GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Estimação espaço-temporal das perdas não técnicas no sistema de distribuição de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Environmental and Farm Management Factors Associated with Tuberculosis on Cattle Farms in Northeastern Michigan

Objective—To identify major environmental and farm management factors associated with the occurrence of tuberculosis (TB) on cattle farms in northeastern Michigan. Design—Case-control study. Sample Population—17 cattle farms with infected cattle and 51 control farms. Procedure—Each case farm (laboratory confirmed diagnosis of Mycobacterium bovis infection) was matched with 2 to 4 control farms (negative whole-herd test results within previous 12 months) on the basis of type of farm (dairy or beef) and location. Cattle farm data were collected from in-person interviews and mailed questionnaires. Wildlife TB data were gathered through state wildlife surveillance. Environmental data were gathered from a satellite image-based geographic information system. Multivariable conditional logistic regression for matched analysis was performed. Results—Major factors associated with increased farm risk of TB were higher TB prevalence among wild deer and cattle farms in the area, herd size, and ponds or creeks in cattle housing areas. Factors associated with reduced farm risk of TB were greater amounts of natural open lands in the surrounding area and reducing deer access to cattle housing areas by housing cattle in barns, barnyards, or feedlots and use of electrified wire or barbed wire for livestock fencing. Conclusions and Clinical Relevance—Results suggest that certain environmental and management factors may be associated with risk of TB on cattle farms.

Geographic Variation in Sea Otters, Enhydra lutris

Univariate and multivariate analyses of 20 skull characters of 304 adult sea otters from throughout the geographic range strongly suggest that three subspecies should be recognized. The nominate form, Enhydra lutris lutris, occurs from the Kuril Islands north to the Commander Islands in the western Pacific Ocean. Individuals of E. l. lutris are characterized by large size and wide skulls with short nasal bones. E. 1. nereis is found along the California coast and off San Nicolas Island, where the species recently has been reintroduced from coastal California. Specimens of E. 1. nereis have narrow skulls with a long rostrum and small teeth, and usually lack the characteristic notch in the postorbital region found in most specimens of the other two subspecies. A new subspecies described by Don E. Wilson in this report, occurs throughout the Aleutian Islands and southward in the eastern Pacific to Washington. Specimens of the new subspecies are intermediate in size in most, but not all, characters and have longer mandibles than either of the other two subspecies

Seasonal Variation in Reception of Fin Whale Calls at Five Geographic Areas in the North Pacific

In late August 1991 scientists at the National Oceanic and Atmospheric Administration’s (NOAA) National Marine Mammal Laboratory (NMML) and Pacific Marine Environmental Laboratory (PMEL) began a pilot study to investigate the capability of hydrophones from the US. Navy’s fixed array system to detect large whales in the North Pacific by passive reception of their calls. PMEL had previously established a direct data link from five bottom-mounted arrays of the Navy SOSUS (Sound Surveillance System), via the Naval Oceanographic Processing Facility (NOPF) at Whidbey Island, Washington, to study low-level seafloor seismicity (Fox et al. 1994). PMEL subsequently provided NMML tapes of SOSUS hydrophone data from which whale calls were analyzed. As in an analogous study conducted in the North Atlantic (Nishimura and Conlon 1994, Clark 1995, Mellinger and Clark 1995), calls attributable to whales were received at each SOSUS site at rates that varied seasonally (Anonymous 1996).

Infrastructure Support for Controlled Experimentation with Software Testing and Regression Testing Techniques

Where the creation, understanding, and assessment of software testing and regression testing techniques are concerned, controlled experimentation is an indispensable research methodology. Obtaining the infrastructure necessary to support such experimentation, however, is difficult and expensive. As a result, progress in experimentation with testing techniques has been slow, and empirical data on the costs and effectiveness of techniques remains relatively scarce. To help address this problem, we have been designing and constructing infrastructure to support controlled experimentation with testing and regression testing techniques. This paper reports on the challenges faced by researchers experimenting with testing techniques, including those that inform the design of our infrastructure. The paper then describes the infrastructure that we are creating in response to these challenges, and that we are now making available to other researchers, and discusses the impact that this infrastructure has and can be expected to have.

Improved Regression Estimation of a Multivariate Relationship with Population Data on the Bivariate Relationship

Regression coefficients specify the partial effect of a regressor on the dependent variable. Sometimes the bivariate or limited multivariate relationship of that regressor variable with the dependent variable is known from population-level data. We show here that such population- level data can be used to reduce variance and bias about estimates of those regression coefficients from sample survey data. The method of constrained MLE is used to achieve these improvements. Its statistical properties are first described. The method constrains the weighted sum of all the covariate-specific associations (partial effects) of the regressors on the dependent variable to equal the overall association of one or more regressors, where the latter is known exactly from the population data. We refer to those regressors whose bivariate or limited multivariate relationships with the dependent variable are constrained by population data as being ‘‘directly constrained.’’ Our study investigates the improvements in the estimation of directly constrained variables as well as the improvements in the estimation of other regressor variables that may be correlated with the directly constrained variables, and thus ‘‘indirectly constrained’’ by the population data. The example application is to the marital fertility of black versus white women. The difference between white and black women’s rates of marital fertility, available from population-level data, gives the overall association of race with fertility. We show that the constrained MLE technique both provides a far more powerful statistical test of the partial effect of being black and purges the test of a bias that would otherwise distort the estimated magnitude of this effect. We find only trivial reductions, however, in the standard errors of the parameters for indirectly constrained regressors.

Spatial analysis of egg distribution and geographic changes in the spawning habitat of the Brazilian sardine Sardinella brasiliensis

This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.

Investigating South American biogeographic history using patterns of skull shape variation on Cerdocyon thous (Mammalia: Canidae)

Patterns of geographic variation of the canid Cerdocyon thous have historically been obscured by its remarkable intraspecific morphological variability. The observed distribution is highly associated with phytophysiognomy, a feature considered highly dynamic along geological time. In the present study, we tested whether vegetation distribution during the Holocene Glacial Maximum of South America (HGM) explains the patterns of morphological variation within Cerdocyon thous. The species was divided in groups according to paleohabitats that could support their presence during the HGM, and then tested for differences in skull morphometrics. The results obtained demonstrate that the climatic changes during the HGM influenced the population structure of this species, resulting in the establishment of geographical groups with different degrees of morphological cohesion. Higher morphological cohesion found in the Northern group might be explained by the marked discontinuity between its geographical range and the rest of the species`distribution. The Eastern and Southern morphological divergence is less striking and, although this could be related to past vegetation distribution, the disappearance of those barriers leads to a population structure that could be slowly breaking down. (C) 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 98, 77-84.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Dropouts or Discontinuity of the Treatment of Tuberculosis in Rio Branco, Acre

This research investigates the factors related to the discontinuity of the treatment of tuberculosis in Rio Branco-Acre. To the fulfillment of this research, a contribution to ethnography has been adopted, for the successful apprehension of the reality to be studied. The research has been developed in two mapping steps: on the first, a search for information on the SINAN (System of National Injuries Notification - Sistema de Notificacao de Agravos Nacionais) and on the Municipal Coordination of the Tuberculosis Program databases was taken; the second aimed to record facts from the observation of the care given on a health care unit, which serves assistance to tuberculosis carriers in treatment, and the interviews of the elected subjects. On the analysis of the observations, narrative and interview collection, it was observed that the professionals of health services label some people as auspicious to discontinue the treatment and don't consider the different ways of life on the approach of their patients, complicating the formation of the bond and favoring the discontinuity. It was also identified people treating for tuberculosis that had many ways of dealing with the limitations generated by the disease, such as restrictions for the work, among others, and people that discontinued the treatment took in consideration their system of beliefs and values, as well as the perception of health/disease, due to the feeling of cure when the treatment was interrupted.

Contextual and individual inequalities in dental pain prevalence among Brazilian adults and elders

This study aimed to assess the prevalence of dental pain among adults and older people living in Brazil's State capitals. Information was gathered from the Telephone Survey Surveillance System for Risk and Protective Factors for Chronic Diseases (VIGITEL) in 2009 (n = 54,367). Dental pain was the outcome. Geographic region, age, gender, race, schooling, private health coverage, smoking, and soft drink consumption were the explanatory variables. Multilevel Poisson regression models were performed. Prevalence of dental pain was 15.2%; Macapa and Sao Luis had prevalence rates greater than 20%; all capitals in the South and Southeast, plus Cuiaba, Campo Grande, Maceio, Recife, and Natal had prevalence rates less than 15%. Factors associated with increased prevalence of dental pain were the North and Northeast regions, female gender, black/brown skin color, lack of private health insurance, smoking, and soft drink consumption. Dental pain is a public health problem that should be monitored by health surveillance systems.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of jau (Zungaro jahu)

Adriano E.A., Ceccarelli P.S., Silva M.R.M. & Maia A.A. M. 2012. [Prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of jau (Zungaro jahu) in the Pantanal of Mato Grosso, Brazil.] Prevalencia, distribuicao geografica e sazonal de protozoarios e mixozoarios parasitos de jau (Zungaro jahu) no Pantanal Matogrossense. Pesquisa Veterinaria Brasileira 32(12):1341-1344. Departamento de Ciencias Basicas, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de Sao Paulo, Av. Duque de Caxias Norte 225, Pirassununga, SP 13635-900, Brazil. E-mail: antomaia@usp.br In a study carried out in the Pantanal of Mato Grosso, Brazil, the prevalence, geographic and seasonal distribution of protozoan and myxozoan parasites of Zungaro jahu was evaluated. The fish were captured in the southern region of Pantanal Mato-grossense (Aquidauana, Miranda and Paraguay rivers) in 2001, 2002 and 2003, in the central region (Pantanal National Park - PARNA Pantanal) in 2003, 2004, 2005 and 2008, and in the northern region (Cuiaba and Manso rivers, in the municipality of Nobres) in 2003, 2004 and 2005. Trichodina sp. was identified parasitized skin and gills of jau in the three regions studied. Epistylis sp. parasitized skin and Cryptobia sp. the gills and were restricted to the Central region, whilst Ichthyophthirius multifiliis parasitized skin in the three regions studied. The occurrence of myxozoans was also observed: Myxobolus cordeiroi parasitized several organs and Henneguya sp. parasitized the gills of jau in the three regions studied.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.