Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

Quantifying urban attractiveness from the distribution and density of digital footprints

In the past, sensors networks in cities have been limited to fixed sensors, embedded in particular locations, under centralised control. Today, new applications can leverage wireless devices and use them as sensors to create aggregated information. In this paper, we show that the emerging patterns unveiled through the analysis of large sets of aggregated digital footprints can provide novel insights into how people experience the city and into some of the drivers behind these emerging patterns. We particularly explore the capacity to quantify the evolution of the attractiveness of urban space with a case study of in the area of the New York City Waterfalls, a public art project of four man-made waterfalls rising from the New York Harbor. Methods to study the impact of an event of this nature are traditionally based on the collection of static information such as surveys and ticket-based people counts, which allow to generate estimates about visitors’ presence in specific areas over time. In contrast, our contribution makes use of the dynamic data that visitors generate, such as the density and distribution of aggregate phone calls and photos taken in different areas of interest and over time. Our analysis provides novel ways to quantify the impact of a public event on the distribution of visitors and on the evolution of the attractiveness of the points of interest in proximity. This information has potential uses for local authorities, researchers, as well as service providers such as mobile network operators.

How do coil configuration and packing density influence intra-aneurysmal hemodynamics?

Endovascular coiling is a well-established therapy for treating intracranial aneurysms. Nonetheless, postoperative hemodynamic changes induced by this therapy remain not fully understood. The purpose of this work is to assess the influence of coil configuration and packing density on intra-aneurysmal hemodynamics

Low-density parity-check codes for nonergodic block-fading channels

We design powerful low-density parity-check (LDPC) codes with iterative decoding for the block-fading channel. We first study the case of maximum-likelihood decoding, and show that the design criterion is rather straightforward. Since optimal constructions for maximum-likelihood decoding do not performwell under iterative decoding, we introduce a new family of full-diversity LDPC codes that exhibit near-outage-limit performance under iterative decoding for all block-lengths. This family competes favorably with multiplexed parallel turbo codes for nonergodic channels.

Generalized low-density codes with BCH constituents for full-diversity near-outage performance

A new graph-based construction of generalized low density codes (GLD-Tanner) with binary BCH constituents is described. The proposed family of GLD codes is optimal on block erasure channels and quasi-optimal on block fading channels. Optimality is considered in the outage probability sense. Aclassical GLD code for ergodic channels (e.g., the AWGN channel,the i.i.d. Rayleigh fading channel, and the i.i.d. binary erasure channel) is built by connecting bitnodes and subcode nodes via a unique random edge permutation. In the proposed construction of full-diversity GLD codes (referred to as root GLD), bitnodes are divided into 4 classes, subcodes are divided into 2 classes, and finally both sides of the Tanner graph are linked via 4 random edge permutations. The study focuses on non-ergodic channels with two states and can be easily extended to channels with 3 states or more.

Testing for convergence clubs in income per-capita: A predictive density approach

The paper proposes a technique to jointly test for groupings of unknown size in the cross sectional dimension of a panel and estimates the parameters of each group, and applies it to identifying convergence clubs in income per-capita. The approach uses the predictive density of the data, conditional on the parameters of the model. The steady state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of incomeper-capita of OECD countries has two poles of attraction and each grouphas clearly identifiable economic characteristics.

Asymptotic behaviour of the density in a parabolic SPDE

Consider the density of the solution $X(t,x)$ of a stochastic heat equation with small noise at a fixed $t\in [0,T]$, $x \in [0,1]$.In the paper we study the asymptotics of this density as the noise is vanishing. A kind of Taylor expansion in powers of the noiseparameter is obtained. The coefficients and the residue of the expansion are explicitly calculated.In order to obtain this result some type of exponential estimates of tail probabilities of the difference between the approximatingprocess and the limit one is proved. Also a suitable local integration by parts formula is developped.

Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

PENELOPE-2008: A Code System for Monte Carlo Simulation of Electron and Photon Transport

The computer code system PENELOPE (version 2008) performs Monte Carlo simulation of coupledelectron-photon transport in arbitrary materials for a wide energy range, from a few hundred eV toabout 1 GeV. Photon transport is simulated by means of the standard, detailed simulation scheme.Electron and positron histories are generated on the basis of a mixed procedure, which combinesdetailed simulation of hard events with condensed simulation of soft interactions. A geometry packagecalled PENGEOM permits the generation of random electron-photon showers in material systemsconsisting of homogeneous bodies limited by quadric surfaces, i.e., planes, spheres, cylinders, etc. Thisreport is intended not only to serve as a manual of the PENELOPE code system, but also to provide theuser with the necessary information to understand the details of the Monte Carlo algorithm.

Changes in the enterocyte cytoskeleton in newborn rats exposed to ethanol in utero

BACKGROUND: Cytoskeletal changes after longterm exposure to ethanol have been described in a number of cell types in adult rat and humans. These changes can play a key part in the impairment of nutrient assimilation and postnatal growth retardation after prenatal damage of the intestinal epithelium produced by ethanol intake. AIMS: To determine, in the newborn rat, which cytoskeletal proteins are affected by longterm ethanol exposure in utero and to what extent. ANIMALS: The offspring of two experimental groups of female Wistar rats: ethanol treated group receiving up to 25% (w/v) of ethanol in the drinking fluid and control group receiving water as drinking fluid. METHODS: Single and double electron microscopy immunolocalisation and label density estimation of cytoskeletal proteins on sections of proximal small intestine incubated with monoclonal antibodies against actin, alpha-tubulin, cytokeratin (polypeptides 1, 5, 6, 7, 8, 10, 11, and 18), and with a polyclonal antibody anti-beta 1,4-galactosyl transferase as trans golgi (TG) or trans golgi network (TGN) marker, or both. SDS-PAGE technique was also performed on cytoskeletal enriched fractions from small intestine. Western blotting analysis was carried out by incubation with the same antibodies used for immunolocalisation. RESULTS: Intestinal epithelium of newborn rats from the ethanol treated group showed an overexpression of cytoskeletal polypeptides ranging from 39 to 54 kDa, affecting actin and some cytokeratins, but not tubulin. Furthermore, a cytokeratin related polypeptide of 28-29 kDa was identified together with an increase in free ubiquitin in the same group. It was noteworthy that actin and cytokeratin were abnormally located in the TG or the TGN, or both. CONCLUSIONS: Longterm exposure to ethanol in utero causes severe dysfunction in the cytoskeleton of the developing intestinal epithelium. Actin and cytokeratins, which are involved in cytoskeleton anchoring to plasma membrane and cell adhesion, are particularly affected, showing overexpression, impaired proteolysis, and mislocalisation.

Changes in the enterocyte cytoskeleton in newborn rats exposed to ethanol in utero

BACKGROUND: Cytoskeletal changes after longterm exposure to ethanol have been described in a number of cell types in adult rat and humans. These changes can play a key part in the impairment of nutrient assimilation and postnatal growth retardation after prenatal damage of the intestinal epithelium produced by ethanol intake. AIMS: To determine, in the newborn rat, which cytoskeletal proteins are affected by longterm ethanol exposure in utero and to what extent. ANIMALS: The offspring of two experimental groups of female Wistar rats: ethanol treated group receiving up to 25% (w/v) of ethanol in the drinking fluid and control group receiving water as drinking fluid. METHODS: Single and double electron microscopy immunolocalisation and label density estimation of cytoskeletal proteins on sections of proximal small intestine incubated with monoclonal antibodies against actin, alpha-tubulin, cytokeratin (polypeptides 1, 5, 6, 7, 8, 10, 11, and 18), and with a polyclonal antibody anti-beta 1,4-galactosyl transferase as trans golgi (TG) or trans golgi network (TGN) marker, or both. SDS-PAGE technique was also performed on cytoskeletal enriched fractions from small intestine. Western blotting analysis was carried out by incubation with the same antibodies used for immunolocalisation. RESULTS: Intestinal epithelium of newborn rats from the ethanol treated group showed an overexpression of cytoskeletal polypeptides ranging from 39 to 54 kDa, affecting actin and some cytokeratins, but not tubulin. Furthermore, a cytokeratin related polypeptide of 28-29 kDa was identified together with an increase in free ubiquitin in the same group. It was noteworthy that actin and cytokeratin were abnormally located in the TG or the TGN, or both. CONCLUSIONS: Longterm exposure to ethanol in utero causes severe dysfunction in the cytoskeleton of the developing intestinal epithelium. Actin and cytokeratins, which are involved in cytoskeleton anchoring to plasma membrane and cell adhesion, are particularly affected, showing overexpression, impaired proteolysis, and mislocalisation.