Density and spatial distribution of Atta sexdens rubropilosa and Atta laevigata colonies (Hym., Formicidae) in Eucalyptus spp. forests

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribuição espacial e plano amostragem seqüencial para a lagarta do minador-dos-citros Phyllocnistis citrella Stainton, 1856 (Lepidoptera: Gracillariidae), em laranjeira 'Pêra-Rio' Citrus sinensis (L.) Osbeck

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Dinâmica populacional, distribuição espacial e plano de amostragem sequencial de Euschistus heros (Fabricius, 1794) (Heteroptera: Pentatomidae) em cultivares de soja

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

Prevalence of gastro esophageal reflux disease following the Montreal Consensus and its association with Helicobacter pylori infection and obesity in a random sample of adults of Ciudad Juarez, Mexico, 2004.

Gastroesophageal reflux disease is a common condition affecting 25 to 40% of the population and causes significant morbidity in the U.S., accounting for at least 9 million office visits to physicians with estimated annual costs of $10 billion. Previous research has not clearly established whether infection with Helicobacter pylori, a known cause of peptic ulcer, atrophic gastritis and non cardia adenocarcinoma of the stomach, is associated with gastroesophageal reflux disease. This study is a secondary analysis of data collected in a cross-sectional study of a random sample of adult residents of Ciudad Juarez, Mexico, that was conducted in 2004 (Prevalence and Determinants of Chronic Atrophic Gastritis Study or CAG study, Dr. Victor M. Cardenas, Principal Investigator). In this study, the presence of gastroesophageal reflux disease was based on responses to the previously validated Spanish Language Dyspepsia Questionnaire. Responses to this questionnaire indicating the presence of gastroesophageal reflux symptoms and disease were compared with the presence of H. pylori infection as measured by culture, histology and rapid urease test, and with findings of upper endoscopy (i.e., hiatus hernia and erosive and atrophic esophagitis). The prevalence ratio was calculated using bivariate, stratified and multivariate negative binomial logistic regression analyses in order to assess the relation between active H. pylori infection and the prevalence of gastroesophageal reflux typical syndrome and disease, while controlling for known risk factors of gastroesophageal reflux disease such as obesity. In a random sample of 174 adults 48 (27.6%) of the study participants had typical reflux syndrome and only 5% (or 9/174) had gastroesophageal reflux disease per se according to the Montreal consensus, which defines reflux syndromes and disease based on whether the symptoms are perceived as troublesome by the subject. There was no association between H. pylori infection and typical reflux syndrome or gastroesophageal reflux disease. However, we found that in this Northern Mexican population, there was a moderate association (Prevalence Ratio=2.5; 95% CI=1.3, 4.7) between obesity (≥30 kg/m2) and typical reflux syndrome. Management and prevention of obesity will significantly curb the growing numbers of persons affected by gastroesophageal reflux symptoms and disease in Northern Mexico. ^

Elección de la duración del viaje vacacional: una aproximación con modelos de recuento

La duración del viaje vacacional es una decisión del turista con unas implicaciones fundamentales para las organizaciones turísticas, pero que ha recibido una escasa atención por la literatura. Además, los escasos estudios se han centrado en los destinos costeros, cuando el turismo de interior se está erigiendo como una alternativa importante en algunos países. El presente trabajo analiza los factores determinantes de la elección temporal del viaje turístico, distinguiendo el tipo de destino elegido -costa e interior-, y proponiendo varias hipótesis acerca de la influencia de las características de los individuos relacionadas con el destino, de las restricciones personales y de las características sociodemográficas. La metodología aplicada estima, como novedad en este tipo de decisiones, un Modelo Binomial Negativo Truncado que evita los sesgos de estimación de los modelos de regresión y el supuesto restrictivo de igualdad media-varianza del Modelo de Poisson. La aplicación empírica realizada en España sobre una muestra de 1.600 individuos permite concluir, por un lado, que el Modelo Binomial Negativo es más adecuado que el de Poisson para realizar este tipo de análisis. Por otro lado, las dimensiones determinantes de la duración del viaje vacacional son, para ambos destinos, el alojamiento en hotel y apartamento propio, las restricciones temporales, la edad del turista y la forma de organizar el viaje; mientras que el tamaño de la ciudad de residencia y el atributo “precios baratos” es un aspecto diferencial de la costa; y el alojamiento en apartamentos alquilados lo es de los destinos de interior.

Effects of roadway geometric features on run-off road crashes on the Florida State Highway System

Run-off-road (ROR) crashes have increasingly become a serious concern for transportation officials in the State of Florida. These types of crashes have increased proportionally in recent years statewide and have been the focus of the Florida Department of Transportation. The goal of this research was to develop statistical models that can be used to investigate the possible causal relationships between roadway geometric features and ROR crashes on Florida's rural and urban principal arterials. ^ In this research, Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) Regression models were used to better model the excessive number of roadway segments with no ROR crashes. Since Florida covers a diverse area and since there are sixty-seven counties, it was divided into four geographical regions to minimize possible unobserved heterogeneity. Three years of crash data (2000–2002) encompassing those for principal arterials on the Florida State Highway System were used. Several statistical models based on the ZIP and ZINB regression methods were fitted to predict the expected number of ROR crashes on urban and rural roads for each region. Each region was further divided into urban and rural areas, resulting in a total of eight crash models. A best-fit predictive model was identified for each of these eight models in terms of AIC values. The ZINB regression was found to be appropriate for seven of the eight models and the ZIP regression was found to be more appropriate for the remaining model. To achieve model convergence, some explanatory variables that were not statistically significant were included. Therefore, strong conclusions cannot be derived from some of these models. ^ Given the complex nature of crashes, recommendations for additional research are made. The interaction of weather and human condition would be quite valuable in discerning additional causal relationships for these types of crashes. Additionally, roadside data should be considered and incorporated into future research of ROR crashes. ^

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Obesity, diet quality and absenteeism in a working population

The relationship between workplace absenteeism and adverse lifestyle factors (smoking, physical inactivity and poor dietary patterns) remains ambiguous. Reliance on self-reported absenteeism and obesity measures may contribute to this uncertainty. Using objective absenteeism and health status measures, the present study aimed to investigate what health status outcomes and lifestyle factors influence workplace absenteeism. Cross-sectional data were obtained from a complex workplace dietary intervention trial, the Food Choice at Work Study. Four multinational manufacturing workplaces in Cork, Republic of Ireland. Participants included 540 randomly selected employees from the four workplaces. Annual count absenteeism data were collected. Physical assessments included objective health status measures (BMI, midway waist circumference and blood pressure). FFQ measured diet quality from which DASH (Dietary Approaches to Stop Hypertension) scores were constructed. A zero-inflated negative binomial (zinb) regression model examined associations between health status outcomes, lifestyle characteristics and absenteeism. The mean number of absences was 2·5 (sd 4·5) d. After controlling for sociodemographic and lifestyle characteristics, the zinb model indicated that absenteeism was positively associated with central obesity, increasing expected absence rate by 72 %. Consuming a high-quality diet and engaging in moderate levels of physical activity were negatively associated with absenteeism and reduced expected frequency by 50 % and 36 %, respectively. Being in a managerial/supervisory position also reduced expected frequency by 50 %. To reduce absenteeism, workplace health promotion policies should incorporate recommendations designed to prevent and manage excess weight, improve diet quality and increase physical activity levels of employees.

Beam Energy Dependence Of Moments Of The Net-charge Multiplicity Distributions In Au+au Collisions At Rhic.

We report the first measurements of the moments--mean (M), variance (σ(2)), skewness (S), and kurtosis (κ)--of the net-charge multiplicity distributions at midrapidity in Au+Au collisions at seven energies, ranging from sqrt[sNN]=7.7 to 200 GeV, as a part of the Beam Energy Scan program at RHIC. The moments are related to the thermodynamic susceptibilities of net charge, and are sensitive to the location of the QCD critical point. We compare the products of the moments, σ(2)/M, Sσ, and κσ(2), with the expectations from Poisson and negative binomial distributions (NBDs). The Sσ values deviate from the Poisson baseline and are close to the NBD baseline, while the κσ(2) values tend to lie between the two. Within the present uncertainties, our data do not show nonmonotonic behavior as a function of collision energy. These measurements provide a valuable tool to extract the freeze-out parameters in heavy-ion collisions by comparing with theoretical models.

Indirect evidence of density-dependent population regulation in Aponomma hydrosauri (Acari : Ixodidae), an ectoparasite of reptiles

The extent to which density-dependent processes regulate natural populations is the subject of an ongoing debate. We contribute evidence to this debate showing that density-dependent processes influence the population dynamics of the ectoparasite Aponomma hydrosauri (Acari: Ixodidae), a tick species that infests reptiles in Australia. The first piece of evidence comes from an unusually long-term dataset on the distribution of ticks among individual hosts. If density-dependent processes are influencing either host mortality or vital rates of the parasite population, and those distributions can be approximated with negative binomial distributions, then general host-parasite models predict that the aggregation coefficient of the parasite distribution will increase with the average intensity of infections. We fit negative binomial distributions to the frequency distributions of ticks on hosts, and find that the estimated aggregation coefficient k increases with increasing average tick density. This pattern indirectly implies that one or more vital rates of the tick population must be changing with increasing tick density, because mortality rates of the tick's main host, the sleepy lizard, Tiliqua rugosa, are unaffected by changes in tick burdens. Our second piece of evidence is a re-analysis of experimental data on the attachment success of individual ticks to lizard hosts using generalized linear modelling. The probability of successful engorgement decreases with increasing numbers of ticks attached to a host. This is direct evidence of a density-dependent process that could lead to an increase in the aggregation coefficient of tick distributions described earlier. The population-scale increase in the aggregation coefficient is indirect evidence of a density-dependent process or processes sufficiently strong to produce a population-wide pattern, and thus also likely to influence population regulation. The direct observation of a density-dependent process is evidence of at least part of the responsible mechanism.

Age-period-cohort effects in the incidence of hip fractures: political and economic events are coincident with changes in risk

Introduction: Healthcare improvements have allowed prevention but have also increased life expectancy, resulting in more people being at risk. Our aim was to analyse the separate effects of age, period and cohort on incidence rates by sex in Portugal, 2000–2008. Methods: From the National Hospital Discharge Register, we selected admissions (aged ≥49 years) with hip fractures (ICD9-CM, codes 820.x) caused by low/moderate trauma (falls from standing height or less), readmissions and bone cancer cases. We calculated person-years at risk using population data from Statistics Portugal. To identify period and cohort effects for all ages, we used an age–period–cohort model (1-year intervals) followed by generalised additive models with a negative binomial distribution of the observed incidence rates of hip fractures. Results: There were 77,083 hospital admissions (77.4 % women). Incidence rates increased exponentially with age for both sexes (age effect). Incidence rates fell after 2004 for women and were random for men (period effect). There was a general cohort effect similar in both sexes; risk of hip fracture altered from an increasing trend for those born before 1930 to a decreasing trend following that year. Risk alterations (not statistically significant) coincident with major political and economic change in the history of Portugal were observed around birth cohorts 1920 (stable–increasing), 1940 (decreasing–increasing) and 1950 (increasing–decreasing only among women). Conclusions: Hip fracture risk was higher for those born during major economically/politically unstable periods. Although bone quality reflects lifetime exposure, conditions at birth may determine future risk for hip fractures.

Zero-Time Kidney Histology Predicts Early Graft Function

Our purposes are to determine the impact of histological factors observed in zero-time biopsies on early post transplant kidney allograft function. We specifically want to compare the semi-quantitative Banff Classification of zero time biopsies with quantification of % cortical area fibrosis. Sixty three zero-time deceased donor allograft biopsies were retrospectively semiquantitatively scored using Banff classification. By adding the individual chronic parameters a Banff Chronic Sum (BCS) Score was generated. Percentage of cortical area Picro Sirius Red (%PSR) staining was assessed and calculated with a computer program. A negative linear regression between %PSR/ GFR at 3 year post-transplantation was established (Y=62.08 +-4.6412X; p=0.022). A significant negative correlation between arteriolar hyalinosis (rho=-0.375; p=0.005), chronic interstitial (rho=0.296; p=0.02) , chronic tubular ( rho=0.276; p=0.04) , chronic vascular (rho= -0.360;P=0.007), BCS (rho=-0.413; p=0.002) and GFR at 3 years were found. However, no correlation was found between % PSR, Ci, Ct or BCS. In multivariate linear regression the negative predictive factors of 3 years GFR were: BCS in histological model; donor kidney age, recipient age and black race in clinical model. The BCS seems a good and easy to perform tool, available to every pathologist, with significant predictive short-term value. The %PSR predicts short term kidney function in univariate study and involves extra-routine and expensive-time work. We think that %PSR must be regarded as a research instrument.

Institutions and firm formation: An empirical analysis of Portuguese municipalities

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics