Controller and Auditor-General v Davison: Three Comments

This article is a case note of Controller and Auditor-General v Davison CA 226/95, 16 February 1996. The case involved an application for judicial review of an order by the "Winebox" Commission of Inquiry to the Audit Office and KPMG Peat Marwick to produce documents relating to their functions as Government Auditor of the Cook Islands. The three authors make comments about the case and its impact on private international law, noting in particular the doctrine of sovereign immunity. *NOTE: a French version summary is provided at 476

Living with an Archaic Treaty: Solving the Problem of the Warsaw Convention's Gold Clause

Article 22 of the Warsaw Convention for the Unification of Certain Rules Relating to International Carriage By Air limits carriers' liability by reference to the franc Poincaré or gold franc, a standard that no longer exists. Until the Montreal Protocols come into force or a revised and consolidated Convention is created, the author proposes a method that relies on cooperation between the executive and the courts to keep Article 22 alive and useful

An Exonic Splicing Enhancer within a Bidirectional Coding Sequence Regulates Alternative Splicing of an Antisense mRNA

The discovery of increasing numbers of genes with overlapping sequences highlights the problem of expression in the context of constraining regulatory elements from more than one gene. This study identifies regulatory sequences encompassed within two genes that overlap in an antisense orientation at their 3’ ends. The genes encode the α-thyroid hormone receptor gene (TRα or NR1A1) and Rev-erbα (NR1D1). In mammals TRα pre-mRNAs are alternatively spliced to yield mRNAs encoding functionally antagonistic proteins: TRα1, an authentic thyroid hormone receptor; and TRα2, a non-hormone-binding variant that acts as a repressor. TRα2-specific splicing requires two regulatory elements that overlap with Rev-erbα sequences. Functional mapping of these elements reveals minimal splicing enhancer elements that have evolved within the constraints of the overlapping Rev-erbα sequence. These results provide insight into the evolution of regulatory elements within the context of bidirectional coding sequences. They also demonstrate the ability of the genetic code to accommodate multiple layers of information within a given sequence, an important property of the code recently suggested on theoretical grounds

Biased Metropolis-Heat-Bath Algorithm for Fundamental-Adjoint SU(2) Lattice Gauge Theory

For SU(2) lattice gauge theory with the fundamental-adjoint action an efficient heat-bath algorithm is not known so that one had to rely on Metropolis simulations supplemented by overrelaxation. Implementing a novel biased Metropolis-heat-bath algorithm for this model, we find improvement factors in the range 1.45 to 2.06 over conventionally optimized Metropolis simulations. If one optimizes further with respect to additional overrelaxation sweeps, the improvement factors are found in the range 1.3 to 1.8.Comment: 4 pages, 2 figures; minor changes and one reference added; accepted for publication in PR

Bayesian inference with an adaptive proposal density for GARCH models

We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adaptive proposal density. The adaptive proposal density is assumed to be the Student's t-distribution and the distribution parameters are evaluated by using the data sampled during the simulation. We apply the method for the QGARCH model which is one of asymmetric GARCH models and make empirical studies for for Nikkei 225, DAX and Hang indexes. We find that autocorrelation times from our method are very small, thus the method is very efficient for generating uncorrelated Monte Carlo data. The results from the QGARCH model show that all the three indexes show the leverage effect, i.e. the volatility is high after negative observations

The statistical mechanics of complex signaling networks : nerve growth factor signaling

It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made to experimentally measure the rate constants for individual steps in these signaling networks, many of the parameters required to describe the behavior of these systems remain unknown, or at best, estimates. With these goals and caveats in mind, we use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. To establish the usefulness of our approach, we have applied our methods towards modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. Using our approach, we are able to extract predictions that are highly specific and accurate, thereby enabling us to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. We show that extracting biologically relevant predictions from complex signaling models appears to be possible even in the absence of measurements of all the individual rate constants. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems wherein particular ''soft'' combinations of parameters can be varied over wide ranges without impacting the final output and demonstrating that a few ''stiff'' parameter combinations center around the paramount regulatory steps of the network. We refer to this property -- which is distinct from robustness -- as ''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption for GIF), IOP style; supp. info/figs. included as brown_supp.pd

LISA Data Analysis using MCMC methods

The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analyses and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we super-cool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.Comment: 14 pages, 7 figure

Projective Ribbon Permutation Statistics: a Remnant of non-Abelian Braiding in Higher Dimensions

In a recent paper, Teo and Kane proposed a 3D model in which the defects support Majorana fermion zero modes. They argued that exchanging and twisting these defects would implement a set R of unitary transformations on the zero mode Hilbert space which is a 'ghostly' recollection of the action of the braid group on Ising anyons in 2D. In this paper, we find the group T_{2n} which governs the statistics of these defects by analyzing the topology of the space K_{2n} of configurations of 2n defects in a slowly spatially-varying gapped free fermion Hamiltonian: T_{2n}\equiv {\pi_1}(K_{2n})$. We find that the group T_{2n}= Z \times T^r_{2n}, where the 'ribbon permutation group' T^r_{2n} is a mild enhancement of the permutation group S_{2n}: T^r_{2n} \equiv \Z_2 \times E((Z_2)^{2n}\rtimes S_{2n}). Here, E((Z_2)^{2n}\rtimes S_{2n}) is the 'even part' of (Z_2)^{2n} \rtimes S_{2n}, namely those elements for which the total parity of the element in (Z_2)^{2n} added to the parity of the permutation is even. Surprisingly, R is only a projective representation of T_{2n}, a possibility proposed by Wilczek. Thus, Teo and Kane's defects realize `Projective Ribbon Permutation Statistics', which we show to be consistent with locality. We extend this phenomenon to other dimensions, co-dimensions, and symmetry classes. Since it is an essential input for our calculation, we review the topological classification of gapped free fermion systems and its relation to Bott periodicity.Comment: Missing figures added. Fixed some typos. Added a paragraph to the conclusio