Revised age estimate of the Mjauvotn tephra A on the Faroe Islands based on Bayesian modelling of C-14 dates from two lake sequences

Tephra horizons are potentially perfect time markers for dating and cross-correlation among diverse Holocene palaeoenvironmental records such as ice cores and marine and terrestrial sequences, but we need to trust their age. Here we present a new age estimate of the Holocene Mjauvotn tephra A using accelerator mass spectrometry C-14 dates from two lakes on the Faroe Islands. With Bayesian age modelling it is dated to 6668-6533 cal. a BP (68.2% confidence interval) - significantly older and better constrained than the previous age. Copyright (C) 2010 John Wiley & Sons, Ltd.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Analysis of transduction in wastewater bacterial populations by targeting the phage-derived 16S rRNA gene sequences

Bacterial 16S rRNA genes transduced by bacteriophages were identified and analyzed in order to estimate the extent of the bacteriophage-mediated horizontal gene transfer in the wastewater environment. For this purpose, phage and bacterial DNA was isolated from the oxidation tank of a municipal wastewater treatment plant. Phylogenetic analysis of the 16S rRNA gene sequences cloned from a phage metagenome revealed that bacteriophages transduce genetic material in several major groups of bacteria. The groups identified were as follows: Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria, Actinomycetales and Firmicutes. Analysis of the 16S rRNA gene sequences in the total bacterial DNA from the same sample revealed that several bacterial groups found in the oxidation tank were not present in the phage metagenome (e.g. Deltaproteobacteria, Nitrospira, Planctomycetes and many Actinobacteria genera). These results suggest that transduction in a wastewater environment occurs in several bacterial groups; however, not all species are equally involved into this process. The data also showed that a number of distinctive bacterial strains participate in transduction-mediated gene transfer within identified bacterial groupings. Denaturing gradient gel electrophoresis analysis confirmed that profiles of the transduced 16S rRNA gene sequences and those present in the whole microbial community show significant differences.

Using simulation to assess cardiac first-responder schemes exhibiting stochastic and spatial complexities

A Monte-Carlo simulation-based model has been constructed to assess a public health scheme involving mobile-volunteer cardiac First-Responders. The scheme being assessed aims to improve survival of Sudden-Cardiac-Arrest (SCA) patients, through reducing the time until administration of life-saving defibrillation treatment, with volunteers being paged to respond to possible SCA incidents alongside the Emergency Medical Services. The need for a model, for example, to assess the impact of the scheme in different geographical regions, was apparent upon collection of observational trial data (given it exhibited stochastic and spatial complexities). The simulation-based model developed has been validated and then used to assess the scheme's benefits in an alternative rural region (not a part of the original trial). These illustrative results conclude that the scheme may not be the most efficient use of National Health Service resources in this geographical region, thus demonstrating the importance and usefulness of simulation modelling in aiding decision making.

Extent and variation of phage-borne bacterial 16S rRNA gene sequences in wastewater environments

Phage metagenomes isolated from wastewater over a 12-month period were analyzed. The results suggested that various strains of Proteobacteria, Bacteroidetes, and other phyla are likely to participate in transduction. The patterns of 16S rRNA sequences found in phage metagenomes did not follow changes in the total bacterial community.

Stochastic Sznajd Model in open community

We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as "stochastic extension of the Sznajd model for an open community, because it allows for "special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B.