Megan Henderson and Gay Walkington in Wattle Dance Group, Christmas 1968

Megan Henderson and Gay Walkington in Wattle Dance Group, Christmas 1968. The Wattle Dance Group met every Saturday in the Trades Hall, Brisbane, Australia. They held an concert at the end of each year. Janet Henderson was the mainstay and taught along with a few others. Jean Leary was the pianist. She took over from Eva Bacon.

El Nino and arboviral disease prediction

Recent El Nino events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to Fl Nino. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.

Quantum error correction for continuously detected errors

We show that quantum feedback control can be used as a quantum-error-correction process for errors induced by a weak continuous measurement. In particular, when the error model is restricted to one, perfectly measured, error channel per physical qubit, quantum feedback can act to perfectly protect a stabilizer codespace. Using the stabilizer formalism we derive an explicit scheme, involving feedback and an additional constant Hamiltonian, to protect an (n-1)-qubit logical state encoded in n physical qubits. This works for both Poisson (jump) and white-noise (diffusion) measurement processes. Universal quantum computation is also possible in this scheme. As an example, we show that detected-spontaneous emission error correction with a driving Hamiltonian can greatly reduce the amount of redundancy required to protect a state from that which has been previously postulated [e.g., Alber , Phys. Rev. Lett. 86, 4402 (2001)].

Millennial and orbital variations of El Nino/Southern Oscillation and high-latitude climate in the last glacial period

The El Nino/Southern Oscillation (ENSO) phenomenon is believed to have operated continuously over the last glacial interglacial cycle(1). ENSO variability has been suggested to be linked to millennial-scale oscillations in North Atlantic climate during that time(2,3), but the proposals disagree on whether increased frequency of El Nino events, the warm phase of ENSO, was linked to North Atlantic warm or cold periods. Here we present a high-resolution record of surface moisture, based on the degree of peat humification and the ratio of sedges to grass, from northern Queensland, Australia, covering the past 45,000 yr. We observe millennial-scale dry periods, indicating periods of frequent El Nino events ( summer precipitation declines in El Nino years in northeastern Australia). We find that these dry periods are correlated to the Dansgaard - Oeschger events - millennial-scale warm events in the North Atlantic climate record - although no direct atmospheric connection from the North Atlantic to our site can be invoked. Additionally, we find climatic cycles at a semiprecessional timescale (, 11,900 yr). We suggest that climate variations in the tropical Pacific Ocean on millennial as well as orbital timescales, which determined precipitation in northeastern Australia, also exerted an influence on North Atlantic climate through atmospheric and oceanic teleconnections.

Bayesian analysis of the error correction model

This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.