Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Dependence of the crossover exponent with the diffusion rate in the generalized contact process model

We study how the crossover exponent, phi, between the directed percolation (DP) and compact directed percolation (CDP) behaves as a function of the diffusion rate in a model that generalizes the contact process. Our conclusions are based in results pointed by perturbative series expansions and numerical simulations, and are consistent with a value phi = 2 for finite diffusion rates and phi = 1 in the limit of infinite diffusion rate.

The Rg1 allele as a valuable tool for genetic transformation of the tomato 'Micro-Tom' model system

Background: The cultivar Micro-Tom (MT) is regarded as a model system for tomato genetics due to its short life cycle and miniature size. However, efforts to improve tomato genetic transformation have led to protocols dependent on the costly hormone zeatin, combined with an excessive number of steps. Results: Here we report the development of a MT near-isogenic genotype harboring the allele Rg1 (MT-Rg1), which greatly improves tomato in vitro regeneration. Regeneration was further improved in MT by including a two-day incubation of cotyledonary explants onto medium containing 0.4 mu M 1-naphthaleneacetic acid (NAA) before cytokinin treatment. Both strategies allowed the use of 5 mu M 6-benzylaminopurine (BAP), a cytokinin 100 times less expensive than zeatin. The use of MT-Rg1 and NAA pre-incubation, followed by BAP regeneration, resulted in high transformation frequencies (near 40%), in a shorter protocol with fewer steps, spanning approximately 40 days from Agrobacterium infection to transgenic plant acclimatization. Conclusions: The genetic resource and the protocol presented here represent invaluable tools for routine gene expression manipulation and high throughput functional genomics by insertional mutagenesis in tomato.

Phase transformation and residual stress probed by Raman spectroscopy in diamond-turned single crystal silicon

Single-point diamond turning of monocrystalline semiconductors is an important field of research within brittle materials machining. Monocrystalline silicon samples with a (100) orientation have been diamond turned under different cutting conditions (feed rate and depth of cut). Micro-Raman spectroscopy and atomic force microscopy have been used to assess structural alterations and surface finish of the samples diamond turned under ductile and brittle modes. It was found that silicon undergoes a phase transformation when machined in the ductile mode. This phase transformation is evidenced by the creation of an amorphous surface layer after machining which has been probed by Raman scattering. Compressive residual stresses are estimated for the machined surface and it is observed that they decrease with an increase in the feed rate and depth of cut. This behaviour has been attributed to the formation of subsurface cracks when the feed rate is higher than or equal to 2.5 mu m/rev. The surface roughness was observed to vary with the feed rate and the depth of cut. An increase in the surface roughness was influenced by microcrack formation when the feed rate reached 5.0 mu m/rev. Furthermore, a high-pressure phase transformation induced by the tool/material interaction and responsible for the ductile response of this typical brittle material is discussed based upon the presented Raman spectra. The application of this machining technology finds use for a wide range of high quality components, for example the creation of a micrometre-range channel for microfluidic devices as well as microlenses used in the infrared spectrum range.

Anticariogenic Properties of ent-Pimarane Diterpenes Obtained by Microbial Transformation

In the present work, the anticariogenic activities of three pimarane-type diterpenes obtained by fungal biotransformation were investigated. Among these metabolites, ent-8(14), 15-pimaradien-19-ol was the most active compound, displaying very promising MIC values (ranging from 1.5 to 4.0 mu g mL(-1)) against the main microorganisms responsible for dental caries: Streptococcus salivarius, S. sobrinus, S. mutans, S. mitis, S. sanguinis, and Lactobacillus casei. Time kill assays performed with ent-8(14), 15-pimaradien-19-ol against the primary causative agent S. mutans revealed that this compound only avoids growth of the inoculum in the first 12 h (bacteriostatic effect). However, its bactericidal effect is clearly noted thereafter (between 12 and 24 h). The curve profile obtained by combining ent-8(14), 15-pimaradien-19-ol and chlorhexidine revealed a significant reduction in the time necessary for killing S. mutans compared with each of these two chemicals alone. However, no synergistic effect was observed using the same combination in the checkerboard assays against this microorganism. In conclusion, our results point out that ent-8(14), 15-pimaradien-19-ol is an important metabolite in the search for new effective anticariogenic agents.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Generalized Sznajd model for opinion propagation

In the last decade the Sznajd model has been successfully employed in modeling some properties and scale features of both proportional and majority elections. We propose a version of the Sznajd model with a generalized bounded confidence rule-a rule that limits the convincing capability of agents and that is essential to allow coexistence of opinions in the stationary state. With an appropriate choice of parameters it can be reduced to previous models. We solved this model both in a mean-field approach (for an arbitrary number of opinions) and numerically in a Barabaacutesi-Albert network (for three and four opinions), studying the transient and the possible stationary states. We built the phase portrait for the special cases of three and four opinions, defining the attractors and their basins of attraction. Through this analysis, we were able to understand and explain discrepancies between mean-field and simulation results obtained in previous works for the usual Sznajd model with bounded confidence and three opinions. Both the dynamical system approach and our generalized bounded confidence rule are quite general and we think it can be useful to the understanding of other similar models.

Coexistence of interacting opinions in a generalized Sznajd model

The Sznajd model is a sociophysics model that mimics the propagation of opinions in a closed society, where the interactions favor groups of agreeing people. It is based in the Ising and Potts ferromagnetic models and, although the original model used only linear chains, it has since been adapted to general networks. This model has a very rich transient, which has been used to model several aspects of elections, but its stationary states are always consensus states. In order to model more complex behaviors, we have, in a recent work, introduced the idea of biases and prejudices to the Sznajd model by generalizing the bounded confidence rule, which is common to many continuous opinion models, to what we called confidence rules. In that work we have found that the mean field version of this model (corresponding to a complete network) allows for stationary states where noninteracting opinions survive, but never for the coexistence of interacting opinions. In the present work, we provide networks that allow for the coexistence of interacting opinions for certain confidence rules. Moreover, we show that the model does not become inactive; that is, the opinions keep changing, even in the stationary regime. This is an important result in the context of understanding how a rule that breeds local conformity is still able to sustain global diversity while avoiding a frozen stationary state. We also provide results that give some insights on how this behavior approaches the mean field behavior as the networks are changed.

Nonempirical hyper-generalized-gradient functionals constructed from the Lieb-Oxford bound

A simple and completely general representation of the exact exchange-correlation functional of density-functional theory is derived from the universal Lieb-Oxford bound, which holds for any Coulomb-interacting system. This representation leads to an alternative point of view on popular hybrid functionals, providing a rationale for why they work and how they can be constructed. A similar representation of the exact correlation functional allows to construct fully nonempirical hyper-generalized-gradient approximations (HGGAs), radically departing from established paradigms of functional construction. Numerical tests of these HGGAs for atomic and molecular correlation energies and molecular atomization energies show that even simple HGGAs match or outperform state-of-the-art correlation functionals currently used in solid-state physics and quantum chemistry.

Multiclass Hammersley-Aldous-Diaconis process and multiclass-customer queues

In the Hammersley-Aldous-Diaconis process, infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x, whose nearest neighbor to the right is at y, jumps at rate y - x to a position uniformly distributed in the interval (x, y). The basic coupling between trajectories with different initial configuration induces a process with different classes of particles. We show that the invariant measures for the two-class process can be obtained as follows. First, a stationary M/M/1 queue is constructed as a function of two homogeneous Poisson processes, the arrivals with rate, and the (attempted) services with rate rho > lambda Then put first class particles at the instants of departures (effective services) and second class particles at the instants of unused services. The procedure is generalized for the n-class case by using n - 1 queues in tandem with n - 1 priority types of customers. A multi-line process is introduced; it consists of a coupling (different from Liggett's basic coupling), having as invariant measure the product of Poisson processes. The definition of the multi-line process involves the dual points of the space-time Poisson process used in the graphical construction of the reversed process. The coupled process is a transformation of the multi-line process and its invariant measure is the transformation described above of the product measure.

Relevance of extractives and wood transformation products on the biodegradation of Pinus taeda by Ceriporiopsis subvermispora

Ceriporiopsis subvermispora is a promising white-rot fungus for biopulping. However, the underlying biochemistry involved in lignin removal and insignificant cellulose degradation by this species is not completely understood. This paper addresses this topic focusing on the involvement of ethanol-soluble extractives and wood transformation products in the biodegradation process. Cultures containing ethanol-extracted or in natura wood chips presented similar levels of extracellular enzymes and degradation of wood components. Fe3+-reducing compounds present in undecayed Pinus taeda were rapidly diminished by fungal degradation. Lignin-degradation products released during biodegradation restored part of the Fe3+-reducing activity. However, Fe3+ reduction was ineffective in presence of 0.5 mM oxalate at pH 4.5. Fungal consumption of Fe3+-reducing compounds and secretion of oxalic acid minimized the significance of Fenton`s reaction in the initial stages of wood biotreatment. This would explain limited polysaccharide degradation by the fungus that also lacks a complete set of hydrolytic enzymes. Scientific relevance of the paper: Ceriporiopsis subvermispora is a white-rot fungus suitable for biopulping processes because it degrades lignin selectively and causes significant structural changes on the wood components during the earlier decay stages. However, the intricate mechanism to explain lignin transformation and insignificant cellulose degradation by this species remains poorly understood. Some recent evidences pointed out for lipid peroxidation reactions as all initiating process explaining lignin degradation. On the other hand, alkylitaconic acids produced by the fungus via transformations of fatty acids occurring in wood showed to prevent polysaccharide degradation in Fenton reactions. In this context, one may conclude that the involvement of native wood substances or their transformation products in the overall wood biodegradation process induced by C subvermispora is still a matter of discussion. While free and esterified fatty acids present in wood extractives may be involved in the biosynthesis of alkylitaconic acids and in lipid peroxidation reactions, some extractives and lignin degradation products can reduce Fe3+, providing Fe2+ species needed to form OH radical via Fenton`s reaction. The present study focuses on this topic by evaluating the relevance of ethanol-soluble extractives and wood transformation products on the biodegradation of P. taeda by C subvermispora. For this, solid-state cultures containing ethanol-extracted and in natura wood chips were evaluated in details for up to 4 weeks. (C) 2007 Elsevier Ltd. All rights reserved.

GENERALIZED FINITE ELEMENT METHOD FOR NONLINEAR THREE-DIMENSIONAL ANALYSIS OF SOLIDS

The Generalized Finite Element Method (GFEM) is employed in this paper for the numerical analysis of three-dimensional solids tinder nonlinear behavior. A brief summary of the GFEM as well as a description of the formulation of the hexahedral element based oil the proposed enrichment strategy are initially presented. Next, in order to introduce the nonlinear analysis of solids, two constitutive models are briefly reviewed: Lemaitre`s model, in which damage and plasticity are coupled, and Mazars`s damage model suitable for concrete tinder increased loading. Both models are employed in the framework of a nonlocal approach to ensure solution objectivity. In the numerical analyses carried out, a selective enrichment of approximation at regions of concern in the domain (mainly those with high strain and damage gradients) is exploited. Such a possibility makes the three-dimensional analysis less expensive and practicable since re-meshing resources, characteristic of h-adaptivity, can be minimized. Moreover, a combination of three-dimensional analysis and the selective enrichment presents a valuable good tool for a better description of both damage and plastic strain scatterings.

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.