Susceptible-infected-recovered and susceptible-exposed-infected models

Two stochastic epidemic lattice models, the susceptible-infected-recovered and the susceptible-exposed-infected models, are studied on a Cayley tree of coordination number k. The spreading of the disease in the former is found to occur when the infection probability b is larger than b(c) = k/2(k - 1). In the latter, which is equivalent to a dynamic site percolation model, the spreading occurs when the infection probability p is greater than p(c) = 1/(k - 1). We set up and solve the time evolution equations for both models and determine the final and time-dependent properties, including the epidemic curve. We show that the two models are closely related by revealing that their relevant properties are exactly mapped into each other when p = b/[k - (k - 1) b]. These include the cluster size distribution and the density of individuals of each type, quantities that have been determined in closed forms.

Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.

Evaluation of petrogenetic models for intermediate and silicic plutonic rocks from the Sierra de Valle Fertil-La Huerta, Argentina: Petrologic constraints on the origin of igneous rocks in the Ordovician Famatinian-Puna paleoarc

The whole Valle Fertil-La Huerta section appears as a calc-alkaline plutonic suite typical of a destructive plate margin. New Sr and Nd isotopic whole-rock data and published whole-rock geochemistry suggest that the less-evolved intermediate (dioritic) rocks can be derived by magmatic differentiation, mainly by hornblende + plagioclase +/- Fe-Ti oxide fractional crystallization, from mafic (gabbroic) igneous precursors. Closed-system differentiation, however, cannot produce the typical intermediate (tonalitic) and silicic (granodioritic) plutonic rocks, which requires a preponderant contribution of crustal components. Intermediate and silicic plutonic rocks from Valle Fertil-La Huerta section have formed in a plate subduction setting where the thermal and material input of mantle-derived magmas promoted fusion of fertile metasedimentary rocks and favored mixing of gabbroic or dioritic magmas with crustal granitic melts. Magma mixing is observable in the field and evident in variations of chemical elemental parameters and isotopic ratios, revealing that hybridization coupled with fractionation of magmas took place in the crust. Consideration of the whole-rock geochemical and isotopic data in the context of the Famatinian-Puna magmatic belt as a whole demonstrates that the petrologic model postulated for the Sierra Valle Fertil-La Huerta section has the potential to explain the generation of plutonic and volcanic rocks across the Early Ordovician paleoarc from central and northwestern Argentina. As the petrologic model does not require the intervention of old Precambrian continental crust, the nature of the basement on which thick accretionary turbiditic sequences were deposited remains a puzzling aspect. Discussion in this paper provides insights into the nature of magmatic source rocks and mechanisms of magma generation in Cordilleran-type volcano-plutonic arcs of destructive plate margins. (C) 2010 Elsevier Ltd. All rights reserved.

Evolution of a rift basin dominated by subaerial deposits: The Guaritas Rift, Early Cambrian, Southern Brazil

Most existing models for the evolution of rift basins predict the development of deep-water depositional systems during the stage of greatest tectonic subsidence, when accommodation generation potentially outpaces sedimentation. Despite this, some rift basins do not present deep-water systems, instead being dominated by subaerial deposits. This paper focuses on one of these particular rift basins, the Cambrian Guaritas Rift, Southern Brazil, characterized by more than 1500 m of alluvial and aeolian strata deposited in a 50-km-wide basin. The deposits of the Guaritas Rift can be ascribed to four depositional systems: basin-border alluvial fans, bedload-dominated ephemeral rivers, mixed-load ephemeral rivers and aeolian dune fields. These four systems are in part coeval and in part succeed each other, forming three stages of basin evolution: (i) Rift Initiation to Early Rift Climax stage, (ii) Mid to Late Rift Climax stage, and (iii) Early Post-Rift stage. The first stage comprises most of the Guaritas Group and is characterized by homogeneous bed-load-dominated river deposits, which do not clearly record the evolution of subsidence rates. The onset of sedimentation of finer-grained deposits occurred as a consequence of a reactivation event that changed the outline of the basin and the distribution of the nearby highlands. This strongly suggests that the capture of the main river system to another depression decreased the sediment supply to the basin. The study of the Guaritas Rift indicates that rift basins in which the sediment supply exceeds the accommodation generation occur as a consequence of moderate subsidence combined with the capture of a major river system to the basin during the initial stages of basin evolution. In these basins, changes in the average discharge of the river system or tectonic modification of the drainage network may be the major control on the stratigraphic architecture. (c) 2009 Published by Elsevier B.V.

ON AMINO ACID AND CODON ASSIGNMENT IN ALGEBRAIC MODELS FOR THE GENETIC CODE

We give a list of all possible schemes for performing amino acid and codon assignments in algebraic models for the genetic code, which are consistent with a few simple symmetry principles, in accordance with the spirit of the algebraic approach to the evolution of the genetic code proposed by Hornos and Hornos. Our results are complete in the sense of covering all the algebraic models that arise within this approach, whether based on Lie groups/Lie algebras, on Lie superalgebras or on finite groups.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.

Diabetes evolution in rats after neonatal treatment with alloxan

Physical exercises have been recommended in the prevention of non-insulin dependent diabetes mellitus (NIDDM), but the mechanisms involved in this intervention are not yet fully understood. Experimental models offer the opportunity for the study of this matter. The present study was designed to analyze the diabetes evolution in rats submitted to neonatal treatment with alloxan with the objective of verifying the suitability of the model to future studies with exercises. For this, newly born rats (6 days old) received intraperitoneal alloxan (A = 200 mg/kg of body weight). Rats injected with vehicle (citrate buffer) were used as controls (C). The fasting blood glucose level (mg/dL) was higher in the alloxan group at the day 28 (C=47.25 +/- 5.08; A=54.51 +/- 7.03) but not at the 60 day of age (C=69.18 +/- 8.31; A=66.81 +/- 6.08). The alloxan group presented higher blood glucose level during glucose tolerance test (GTT) (mg/dL. 120 min) in relation to the control group both at day 28 (C=16908.9 +/- 1078.8; A=21737,7 +/- 1106.4) and at day 60 (C=11463.45 +/- 655.30; A=15282.21 +/- 1221.84). Insulinaemia during GTT (ng/mL.120 min) was lower at day 28 (C=158.67 +/- 33.34; A=123.90 +/- 19.80), but presented no difference at day 60 (C=118.83 +/- 26.02; A=97.8 +/- 10.88). At day 60, the glycogen concentration in the soleus muscle (mg/100mg) was lower in the alloxan group (0.3 +/- 0.13) in relation to the control group (0.5 +/- 0.07). No difference was observed between groups in relation to (mu mol/g.h): Glucose Uptake (C = 5.8 +/- 0.63; A = 5.2 +/- 0.73); Glucose Oxidation (C= 4.3 +/- 1.13; A= 3.9 +/- 0.44); Glycogen Synthesis (C= 0.8 +/- 0.18; A= 0.7 +/- 0.18) and Lactate Production (C= 3.8 +/- 0.8; A= 3.8 0.7) by the isolated soleus muscle. The glucose-stimulated insulin secretion (16.7mM) by the isolated islets (ng/5 islets. h) of the alloxan group was lower (14.3 +/- 4.7) than the control group (32.0 +/- 7.9). Thus, we may conclude that this neonatal diabetes induction model gathers interesting characteristics and may be useful for further studies on the role of the exercise in the diabetes mellitus appearance.

Reconstruction of interacting dark energy models from parametrizations

Models with interacting dark energy can alleviate the cosmic coincidence problem by allowing dark matter and dark energy to evolve in a similar fashion. At a fundamental level, these models are specified by choosing a functional form for the scalar potential and for the interaction term. However, in order to compare to observational data it is usually more convenient to use parametrizations of the dark energy equation of state and the evolution of the dark matter energy density. Once the relevant parameters are fitted, it is important to obtain the shape of the fundamental functions. In this paper I show how to reconstruct the scalar potential and the scalar interaction with dark matter from general parametrizations. I give a few examples and show that it is possible for the effective equation of state for the scalar field to cross the phantom barrier when interactions are allowed. I analyze the uncertainties in the reconstructed potential arising from foreseen errors in the estimation of fit parameters and point out that a Yukawa-like linear interaction results from a simple parametrization of the coupling.

Degeneration of the Y chromosome in evolutionary aging models

The Y chromosomes are genetically degenerated and do not recombine with their matching partners X. Recombination of XX pairs is pointed out as the key factor for the Y chromosome degeneration. However, there is an additional evolutionary force driving sex-chromosomes evolution. Here we show this mechanism by means of two different evolutionary models, in which sex chromosomes with non-recombining XX and XY pairs of chromosomes is considered. Our results show three curious effects. First, we observed that even when both XX and XY pairs of chromosomes do not recombine, the Y chromosomes still degenerate. Second, the accumulation of mutations on Y chromosomes followed a completely different pattern then those accumulated on X chromosomes. and third, the models may differ with respect to sexual proportion. These findings suggest that a more primeval mechanism rules the evolution of Y chromosomes due exclusively to the sex-chromosomes asymmetry itself, i.e., the fact that Y chromosomes never experience female bodies. Over aeons, natural selection favored X chromosomes spontaneously, even if at the very beginning of evolution, both XX and XY pairs of chromosomes did not recombine.

Monte Carlo renormalization group with evolution in the space of parameters

Using data from a single simulation we obtain Monte Carlo renormalization-group information in a finite region of parameter space by adapting the Ferrenberg-Swendsen histogram method. Several quantities are calculated in the two-dimensional N 2 Ashkin-Teller and Ising models to show the feasibility of the method. We show renormalization-group Hamiltonian flows and critical-point location by matching of correlations by doing just two simulations at a single temperature in lattices of different sizes to partially eliminate finite-size effects.

Cranial differentiation and evolution in Thrichomys apereoides (Rodentia: Echimyidae)

Thrichomys apereoides is an echimyid rodent which ranges in distribution from north-eastern and central Brazil into Paraguay, and currently five subspecies are recognized. Recent morphometric analyses of population samples formally assignable to T. a. laurentius and T. a. inermis, which occur in north-eastern Brazil, have shown that a major group of populations including both subspecies differ in cranial shape from a single population allocated to T. a. laurentius. In this study we employed mathematical models of evolutionary quantitative genetics to assess the role that random drift and selection may have played in the evolution of cranial shape differences in T. apereoides. The hypothesis of evolution due to drift was rejected and the selective forces necessary to account for shape differences were estimated. Minimum selective mortalities of the order of 10(-3) per generation were sufficient to explain the observed morphologic differentiation.

Multivariate quality control studies applied to Ca(II) and Mg(II) determination by a portable method

A portable or field test method for simultaneous spectrophotometric determination of calcium and magnesium in water using multivariate partial least squares (PLS) calibration methods is proposed. The method is based on the reaction between the analytes and methylthymol blue at pH 11. The spectral information was used as the X-block, and the Ca(II) and Mg(II) concentrations obtained by a reference technique (ICP-AES) were used as the Y-block. Two series of analyses were performed, with a month's difference between them. The first series was used as the calibration set and the second one as the validation set. Multivariate statistical process control (MSPC) techniques, based on statistics from principal component models, were used to study the features and evolution with time of the spectral signals. Signal standardization was used to correct the deviations between series. Method validation was performed by comparing the predictions of the PLS model with the reference Ca(II) and Mg(II) concentrations determined by ICP-AES using the joint interval test for the slope and intercept of the regression line with errors in both axes. (C) 1998 John Wiley & Sons, Ltd.

The use of apatite fission track thermochronology to constrain fault movements and sedimentary basin evolution in northeastern Brazil

An apatite fission track study of crystalline rocks underlying sedimentary basins in northeastern Brazil indicate that crustal blocks that occur on opposite sides of a geological fault experienced different thermal histories. Samples collected on the West block yielded corrected fission-track ages from 140 to 375 Ma, whereas samples collected on the East block yielded ages between 90 and 125 Ma. The thermal models suggest that each block experienced two cooling events separated by a heating event at different times. We concluded that the West block moved downward relative to the East block ca. 140 Ma ago, when sediments eroded from the East side were deposited on the West side. This process represents the early stage of sedimentary basin formation and the opening of the South Atlantic Ocean in the region. Downward and upward movements related to heating and cooling events of these crustal blocks at different periods until recent times are proposed. (c) 2005 Elsevier Ltd. All rights reserved.

Allometric analysis of the ontogenetic variation and evolution of the skull in Caiman spix, 1825 (Crocodylia: Alligatoridae)

We studied ontogenetic variation in the shape of the skull among species of Caiman using principal component analysis. Comparison of multivariate allometric coefficients and ontogenetic trends between size and shape reveals that C. sclerops and C. yacare have similar ontogenetic processes, and they are more related to each other than either is to C. latirostris. Allometric relationships of the characters measured are similar in all species studied. The greater differences were in the width measurements, with higher coefficients in shape (second principal component) for C. latirostris, and length measurements with higher coefficients in shape for C. yacare and C. sclerops. The ontogenetic process leading to change in skull shape in the group seems to be plesiomorphic for elongation and derived for broadening. Statistical comparison of the ontogenetic trends with models of allometric heterochrony suggests that C. latirostris has diverged from the other species by a neotenic process, and that C. sclerops is separated from C. yacare by ontogenetic scaling (progenesis).