As rodovias e as aves de rapina nocturnas relação entre a densidade, o habitat e a mortalidade

As estradas e tráfego inerente surgem como a criação antrópica mais conspícua e penetrante na paisagem natural, sendo considerados os principais agentes causadores de fragmentação e destruição de habitats, assim como representam um obstáculo físico sem precedentes, limitando as relações directas entre os indivíduos, por diminuição da frequência de dispersão e aumento da mortalidade por atropelamento, impedindo o fluxo natural de genes e suscitando o aumento de fenómenos de inbreeding e perda de heterozigotia. Todos os impactes deletérios associados às rodovias são claramente perceptíveis em vertebrados, onde as aves de rapinas nocturnas não são excepção. Uma vez que estas rapaces beneficiam das suas bermas e orlas, como locais de poiso, nidificação ou como corredores de dispersão através da paisagem, são frequentemente vítimas de mortalidade por atropelamento em estradas, sendo esta problemática considerada actualmente uma das mais recentes e importantes formas de mortalidade não natural em rapinas nocturnas e vinculada como um dos maiores problemas de conservação que afecta este grupo. Não obstante, esse mútuo efeito de atracção/repulsa das estradas a estas rapaces, as rodovias criam uma barreira específica que limita a dinâmica, comportamento e densidade populacional das espécies residentes, reconhecendo-se que o isolamento daí resultante, pode comprometer a viabilidade populacional a longo prazo, podendo mesmo conduzir a altos riscos de extinção das populações locais devido a efeitos estocásticos. Mediante esta problemática, este trabalho debruçou-se sobre um único objectivo principal: a avaliação do impacte das rodovias e do tráfego, na densidade das aves de rapina nocturnas. Este estudo foi efectuado na região Alentejana, abrangendo uma área de cariz tipicamente mediterrânico, delimitada pelas localidades de Montemor-o-Novo, Arraiolos e Évora, sendo seccionada por 143 quilómetros de estradas, divididas em autoestrada, rodovias com elevada e reduzida densidade de tráfego. A monitorização das rapinas nocturnas foi conduzida em dois anos amostrais (2005 e 2007), tendo sido focalizada sobretudo em duas espécies de Strigiformes, a Coruja­ do-mato Strix aluco e o Mocho-galego Athene noctua, recorrendo ao uso de playbacks com reprodução de vocalizações de indivíduos conspecíficos. Foram usadas 32 variáveis explicativas integradas em três grandes grupos: variáveis de estrada, métricas da paisagem, uso do solo, tendo sido analiticamente testadas, recorrendo à aplicação de Modelos Lineares Generalizados. Os principais resultados obtidos demonstram que as variáveis de estrada, aliadas à densidade de tráfego e ruído inerente à sua circulação, são provavelmente, responsáveis por um comportamento de repulsa das espécies de aves de rapina nocturnas em estudo, apresentando estas densidades mais elevadas longe de áreas antropicamente perturbadas e, portanto, de menor qualidade que se encontram adjacentes às rodovias. Todavia a presença de habitat favorável a estas rapaces é provavelmente o descritor com maior poder estatístico no que concerne à sua distribuição e densidade, sendo os montados densos e a presença de zonas agrícolas de sequeiro, positivamente correlacionadas, respectivamente com a densidade de casais reprodutores de Coruja-do-mato e Mocho-galego. Mediante a observação dos resultados será veemente a aplicação de medidas de mitigação específicas, que fundamentalmente considerem o afastamento dos efectivos populacionais longe das estradas e tráfego, conservando e assegurando as características estruturais, requisitos e qualidade dos habitats, de modo a incrementar e garantir a viabilidade e densidade das populações, fidelizando a territorialidade e permanência destas aves nestas áreas. Adicionalmente deverá investir-se na conectividade das manchas de paisagem fragmentada pelas rodovias, criando opções de conservação estratégicas, em zonas ecologicamente mais sensíveis, que não somente minimizem o efeito de repulsa reconhecido nestas aves, mas também os níveis de mortalidade por atropelamento, tornando os ecossistemas mais funcionais para a sobrevivência destes rapaces. ABSTRACT; Roads and traffic are the most conspicuous and pervasive human creation, being the great responsible for fragmentation and habitats destruction, reducing animal movement through landscape, which implies decrease of gene flow and loss of variability that can fragmented populations, thus reducing their sizes and densities. All deleterious impacts associated with roads are clearly visible in vertebrates, where owls aren't exception, being frequent victims of road mortality, since they can use roadside habitats and edges for hunting, nesting or dispersal corridors through the landscape, being nowadays one of the most recent and important causes of non­natural mortality in owls and has been recognized as one of the largest conservation problems affecting this group. However, the attractive and avoidance effect of roads and his edges on owls creates a barrier effect that limits dynamics, behaviour and breeding density of resident species, recognizing that possible isolation, could compromise populations survival, make them more vulnerable to high risks of local extinction due to stochastic effects. Despite that, several authors suggest that owls use roads to hunt, as marginal habitats, or for navigation corridors through the landscape ln this context, the major aims of this study was to verify if there are negative effects of roads on the density of owls, considering traffic as an influencing factor. This study was conducted in Alentejo, covering a typical Mediterranean area, including three main localities Montemor-o-Novo, Évora and Arraiolos, being sectioned by 143 km of roads, including highway, roads with high traffic density, and the remaining with low traffic density. The owl census was conducted in two sampling years (2005 and 2007) and was focused mainly on Little owl Athene noctua and Tawny Owl Strix aluco species, using the playback technique, with conspecific calls. We used 32 explanatory variables, mainly included in three groups: road variables, landscape metrics and land use, having been analytically tested, with application of Generalised Linear Models. The main results show that noisy roads with high traffic density are probably the most responsible for the avoidance behaviour of owls, under the study area, showing density depression near high anthropogenic disturbed areas adjacent to roads. However, the presence of habitat quality to these birds is probably the descriptor with greater statistical power, considering its distribution and density, with the dense oak woodland and croplands and arable lands, positively correlated, respectively with Tawny owl and Little owl density. ln consequence, the great conservation effort should be done in order to keep breeding populations away from roads and traffic, ensuring the structural features, requirements and quality of its habitats in order to enhance and ensure the viability and density of owl's populations in these areas. ln addition, it is important to invest in connectivity between roadside fragmented patches, creating strategic conservation options, in sensitive areas, which minimize the avoidance effect, recognized in owls, but also road-kill levels, making ecosystems more functional to survival of these top predators.

Analysis of the claims data of a life insurance portfolio

Mestrado em Ciências Actuariais

Feasibility of resting-state microstates neurofeedback

Despite major progress, currently available treatment options for patients suffering from schizophrenia remain suboptimal. Antipsychotic medication is one such option, and is helpful in acute phases of the disease. However, antipsychotics cause significant side-effects that often require additional medication, and can even trigger the discontinuation of treatment. Taken together, along with the fact that 20-30% of patients are medication-resistant, it is clear that new medical care options should be developed for patients with schizophrenia. Besides medication, an emerging option to treat psychiatric symptoms is through the use of neurofeedback. This technique has proven efficacy for other disorders and, more importantly, has also proven to be feasible in patients with schizophrenia. One of the major advantages of this approach is that it allows for the influence of brain states that otherwise would be inaccessible; i.e. the physiological markers underlying psychotic symptoms. EEG resting-state microstates are a very interesting electrophysiological marker of schizophrenia symptoms. Precisely, a specific class of resting-state microstates, namely microstate class D, has consistently been found to show a temporal shortening in patients with schizophrenia compared to controls, and this shortening is correlated with the presence positive psychotic symptoms. Under the scope of biological psychiatry, appropriate treatment of psychotic symptoms can be expected to modify the underlying physiological markers accompanying behavioral manifestations of a disease. We reason that if abnormal temporal parameters of resting-state microstates seem to be related to positive symptoms in schizophrenia, regulating this EEG feature might be helpful as a treatment for patients. The goal of this thesis was to prove the feasibility of microstate class D contribution self-regulation via neurofeedback. Given that no other study has attempted to regulate microstates via neurofeedback, we first tested its feasibility in a population of healthy subjects. In the first paper we describe the methodological characteristics of the neurofeedback protocol and its implementation. Neurofeedback performance was assessed by means of linear mixed effects modeling, which provided a complete profile of the neurofeedback’s training response within and between-subjects. The protocol included 20 training sessions, and each session contained three conditions: baseline (resting-state) and two active conditions: training (auditory feedback upon self-regulation performance) and transfer (self-regulation with no feedback). With linear modeling we obtained performance indices for each of them as follows: baseline carryover (baseline increments time-dependent) and learning and aptitude for each of the active conditions. Learning refers to the increase/decrease of the microstate class D contribution, time-dependent during each active condition, and aptitude refers to the constant difference of the microstate class D contribution between each active condition and baseline independent of time. The indices provided are discussed in terms of tailoring neurofeedback treatment to individual profiles so that it can be applied in future studies or clinical practice. In our sample of participants, neurofeedback proved feasible, as all participants at least showed positive results in one of the aforementioned learning indices. Furthermore, between-subjects we observed that the contribution of microstate class D across-sessions increased by 0.42% during baseline, 1.93% during training trials, and 1.83% during transfer. This range is expected to be effective in treating psychotic symptoms in patients. In the second paper presented in this thesis, we explored the possible predictors of neurofeedback success among psychological variables measured with questionnaires. An interesting finding was the negative correlation between “motivational incongruence” and some of the neurofeedback performance indices. Even though this finding requires replication, we discuss it in terms of the interfering effects of incompatible psychological processes with neurofeedback training requirements. In the third paper, we present a meta-analysis on all available studies that have related resting-state microstate abnormalities and schizophrenia. We obtained medium effect sizes for two microstate classes, namely C and D. Combining the meta-analysis results with the fact that microstate class D abnormalities are correlated with the presence of positive symptoms in patients with schizophrenia, these results add further support for the training of this precise microstate. Overall, the results obtained in this study encourage the implementation of this protocol in a population of patients with schizophrenia. However, future studies will have to show whether patients will be able to successfully self-regulate the contribution of microstate class D and, if so, whether this regulation will have an impact on symptomatology.

Endemic zoonoses: a one health approach

Endemic zoonotic diseases remain a serious but poorly recognised problem in affected communities in developing countries. Despite the overall burden of zoonoses on human and animal health, information about their impacts in endemic settings is lacking and most of these diseases are continuously being neglected. The non-specific clinical presentation of these diseases has been identified as a major challenge in their identification (even with good laboratory diagnosis), and control. The signs and symptoms in animals and humans respectively, are easily confused with other non-zoonotic diseases, leading to widespread misdiagnosis in areas where diagnostic capacity is limited. The communities that are mostly affected by these diseases live in close proximity with their animals which they depend on for livelihood, which further complicates the understanding of the epidemiology of zoonoses. This thesis reviewed the pattern of reporting of zoonotic pathogens that cause febrile illness in malaria endemic countries, and evaluates the recognition of animal associations among other risk factors in the transmission and management of zoonoses. The findings of the review chapter were further investigated through a laboratory study of risk factors for bovine leptospirosis, and exposure patterns of livestock coxiellosis in the subsequent chapters. A review was undertaken on 840 articles that were part of a bigger review of zoonotic pathogens that cause human fever. The review process involves three main steps: filtering and reference classification, identification of abstracts that describe risk factors, and data extraction and summary analysis of data. Abstracts of the 840 references were transferred into a Microsoft excel spread sheet, where several subsets of abstracts were generated using excel filters and text searches to classify the content of each abstract. Data was then extracted and summarised to describe geographical patterns of the pathogens reported, and determine the frequency animal related risk factors were considered among studies that investigated risk factors for zoonotic pathogen transmission. Subsequently, a seroprevalence study of bovine leptospirosis in northern Tanzania was undertaken in the second chapter of this thesis. The study involved screening of serum samples, which were obtained from an abattoir survey and cross-sectional study (Bacterial Zoonoses Project), for antibodies against Leptospira serovar Hardjo. The data were analysed using generalised linear mixed models (GLMMs), to identify risk factors for cattle infection. The final chapter was the analysis of Q fever data, which were also obtained from the Bacterial Zoonoses Project, to determine exposure patterns across livestock species using generalized linear mixed models (GLMMs). Leptospira spp. (10.8%, 90/840) and Rickettsia spp. (10.7%, 86/840) were identified as the most frequently reported zoonotic pathogens that cause febrile illness, while Rabies virus (0.4%, 3/840) and Francisella spp. (0.1%, 1/840) were least reported, across malaria endemic countries. The majority of the pathogens were reported in Asia, and the frequency of reporting seems to be higher in areas where outbreaks are mostly reported. It was also observed that animal related risk factors are not often considered among other risk factors for zoonotic pathogens that cause human fever in malaria endemic countries. The seroprevalence study indicated that Leptospira serovar Hardjo is widespread in cattle population in northern Tanzania, and animal husbandry systems and age are the two most important risk factors that influence seroprevalence. Cattle in the pastoral systems and adult cattle were significantly more likely to be seropositive compared to non-pastoral and young animals respectively, while there was no significant effect of cattle breed or sex. Exposure patterns of Coxiella burnetii appear different for each livestock species. While most risk factors were identified for goats (such as animal husbandry systems, age and sex) and sheep (animal husbandry systems and sex), there were none for cattle. In addition, there was no evidence of a significant influence of mixed livestock-keeping on animal coxiellosis. Zoonotic agents that cause human fever are common in developing countries. The role of animals in the transmission of zoonotic pathogens that cause febrile illness is not fully recognised and appreciated. Since Leptospira spp. and C. burnetii are among the most frequently reported pathogens that cause human fever across malaria endemic countries, and are also prevalent in livestock population, control and preventive measures that recognise animals as source of infection would be very important especially in livestock-keeping communities where people live in close proximity with their animals.

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures

Geographical and environmental correlates of big and small game in Andalusia (southern Spain)

In Andalusia, southern Spain, each game estate applies its own rules and presents its results in annual hunting reports, which have been mandatory for Spanish game estates since 1989. We used the information about hunting yields, included in 32134 annual hunting reports produced during the period 1993/94 to 2001/02 by 6049 game estates, to determine the current distribution of hunting yields of big and small game species in Andalusia. Using generalised linear models and a geographic information system, we determined the most favourable municipalities to big and small game, respectively, and delimited potential areas to attain good hunting yields for big and small game at a 1-km2 resolution. Municipalities and areas favourable to big game are mainly located in the Sierra Morena and the westernmost fringe of the Betic Range, while those favourable to small game occupy the upper Guadalquivir River valley. There is a clear segregation between big and small game species according to the physiography and land uses of the territory. Big game species are typical of Mediterranean woodland areas, while the most emblematic small game species prefer agricultural areas. Our results provide a territorial ordination of hunting yields in southern Spain and have several potential applications in strategic planning for hunting activities and biodiversity conservation in Andalusia that can be extrapolated to other regions.

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model

Modeling volatile organic compounds (voc`s) adsorption onto cup-stacked carbon nanotubes (cscnt) using the linear driving force model. Volatile organic compounds (VOC`s) are an important category of air pollutants and adsorption has been employed in the treatment (or simply concentration) of these compounds. The current study used an ordinary analytical methodology to evaluate the properties of a cup-stacked nanotube (CSCNT), a stacking morphology of truncated conical graphene, with large amounts of open edges on the outer surface and empty central channels. This work used a Carbotrap bearing a cup-stacked structure (composite); for comparison, Carbotrap was used as reference (without the nanotube). The retention and saturation capacities of both adsorbents to each concentration used (1, 5, 20 and 35 ppm of toluene and phenol) were evaluated. The composite performance was greater than Carbotrap; the saturation capacities for the composite was 67% higher than Carbotrap (average values). The Langmuir isotherm model was used to fit equilibrium data for both adsorbents, and a linear driving force model (LDF) was used to quantify intraparticle adsorption kinetics. LDF was suitable to describe the curves.

Computational modeling for irrigated agriculture planning. Part I: general description and linear programming

Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

Affiliation: Institut de recherche en immunologie et en cancérologie, Université de Montréal

A new approach for modeling and control of nonlinear systems via norm-bounded linear differential inclusions

A systematic approach to model nonlinear systems using norm-bounded linear differential inclusions (NLDIs) is proposed in this paper. The resulting NLDI model is suitable for the application of linear control design techniques and, therefore, it is possible to fulfill certain specifications for the underlying nonlinear system, within an operating region of interest in the state-space, using a linear controller designed for this NLDI model. Hence, a procedure to design a dynamic output feedback controller for the NLDI model is also proposed in this paper. One of the main contributions of the proposed modeling and control approach is the use of the mean-value theorem to represent the nonlinear system by a linear parameter-varying model, which is then mapped into a polytopic linear differential inclusion (PLDI) within the region of interest. To avoid the combinatorial problem that is inherent of polytopic models for medium- and large-sized systems, the PLDI is transformed into an NLDI, and the whole process is carried out ensuring that all trajectories of the underlying nonlinear system are also trajectories of the resulting NLDI within the operating region of interest. Furthermore, it is also possible to choose a particular structure for the NLDI parameters to reduce the conservatism in the representation of the nonlinear system by the NLDI model, and this feature is also one important contribution of this paper. Once the NLDI representation of the nonlinear system is obtained, the paper proposes the application of a linear control design method to this representation. The design is based on quadratic Lyapunov functions and formulated as search problem over a set of bilinear matrix inequalities (BMIs), which is solved using a two-step separation procedure that maps the BMIs into a set of corresponding linear matrix inequalities. Two numerical examples are given to demonstrate the effectiveness of the proposed approach.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

Non-linear gain - look-up table based approach for modeling a family of DC to DC converters based on transient response analysis

The purpose of this work is to propose a structure for simulating power systems using behavioral models of nonlinear DC to DC converters implemented through a look-up table of gains. This structure is specially designed for converters whose output impedance depends on the load current level, e.g. quasi-resonant converters. The proposed model is a generic one whose parameters can be obtained by direct measuring the transient response at different operating points. It also includes optional functionalities for modeling converters with current limitation and current sharing in paralleling characteristics. The pusposed structured also allows including aditional characteristics of the DC to DC converter as the efficency as a function of the input voltage and the output current or overvoltage and undervoltage protections. In addition, this proposed model is valid for overdamped and underdamped situations.