Accessing extremes of mid-latitudinal wave activity: methodology and application

A statistical methodology is proposed and tested for the analysis of extreme values of atmospheric wave activity at mid-latitudes. The adopted methods are the classical block-maximum and peak over threshold, respectively based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD). Time-series of the ‘Wave Activity Index’ (WAI) and the ‘Baroclinic Activity Index’ (BAI) are computed from simulations of the General Circulation Model ECHAM4.6, which is run under perpetual January conditions. Both the GEV and the GPD analyses indicate that the extremes ofWAI and BAI areWeibull distributed, this corresponds to distributions with an upper bound. However, a remarkably large variability is found in the tails of such distributions; distinct simulations carried out under the same experimental setup provide sensibly different estimates of the 200-yr WAI return level. The consequences of this phenomenon in applications of the methodology to climate change studies are discussed. The atmospheric configurations characteristic of the maxima and minima of WAI and BAI are also examined.

Pollinator community responses to the spatial population structure of wild plants: A pan-European approach

Land-use changes can alter the spatial population structure of plant species, which may in turn affect the attractiveness of flower aggregations to different groups of pollinators at different spatial scales. To assess how pollinators respond to spatial heterogeneity of plant distributions and whether honeybees affect visitation by other pollinators we used an extensive data set comprising ten plant species and their flower visitors from five European countries. In particular we tested the hypothesis that the composition of the flower visitor community in terms of visitation frequencies by different pollinator groups were affected by the spatial plant population structure, viz. area and density measures, at a within-population (‘patch’) and among-population (‘population’) scale. We found that patch area and population density were the spatial variables that best explained the variation in visitation frequencies within the pollinator community. Honeybees had higher visitation frequencies in larger patches, while bumblebees and hoverflies had higher visitation frequencies in sparser populations. Solitary bees had higher visitation frequencies in sparser populations and smaller patches. We also tested the hypothesis that honeybees affect the composition of the pollinator community by altering the visitation frequencies of other groups of pollinators. There was a positive relationship between visitation frequencies of honeybees and bumblebees, while the relationship with hoverflies and solitary bees varied (positive, negative and no relationship) depending on the plant species under study. The overall conclusion is that the spatial structure of plant populations affects different groups of pollinators in contrasting ways at both the local (‘patch’) and the larger (‘population’) scales and, that honeybees affect the flower visitation by other pollinator groups in various ways, depending on the plant species under study. These contrasting responses emphasize the need to investigate the entire pollinator community when the effects of landscape change on plant–pollinator interactions are studied.

Some results from an intercomparison of the climates simulated by 14 atmospheric general circulation models

Some climatological information from 14 atmospheric general circulation models is presented and compared in order to assess the ability of a broad group of models to simulate current climate. The quantities considered are cross sections of temperature, zonal wind, and meridional stream function together with latitudinal distributions of mean sea level pressure and precipitation rate. The nature of the deficiencies in the simulated climates that are common to all models and those which differ among models is investigated; the general improvement in the ability of models to simulate certain aspects of the climate is shown; consideration is given to the effect of increasing resolution on simulated climate; and approaches to understanding and reducing model deficiencies are discussed. The information presented here is a subset of a more voluminous compilation which is available in report form (Boer et al., 1991). This report contains essentially the same text, but results from all 14 models are presented together with additional results in the form of geographical distributions of surface variables and certain difference statistics.

Analytical solutions of a minimal model of species migration in a bounded domain

A minimal model of species migration is presented which takes the form of a parabolic equation with boundary conditions and initial data. Solutions to the differential problem are obtained that can be used to describe the small- and large-time evolution of a species distribution within a bounded domain. These expressions are compared with the results of numerical simulations and are found to be satisfactory within appropriate temporal regimes. The solutions presented can be used to describe existing observations of nematode distributions, can be used as the basis for further work on nematode migration, and may also be interpreted more generally.

Non-Maxwellian ion velocity distributions observed using EISCAT

Recent observations from the EISCAT incoherent scatter radar have revealed bursts of poleward ion flow in the dayside auroral ionosphere which are consistent with the ionospheric signature of flux transfer events at the magnetopause. These bursts frequently contain ion drifts which exceed the neutral thermal speed and, because the neutral thermospheric wind is incapable of responding sufficiently rapidly, toroidal, non-Maxwellian ion velocity distributions are expected. The EISCAT observations are made with high time resolution (15 seconds) and at a large angle to the geomagnetic field (73.5°), allowing the non-Maxwellian nature of the distribution to be observed remotely for the first time. The observed features are also strongly suggestive of a toroidal distribution: characteristic spectral shape, increased scattered power (both consistent with reduced Landau damping and enhanced electric field fluctuations) and excessively high line-of-sight ion temperatures deduced if a Maxwellian distribution is assumed. These remote sensing observations allow the evolution of the distributions to be observed. They are found to be non-Maxwellian whenever the ion drift exceeds the neutral thermal speed, indicating that such distributions can exist over the time scale of the flow burst events (several minutes).

Genome-wide mapping of 5-hydroxymethylcytosine in three rice cultivars reveals its preferential localization in transcriptionally silent transposable element genes

5-Hydroxymethylcytosine (5hmC), a modified form of cytosine that is considered the sixth nucleobase in DNA, has been detected in mammals and is believed to play an important role in gene regulation. In this study, 5hmC modification was detected in rice by employing a dot-blot assay, and its levels was further quantified in DNA from different rice tissues using liquid chromatography-multistage mass spectrometry (LC-MS/MS/MS). The results showed large intertissue variation in 5hmC levels. The genome-wide profiles of 5hmC modification in three different rice cultivars were also obtained using a sensitive chemical labelling followed by a next-generation sequencing method. Thousands of 5hmC peaks were identified, and a comparison of the distributions of 5hmC among different rice cultivars revealed the specificity and conservation of 5hmC modification. The identified 5hmC peaks were significantly enriched in heterochromatin regions,and mainly located in transposable element (TE) genes, especially around retrotransposons. The correlation analysis of 5hmC and gene expression data revealed a close association between 5hmC and silent TEs. These findings provide a resource for plant DNA 5hmC epigenetic studies and expand our knowledge of 5hmC modification.

Exploring the source of differences and similarities in L1 attrition and heritage speaker competence: evidence from pronominal resolution

Several studies of different bilingual groups including L2 learners, child bilinguals, heritage speakers and L1 attriters reveal similar performance on syntax-discourse interface properties such as anaphora resolution (Sorace, 2011 and references therein). Specifically, bilinguals seem to allow more optionality in the interpretation of overt subject pronouns in null subject languages, such as Greek, Italian and Spanish while the interpretation of null subject pronouns is indistinguishable from monolingual natives. Nevertheless, there is some evidence pointing to bilingualism effects on the interpretation of null subject pronouns too in heritage speakers’ grammars (Montrul, 2004) due to some form of ‘arrested’ development in this group of bilinguals. The present study seeks to investigate similarities and differences between two Greek–Swedish bilingual groups, heritage speakers and L1 attriters, in anaphora resolution of null and overt subject pronouns in Greek using a self-paced listening with a sentence-picture matching decision task at the end of each sentence. The two groups differ in crucial ways: heritage speakers were simultaneous or early bilinguals while the L1 attriters were adult learners of the second language, Swedish. Our findings reveal differences from monolingual preferences in the interpretation of the overt pronoun for both heritage and attrited speakers while the differences attested between the two groups in the interpretation of null subject pronouns affect only response times with heritage being faster than attrited speakers. We argue that our results do not support an age of onset or differential input effects on bilingual performance in pronoun resolution.

Genetic and phenotypic characterization of complex hereditary spastic paraplegia

The hereditary spastic paraplegias are a heterogeneous group of degenerative disorders that are clinically classified as either pure with predominant lower limb spasticity, or complex where spastic paraplegia is complicated with additional neurological features, and are inherited in autosomal dominant, autosomal recessive or X-linked patterns. Genetic defects have been identified in over 40 different genes, with more than 70 loci in total. Complex recessive spastic paraplegias have in the past been frequently associated with mutations in SPG11 (spatacsin), ZFYVE26/SPG15, SPG7 (paraplegin) and a handful of other rare genes, but many cases remain genetically undefined. The overlap with other neurodegenerative disorders has been implied in a small number of reports, but not in larger disease series. This deficiency has been largely due to the lack of suitable high throughput techniques to investigate the genetic basis of disease, but the recent availability of next generation sequencing can facilitate the identification of disease- causing mutations even in extremely heterogeneous disorders. We investigated a series of 97 index cases with complex spastic paraplegia referred to a tertiary referral neurology centre in London for diagnosis or management. The mean age of onset was 16 years (range 3 to 39). The SPG11 gene was first analysed, revealing homozygous or compound heterozygous mutations in 30/97 (30.9%) of probands, the largest SPG11 series reported to date, and by far the most common cause of complex spastic paraplegia in the UK, with severe and progressive clinical features and other neurological manifestations, linked with magnetic resonance imaging defects. Given the high frequency of SPG11 mutations, we studied the autophagic response to starvation in eight affected SPG11 cases and control fibroblast cell lines, but in our restricted study we did not observe correlations between disease status and autophagic or lysosomal markers. In the remaining cases, next generation sequencing was carried out revealing variants in a number of other known complex spastic paraplegia genes, including five in SPG7 (5/97), four in FA2H (also known as SPG35) (4/97) and two in ZFYVE26/SPG15. Variants were identified in genes usually associated with pure spastic paraplegia and also in the Parkinson’s disease-associated gene ATP13A2, neuronal ceroid lipofuscinosis gene TPP1 and the hereditary motor and sensory neuropathy DNMT1 gene, highlighting the genetic heterogeneity of spastic paraplegia. No plausible genetic cause was identified in 51% of probands, likely indicating the existence of as yet unidentified genes.

Geographical distribution of American cutaneous leishmaniasis and its phlebotomine vectors (Diptera: Psychodidae) in the state of Sao Paulo, Brazil

Background: American cutaneous leishmaniasis (ACL) is a re-emerging disease in the state of Sao Paulo, Brazil. It is important to understand both the vector and disease distribution to help design control strategies. As an initial step in applying geographic information systems (GIS) and remote sensing (RS) tools to map disease-risk, the objectives of the present work were to: (i) produce a single database of species distributions of the sand fly vectors in the state of Sao Paulo, (ii) create combined distributional maps of both the incidence of ACL and its sand fly vectors, and (iii) thereby provide individual municipalities with a source of reference material for work carried out in their area. Results: A database containing 910 individual records of sand fly occurrence in the state of Sao Paulo, from 37 different sources, was compiled. These records date from between 1943 to 2009, and describe the presence of at least one of the six incriminated or suspected sand fly vector species in 183/645 (28.4%) municipalities. For the remaining 462 (71.6%) municipalities, we were unable to locate records of any of the six incriminated or suspected sand fly vector species (Nyssomyia intermedia, N. neivai, N. whitmani, Pintomyia fischeri, P. pessoai and Migonemyia migonei). The distribution of each of the six incriminated or suspected vector species of ACL in the state of Sao Paulo were individually mapped and overlaid on the incidence of ACL for the period 1993 to 1995 and 1998 to 2007. Overall, the maps reveal that the six sand fly vector species analyzed have unique and heterogeneous, although often overlapping, distributions. Several sand fly species - Nyssomyia intermedia and N. neivai - are highly localized, while the other sand fly species - N. whitmani, M. migonei, P. fischeri and P. pessoai - are much more broadly distributed. ACL has been reported in 160/183 (87.4%) of the municipalities with records for at least one of the six incriminated or suspected sand fly vector species, while there are no records of any of these sand fly species in 318/478 (66.5%) municipalities with ACL. Conclusions: The maps produced in this work provide basic data on the distribution of the six incriminated or suspected sand fly vectors of ACL in the state of Sao Paulo, and highlight the complex and geographically heterogeneous pattern of ACL transmission in the region. Further studies are required to clarify the role of each of the six suspected sand fly vector species in different regions of the state of Sao Paulo, especially in the majority of municipalities where ACL is present but sand fly vectors have not yet been identified.

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.

Early Onset Obsessive-Compulsive Disorder With and Without Tics

Introduction: Research suggests that obsessive-compulsive disorder (OCD) is not a unitary entity, but rather a highly heterogeneous condition, with complex and variable clinical manifestations. Objective: The aims of this study were to compare clinical and demographic characteristics of OCD patients with early and late age of onset of obsessive-compulsive symptoms (OCS); and to compare the same features in early onset OCD with and without tics. The independent impact of age at onset and presence of tics on comorbidity patterns was investigated. Methods: Three hundred and thirty consecutive outpatients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for OCD were evaluated: 160 patients belonged to the ""early onset"" group (EOG): before 11 years of age, 75 patients had an ""intermediate onset"" (IOG), and 95 patients were from the ""late onset"" group (LOG): after 18 years of age. From the 160 EOG, 60 had comorbidity with tic disorders. The diagnostic instruments used were: the Yale-Brown Obsessive Compulsive Scale and the Dimensional Yale-Brown Obsessive Compulsive Scale (DY-BOCS), Yale Global Tics Severity Scale; and Structured Clinical Interview for DSM-IV Axis I Disorders-patient edition. Statistical tests used were: Mann-Whitney, full Bayesian significance test, and logistic regression. Results: The EOG had a predominance of males, higher frequency of family history of OCS, higher mean scores on the ""aggression/violence"" and ""miscellaneous"" dimensions, and higher mean global DY-BOCS scores. Patients with EOG without tic disorders presented higher mean global DY-BOCS scores and higher mean scores in the ""contamination/cleaning"" dimension. Conclusion: The current results disentangle some of the clinical overlap between early onset OCD with and without tics. CNS Spectr. 2009; 14(7):362-370

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

An extension of the generalized Birnbaum-Saunders distribution

In this paper we present an extension of the generalized Birnbaum-Saunders distribution family introduced in [Diaz-Garcia, J.A., Leiva-Sanchez, V., 2005. A new family of life distributions based on the contoured elliptically distributions. Journal of Statistical Planning and Inference 128 (2), 445-457] with a view to make it even more flexible in terms of its kurtosis coefficient. Properties involving moments and asymmetry and kurtosis indexes are studied for some special members of this family such as the slash Birnbaum-Saunders and slash-t Birnbaum-Saunders. Simulation studies for some particular cases and a real data analysis are also reported, illustrating the usefulness of the extension considered. (C) 2008 Elsevier B.V. All rights reserved.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.