What controls the vertical distribution of aerosol? Relationships between process sensitivity in HadGEM3–UKCA and inter-model variation from AeroCom Phase II

The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3–UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3–UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN  >  3 nm), while the profiles of larger particles (e.g. CN  >  100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.

Sparse density estimation on multinomial manifold combining local component analysis

A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

Effects of exercise training on autonomic dysfunction management in an experimental model of menopause and myocardial infarction

Objective: The aim of this study was to investigate the effects of exercise training on cardiovascular autonomic dysfunction in ovariectomized rats submitted to myocardial infarction. Methods: Female Wistar rats were divided into the following ovariectomized groups: sedentary ovariectomized (SO), trained ovariectomized (TO), sedentary ovariectomized infarcted (SOI), and trained ovariectomized infarcted (TOI). Trained groups were submitted to an exercise training protocol on a treadmill (8 wk). Arterial baroreflex sensitivity was evaluated by heart rate responses to arterial pressure changes, and cardiopulmonary baroreflex sensitivity was tested by bradycardic and hypotension responses to serotonin injection. Vagal and sympathetic effects were calculated by pharmacological blockade. Results: Arterial pressure was reduced in the TO in comparison with the SO group and increased in the TOI in relation to the SOI group. Exercise training improved the baroreflex sensitivity in both the TO and TOI groups. The TOI group displayed improvement in cardiopulmonary reflex sensitivity compared with the SOI group at the 16 mu g/kg serotonin dose. Exercise training enhanced the vagal effect in both the TO (45%) and TOI (46%) animals compared with the SO and SOI animals and reduced the sympathetic effect in the TOI (38%) in comparison with the SOI animals. Significant correlations were obtained between bradycardic baroreflex responses and vagal (r = -0.7, P < 0.005) and sympathetic (r = 0.7, P < 0.001) effects. Conclusions: These results indicate that exercise training in ovariectomized rats submitted to myocardial infarction improves resting hemodynamic status and reflex control of the circulation, which may be due to an increase in the vagal component. This suggests a homeostatic role for exercise training in reducing the autonomic impairment of myocardial infarction in postmenopausal women.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

QoS-aware model driven architecture through the UML and CIM

The specification of Quality of Service (QoS) constraints over software design requires measures that ensure such requirements are met by the delivered product. Achieving this goal is non-trivial, as it involves, at least, identifying how QoS constraint specifications should be checked at the runtime. In this paper we present an implementation of a Model Driven Architecture (MDA) based framework for the runtime monitoring of QoS properties. We incorporate the UML2 superstructure and the UML profile for Quality of Service to provide abstract descriptions of component-and-connector systems. We then define transformations that refine the UML2 models to conform with the Distributed Management Taskforce (DMTF) Common Information Model (CIM) (Distributed Management Task Force Inc. 2006), a schema standard for management and instrumentation of hardware and software. Finally, we provide a mapping the CIM metamodel to a .NET-based metamodel for implementation of the monitoring infrastructure utilising various .NET features including the Windows Management Instrumentation (WMI) interface.

A Resource Centric Approach For Advancing Collaboration Through Hydrologic Data And Model Sharing

HydroShare is an online, collaborative system being developed for open sharing of hydrologic data and models. The goal of HydroShare is to enable scientists to easily discover and access hydrologic data and models, retrieve them to their desktop or perform analyses in a distributed computing environment that may include grid, cloud or high performance computing model instances as necessary. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models and analyses. HydroShare is expanding the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated, creating new capability to share models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. One of the fundamental concepts in HydroShare is that of a Resource. All content is represented using a Resource Data Model that separates system and science metadata and has elements common to all resources as well as elements specific to the types of resources HydroShare will support. These will include different data types used in the hydrology community and models and workflows that require metadata on execution functionality. The HydroShare web interface and social media functions are being developed using the Drupal content management system. A geospatial visualization and analysis component enables searching, visualizing, and analyzing geographic datasets. The integrated Rule-Oriented Data System (iRODS) is being used to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the execution of models and workflows. This presentation will introduce the HydroShare functionality developed to date, describe key elements of the Resource Data Model and outline the roadmap for future development.

Redistribution with ex-ante unobserved choice

Introducing dynamics to Mirrlees' (1971) optimal taxation model creates a whole new set of issues that are only starting to be investigated in the literature. When choices are made before one's realizing her productivity incentive constraints ought to be defined as a function of more complex strategies than in the static case. 80 far, all work has assumed that these choices are observable and can be contracted upon by the government. Here we investigate choices that : i) are not observed, andj ii) affect preferences conditional Oil the realization of types. In the simplest possible model where a non-trivial filtration is incorporated we show how these two characteristics make it necessary for IC constraints to be defined in terms of strategies rather than pure announcements. Tax prescriptions are derived, and it is shown that they bear some resemblance to classic optimal taxation results. We are able to show that in the most 'natural' cases return on capital ought to be taxed . However, we also show that the uniform taxation prescription of Atkinson and Stiglitz fails to hold, in general.

Temporal variability of soil CO2 emission after conventional and reduced tillage described by an exponential decay in time model

A quantificação do impacto das práticas de preparo sobre as perdas de carbono do solo é dependente da habilidade de se descrever a variabilidade temporal da emissão de CO2 do solo após preparo. Tem sido sugerido que as grandes quantidades de CO2 emitido após o preparo do solo podem servir como um indicador das modificações nos estoques de carbono do solo em longo termo. Neste trabalho é apresentado um modelo de duas partes baseado na temperatura e na umidade do solo e que inclui um termo exponencial decrescente do tempo que é eficiente no ajuste das emissões intermediárias após preparo: arado de disco seguido de uma passagem com a grade niveladora (convencional) e escarificador de arrasto seguido da passagem com rolo destorroador (reduzido). As emissões após o preparo do solo são descritas utilizando-se estimativa não linear com um coeficiente de determinação (R²) tão alto quanto 0.98 após preparo reduzido. Os resultados indicam que nas previsões da emissão de CO2 após o preparo do solo é importante considerar um termo exponencial decrescente no tempo após preparo.

Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A model for the plankton system of the Broa reservoir, Sao Carlos, Brazil

In this paper a model, called ELLOBO running in STELLA II, was set to describe the plankton system of the Broa reservoir (SP). The three state variables of the model are: phytoplankton, zooplankton, and the fish Astyanax fasciatus. The forcing variables are: temperature, nitrate, phosphorus and solar radiation. The model did not consider the cycling of nutrients inside the reservoir. The results show that: temperature is the principal forcing variable in the phytoplankton dynamic and in the subsequent evolution of the whole system. The zooplankton predation was described by Odum's equation, and there is a strong random component in zooplankton grazing, which was essential for the model, because zooplankton estimates have high variance. One must collect data in a short space of time (maybe daily) to better explain the zooplankton and phytoplankton variation. Validation was performed using simple statistics (arithmetic mean, standard deviation) and the results show concordance between observed and simulated values. Overhead was used to calibrate some parameters and to validate the model. The highest overhead value (5%) imply in the better accordance between estimated and;observed state variables values. We believe this approach in Broa reservoir will provide an useful tool for future research and it could be used comparatively in other continental aquatic ecosystems. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Lobe identity in the Mongolian gerbil prostatic complex: A new rodent model for prostate study

Knowledge of structural and physiological differences among the prostatic lobes (PL) is the basis for development of experimental studies in traditional laboratory rodents. Although Mongolian gerbil reproductive organs have been increasingly investigated, its prostate structure is far from being properly known, and investigations of this organ focused on the ventral lobe (VL). Thus, the present study provides a thorough morphological description of prostatic complex in the male adult gerbil on the basis of topographic, histological, and ultrastructural analysis and ductal branching. Like other rodents, four pairs of PL were observed. However, in contrast to the rat and mouse, the VL is the least voluminous component and the dorsolateral lobe (DLL) is the most prominent and spatially isolated from remaining PL. The occurrence of a dorsal lobe (DL), hidden between bladder and insertion of seminal vesicles, has not been mentioned in previous reports with Mongolian gerbil. Collagenase digestion followed by microdissection revealed that, except for DL, which has a tubularacinar organization, all PL exhibit tubular organization and variable ductal branching. Distinct histological and ultrastructural features such as secretory epithelium, aspect of luminal secretion and stromal organization are reported for each PL and are confirmed by morphometric and stereological methods. Histological sections showed at least three intralobar segments in VL and DL. Ultrastructural analysis evidenced that, although luminal epithelial cells of PL share typical features of exocrine secretory cells, there are striking lobe phenotypical variations. Both merocrine and apocrine pathways are observed in variable rates in all PL, with the predominance of the former in the DLL and the latter in the CG. The morphological observations presented herein point to distinct structural identities for each PL, which probably reflects,specific functional compromise of seminal fluid secretion. These data also point to the gerbil as a good model for investigations concerning the regulation of prostate development and homeostasis, mainly with regard to the dorsal and dorsolateral PL.

Crystal structure of a dimeric Ser49 PLA(2)-like myotoxic component of the Vipera ammodytes meridionalis venomics reveals determinants of myotoxicity and membrane damaging activity

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)