World-making with extended gravity black holes for cosmic natural selection in the multiverse scenario

Physics is facing contingency. Not only in facts but also in laws (the frontier becoming extremely narrow). Cosmic natural selection is a tantalizing idea to explain the apparently highly improbable structure of our Universe. In this brief note I will study the creation of Universes by black holes in -string inspired- higher order curvature gravity.Comment: 5 pages, 1 figure. Proceedings of the Eleventh Marcel Grossmann Meeting on General Relativity, edited by H. Kleinert, R.T. Jantzen and R. Ruffini, World Scientific, Singapore, 200

Model selection in regression under structural constraints

The paper considers model selection in regression under the additional structural constraints on admissible models where the number of potential predictors might be even larger than the available sample size. We develop a Bayesian formalism as a natural tool for generating a wide class of model selection criteria based on penalized least squares estimation with various complexity penalties associated with a prior on a model size. The resulting criteria are adaptive to structural constraints. We establish the upper bound for the quadratic risk of the resulting MAP estimator and the corresponding lower bound for the minimax risk over a set of admissible models of a given size. We then specify the class of priors (and, therefore, the class of complexity penalties) where for the "nearly-orthogonal" design the MAP estimator is asymptotically at least nearly-minimax (up to a log-factor) simultaneously over an entire range of sparse and dense setups. Moreover, when the numbers of admissible models are "small" (e.g., ordered variable selection) or, on the opposite, for the case of complete variable selection, the proposed estimator achieves the exact minimax rates.Comment: arXiv admin note: text overlap with arXiv:0912.438

Adaptive Fitness Landscape for Replicator Systems: To Maximize or not to Maximize

Sewall Wright's adaptive landscape metaphor penetrates a significant part of evolutionary thinking. Supplemented with Fisher's fundamental theorem of natural selection and Kimura's maximum principle, it provides a unifying and intuitive representation of the evolutionary process under the influence of natural selection as the hill climbing on the surface of mean population fitness. On the other hand, it is also well known that for many more or less realistic mathematical models this picture is a sever misrepresentation of what actually occurs. Therefore, we are faced with two questions. First, it is important to identify the cases in which adaptive landscape metaphor actually holds exactly in the models, that is, to identify the conditions under which system's dynamics coincides with the process of searching for a (local) fitness maximum. Second, even if the mean fitness is not maximized in the process of evolution, it is still important to understand the structure of the mean fitness manifold and see the implications of this structure on the system's dynamics. Using as a basic model the classical replicator equation, in this note we attempt to answer these two questions and illustrate our results with simple well studied systems.Comment: 13 pages, 4 figure

Genetic Evolution and Molecular Selection of the HE Gene of Influenza C Virus

Influenza C virus (ICV) was first identified in humans and swine, but recently also in cattle, indicating a wider host range and potential threat to both the livestock industry and public health than was originally anticipated. The ICV hemagglutinin-esterase (HE) glycoprotein has multiple functions in the viral replication cycle and is the major determinant of antigenicity. Here, we developed a comparative approach integrating genetics, molecular selection analysis, and structural biology to identify the codon usage and adaptive evolution of ICV. We show that ICV can be classified into six lineages, consistent with previous studies. The HE gene has a low codon usage bias, which may facilitate ICV replication by reducing competition during evolution. Natural selection, dinucleotide composition, and mutation pressure shape the codon usage patterns of the ICV HE gene, with natural selection being the most important factor. Codon adaptation index (CAI) and relative codon deoptimization index (RCDI) analysis revealed that the greatest adaption of ICV was to humans, followed by cattle and swine. Additionally, similarity index (SiD) analysis revealed that swine exerted a stronger evolutionary pressure on ICV than humans, which is considered the primary reservoir. Furthermore, a similar tendency was also observed in the M gene. Of note, we found HE residues 176, 194, and 198 to be under positive selection, which may be the result of escape from antibody responses. Our study provides useful information on the genetic evolution of ICV from a new perspective that can help devise prevention and control strategies

Statistical methods for cricket team selection : a thesis presented in partial fulfilment of the requirement of the degree of Master of Applied Statistics at Massey University

Cricket generates a large amount of data for both batsmen and bowlers. Methods for using this data to select a cricket team are examined. Utilising the assumption that an individual's natural ability is expressed via performance outputs, this thesis seeks to describe and understand the underlying statistical processes of player performance. Randomness is tested for and then the distributional properties of the data are sought. This information is then used to monitor the estimate of natural ability via widely accepted control methods, such as Shewhart control charts, CUSUM, EWMA and multivariate versions of these procedures. To accommodate the distribution presented by batting scores, a new control chart based on quartiles is also studied. Further, ranking and selection procedures employ the estimates of individual ability to select the best individuals and note the probability of correct selection. Major contributions of this study include: a) Development of performance measures for cricket b) 2 - Dimensional runs test, with further applicability outside cricket. c) Statistical interpretation specific to cricket • Outliers are very important • Form is autocorrelation • Zone rules for cricket needed to detect good/poor performance • Relatively short nominal ARL's d) Control Chart based on quantiles to preserve outlier influences in a non-parametric procedure. e) The recommendation of appropriate tools for monitoring batting, bowling and all-rounder performance and also choosing man of the match. f) Discriminates between different types of bowlers using the consistency of their performance measures. g) Evaluates the members of a team relative to potential contenders

The technology and cost structure of a natural gas pipeline: Insights for costs and rate-of-return regulation

This note details a complete microeconomic characterization of the physical relationships between input use and the level of output of a simple point-to-point gas pipeline system and uses it to contribute to the public policy discussions pertaining to the economic regulation of natural gas pipelines. We show that the engineering equations governing the design and operations of that infrastructure can be approximated by a single production equation of the Cobb-Douglas type. We use that result to inform three public policy debates. First, we prove that the long-run cost function of the infrastructure formally verifies the condition for a natural monopoly, thereby justifying the need of regulatory intervention in that industry. Second, we examine the conditions for cost-recovery in the short-run and contribute to the emerging European discussions on the implementation of short-run marginal cost pricing on interconnector pipelines. Lastly, we analyze the performance of rate-of-return regulation in that industry and inform the regulatory policy debates on the selection of an appropriate authorized rate of return. We highlight that, contrary to popular belief, the socially desirable rate of return can be larger than the market price of capital for that industry

A complex adaptive systems approach to the kinetic folding of RNA

The kinetic folding of RNA sequences into secondary structures is modeled as a complex adaptive system, the components of which are possible RNA structural rearrangements (SRs) and their associated bases and base pairs. RNA bases and base pairs engage in local stacking interactions that determine the probabilities (or fitnesses) of possible SRs. Meanwhile, selection operates at the level of SRs; an autonomous stochastic process periodically (i.e., from one time step to another) selects a subset of possible SRs for realization based on the fitnesses of the SRs. Using examples based on selected natural and synthetic RNAs, the model is shown to qualitatively reproduce characteristic (nonlinear) RNA folding dynamics such as the attainment by RNAs of alternative stable states. Possible applications of the model to the analysis of properties of fitness landscapes, and of the RNA sequence to structure mapping are discussed.Comment: 23 pages, 4 figures, 2 tables, to be published in BioSystems (Note: updated 2 references