Short-term temporal changes in the spatial variability model of CO2 emissions from a Brazilian bare soil

In this work, the spatial variability model of CO2 emissions and soil properties of a Brazilian bare soil were investigated. Carbon dioxide emissions were measured on three different days at contrasted soil temperature and soil moisture conditions, and soil properties were investigated at the same points where emissions were measured. One spatial variability model of soil CO2 emissions was found for each measurement day, and these models are similar to the ones of soil properties studied in an area of 100 x 100 m. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data

We describe a general likelihood-based 'mixture model' for inferring phylogenetic trees from gene-sequence or other character-state data. The model accommodates cases in which different sites in the alignment evolve in qualitatively distinct ways, but does not require prior knowledge of these patterns or partitioning of the data. We call this qualitative variability in the pattern of evolution across sites "pattern-heterogeneity" to distinguish it from both a homogenous process of evolution and from one characterized principally by differences in rates of evolution. We present studies to show that the model correctly retrieves the signals of pattern-heterogeneity from simulated gene-sequence data, and we apply the method to protein-coding genes and to a ribosomal 12S data set. The mixture model outperforms conventional partitioning in both these data sets. We implement the mixture model such that it can simultaneously detect rate- and pattern-heterogeneity. The model simplifies to a homogeneous model or a rate- variability model as special cases, and therefore always performs at least as well as these two approaches, and often considerably improves upon them. We make the model available within a Bayesian Markov-chain Monte Carlo framework for phylogenetic inference, as an easy-to-use computer program.

Adaptive SOA Infrastructure Based on Variability Management

In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide platform mechanisms that support a mapping of the variability in the applications to the variability provided by the infrastructure. The approach focuses on the configuration of the needed infrastructure mechanisms including support for the derivation of the infrastructure variability model.

Derivation and consistency checking of models in early software product line engineering

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

User-centric product derivation in software product lines

Software Product Line (SPL) engineering aims at achieving efficient development of software products in a specific domain. New products are obtained via a process which entails creating a new configuration specifying the desired product’s features. This configuration must necessarily conform to a variability model, that describes the scope of the SPL, or else it is not viable. To ensure this, configuration tools are used that do not allow invalid configurations to be expressed. A different concern, however, is making sure that a product addresses the stakeholders’ needs as best as possible. The stakeholders may not be experts on the domain, so they may have unrealistic expectations. Also, the scope of the SPL is determined not only by the domain but also by limitations of the development platforms. It is therefore possible that the desired set of features goes beyond what is possible to currently create with the SPL. This means that configuration tools should provide support not only for creating valid products, but also for improving satisfaction of user concerns. We address this goal by providing a user-centric configuration process that offers suggestions during the configuration process, based on the use of soft constraints, and identifying and explaining potential conflicts that may arise. Suggestions help mitigating stakeholder uncertainty and poor domain knowledge, by helping them address well known and desirable domain-related concerns. On the other hand, automated conflict identification and explanation helps the stakeholders to understand the trade-offs required for realizing their vision, allowing informed resolution of conflicts. Additionally, we propose a prototype-based approach to configuration, that addresses the order-dependency issues by allowing the complete (or partial) specification of the features in a single step. A subsequent resolution process will then identify possible repairs, or trade-offs, that may be required for viabilization.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

The potential to narrow uncertainty in regional climate predictions

Faced by the realities of a changing climate, decision makers in a wide variety of organisations are increasingly seeking quantitative predictions of regional and local climate. An important issue for these decision makers, and for organisations that fund climate research, is what is the potential for climate science to deliver improvements - especially reductions in uncertainty - in such predictions? Uncertainty in climate predictions arises from three distinct sources: internal variability, model uncertainty and scenario uncertainty. Using data from a suite of climate models we separate and quantify these sources. For predictions of changes in surface air temperature on decadal timescales and regional spatial scales, we show that uncertainty for the next few decades is dominated by sources (model uncertainty and internal variability) that are potentially reducible through progress in climate science. Furthermore, we find that model uncertainty is of greater importance than internal variability. Our findings have implications for managing adaptation to a changing climate. Because the costs of adaptation are very large, and greater uncertainty about future climate is likely to be associated with more expensive adaptation, reducing uncertainty in climate predictions is potentially of enormous economic value. We highlight the need for much more work to compare: a) the cost of various degrees of adaptation, given current levels of uncertainty; and b) the cost of new investments in climate science to reduce current levels of uncertainty. Our study also highlights the importance of targeting climate science investments on the most promising opportunities to reduce prediction uncertainty.

SPARC Data Initiative: A comparison of ozone climatologies from international satellite limb sounders

A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.

Uma investigação sobre o impacto dos accruals na variabilidade dos resultados nos diferentes contrastes cross-sectional nas firmas brasileiras de capital aberto

Esta dissertação tem como objetivo principal investigar o impacto dos accruals na variabilidade dos resultados corporativos (EVAR) que influenciam a aplicação prática do income smoothing nas firmas brasileiras de capital aberto. Inicialmente, é demonstrada a importância das demonstrações contábeis que devem ser evidenciadas em cumprimento aos princípios contábeis geralmente aceitos. Sua evidenciação deve representar a realidade econômico-financeira da firma para o processo de tomada de decisão dos acionistas e credores. Porém, em determinados momentos, os gestores se sentem motivados a praticar o gerenciamento dos resultados contábeis na tentativa de reduzir a variabilidade dos lucros por meio da utilização dos accruals. Os accruals correspondem à diferença entre o lucro líquido e o fluxo de caixa operacional. Nesse processo de redução da volatilidade dos resultados, os gestores se utilizam da prática do income smoothing procurando reduzir eventuais distorções no preço das ações da firma. A amostra neste estudo é composta por um grupo de 163 firmas de capital aberto listadas na Bovespa e que apresentaram informações financeiras no intervalo de 2000 a 2007, categorizadas por setores através de dados obtidos na Economática. O modelo estatístico utilizado na pesquisa foi a análise de regressão para explicar os diferentes modelos de cross-sectional. Os resultados desta pesquisa indicam que os accruals são significativos para explicar a variabilidade dos resultados corporativos (EVAR) de empresas brasileiras. Além disso, nossos resultados sugerem que o modelo estrutural de identificação do EVAR nas empresas brasileiras deve ser explicado por variáveis não contábeis diferentes das que são apresentadas pelas firmas norte-americanas.

CrossMDA-SPL: uma abordagem para gerência de variabilidades dirigida por modelos e aspectos

This paper proposes a systematic approach to management of variability modelsdriven and aspects using the mechanisms of approaches Aspect-Oriented Software Development (AOSD) and Model-Driven Development (MDD). The main goal of the approach, named CrossMDA-SPL, is to improve the management(gerência), modularization and isolation ou separation of the variability of the LPSs of architecture in a high level of abstraction (model) at the design and implementing phases of development Software Product Lines (SPLs), exploiting the synergy between AOSD and MDD. The CrossMDA-SPL approach defines some artifacts basis for advance the separation clear in between the mandatory (bounden) and optional features in the architecture of SPL. The artifacts are represented by two models named: (i) core model (base domain) - responsible for specify the common features the all members of the SPL, and (ii) variability model - responsible for represent the variables features of SPL. In addition, the CrossMDA-SPL approach is composed of: (i) guidelines for modeling and representation of variability, (ii) CrossMDA-SPL services and process, and (iii) models of the architecture of SPL or product instance of SPL. The guidelines use the advantages of AOSD and MDD to promote a better modularization of the variable features of the architecture of SPL during the creation of core and variability models of the approach. The services and sub-processes are responsible for combination automatically, through of process of transformation between the core and variability models, and the generation of new models that represent the implementation of the architecture of SPL or a instance model of SPL. Mechanisms for effective modularization of variability for architectures of SPL at model level. The concepts are described and measured with the execution of a case study of an SPL for management systems of transport electronic tickets

Contribution to flexible service coordination in mobile prosumer environments

Este trabajo de Tesis se desarrolla en el marco de los escenarios de ejecución distribuida de servicios móviles y contribuye a la definición y desarrollo del concepto de usuario prosumer. El usuario prosumer se caracteriza por utilizar su teléfono móvil para crear, proveer y ejecutar servicios. Este nuevo modelo de usuario contribuye al avance de la sociedad de la información, ya que el usuario prosumer se transforma de creador de contenidos a creador de servicios (estos últimos formados por contenidos y la lógica para acceder a ellos, procesarlos y representarlos). El objetivo general de este trabajo de Tesis es la provisión de un modelo de creación, distribución y ejecución de servicios para entorno móvil que permita a los usuarios no programadores (usuarios prosumer), pero expertos en un determinado dominio, crear y ejecutar sus propias aplicaciones y servicios. Para ello se definen, desarrollan e implementan metodologías, procesos, algoritmos y mecanismos adaptables a dominios específicos, para construir entornos de ejecución distribuida de servicios móviles para usuarios prosumer. La provisión de herramientas de creación adaptadas a usuarios no expertos es una tendencia actual que está siendo desarrollada en distintos trabajos de investigación. Sin embargo, no se ha propuesto una metodología de desarrollo de servicios que involucre al usuario prosumer en el proceso de diseño, desarrollo, implementación y validación de servicios. Este trabajo de Tesis realiza un estudio de las metodologías y tecnologías más innovadoras relacionadas con la co‐creación y utiliza este análisis para definir y validar una metodología que habilita al usuario para ser el responsable de la creación de servicios finales. Siendo los entornos móviles prosumer (mobile prosumer environments) una particularización de los entornos de ejecución distribuida de servicios móviles, en este trabajo se tesis se investiga en técnicas de adaptación, distribución, coordinación de servicios y acceso a recursos identificando como requisitos las problemáticas de este tipo de entornos y las características de los usuarios que participan en los mismos. Se contribuye a la adaptación de servicios definiendo un modelo de variabilidad que soporte la interdependencia entre las decisiones de personalización de los usuarios, incorporando mecanismos de guiado y detección de errores. La distribución de servicios se implementa utilizando técnicas de descomposición en árbol SPQR, cuantificando el impacto de separar cualquier servicio en distintos dominios. Considerando el plano de comunicaciones para la coordinación en la ejecución de servicios distribuidos hemos identificado varias problemáticas, como las pérdidas de enlace, conexiones, desconexiones y descubrimiento de participantes, que resolvemos utilizando técnicas de diseminación basadas en publicación subscripción y algoritmos Gossip. Para lograr una ejecución flexible de servicios distribuidos en entorno móvil, soportamos la adaptación a cambios en la disponibilidad de los recursos, proporcionando una infraestructura de comunicaciones para el acceso uniforme y eficiente a recursos. Se han realizado validaciones experimentales para evaluar la viabilidad de las soluciones propuestas, definiendo escenarios de aplicación relevantes (el nuevo universo inteligente, prosumerización de servicios en entornos hospitalarios y emergencias en la web de la cosas). Abstract This Thesis work is developed in the framework of distributed execution of mobile services and contributes to the definition and development of the concept of prosumer user. The prosumer user is characterized by using his mobile phone to create, provide and execute services. This new user model contributes to the advancement of the information society, as the prosumer is transformed from producer of content, to producer of services (consisting of content and logic to access them, process them and represent them). The overall goal of this Thesis work is to provide a model for creation, distribution and execution of services for the mobile environment that enables non‐programmers (prosumer users), but experts in a given domain, to create and execute their own applications and services. For this purpose I define, develop and implement methodologies, processes, algorithms and mechanisms, adapted to specific domains, to build distributed environments for the execution of mobile services for prosumer users. The provision of creation tools adapted to non‐expert users is a current trend that is being developed in different research works. However, it has not been proposed a service development methodology involving the prosumer user in the process of design, development, implementation and validation of services. This thesis work studies innovative methodologies and technologies related to the co‐creation and relies on this analysis to define and validate a methodological approach that enables the user to be responsible for creating final services. Being mobile prosumer environments a specific case of environments for distributed execution of mobile services, this Thesis work researches in service adaptation, distribution, coordination and resource access techniques, and identifies as requirements the challenges of such environments and characteristics of the participating users. I contribute to service adaptation by defining a variability model that supports the dependency of user personalization decisions, incorporating guiding and error detection mechanisms. Service distribution is implemented by using decomposition techniques based on SPQR trees, quantifying the impact of separating any service in different domains. Considering the communication level for the coordination of distributed service executions I have identified several problems, such as link losses, connections, disconnections and discovery of participants, which I solve using dissemination techniques based on publish‐subscribe communication models and Gossip algorithms. To achieve a flexible distributed service execution in mobile environments, I support adaptation to changes in the availability of resources, while providing a communication infrastructure for the uniform and efficient access to resources. Experimental validations have been conducted to assess the feasibility of the proposed solutions, defining relevant application scenarios (the new intelligent universe, service prosumerization in hospitals and emergency situations in the web of things).

A New Mouse Model for Marfan Syndrome Presents Phenotypic Variability Associated with the Genetic Background and Overall Levels of Fbn1 Expression

Marfan syndrome is an autosomal dominant disease of connective tissue caused by mutations in the fibrillin-1 encoding gene FBN1. Patients present cardiovascular, ocular and skeletal manifestations, and although being fully penetrant, MFS is characterized by a wide clinical variability both within and between families. Here we describe a new mouse model of MFS that recapitulates the clinical heterogeneity of the syndrome in humans. Heterozygotes for the mutant Fbn1 allele mg Delta(loxPneo), carrying the same internal deletion of exons 19-24 as the mg Delta mouse model, present defective microfibrillar deposition, emphysema, deterioration of aortic wall and kyphosis. However, the onset of a clinical phenotypes is earlier in the 129/Sv than in C57BL/6 background, indicating the existence of genetic modifiers of MFS between these two mouse strains. In addition, we characterized a wide clinical variability within the 129/Sv congenic heterozygotes, suggesting involvement of epigenetic factors in disease severity. Finally, we show a strong negative correlation between overall levels of Fbn1 expression and the severity of the phenotypes, corroborating the suggested protective role of normal fibrillin-1 in MFS pathogenesis, and supporting the development of therapies based on increasing Fbn1 expression.