Discrete time Non-homogeneous Semi-Markov Processes applied to Models for Disability Insurance

In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.

Ultrastructural, Antigenic and Physicochemical Characterization of the Mojuí dos Campos (Bunyavirus) Isolated from Bat in the Brazilian Amazon Region

The Mojuí dos Campos virus (MDCV) was isolated from the blood of an unidentified bat (Chiroptera) captured in Mojuí dos Campos, Santarém, State of Pará, Brazil, in 1975 and considerated to be antigenically different from other 102 arboviruses belonging to several antigenic groups isolated in the Amazon region or another region by complement fixation tests. The objective of this work was to develop a morphologic, an antigenic and physicochemical characterization of this virus. MDCV produces cytopathic effect in Vero cells, 24 h post-infection (p.i), and the degree of cellular destruction increases after a few hours. Negative staining electron microscopy of the supernatant of Vero cell cultures showed the presence of coated viral particles with a diameter of around 98 nm. Ultrathin sections of Vero cells, and brain and liver of newborn mice infected with MDCV showed an assembly of the viral particles into the Golgi vesicles. The synthesis kinetics of the proteins for MDCV were similar to that observed for other bunyaviruses, and viral proteins could be detected as early as 6 h p.i. Our results reinforce the original studies which had classified MDCV in the family Bunyaviridae, genus Bunyavirus as an ungrouped virus, and it may represent the prototype of a new serogroup.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

The cost-effectiveness and public health benefit of nalmefene added to psychosocial support for the reduction of alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels: a Markov model.

OBJECTIVES: To determine whether nalmefene combined with psychosocial support is cost-effective compared with psychosocial support alone for reducing alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels (DRLs) as defined by the WHO, and to evaluate the public health benefit of reducing harmful alcohol-attributable diseases, injuries and deaths. DESIGN: Decision modelling using Markov chains compared costs and effects over 5 years. SETTING: The analysis was from the perspective of the National Health Service (NHS) in England and Wales. PARTICIPANTS: The model considered the licensed population for nalmefene, specifically adults with both alcohol dependence and high/very high DRLs, who do not require immediate detoxification and who continue to have high/very high DRLs after initial assessment. DATA SOURCES: We modelled treatment effect using data from three clinical trials for nalmefene (ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941)). Baseline characteristics of the model population, treatment resource utilisation and utilities were from these trials. We estimated the number of alcohol-attributable events occurring at different levels of alcohol consumption based on published epidemiological risk-relation studies. Health-related costs were from UK sources. MAIN OUTCOME MEASURES: We measured incremental cost per quality-adjusted life year (QALY) gained and number of alcohol-attributable harmful events avoided. RESULTS: Nalmefene in combination with psychosocial support had an incremental cost-effectiveness ratio (ICER) of £5204 per QALY gained, and was therefore cost-effective at the £20,000 per QALY gained decision threshold. Sensitivity analyses showed that the conclusion was robust. Nalmefene plus psychosocial support led to the avoidance of 7179 alcohol-attributable diseases/injuries and 309 deaths per 100,000 patients compared to psychosocial support alone over the course of 5 years. CONCLUSIONS: Nalmefene can be seen as a cost-effective treatment for alcohol dependence, with substantial public health benefits. TRIAL REGISTRATION NUMBERS: This cost-effectiveness analysis was developed based on data from three randomised clinical trials: ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941).

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Bayesian Markov chain Monte Carlo inversion of geophysical data for the purpose of estimating the hydraulic properties of the unsaturated zone

Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

Análise de chuvas intensas a partir da desagregação das chuvas diárias de Lages e de Campos Novos (SC)

O conhecimento da magnitude das chuvas intensas é de fundamental importância para a elaboração de projetos hidráulicos e gerenciamento dos recursos hídricos em engenharia, além do dimensionamento de estruturas para o controle de erosão hídrica na conservação do solo. No entanto, informações sobre a intensidade da chuva só podem ser obtidas diretamente de pluviogramas, os quais nem sempre estão disponíveis no local de estudo, sendo mais comum a presença de dados de pluviômetro (chuva de "um dia"). Nesse caso, pode-se utilizar o método que desagrega as chuvas diárias em chuvas de 24 horas de duração e menores, possibilitando, assim, estimar as intensidades correspondentes. O estudo foi desenvolvido na Universidade do Estado de Santa Catarina (UDESC), em Lages (SC), durante o primeiro semestre de 1996. Utilizaram-se séries anuais de chuvas máximas de "um dia", obtidas de pluviômetros localizados em Lages e Campos Novos (SC), durante um período de 30 anos consecutivos (1966 a 1995). Aplicou-se a distribuição estatística de Gumbel para a obtenção das alturas de chuvas em períodos de retorno de 2, 5, 10, 15, 20, 25, 50 e 100 anos e, a partir destas, o modelo de desagregação de chuvas diárias, obtendo-se as alturas máximas esperadas para tempos de duração entre 24 horas e 5 minutos e suas respectivas intensidades máximas médias. Foram obtidas as curvas intensidade-duração-freqüência (I-D-F) para os tempos de retorno selecionados, bem como suas relações matemáticas. Para Lages, a equação da família de curvas I-D-F obtida foi: I = 2050TR0,20 (T + 29,41)-0,89 e, para Campos Novos, a equação foi I = 2157TR0,17(T + 29,42) -0,89: , em que i é a intensidade máxima média (mm h-1),T a duração (minuto) e TR o período de retorno (ano) das chuvas.

Caracterização da matéria orgânica e micromorfologia de solos sob Campos de Altitude no parque estadual da Serra do Brigadeiro (MG)

O Parque Estadual da Serra do Brigadeiro (MG) engloba uma área de Mata Atlântica em uma parte da Serra da Mantiqueira. Nas porções mais elevadas da serra (acima de 1.600 m), encontram-se os Campos de Altitude, caracterizados por uma composição florística ímpar, elevado grau de endemismo e pela presença de várias espécies ameaçadas de extinção. Foram amostrados, na área do Campos de Altitude, um Neossolo Litólico, um Espodossolo Ferrocárbico, um Cambissolo Húmico e, na área de Mata Atlântica, um Latossolo Vermelho-Amarelo. Todos os solos estudados apresentaram-se álicos, com baixo pH e baixa capacidade de troca catiônica efetiva, além de acúmulo de matéria orgânica humificada. Os solos estão estreitamente relacionados com a cobertura vegetal, observando-se uma vegetação de menor biomassa sobre materiais mais oligotróficos. Análises micromorfológicas indicaram feições relacionadas com processos de podzolização. A interpretação das formas identificadas nas lâminas de solo permitiu inferências sobre os processos de gênese dos solos, não identificados pelas análises químicas. As substâncias húmicas foram fracionadas, indicando elevado teor de ácidos fúlvicos. Os teores dessa fração orgânica estiveram associados a formas pouco cristalinas de Fe e Al, extraídas pelo oxalato, indicando o papel da matéria orgânica na mobilidade desses elementos. Análises espectroscópicas das substâncias húmicas, como espectrometria no infravermelho e de ressonância paramagnética eletrônica, indicaram alta aromaticidade das substâncias húmicas produzidas sob vegetação de Campos de Altitude, em relação às substâncias húmicas produzidas sob vegetação florestal. Esta maior aromaticidade pode estar relacionada com o efeito do fogo ou com a própria constituição fisiológica da cobertura vegetal. A associação entre os solos em processo de podzolização e a vegetação de Campos de Altitude revela maior eficiência da matéria orgânica formada nesses ambientes nos processos de queluviação e intemperismo da fração mineral. Esta hipótese é sustentada pela caracterização das substâncias húmicas extraídas deste pedoambiente.

Diagnose nutricional da cana-de-açúcar em campos dos Goytacazes (RJ)

Este trabalho objetivou avaliar o estado nutricional de lavouras canavieiras em Campos dos Goytacazes (RJ) por meio de teores adequados e do Sistema Integrado de Diagnose e Recomendação (DRIS), bem como comparar a diagnose nutricional de padrões descritos na literatura com a diagnose obtida de padrões calibrados regionalmente. Foram coletadas 126 amostras foliares de cana-de-açúcar aos quatro meses de idade das plantas. Essas amostras foram analisadas quimicamente para N, P, K, Ca, Mg, S, Cu, Mn e Zn, cujos teores foram comparados com: (a) os teores considerados adequados pela literatura, (b) os teores médios de canaviais de alta produtividade localizados em Campos dos Goytacazes e (c) os teores adequados obtidos do DRIS, determinando-se a freqüência com que o teor de cada nutriente foi inferior aos padrões mencionados. As amostras coletadas foram submetidas à diagnose por meio do DRIS, determinando-se a freqüência com que o índice DRIS de cada nutriente apresentou valor negativo e a freqüência com que o índice DRIS de cada nutriente foi o mais negativo dentro de cada amostra. Padrões de diagnose nutricional desenvolvidos em locais distintos forneceram diagnósticos nutricionais diferentes na cana-de-açúcar. As diagnoses nutricionais obtidas de padrões calibrados regionalmente (teores adequados e DRIS) indicaram K, P e S como os principais nutrientes limitantes, enquanto as diagnoses nutricionais de padrões descritos na literatura indicaram N, Zn e Cu como os principais nutrientes limitantes. A calibração regional dos padrões de diagnose da cana-de-açúcar é de grande importância para garantir o sucesso da avaliação do estado nutricional da cana-de-açúcar em Campos dos Goytacazes (RJ).