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This paper analyzes the productivity of farms across 370 municipalities in the Center-West region of Brazil. A stochastic frontier model with a latent spatial structure is proposed to account for possible unknown geographical variation of the outputs. The paper compares versions of the model that include the latent spatial effect in the mean of output or as a variable that conditions the distribution of inefficiency, include or not observed municipal variables, and specify independent normal or conditional autoregressive priors for the spatial effects. The Bayesian paradigm is used to estimate the proposed models. As the resultant posterior distributions do not have a closed form, stochastic simulation techniques are used to obtain samples from them. Two model comparison criteria provide support for including the latent spatial effects, even after considering covariates at the municipal level. Models that ignore the latent spatial effects produce significantly different rankings of inefficiencies across agents. [ABSTRACT FROM AUTHOR]

The Diplostomidae include a large group of flatworms with complex life cycles and are frequently found parasitizing the eyes and central nervous system of freshwater fishes. The morphological identification of the metacercariae at species level is not always possible. Thus, molecular tools have become essential to assist in the parasite species determination. This study was aimed at describing two diplostomid metacercariae found in freshwater fish in São Paulo, Brazil, based on morphological characters and in the genetic characterization of COI sequences. Our results showed that the two recognized taxa (Tylodelphys sp. and Diplostomidae gen. sp.) appear to be different from the species already described in South America. Tylodelphys sp. differs morphologically from Tylodelphys xenopi, T. mashonense, T. jenynsiae, and T. scheuringi. The metacercariae of T. clavata and T. conifera are smaller than Tylodelphys sp., while T. podicipina is larger than the metacercariae described here. The phylogenetic analysis of COI sequences yielded Tylodelphys sp. as the sister species of Tylodelphys sp. 4, a species reported from the brain of the eleotrid Gobiomorus maculatus in Oaxaca, Mexico. The metacercariae identified as Diplostomidae gen. sp. are morphologically different from the known diplostomid metacercariae and did not match with other diplostomid sequences available. Diplostomidae gen. sp. is recovered as the sister species of Diplostomum ardeae. Although the morphological evidence and the COI sequences differentiate the metacercariae found, the absence of adult specimens of both species precludes the specific designation. This is one of the first papers that use an integrative taxonomy approach to describe the species diversity of diplostomid trematodes in Brazil. [ABSTRACT FROM AUTHOR]

Parametric and non-parametric approaches for rainfall generation have been widely used in hydrological simulation. Both approaches, however, show inherent limitations for representing precipitation extremes. Hence, a stochastic generator able to represent all the range of precipitation amounts is desired. This paper presents a mixed stochastic generator designed for this purpose: the low to moderate rainfall amounts are modeled by the non-parametric approach, avoiding the adjustment of theoretical probability density functions to this range of precipitation and, the extreme rainfall amounts are modeled by the parametric approach, employing the upper-bounded 4-parameter log-normal (LN4) distribution function, with the upper bound estimated under a Bayesian framework, having the at-site probable maximum precipitation (PMP) as a reference value. The mixed generator was used for simulating a 10,000-year long series in the Pará river catchment, in the Brazilian state of Minas Gerais. Results showed that mean daily rainfall, the correspondent standard deviation, coefficient of skewness, number of wet days, and mean monthly and annual rainfall are adequately reproduced. Furthermore, by combining in a logical structure of analysis a prior distribution describing the uncertainties about the PMP estimates and the rainfall data, one can expect more reliable estimates of rare and extreme quantiles and their related uncertainties. [ABSTRACT FROM AUTHOR]

Flood mapping is a crucial tool for assisting urban planning and emergency response plans and, consequently, preventing or reducing the risks associated with flood disasters. However, in developing countries that often lack or have limited data, to produce such maps is a challenging task. When topographic data are lacking, digital elevation models (DEMs) derived from the Shuttle Radar Topography Mission (SRTM) are frequently used as a freely available surrogate, albeit with additional uncertainty. This work presents an integrated framework to investigate flood inundation areas using a Bayesian approach, while including steps for calibrating SRTM data and determining the river bathymetry below the WSE. A flood event in the Itaqui municipality, in the state of Rio Grande do Sul, southern Brazil is used to demonstrate the proposed framework. Findings suggest benefits in using calibrated SRTM DEMs for flood mapping regardless of whether flood inundation areas were derived directly from projections of WSEs on the terrain or based on hydraulic simulations. Results further highlight the potential of using a Bayesian approach to improve quality and reliability of flood hazards maps, especially in regions that lack topographic data. [ABSTRACT FROM AUTHOR]

Background: Brazil has one of the highest prevalence of cesarean sections in the world. The private health system is responsible for carrying out most of these surgical procedures. A quality improvement project called Adequate Childbirth Project ("Projeto Parto Adequado"- PPA) was developed to identify models of care for labor and childbirth, which place value on vaginal birth and reduce the frequency of cesarean sections without a clinical indication. This research aims to evaluate the implementation of PPA in private hospitals in Brazil. Method: Evaluative hospital-based survey, carried out in 2017, in 12 private hospitals, including 4,322 women. We used a Bayesian network strategy to develop a theoretical model for implementation analysis. We estimated and compared the degree of implementation of two major driving components of PPA—"Participation of women" and "Reorganization of care" – among the 12 hospitals and according to type of hospital (belonging to a health insurance company or not). To assess whether the degree of implementation was correlated with the rate of vaginal birth data we used the Bayesian Network and compared the difference between the group "Exposed to the PPA model of care" and the group "Standard of care model". Results: PPA had a low degree of implementation in both components "Reorganization of Care" (0.17 – 0.32) and "Participation of Women" (0.21 – 0.34). The combined implementation score was 0.39–0.64 and was higher in hospitals that belonged to a health insurance company. The vaginal birth rate was higher in hospitals with a higher degree of implementation of PPA. Conclusion: The degree of implementation of PPA was low, which reflects the difficulties in changing childbirth care practices. Nevertheless, PPA increased vaginal birth rates in private hospitals with higher implementation scores. PPA is an ongoing quality improvement project and these results demonstrate the need for changes in the involvement of women and the care offered by the provider. [ABSTRACT FROM AUTHOR]

This paper provides evidence on monetary policy transmission for five key emerging market economies: Brazil, Russia, India, China, and South Africa. Monetary policy (interest rate) shocks are identified using modern Bayesian methods along with the more recent sign restrictions approach. We find that contractionary monetary policy has a strong and negative effect on output. We also show that such contractionary monetary policy shocks do tend to stabilize inflation in these countries in the short term, while producing a strongly persistent negative effect on real equity prices. Overall, the impulse responses are robust to the alternative identification procedures. [ABSTRACT FROM AUTHOR]

This paper develops a novel spatial process using generalized skew-normal/independent distributions when the usual Gaussian process assumptions are questionable and transformation to a Gaussian random field is not appropriate. The proposed model provides flexibility in capturing the effects of skewness and heavy tail behavior of the data while maintaining spatial dependence using a conditional autoregressive structure. We use Bayesian hierarchical methods to fit such models and show the validity of our approach. Furthermore, we use Bayesian model selection criteria to choose appropriate models for a real data set on the dengue fever infection in the state of Rio de Janeiro. [ABSTRACT FROM AUTHOR]

Abstract: One of the most desired aspects for power suppliers is the acquisition/sale of energy for a future demand. However, power consumption forecast is characterized not only by the variables of the power system itself, but also related to social–economic and climatic factors. Hence, it is imperative for the power suppliers to project and correlate these parameters. This paper presents a study of power load forecast for power suppliers, considering the applicability of wavelets, time series analysis methods and artificial neural networks, for both mid and long term forecasts. Both the periods of forecast are of major importance for power suppliers to define the future power consumption of a given region. The paper also studies the establishment of correlations among the variables using Bayesian networks. The results obtained are much more effective when compared to those projected by the power suppliers based on specialist information. The research discussed here is implemented on a decision support system, contributing to the decision making for acquisition/sale of energy at a future demand; also providing them with new ways for inference and analyses with the correlation model presented here. [Copyright &y& Elsevier]

Many situations in practice require appropriate specification of operating characteristics under extreme conditions. Typical examples include environmental sciences where studies include extreme temperature, rainfall and river flow to name a few. In these cases, the effect of geographic and climatological inputs are likely to play a relevant role. This paper is concerned with the study of extreme data in the presence of relevant auxiliary information. The underlying model involves a mixture distribution: a generalized Pareto distribution is assumed for the exceedances beyond a high threshold and a non-parametric approach is assumed for the data below the threshold. Thus, the full likelihood including data below and above the threshold is considered in the estimation. The main novelty is the introduction of a regression structure to explain the variation of the exceedances through all tail parameters. Estimation is performed under the Bayesian paradigm and includes model choice. This allows for determination of higher quantiles under each covariate configuration and upper bounds for the data, where appropriate. Simulation results show that the models are appropriate and identifiable. The models are applied to the study of two temperature datasets: maxima in the U.S.A. and minima in Brazil, and compared to other related models. [ABSTRACT FROM AUTHOR]

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification. [ABSTRACT FROM AUTHOR]

This paper assesses the effects of non-aqueous fluids (NAF)-associated drill cuttings discharge on shelf break macrobenthic communities in the Campos Basin, off the southeast Brazilian coast, Rio de Janeiro State. Samples were taken with a 0.25-m2 box corer from surrounding two oil and gas wells on three monitoring cruises: before drilling, three months after drilling, and 22 months after drilling. Statistical methodologies used Bayesian geostatistical and analysis of variance models to evaluate the effects of the NAF-associated drill cuttings discharge and to define the impact area. The results indicated that marked variations were not observed in the number of families between cruises, though there were changes in the fauna composition. The changes seen in biological descriptors in both control and background situation areas were not considered significant, showing a temporal homogeneity in means. The impact area presented changes in biological descriptors of communities and trophic structure during the three cruises and such changes were correlated to chemical and physical variables related to the drilling activities, as a result of the mix of drill cuttings and sediment and the anoxic conditions established in the substrate. In that area, three months after drilling, a decrease in diversity and an increase in density, motile deposit-feeders and Pol/Crp ratio, and dominance of opportunistic organisms, such as the capitellid Capitella sp., were observed and, 22 months after drilling, an increase of diversity, reduction of dominance of capitellid polychaete, changes in the fauna composition, and a dominance of opportunistic burrowing and tube-building organisms were observed, indicating an ecological succession process. [ABSTRACT FROM AUTHOR]

This paper describes the use of Bayesian spatial models to develop the concept of a spatial–temporal mask for the purpose of identifying regions in which before and after drilling effects are most clearly defined and from which the consequences of exposure of macrofauna and meiofauna to the release of drilling discharges can be evaluated over time. To determine the effects of drilling fluids and drill-cuttings on the marine benthic community, it is essential to know not only where discharged materials ended up within the possible impact area, but also the chemical concentrations to which biota were exposed during and after drilling. Barium and light hydrocarbons were used as chemical tracers for water-based and non-aqueous-based fluids in a shallow water site in the Campos Basin, off the coast of Brazil. Since the site showed evidence of exposure to waste material from earlier drilling, the analysis needed to take into account the background concentrations of these compounds. Using the Bayesian models, concentrations at unsampled sites were predicted and regions altered and previously contaminated were identified. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models. [ABSTRACT FROM AUTHOR]

Time series models are often used in hydrology and meteorology studies to model streamflows series in order to make forecasting and generate synthetic series which are inputs for the analysis of complex water resources systems. In this paper we introduce a new modeling approach for hydrologic and meteorological time series assuming a continuous distribution for the data, where both the conditional mean and conditional variance parameters are modeled. Bayesian methods using standard MCMC (Markov Chain Monte Carlo Methods) are used to simulate samples for the joint posterior distribution of interest. Two applications to real data sets illustrate the proposed methodology, assuming that the observations come from a normal, a gamma or a beta distribution. A first example is given by a time series of monthly averages of natural streamflows, measured in the year period ranging from 1931 to 2010 in Furnas hydroelectric dam, Brazil. A second example is given with a time series of 313 air humidity data measured in a weather station of Rio Claro, a Brazilian city located in southeastern of Brazil. These applications motivate us to introduce new classes of models to analyze hydrological and meteorological time series. [ABSTRACT FROM AUTHOR]

The crew of a nuclear‐powered submarine under development in Brasil plays an important role in its safety. For this reason, crew members must be trained in procedures against undesired events. However, information that would help to accurately decrease human error probability (HEP) on board nuclear‐powered submarines is not available in the literature. Therefore, a methodology is required to obtain this information. This study introduces importance measures to evaluate the contribution of performance shaping factors (PSFs) and their levels to HEP. Importance measures Fussell‐Vesely, risk reduction worth, risk achievement worth, and Birnbaum importance, commonly used in probabilistic safety assessment, are introduced to identify PSFs and PSF levels that contribute the most to HEP. The proposed approach is focused on identifying HEP's main contributors, oriented toward decision‐making. The methodology uses the PSFs established in the Standardized Plant Analysis Risk‐Human Reliability Analysis method and a Bayesian network to quantify HEP. Moreover, the results of an application case demonstrate the method's effectiveness in integrating expert opinions into representative values of HEP and in identifying critical PSFs and PSF levels that should be the object of the decision‐making process to improve human performance. [ABSTRACT FROM AUTHOR]

In the analysis of financial market data, random variations in price movements can share non-trivial statistical properties as observed for the distributions of returns, with possibility of absence of autocorrelations in asset returns, volatility in blocks and presence of asymmetry between rises and falls of stock values. Asset price fluctuations are usually investigated using time series models to obtain inferences about interest rates and future forecasts. In this study we consider the use of existing probability distributions to model run lengths and absolute historical price run returns as an alternative to the use of usual time series models with applications for time series obtained from the NYSE stock exchange for three private banks located in the Brazil in the period from July 19, 2013, to July 19, 2018. We assume discrete Weibull distributions as an alternative to the exponential law commonly used in this type of analysis. Under this modeling approach it is possible to obtain information about the structure of the market such as the probability of the stock market rising and falling daily and the magnitude of the returns. [ABSTRACT FROM AUTHOR]

Prehistoric shell mounds can be useful for the quantification of the radiocarbon marine reservoir effect (MRE) and, at the same time, knowledge about the MRE allows for the establishment of robust chronologies for these sites. This creates a loop in which the archaeological setting has a dual role: it is part of both the method and the application. Therefore, it is paramount to address these sites from both archaeological and environmental perspectives, investigating their origin and diagenesis in order to overcome biases caused by post-depositional alterations. In this study, samples of bone, charcoal and shell from a Late Holocene shell mound in Southern Brazil, the Sambaqui de Cabeçuda, were analyzed following a multidisciplinary approach to disentangle the complex relationships between archaeology and the environment. We performed X-ray diffraction, radiocarbon dating, stable isotopes (δ13C, δ18O, δ15N) and anthracology analyses as well as Bayesian Chronological Models and Isotope Mixing Models to assess the local MRE and to reconstruct the diet of Cabeçuda builders. Our results reveal a negative local correction for the MRE (ΔR = –263 ± 46 14C yr), expected for the lagoon next to the site, and diets with considerable intakes of marine proteins. We examine the implications of these results for the chronology of the site and discuss a series of complications when performing MRE studies using shell mound sites. [ABSTRACT FROM AUTHOR]

In 2021, the 88th General Session of the World Assembly of National Delegates to the World Organisation for Animal Health (OIE) recognized the estates of Acre, Paraná, the Rio Grande do Sul, and Rondônia as being free of foot-and-mouth disease (FMD) without vaccination. The certification was also extended to some cities in Amazonas and Mato Grosso. The new national strategic plan for 2026, which focuses on creating and maintaining sustainable conditions to expand FMD-free zones without vaccination, imposes new challenges and requires continuous evaluation of the FMD surveillance system. The objective of this research was to evaluate the FMD surveillance system in Brazil using quantitative models through Bayesian network approaches. The research was conducted using the Continental Surveillance and Information System (SivCont) database for Official Veterinary Services in Brazil, which refers to notified vesicular syndromes. The data on states, reported diseases, source of notification, disease confirmation, and timeliness (TL in days) of the delay by owners in notifying (TL.1) after a suspected case of the disease, and the response of Brazilian Veterinary Services after being notified (TL.2), were analysed. The collected data were analysed using Bayesian networks. It was observed that diseases with symptoms identical to FMD are the most notified events. TL.1 was long (mean of 18.96, CI: 18.33–19.59), and a low number of notifications was observed throughout the study period, which increases the chances of disseminating FMD in the population. Meanwhile, TL.2 suggests appropriate effectiveness of the Veterinary Services responding to suspected cases of FMD with interventions in less than 24 h (mean of 1, CI: 0.68–1.31). This study evaluated the performance of Brazilian Veterinary Services facing the report of vesicular diseases in the period 2004–2018. The results can help the states improve the surveillance system and the transition to the vaccination stop. Furthermore, the analytical method presented in the paper could serve as a model for other countries to evaluate the effectiveness of FMD surveillance systems. [ABSTRACT FROM AUTHOR]

Unveiling the ecological processes driving diversity and its relationship to the environment remains a central goal in ecological studies. Here, we investigated the elevation effect on plant beta-, phylogenetic and alpha-diversity patterns in the coastal Atlantic Forest, considering two scenarios: excluding one basal clade (tree ferns), which are usually neglected in diversity analysis, and depicting the patterns of the five richest families. To do so, we compiled a forest dataset with 22,236 individuals (trees, palms, and tree ferns) from 17 plots in southeastern Brazil. We found significant phylogenetic and species rates of turnover along the elevational gradient; however, species dissimilarities were higher than phylogenetic dissimilarities between communities. Alpha phylodiversity showed a monotonic decrease with increasing elevation, including or not tree ferns, while the phylogenetic structure was highly affected by the inclusion of tree ferns. We found that the unimodal species diversity pattern of the whole community emerged from differences among the species distributions of the richest families (e.g., Myrtaceae, Lauraceae, and Fabaceae), while phylogenetic diversity seemed to be gradually filtered by elevation. The higher species diversification within families and their different diversity patterns might support the idea of different ecological strategies leading to a high species co-occurrence in Tropical Forests. Thus, we show that the intricated effects of elevation on species assemblages can be better assessed using both ecological and evolutionary approaches, stressing the importance of species selection in diversity analyses. These results should be considered in conservation planning, since focusing only on greater diversity for the whole community may not encompass the high diversity of all Tropical Forest families. [ABSTRACT FROM AUTHOR]

With some 3,700 described species, Dryopoidea are a moderately diverse superfamily of beetles whose position within basal Polyphaga has been historically difficult to elucidate. Members of most extant dryopoid families are set apart from the majority of other polyphagans by their association with aquatic habitats, but little is known about the origin of these derived life habits and the phylogeny of the superfamily. Here we describe Mastigocoleidae Tihelka, Jäch, Kundrata & Cai fam. nov. , a new family of Mesozoic dryopoids represented by fossils from the Cretaceous Yixian Formation in northeastern China (undescribed species; ~125 Ma), Crato Formation in northeastern Brazil (Mastigocoleus rhinoceros Tihelka & Cai gen. et sp. nov. ; ~113 Ma), and amber from northern Myanmar (Mastigocoleus resinicola Tihelka & Cai gen. et sp. nov. and Cretaceocoleus saetosus Tihelka, Kundrata & Cai gen. et sp. nov. ; ~99 Ma). Integrating the findings of recent molecular and morphological phylogenetic analyses, we recover Mastigocoleidae as an early-diverging dryopoid clade sister to the families Lutrochidae and Dryopidae, or less likely as a group of putative stem-dryopoids. Mastigocoleidae are most distinctly separated from all other dryopoid families by their whip-like antennae, with 11 antennomeres, reaching to the pronotal base, and with the scape broadest and longest, a short pedicel, and antennomeres II–XI more or less distinctively gradually tapering toward the apex. Mastigocoleidae indicate that the last common ancestor of Dryopoidea was likely terrestrial in the adult stage, and document character acquisitions associated with a specialization for aquatic life. [ABSTRACT FROM AUTHOR]

Question: Grazing is an important disturbance for maintenance of structure and functioning of the plant communities in grassy ecosystems. Functional characteristics of plants, which are responsible for their response to grazing, vary at inter‐ and intraspecific levels. Here, we assessed: (1) the extent of intraspecific trait variation when compared to interspecific variability; and (2) how grazing regime affects intraspecific trait variation in leaf functional traits of species with different leaf economics strategies. Location: A multisite grazing experiment in subtropical grasslands, southern Brazil. Methods: For 30 dominant grassland plant species we measured functional traits related to resource acquisition strategy and grazing response (SLA, specific leaf area; LDMC, leaf dry matter content; LA, leaf area; and FT, leaf resistance to traction) under three grazing treatments (grazing exclusion, traditional, or deferred grazing) arranged in a randomized block design. We quantified the overall proportion of intra‐ and interspecific variation and, for each species, we tested for the grazing treatment effects on intraspecific trait variation through Bayesian analysis of variance. Results: The overall contribution of intraspecific variation was up to 37% of the total variation. For most grass species, grazing exclusion led to lower values of SLA and higher values of LA, while no effect of grazing treatments was detected on intraspecific variation of LDMC and FT. Altogether, the effect of grazing management on intraspecific trait variation was more prevalent in species presenting a conservative strategy than in species with an acquisitive strategy. Conclusion: The expression of leaf traits is variable within species, especially for those species with a conservative strategy of resource acquisition. The extent of intraspecific trait variation in response to grazing depends on the considered traits and the resource acquisition strategy of the studied species. [ABSTRACT FROM AUTHOR]

Background: Mosquito control is currently the main tool available to contain the spread of several arboviruses in Brazil. We have evaluated the association between entomological surveys of female adult Aedes aegypti and the Breteau index (BI) in space and time in a hyperendemic area, and compared the human resources costs required to measure each of these indicators. Methods: Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood in the city of São José do Rio Preto, Brazil. Monthly records of collected mosquito specimens were made and then grouped by season. Results: Our findings showed that adult and immature mosquitoes are more related in time than in space, possibly due to differences in their habitats or in climate variables. Bayesian temporal modeling revealed that an increase in 1 standard deviation in the BI was associated with a 27% increase in the number of adult female mosquitoes when adjusted for climatic conditions. The cost of entomological surveys of adult mosquitoes was found to be 83% lower than the cost of determining the BI when covering the same geographic area. Conclusions: For fine-scale assessments, a simple measure of adult Ae. aegypti abundance may be more realistic than aquatic indicators, but the adult indices are not necessarily the only reliable measure. Surveying adult female mosquitoes has significant potential for optimizing vector control strategies because, unlike the BI, this tool provides an effective indicator for micro-areas within an urban region. It should be noted that the results of the present study may be due to specific features of of the study area, and future studies should analyze whether the patterns found in the study neighborhood are also found in other regions. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to estimate the preferences of the Central Bank of Brazil after the inflation targeting regime (January 2000 to December 2013), using a DSGE model with microeconomic foundations for a small open economy, based especially on the work of Kam et al. (2009) . The model used in this study considers that the Central Bank minimizes a loss function, taking into account the deviation of inflation from its target, output stabilization, the interest rate smoothing and, unlike the previous works, the exchange rate. The results show that the major concern of the monetary authority in the period was the stabilization of inflation, followed by interest rate smoothing, exchange stabilization and, finally, output stabilization. The large value for the exchange rate smoothing parameter suggests the presence of fear of floating in the Brazilian case. An improved inflation targeting strategy should allow for less Central Bank intervention in the exchange rate market. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. [Copyright &y& Elsevier]

Abstract: This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a longitude–latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil. [Copyright &y& Elsevier]

Abstract: Toxic drilling fluids and cutting discharges from oil and gas wells adversely affect local environment near the well site. To determine their effects on benthic communities, it is essential to know both the fate of the discharged materials and the chemical concentrations to which biota were exposed during and after drilling. This paper describes a mapping procedure using Bayesian spatial models to define the deposition area of drilling cuttings and fluids from an exploratory well in a deep-sea site in the Campus Basin, RJ, Brazil, taking into account the concentrations of barium and light hydrocarbons used as chemical tracers. The statistical procedures used allow comparisons between sampled sites and the prediction of results at unsampled sites, as well as the delineation of affected areas. The probable impact of the use of non-aqueous fluid (NAF) was measured through observed changes in sea-floor sediments by using Before–After Control-Impact comparisons in a study with three moments: one before drilling and two after drilling. [Copyright &y& Elsevier]

Identification of terrestrial carbon (C) sources and sinks is critical for understanding the Earth system as well as mitigating and adapting to climate change resulting from greenhouse gas emissions. Predicting whether a given location will act as a C source or sink using terrestrial ecosystem models (TEMs) is challenging due to net flux being the difference between far larger, spatially and temporally variable fluxes with large uncertainties. Uncertainty in projections of future dynamics, critical for policy evaluation, has been determined using multi-TEM intercomparisons, for various emissions scenarios. This approach quantifies structural and forcing errors. However, the role of parameter error within models has not been determined. TEMs typically have defined parameters for specific plant functional types generated from the literature. To ascertain the importance of parameter error in forecasts, we present a Bayesian analysis that uses data on historical and current C cycling for Brazil to parameterise five TEMs of varied complexity with a retrieval of model error covariance at 1 ∘ spatial resolution. After evaluation against data from 2001–2017, the parameterised models are simulated to 2100 under four climate change scenarios spanning the likely range of climate projections. Using multiple models, each with per pixel parameter ensembles, we partition forecast uncertainties. Parameter uncertainty dominates across most of Brazil when simulating future stock changes in biomass C and dead organic matter (DOM). Uncertainty of simulated biomass change is most strongly correlated with net primary productivity allocation to wood (NPPwood) and mean residence time of wood (MRTwood). Uncertainty of simulated DOM change is most strongly correlated with MRTsoil and NPPwood. Due to the coupling between these variables and C stock dynamics being bi-directional, we argue that using repeat estimates of woody biomass will provide a valuable constraint needed to refine predictions of the future carbon cycle. Finally, evaluation of our multi-model analysis shows that wood litter contributes substantially to fire emissions, necessitating a greater understanding of wood litter C cycling than is typically considered in large-scale TEMs. [ABSTRACT FROM AUTHOR]

Summary: Among the many disparities for which Brazil is known is the difference in performance across students who attend the three administrative levels of Brazilian public schools: federal, state and municipal. Our main goal is to investigate whether student performance in the Brazilian Mathematical Olympics for Public Schools is associated with school administrative level and student gender. For this, we propose a hurdle hierarchical beta model for the scores of students who took the examination in the second phase of these Olympics, in 2013. The mean of the beta model incorporates fixed and random effects at the student and school levels. We explore different distributions for the random school effect. As the posterior distributions of some fixed effects change in the presence, and distribution, of the random school effects, we also explore models that constrain random school effects to the orthogonal complement of the fixed effects. We conclude that male students perform slightly better than female students and that, on average, federal schools perform substantially better than state or municipal schools. However, some of the best municipal and state schools perform as well as some federal schools. We hypothesize that this is due to individual teachers who successfully motivate and prepare their students to perform well in the mathematical Olympics. [ABSTRACT FROM AUTHOR]

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Despite all the research done on the first Zika virus (ZIKV) epidemics, it was only after the Brazilian epidemic that the Congenital Zika Syndrome was described. This was made possible due to the large number of babies born with microcephaly in the Northeast region (NE) in a narrow time. We hypothesize that the fivefold difference in the rate of microcephalic neonates between the NE and other regions is partially an effect of the population prior immunity against Dengue viruses (DENV), that cross-react with ZIKV. In this ecological study, we analysed the interaction between dengue fever epidemics from 2001 to 2014 and the 2015/2016 microcephaly epidemic in 400 microregions in Brazil using random-effects models under a Bayesian approach. The estimated effect of the time lag between the most recent large dengue epidemic (>400/100,000 inhabitants) and the microcephaly epidemic ranged from protection (up to 6 years prior) to an increased risk (from 7 to 12 years). This sustained window of protection, larger than described in previous longitudinal studies, is possibly an effect of herd immunity and of multiple exposures to DENV that could boost immunity. [ABSTRACT FROM AUTHOR]

Six Nowakowskiella species from Brazil were identified and purified on corn meal agar (CMA) plus glucose and Peptonized Milk-Tryptone-Glucose (PmTG) media and placed into a phylogenetic framework for the genus. New sequence data are presented for four species: N. elongata, N. multispora, and N. ramosa and the new species N. crenulata. Our maximum likelihood and Bayesian analyses of combined 18S, 5.8S, and 28S subunits of nuc rDNA showed that Nowakowskiella is not a monophyletic clade because of the position of Nowakowskiella elongata, which is more related to Cladochytrium. We reclassify N. elongata as the type of a new genus, Karlingiella. [ABSTRACT FROM AUTHOR]

In Brazil’s semi-arid Northeast, most rural dwellers derive income from the dry Caatinga forest through livestock farming, fruit collection, and firewood extraction. However, recurring droughts and inadequate land use practices jeopardize farmers’ livelihoods. The drought-resistant, endemic Umbuzeiro tree provides fruit for direct consumption and allows for the creation of transformed products. The planting of this native species can enhance the well-being of the ecosystem and establish future benefits for smallholdings. However, it is crucial that when taking up innovative practices to cope with environmental change, a willingness to apply them should be fostered among local farmers. We used constellation analysis as a transdisciplinary approach to identify elements of current land management which subsequently defined the nodes of a Bayesian network (BN). We developed probabilities of practice uptake that strengthen success, namely the conservation of natural resources while securing the incomes of smallholders. In collaboration with stakeholders and experts, 25 identified nodes for the BN were tested under various scenarios. Adopting all suggested innovative practices secures the final objectives—ecosystem health and farmer benefits (approx. 90%). The analysis quantified the relevance of single issues that may impede farmers to adopt the practices, such as having to cultivate seedlings or avoiding long-term investments. Further crucial actions include the fencing-off of livestock and marketing pathways. Affordable credit, research, and supportive farmers’ institutions can encourage farmers to implement innovative practices. The use of modeled scenarios can provide evidence, which might encourage sustainable land management. [ABSTRACT FROM AUTHOR]

The 37th edition of MaxEnt was held in Brazil, hosting several distinguished researchers and students. The workshop offered four tutorials, nine invited talks, twenty four oral presentations and twenty seven poster presentations. All submissions received their first choice between oral and poster presentations. The event held a celebration to Julio Stern's 60th anniversary and awarded two prizes to young researchers. As customary, the workshop had one free afternoon, in which participants visited the city's surroundings and experienced Brazilian food and traditions. [ABSTRACT FROM AUTHOR]

The aim of this study was to estimate the genetic parameters for the ability of a sheep to rank among the top three in its age category (ABI3) and for its total score (TS) on the judgement championships held in different agricultural fairs in Brazil. Data files included 3180 records referring to 1896 animals for ABI3 and 4383 records referring to 2170 animals for TS. The relationship matrix was composed by 4069 animals. Variance components were estimated fitting threshold and linear animal models for ABI3 and TS, respectively, by Bayesian analysis using the Gibbs sampler. The posterior means of the heritability and repeatability were, respectively, 0.10 ± 0.07 and 0.57 ± 0.11 for ABI3 and 0.12 ± 0.04 and 0.31 ± 0.02 for TS. The low values for the heritabilities related to these traits reveal a strong influence of the environmental factors, as the differential management offered to the animals before and during the fair. The repeatability values for ABI3 suggest high correlation among the animal classifications in different fairs. However, for TS, the observed performance has moderate confidence to be repeated over time. We conclude that although reduced, there is genetic variability for the animal’s performance in agricultural fairs. Nevertheless, due to the low heritability estimates, the expected response to direct selection for ABI3 and TS will be low. [ABSTRACT FROM PUBLISHER]

While South Americans are underrepresented in human genomic diversity studies, Brazil has been a classical model for population genetics studies on admixture. We present the results of the EPIGEN Brazil Initiative, the most comprehensive up-to-date genomic analysis of any Latin-American population. A population-based genomewide analysis of 6,487 individuals was performed in the context of worldwide genomic diversity to elucidate how ancestry, kinship, and inbreeding interact in three populations with different histories from the Northeast (African ancestry: 50%), Southeast, and South (both with European ancestry >70%) of Brazil. We showed that ancestry-positive assortative mating permeated Brazilian history. We traced European ancestry in the Southeast/South to a wider European/Middle Eastern region with respect to the Northeast, where ancestry seems restricted to Iberia. By developing an approximate Bayesian computation framework, we infer more recent European immigration to the Southeast/South than to the Northeast. Also, the observed low Native-American ancestry (6-8%) was mostly introduced in different regions of Brazil soon after the European Conquest. We broadened our understanding of the African diaspora, the major destination of which was Brazil, by revealing that Brazilians display two within-Africa ancestry components: one associated with non-Bantu/western Africans (more evident in the Northeast and African Americans) and one associated with Bantu/eastern Africans (more present in the Southeast/ South). Furthermore, the whole-genome analysis of 30 individuals (42-fold deep coverage) shows that continental admixture rather than local post-Columbian history is the main and complex determinant of the individual amount of deleterious genotypes. [ABSTRACT FROM AUTHOR]

Hansen’s disease (leprosy) elimination has proven difficult in several countries, including Brazil, and there is a need for a mathematical model that can predict control program efficacy. This study applied the Approximate Bayesian Computation algorithm to fit 6 different proposed models to each of the 5 regions of Brazil, then fitted hierarchical models based on the best-fit regional models to the entire country. The best model proposed for most regions was a simple model. Posterior checks found that the model results were more similar to the observed incidence after fitting than before, and that parameters varied slightly by region. Current control programs were predicted to require additional measures to eliminate Hansen’s Disease as a public health problem in Brazil. [ABSTRACT FROM AUTHOR]

This study analyzed sequences of the control region of mitochondrial DNA (D-loop) in three populations of Parauchenipterus galeatus from the basins of the Paraná, São Francisco, and Piumhi rivers, of which the last river being a region that suffered transposition river. A fragment of 850 base pairs was obtained with a total of 65 polymorphic sites. The data discuss aspects related to the genetic distance between the populations through the phylogenetic reconstruction methods (neighbor-joining, maximum-likelihood, and Bayesian analysis). Moreover, the data suggest that the Piumhi River population (transposition region) has recently gone through a significant bottleneck effect, which must be directly related to the anthropic action that occurred in this region, since the drainage the old existing swamp was necessary for the construction of the transposition channel potentially leading this population in to the current lack of genetic diversity. [ABSTRACT FROM AUTHOR]

Herein, we propose a fully Bayesian approach to the greenhouse gas emission problem. The goal of this work is to estimate the emission rate of polluting gases from the area flooded by hydroelectric reservoirs. We present models for gas concentration evolution in two ways: first, by proposing them from ordinary differential equation solutions and, second, by using stochastic differential equations with a discretization scheme. Finally, we present techniques to estimate the emission rate for the entire reservoir. In order to carry out the inference, we use the Bayesian framework with Monte Carlo via Markov Chain methods. Discretization schemes over continuous differential equations are used when necessary. These models applied to greenhouse gas emission and Bayesian inference for this purpose are completely new in statistical literature, as far as we know, and contribute to estimate the amount of polluting gases released from hydroelectric reservoirs in Brazil. The proposed models are applied in a real data set and results are presented. [ABSTRACT FROM PUBLISHER]

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In 2001, a probabilistic safety assessment of the Radiation Monitor Calibration Laboratory of a Brazilian nuclear power station was performed to estimate its radiological risk. Owing to the lack of data, many conservative assumptions were considered. The purpose of this paper is to obtain the updated laboratory radiological risk. A human reliability analysis of the procedure for calibrating the monitors was performed by applying the Technique for Human Error Rate Prediction (THERP) methodology. For facing the lack of failure data, the Bayesian approach was used for the calculation of the irradiator failure probability. The exponential distribution was used to model the failure times of the electronic dosimeters. The radiological risk was obtained through an event tree, in which all relevant scenarios were considered. Although more accident scenarios were considered in the analysis, like external events, the approach was by no means conservative, and a radiological risk about one order of magnitude smaller was obtained. [ABSTRACT FROM AUTHOR]

In this study, Bayesian analysis under a threshold animal model was used to estimate genetic correlations between morphological traits (body structure, finishing precocity and muscling) in Nelore cattle evaluated at weaning and yearling. Visual scores obtained from 7651 Nelore cattle at weaning and from 4155 animals at yearling, belonging to the Brazilian Nelore Program, were used. Genetic parameters for the morphological traits were estimated by two-trait Bayesian analysis under a threshold animal model. The genetic correlations between the morphological traits evaluated at two ages of the animal (weaning and yearling) were positive and high for body structure (0.91), finishing precocity (0.96) and muscling (0.94). These results indicate that the traits are mainly determined by the same set of genes of additive action and that direct selection at weaning will also result in genetic progress for the same traits at yearling. Thus, selection of the best genotypes during only one phase of life of the animal is suggested. However, genetic differences between morphological traits were better detected during the growth phase to yearling. Direct selection for body structure, finishing precocity and muscling at only one age, preferentially at yearling, is recommended as genetic differences between traits can be detected at this age. [ABSTRACT FROM AUTHOR]

In this study we tested a Bayesian model based on a conjugate gamma/Poisson pair associated with environmental variables derived from satellite data such as sea surface temperature (SST) and its derived gradient fields from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, chlorophyll-a concentration from Sea Viewing Wide field of View Sensor (SEAWiFS)/SeaStar and surface winds and Ekman pumping from SeaWinds/Quick Scatterometer (QuikSCAT) to predict weekly catch estimates of the skipjack tuna in the South Brazil Bight. This was achieved by confronting the fishery data with model estimates and regressing the results on the satellite data. The fishery data were expressed by an index of catch per unit effort (CPUE) calculated as the weight of fish caught (in tonnes) by fishing week, and were divided into two series, called historical series (1996-1998; 2001), and validation year (2002). The output of model CPUE estimates is in good agreement with the historical weekly CPUE and generated updated weekly estimates that explained up to 62% of weekly CPUE from 2002. In general, the best proxy for the Bayesian weekly estimates is the gradient zonal SST field. The results refined previous knowledge of the influence of SST on the occurrence of skipjack tuna. [ABSTRACT FROM AUTHOR]

Background: The global spread of HIV-1 has been accompanied by the emergence of genetically distinct viral strains. Over the past two decades subtype C viruses, which predominate in Southern and Eastern Africa, have spread rapidly throughout parts of South America. Phylogenetic studies indicate that subtype C viruses were introduced to South America through a single founder event that occurred in Southern Brazil. However, the external route via which subtype C viruses spread to the South American continent has remained unclear. Methodology/Principal Findings: We used automated genotyping to screen 8,309 HIV-1 subtype C pol gene sequences sampled within the UK for isolates genetically linked to the subtype C epidemic in South America. Maximum likelihood and Bayesian approaches were used to explore the phylogenetic relationships between 54 sequences identified in this screen, and a set of globally sampled subtype C reference sequences. Phylogenetic trees disclosed a robustly supported relationship between sequences from Brazil, the UK and East Africa. A monophyletic cluster comprised exclusively of sequences from the UK and Brazil was identified and dated to approximately the early 1980s using a Bayesian coalescent-based method. A sub-cluster of 27 sequences isolated from homosexual men of UK origin was also identified and dated to the early 1990s. Conclusions: Phylogenetic, demographic and temporal data support the conclusion that the UK was a crucial staging post in the spread of subtype C from East Africa to South America. This unexpected finding demonstrates the role of diffuse international networks in the global spread of HIV-1 infection, and the utility of globally sampled viral sequence data in revealing these networks. Additionally, we show that subtype C viruses are spreading within the UK amongst men who have sex with men. [ABSTRACT FROM AUTHOR]

Methods for modeling and mapping spatial variation in disease risk continue to motivate much research. In particular, spatial analyses provide a useful tool for exploring geographical heterogeneity in health outcomes, and consequently can yield clues as to disease etiology, direct public health management, and generate research hypotheses. This article presents a Bayesian partitioning approach for the analysis of individual level geo-referenced health data. The model makes few assumptions about the underlying form of the risk surface, is data adaptive, and allows for the inclusion of known determinants of disease. The methodology is used to model spatial variation in neonatal mortality in Porto Alegre, Brazil. [ABSTRACT FROM AUTHOR]

The article presents a Bayesian estimation of a dynamic factor model where the factors follow a multivariate autoregressive model. The authors derive the posterior distributions for the parameters and the factors and use Monte Carlo methods in the computation. The mathematical model is used by the authors in studying the association between air pollution and mortality in the city of São Paulo, Brazil. A Bayesian analysis of a dynamic factor model was used in performing the statistical analysis. The authors found a strong association between air pollutant, humidity and mortality respiratory disease for the city of São Paulo.

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices. [ABSTRACT FROM AUTHOR]