Large contribution of supercooled liquid clouds to the solar radiation budget of the Southern Ocean

The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections.

CHEMICAL EVOLUTION OF THE GALACTIC BULGE: SINGLE AND DOUBLE INFALL MODELS

Recent work, has produced a wealth of data concerning the chemical evolution of the Galactic bulge, both for stars and nebulae. Present theoretical models generally adopt it limited range of such constraints, frequenfly using it single chemical element (usually iron), which is not enough to describe it unambiguously. In this work, we take into account contraints involving,9 Many chemical elements as possible, basically obtained from bulge nebulae and stars. Our main goal is to show that different scenarios can describe, at least partially the abundance distribution and several dishuice-independent correlations for these objects . Three classes of models were developed. The first is it one-zone, single-infall model, the. Second is it one-zone, double-infall model and the third is a multizone, double-infall model. We show that a one-zone model with it single infall episode is able to reproduce some of the observational data, but the best results tire achieved using it multizone, double-infall model.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Population structure of the migratory fish Prochilodus lineatus (Characiformes) from rio Grande basin (Brazil), an area fragmented by dams

1. Prochilodus lineatus (Prochilodontidae, Characiformes) is a migratory species of great economic importance both in fisheries and aquaculture that is found throughout the Jacui, Paraiba do Sul, Parana, Paraguay and Uruguay river basins in South America. Earlier population studies of P. lineatus in the rio Grande basin (Parana basin) indicated the existence of a single population; however, the range of this species has been fragmented by the construction of several dams. Such dams modified the environmental conditions and could have constrained the reproductive migration of P. lineatus, possibly leading to changes in the population genetic structure. 2. In order to evaluate how genetic diversity is allocated in the rio Grande basin, 141 specimens of P. lineatus from eight collection sites were analysed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) with 15 restriction enzymes. 3. Forty-six haplotypes were detected, and 70% of them are restricted. The mean genetic variability indexes (h = 0.7721 and pi = 1.6%) were similar to those found in natural populations with a large effective size. Fst and Exact Test values indicated a lack of structuring among the samples, and the model of isolation by distance was tested and rejected. 4. The haplotype network indicated that this population of P. lineatus has been maintained as a single variable stock with some differences in the genetic composition (haplotypes) between samples. Indications of population expansion were detected, and this finding was supported by neutrality tests and mismatch distribution analyses. 5. The present study focused on regions between dams to serve as a parameter for further evaluations of genetic variability and the putative impact of dams and repopulation programmes in natural populations of P. lineatus. Copyright (C) 2011 John Wiley & Sons, Ltd.

Genetic variation and population structure of the endangered Hyacinth Macaw (Anodorhynchus hyacinthinus): implications for conservation

The Hyacinth Macaw (Anodorhynchus hyacinthinus) is one of 14 endangered species in the family Psittacidae occurring in Brazil, with an estimated total population of 6,500 specimens. We used nuclear molecular markers (single locus minisatellites and microsatellites) and 472 bp of the mitochondrial DNA control region to characterize levels of genetic variability in this species and to assess the degree of gene flow among three nesting sites in Brazil (Pantanal do Abobral, Pantanal de Miranda and Piaui). The origin of five apprehended specimens was also investigated. The results suggest that, in comparison to other species of parrots, Hyacinth Macaws possess relatively lower genetic variation and that individuals from two different localities within the Pantanal (Abobral and Miranda) belong to a unique interbreeding population and are genetically distinct at nuclear level from birds from the state of Piaui. The analyses of the five apprehended birds suggest that the Pantanal is not the source of birds for illegal trade, but their precise origin could not be assigned. The low genetic variability detected in the Hyacinth Macaw does not seem to pose a threat to the survival of this species. Nevertheless, habitat destruction and nest poaching are the most important factors negatively affecting their populations in the wild. The observed genetic structure emphasizes the need of protection of Hyacinth Macaws from different regions in order to maintain the genetic diversity of this species.

The Prospective and Retrospective Memory Questionnaire: A population-based random sampling study

The Prospective and Retrospective Memory Questionnaire (PRMQ) has been shown to have acceptable reliability and factorial, predictive, and concurrent validity. However, the PRMQ has never been administered to a probability sample survey representative of all ages in adulthood, nor have previous studies controlled for factors that are known to influence metamemory, such as affective status. Here, the PRMQ was applied in a survey adopting a probabilistic three-stage cluster sample representative of the population of Sao Paulo, Brazil, according to gender, age (20-80 years), and economic status (n=1042). After excluding participants who had conditions that impair memory (depression, anxiety, used psychotropics, and/or had neurological/psychiatric disorders), in the remaining 664 individuals we (a) used confirmatory factor analyses to test competing models of the latent structure of the PRMQ, and (b) studied effects of gender, age, schooling, and economic status on prospective and retrospective memory complaints. The model with the best fit confirmed the same tripartite structure (general memory factor and two orthogonal prospective and retrospective memory factors) previously reported. Women complained more of general memory slips, especially those in the first 5 years after menopause, and there were more complaints of prospective than retrospective memory, except in participants with lower family income.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

Opinion dynamics of learning agents: does seeking consensus lead to disagreement?

We study opinion dynamics in a population of interacting adaptive agents voting on a set of issues represented by vectors. We consider agents who can classify issues into one of two categories and can arrive at their opinions using an adaptive algorithm. Adaptation comes from learning and the information for the learning process comes from interacting with other neighboring agents and trying to change the internal state in order to concur with their opinions. The change in the internal state is driven by the information contained in the issue and in the opinion of the other agent. We present results in a simple yet rich context where each agent uses a Boolean perceptron to state their opinion. If the update occurs with information asynchronously exchanged among pairs of agents, then the typical case, if the number of issues is kept small, is the evolution into a society torn by the emergence of factions with extreme opposite beliefs. This occurs even when seeking consensus with agents with opposite opinions. If the number of issues is large, the dynamics becomes trapped, the society does not evolve into factions and a distribution of moderate opinions is observed. The synchronous case is technically simpler and is studied by formulating the problem in terms of differential equations that describe the evolution of order parameters that measure the consensus between pairs of agents. We show that for a large number of issues and unidirectional information flow, global consensus is a fixed point; however, the approach to this consensus is glassy for large societies.

Epidemics in networks of spatially correlated three-dimensional root-branching structures

Using digitized images of the three-dimensional, branching structures for root systems of bean seedlings, together with analytical and numerical methods that map a common susceptible-infected- recovered (`SIR`) epidemiological model onto the bond percolation problem, we show how the spatially correlated branching structures of plant roots affect transmission efficiencies, and hence the invasion criterion, for a soil-borne pathogen as it spreads through ensembles of morphologically complex hosts. We conclude that the inherent heterogeneities in transmissibilities arising from correlations in the degrees of overlap between neighbouring plants render a population of root systems less susceptible to epidemic invasion than a corresponding homogeneous system. Several components of morphological complexity are analysed that contribute to disorder and heterogeneities in the transmissibility of infection. Anisotropy in root shape is shown to increase resilience to epidemic invasion, while increasing the degree of branching enhances the spread of epidemics in the population of roots. Some extension of the methods for other epidemiological systems are discussed.

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

Multiple stages of detergent-erythrocyte membrane interaction-A spin label study

The various stages of the interaction between the detergent Triton X-100 (TTX-100) and membranes of whole red blood cells (RBC) were investigated in a broad range of detergent concentrations. The interaction was monitored by RBC hemolysis-assessed by release of intracellular hemoglobin (Hb) and inorganic phosphate- and by analysis of EPR spectra of a fatty acid spin probe intercalated in whole RBC suspensions, as well as pellets and supernatants obtained upon centrifugation of detergent-treated cells. Hemolysis finished at ca. 0.9 mM TTX-100. Spectral analysis and calculation of order parameters (S) indicated that a complex sequence of events takes place, and allowed the characterization of various structures formed in the different stages of detergent-membrane interaction. Upon reaching the end of cell lysis, essentially no pellet was detected, the remaining EPR signal being found almost entirely in the supernatants. Calculated order parameters revealed that whole RBC suspensions, pellets, and supernatants possessed a similar degree of molecular packing, which decreased to a small extent up to 2.5 mM detergent. Between 3.2 and 10 mM TTX-100, a steep decrease in S was observed for both whole RBC suspensions and supernatants. Above 10 mM detergent, S decreased in a less pronounced manner and the EPR spectra approached that of pure TTX-100 micelles. The data were interpreted in terms of the following events: at the lower detergent concentrations, an increase in membrane permeability occurs: the end of hemolysis coincides with the lack of pellet upon centrifugation. Up to 2.5 mM TTX-100 the supernatants consist of a (very likely) heterogeneous population of membrane fragments with molecular packing similar to that of whole cells. As the detergent concentration increases, mixed micelles are formed containing lipid and/or protein, approaching the packing found in pure TTX-100 micelles. This analysis is in agreement with the models proposed by Lasch (Biochim. Biophys Acta 1241 (1995) 269-292) and by Le Maire and coworkers (Biochim. Biophys. Acta 1508 (2000) 86-111). (C) 2010 Elsevier B.V. All rights reserved.

Analysis of Structure and Tendencies of Qualified Immigrant Workforce on the Swedish Labor Market

The purpose of this paper is to make quantitative and qualitative analysis of foreign citizens who may participate on the Swedish labor market (in text refers to as ‘immigrants’). This research covers the period 1973-2005 and gives prediction figures of immigrant population, age and gender structure, and education attainment in 2010. To cope with data regarding immigrants from different countries, the population was divided into six groups. The main chapter is divided into two parts. The first part specifies division of immigrants into groups by country of origin according to geographical, ethnical, economical and historical criteria. Brief characteristics and geographic position, dynamic and structure description were given for each group; historical review explain rapid changes in immigrant population. Statistical models for description and estimation future population were given. The second part specifies education and qualification level of the immigrants according to international and Swedish standards. Models for estimating age and gender structure, level of education and professional orientation of immigrants in different groups are given. Inferences were made regarding ethnic, gender and education structure of immigrants; the distribution of immigrants among Swedish counties is given. Discussion part presents the results of the research, gives perspectives for the future brief evaluation of the role of immigrants on the Swedish labor market.

Future Students, Future Revenues: Thriving in a Decade of Demographic Decline:

Over the past decade, universities were able to grow revenue primarily by growing enrollment and increasing net tuition per student. But demographic and economic changes will make it increasingly difficult for all but a handful of institutions to grow tuition revenue at historic rates. Despite rising access rates, demographic projections suggest that the number of high school graduates will decline over the coming decade, leading to a dramatic drop-off in the overall rate of enrollment growth. The traditional population of 18- to 22-year-olds will remain a majority at most institutions, but enrollment growth will come primarily from other student segments. Populations such as community college transfers, international undergraduates, professional master’s students, and adult degree completers offer the best opportunities to grow enrollment and tuition revenue. Serving them well requires significant investments, new organizational models, and cultural change on campus. This can be done in a financially sustainable way—fulfilling the university’s mission to serve a diverse range of students while providing financial resources to support the core. This brief analyzes the forces that will shape higher education over the next decade and highlights the strategies and competencies that colleges and universities will need to be successful.

On the consistency of arbitrary money-demand functions with the Sidrauski and the shopping-time models

This paper investigates which properties money-demand functions have to satisfy to be consistent with multidimensional extensions of Lucasí(2000) versions of the Sidrauski (1967) and the shopping-time models. We also investigate how such classes of models relate to each other regarding the rationalization of money demands. We conclude that money demand functions rationalizable by the shoppingtime model are always rationalizable by the Sidrauski model, but that the converse is not true. The log-log money demand with an interest-rate elasticity greater than or equal to one and the semi-log money demand are counterexamples.