Microcontroller-based peak current mode control using digital slope compensation

Microcontroller-based peak current mode control of a buck converter is investigated. The new solution uses a discrete time controller with digital slope compensation. This is implemented using only a single-chip microcontroller to achieve desirable cycle-by-cycle peak current limiting. The digital controller is implemented as a two-pole, two-zero linear difference equation designed using a continuous time model of the buck converter and a discrete time transform. Subharmonic oscillations are removed with digital slope compensation using a discrete staircase ramp. A 16 W hardware implementation directly compares analog and digital control. Frequency response measurements are taken and it is shown that the crossover frequency and expected phase margin of the digital control system match that of its analog counterpart.

An Ensemble Kalman Smoother for Nonlinear Dynamics

It is for mally proved that the general smoother for nonlinear dynamics can be for mulated as a sequential method, that is, obser vations can be assimilated sequentially during a for ward integration. The general filter can be derived from the smoother and it is shown that the general smoother and filter solutions at the final time become identical, as is expected from linear theor y. Then, a new smoother algorithm based on ensemble statistics is presented and examined in an example with the Lorenz equations. The new smoother can be computed as a sequential algorithm using only for ward-in-time model integrations. It bears a strong resemblance with the ensemble Kalman filter . The difference is that ever y time a new dataset is available during the for ward integration, an analysis is computed for all previous times up to this time. Thus, the first guess for the smoother is the ensemble Kalman filter solution, and the smoother estimate provides an improvement of this, as one would expect a smoother to do. The method is demonstrated in this paper in an intercomparison with the ensemble Kalman filter and the ensemble smoother introduced by van Leeuwen and Evensen, and it is shown to be superior in an application with the Lorenz equations. Finally , a discussion is given regarding the properties of the analysis schemes when strongly non-Gaussian distributions are used. It is shown that in these cases more sophisticated analysis schemes based on Bayesian statistics must be used.

Parametric conditional frailty models for recurrent cardiovascular events in the lipid study

Background Analysis of recurrent event data is frequently needed in clinical and epidemiological studies. An important issue in such analysis is how to account for the dependence of the events in an individual and any unobserved heterogeneity of the event propensity across individuals.Methods We applied a number of conditional frailty and nonfrailty models in an analysis involving recurrent myocardial infarction events in the Long-Term Intervention with Pravastatin in Ischaemic Disease study. A multiple variable risk prediction model was developed for both males and females. Results A Weibull model with a gamma frailty term fitted the data better than other frailty models for each gender. Among nonfrailty models the stratified survival model fitted the data best for each gender. The relative risk estimated by the elapsed time model was close to that estimated by the gap time model. We found that a cholesterol-lowering drug, pravastatin (the intervention being tested in the trial) had significant protective effect against the occurrence of myocardial infarction in men (HR¼0.71, 95% CI0.60–0.83). However, the treatment effect was not significant in women due to smaller sample size (HR¼0.75, 95% CI 0.51–1.10). There were no significant interactions between the treatment effect and each recurrent MI event (p¼0.24 for men and p¼0.55 for women). The risk of developing an MI event for a male who had an MI event during follow-up was about 3.4 (95% CI 2.6–4.4) times the risk compared with those who did not have an MI event. The corresponding relative risk for a female was about 7.8 (95% CI 4.4–13.6). Limitations The number of female patients was relatively small compared with their male counterparts, which may result in low statistical power to find real differences in the effect of treatment and other potential risk factors.Conclusions The conditional frailty model suggested that after accounting for all the risk factors in the model, there was still unmeasured heterogeneity of the risk for myocardial infarction, indicating the effect of subject-specific risk factors. These risk prediction models can be used to classify cardiovascular disease patients into different risk categories and may be useful for the most effective targeting of preventive therapies for cardiovascular disease.

How precarious employment affects health and safety at work : the case of temporary agency workers

International studies indicate temporary agency workers are more likely to be injured at work than other types of employees. However explanations for this have been less forthcoming. This paper seeks to begin filling this gap. A study was undertaken in Victoria, Australia, of occupational health and safety (OHS) amongst temporary agency workers drawing upon workers' compensation claim files for injured agency and directly hired workers from 1995-2001, and focus groups of temporary agency workers conducted in 2003. In analyzing the results, use was made of risk factors identified in a model that has been developed to explain how precarious employment affects OHS--the pressure, disorganization and regulatory failure (PDR) model (Quinlan and Bohle, 2004, 2009). Drawing principally on qualitative data, the paper finds that whilst agency workers share common risk factors with other forms of precarious workers, unique characteristics associated with the triangular nature of agency employment heighten their vulnerability further.

Modelling grouped survival times in toxicological studies using generalized additive models

A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.

A theoretical connection between inflation and income inequality

This work investigates the effects of inflation on income distribution. We use a dynamic shopping-time model to show that a differentiated access to transacting technologies by poor and rich consumers is enough to generate a positive link between inflation and the Gini coefficient of income distribution.

On the optimality of the Friedman Rule with heterogeneous agents and non-linear income taxation

We study the optimal “inflation tax” in an environment with heterogeneous agents and non-linear income taxes. We first derive the general conditions needed for the optimality of the Friedman rule in this setup. These general conditions are distinct in nature and more easily interpretable than those obtained in the literature with a representative agent and linear taxation. We then study two standard monetary specifications and derive their implications for the optimality of the Friedman rule. For the shopping-time model the Friedman rule is optimal with essentially no restrictions on preferences or transaction technologies. For the cash-credit model the Friedman rule is optimal if preferences are separable between the consumption goods and leisure, or if leisure shifts consumption towards the credit good. We also study a generalized model which nests both models as special cases.

Trust-based trade

There is substantially more trade within national borders than across borders. An important explanation for this fact is the weak enforcement of international contracts. We develop a model in which agents build reputations to overcome this institutional failure. The model describes the interplay between institutional quality, reputations and the dynamics of international trade. It also rationalizes several empirical regularities. We find that history matters for trade volumes, but that its effects vary with the institutional setting of the country. The same is true for the efticacy of trade liberalization programs. Moreover, while stricter enforcement of contracts enhances trade in the short run, it makes it harder for individual traders to develop good reputations. We show that this indirect negative effect may produce an "institutional trap": for sufliciently low initial levels of contract enforcement, a small tightening in enforcement reduces future trade fiows. We find also that search frictions aggravate the problems created by weak enforceability of contracts, even if they impose no direct cost on agents. The model allows extensions in several directions. We outline two of them, indicating how one could study transnational networks and the effects of firm heterogeneity within our structure.

Predição em modelos de tempo de falha acelerado com efeito aleatório para avaliação de riscos de falha em poços petrolíferos

We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.

Testes de hipóteses em modelos de sobrevivência com Fração de cura

Survival models deals with the modeling of time to event data. However in some situations part of the population may be no longer subject to the event. Models that take this fact into account are called cure rate models. There are few studies about hypothesis tests in cure rate models. Recently a new test statistic, the gradient statistic, has been proposed. It shares the same asymptotic properties with the classic large sample tests, the likelihood ratio, score and Wald tests. Some simulation studies have been carried out to explore the behavior of the gradient statistic in fi nite samples and compare it with the classic statistics in diff erent models. The main objective of this work is to study and compare the performance of gradient test and likelihood ratio test in cure rate models. We first describe the models and present the main asymptotic properties of the tests. We perform a simulation study based on the promotion time model with Weibull distribution to assess the performance of the tests in finite samples. An application is presented to illustrate the studied concepts

Influência das cargas selecionadas na determinação da potência crítica determinada no ergômetro de braço em dois modelos lineares

O objetivo deste estudo foi verificar o efeito da seleção das cargas e do modelo utilizado para a determinação da PC no ergômetro de braço. Participaram do estudo oito voluntários do sexo masculino, que praticavam atividade física regularmente e eram aparentemente saudáveis. Os sujeitos realizaram quatro testes com cargas constantes mantidas até a exaustão voluntária no ergômetro de braço UBE 2462-Cybex. As cargas foram individualmente selecionadas para induzir a fadiga entre 1 e 15 minutos. Para cada sujeito, a determinação da PC foi realizada através de dois modelos lineares: potência-1/tempo e trabalho-tempo. em cada um dos modelos, foram utilizadas todas as potências (1), as três maiores (2) e as três menores (3). As PC encontradas no modelo potência-1/tempo e trabalho-tempo para a condição 3 (177,5 + 29,5; 173,9 + 33,3, respectivamente) foram significantemente menores do que as da condição 2 (190,5 + 23,2; 183,4 + 22,3, respectivamente), não existindo diferenças destas com as da condição 1 (184,2 + 25,4; 176,4 + 28,8, respectivamente). As PC determinadas no modelo potência-1/tempo para as condições 1 e 2 foram significantemente maiores do que as determinadas no modelo trabalho-tempo, não existindo diferenças para a condição 3. Pode-se concluir que as cargas selecionadas e o modelo utilizado interferem na determinação da PC encontrada no ergômetro de braço, podendo interferir no tempo de exaustão durante o exercício submáximo realizado em cargas relativas a este índice.

Germinação de Ternstroemia brasiliensis Cambess. (Pentaphylacaceae) de floresta de restinga

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Dependência térmica da germinação de sementes de Drymaria cordata (L.) Willd. ex Roem. & Schult. (Cariophyllaceae)

A temperatura representa um importante fator ambiental regulador da germinação de sementes. Procurou-se avaliar a resposta de sementes de D. cordata à temperatura, com base no modelo de graus-dia, testando-se assim a eficiência desse modelo em descrever o comportamento germinativo da semente em diferentes regimes térmicos. Testou-se também a resposta das sementes à luz, concluindo-se que a luz branca promove a germinação. As temperaturas mínima, ótima e máxima de germinação foram, respectivamente, 17,1, 26 e 33,4 ºC. Considerando-se que a velocidade de germinação de D. cordata variou com a temperatura numa relação aproximadamente linear, o modelo de graus-dia pode ser uma ferramenta válida para se estudar a dependência da temperatura da germinação dessas sementes. Uma possível aquisição de dormência durante a incubação isotérmica pode exigir a aplicação de outros modelos que descrevam melhor o comportamento germinativo de D. cordata em diferentes regimes térmicos.

Analysis of culling probability in dairy buffalo using survival models

In order to contribute to the genetic breeding programs of buffaloes, this study aimed to determine the influence of environmental effects on the stayability (ST) of dairy female Murrah buffalo in the herd. Data from 1016 buffaloes were used. ST was defined as the ability of the female to remain in the herd for 1, 2, 3, 4, 5 or 6 years after the first calving. Environmental effects were studied by survival analysis, adjusted to the fixed effects of farm, year and season of birth, class of first-lactation milk yield and age at first calving. The data were analyzed using the LIFEREG procedure of the SAS program that fits parametric models to failure time data (culling or ST = 0), and estimates parameters by maximum likelihood estimation. Breeding farm, year of birth and first-lactation milk yield significantly influenced (P < 0.0001) the ST to the specific ages (1 to 6 years after the first calving). Buffaloes that were older at first calving presented higher probabilities of being culled 1 year after the first calving, without any effect on culling at older ages. Buffaloes with a higher milk yield at first calving presented a lower culling probability and remained for a longer period of time in the herd. The effects of breeding farm, year of birth and first-lactation milk yield should be included in models used for the analysis of ST in buffaloes. Copyright © The Animal Consortium 2010.

Metodologia para análise da dependência térmica da germinação pelo modelo de grausdia

The effects of temperature on the rate of biological processes such as the germination are reported in several papers. The analysis of the thermal effect can be performed either from numerical indices or germination curves, which is usually presented as the accumulated percentage of germination versus time. Such curves can be fitted by empirical models and generally they offer a better description of the time-course of germination than single-value indices. On the other hand, in analyzing the germination curves, a question arises whether the model parameters have biological meaning. Thus, it is desirable that the model parameters both describe properly the germination curve and have biological meaning, which often does not occur. Considering the involvement of populations and percentages in germination assays, an analytical model has been widely used in the last two decades which is based on the concept of thermal time. This article discusses the conceptual basis and provides procedures for applying the thermal-time model in germination studies by using the probit regression method, both at infra and supra-optimal temperatures.