well, leading to excellent finite sample performance. Detailed numerical studies are carried out on both simulated and real datasets. Extensions to the class of generalized linear models are also detailed.Comment: This manuscript contains 41 pages and 14 figure

Spike and slab variable selection: Frequentist and Bayesian strategies

Variable selection in the linear regression model takes many apparent faces from both frequentist and Bayesian standpoints. In this paper we introduce a variable selection method referred to as a rescaled spike and slab model. We study the importance of prior hierarchical specifications and draw connections to frequentist generalized ridge regression estimation. Specifically, we study the usefulness of continuous bimodal priors to model hypervariance parameters, and the effect scaling has on the posterior mean through its relationship to penalization. Several model selection strategies, some frequentist and some Bayesian in nature, are developed and studied theoretically. We demonstrate the importance of selective shrinkage for effective variable selection in terms of risk misclassification, and show this is achieved using the posterior from a rescaled spike and slab model. We also show how to verify a procedure's ability to reduce model uncertainty in finite samples using a specialized forward selection strategy. Using this tool, we illustrate the effectiveness of rescaled spike and slab models in reducing model uncertainty.Comment: Published at http://dx.doi.org/10.1214/009053604000001147 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Tectonic evolution of greenstone-Gneiss association in Dharwar Craton, South India: Problems and perspectives for future research

The two fold stratigraphic subdivision of the Archean-Proterozoic greenstone-gneiss association of Dharwar craton into an older Sargur group (older than 2.9 Ga.) and a younger Dharwar Supergroup serves as an a priori stratigraphic model. The concordant greenstone (schist)-gneiss (Peninsular gneiss) relationships, ambiguities in stratigraphic correlations of the schist belts assigned to Sargur group and difficulties in deciphering the older gneiss units can be best appreciated if the Sargur group be regarded as a trimodal association of: (1) ultrabasic-mafic metavolcanics (including komatiites), (2) clastic and nonclastic metasediments and paragneisses and (3) mainly tonalite/trondhemite gneisses and migmatites of diverse ages which could be as old as c. 3.4 ga. or even older. The extensive occurrence of this greenstone-gneiss complex is evident from recent mapping in many areas of central and southern Karnataka State

Shaped cassegrain reflector antenna

Design equations are developed to compute the reflector surfaces required to produce uniform illumination on the main reflector of a cassegrain system when the feed pattern is specified. The final equations are somewhat simple and straightforward to solve (using a computer) compared to the ones which exist already in the literature. Step by step procedure for solving the design equations is discussed in detail

RFI emitter location techniques

The possibility is discussed of using Doppler techniques for determining the location of ground based emitters causing radio frequency interference with low orbiting satellites. An error analysis indicates that it is possible to find the emitter location within an error range of 2 n.mi. The parameters which determine the required satellite receiver characteristic are discussed briefly along with the non-real time signal processing which may by used in obtaining the Doppler curve. Finally, the required characteristics of the satellite antenna are analyzed

Near Infrared Spectroscopy Describes Physiologic Payback Associated With Excess Postexercise Oxygen Consumption in Healthy Controls and Children With Complex Congenital Heart Disease

Exercise creates a physiologic burden with recovery from such effort crucial to adaptation. Excess postexercise oxygen consumption (EPOC) refers to the body’s increased metabolic need after work. This investigation was designed to determine the role of near infrared spectroscopy (NIRS) in the description of exercise recovery in healthy controls (NL) and children with congenital heart disease (CHD). Subjects were recruited with exercise testing performed to exhaustion. Exercise time (EXT), heart rate (HR), and oxygen consumption (VO2) were measured. Four-site NIRS (brain, kidney, deltoid, and vastus lateralis) were measured during exercise and into recovery to establish trends. Fifty individuals were recruited for each group (NL = 26 boys and 24 girls; CHD = 33 boys and 17 girls). Significant differences existed between EXT, VO2, and peak HR (P \u3c 0.01). NIRS values were examined at four distinct intervals: rest, peak work, and 2 and 5 min after exercise. Significant cerebral hyperemia was seen in children with CHD post exercise when compared to normal individuals in whom redistribution patterns were directed to somatic muscles. These identified trends support an immediate compensation of organ systems to re-establish homeostasis in peripheral beds through enhanced perfusion. Noninvasive NIRS monitoring helps delineate patterns of redistribution associated with EPOC in healthy adolescents and children with CHD