Desempenho de analistas sell-side no mercado de ações brasileiro

The purpose of this study was to analyze the behavior of Sell-Side analysts and analysts propose a classification, considering the performance of the price forecasts and recom- mendations (sell-hold-buy) in the Brazilian stock market. For this, the first step was to analyze the consensus of analysts to understand the importance of this collective interven- tion in the market; the second was to analyze the analysts individually to understand how improve their analysis in time. Third was to understand how are the main methods of ranking used in markets. Finally, propose a form of classification that reflects the previous aspects discussed. To investigate the hypotheses proposed in the study were used linear models for panel to capture elements in time. The data of price forecasts and analyst recommendations individually and consensus, in the period 2005-2013 were obtained from Bloomberg R ○ . The main results were: (i) superior performance of consensus recommen- dations, compared with the individual analyzes; (ii) associating the number of analysts issuing recommendations with improved accuracy allows supposing that this number may be associated with increased consensus strength and hence accuracy; (iii) the anchoring effect of the analysts consensus revisions makes his predictions are biased, overvaluating the assets; (iv) analysts need to have greater caution in times of economic turbulence, noting also foreign markets such as the USA. For these may result changes in bias between optimism and pessimism; (v) effects due to changes in bias, as increased pessimism can cause excessive increase in purchase recommendations number. In this case, analysts can should be more cautious in analysis, mainly for consistency between recommendation and the expected price; (vi) the experience of the analyst with the asset economic sector and the asset contributes to the improvement of forecasts, however, the overall experience showed opposite evidence; (vii) the optimism associated with the overall experience, over time, shows a similar behavior to an excess of confidence, which could cause reduction of accuracy; (viii) the conflicting effect of general experience between the accuracy and the observed return shows evidence that, over time, the analyst has effects similar to the endowment bias on assets, which would result in a conflict analysis of recommendations and forecasts ; (ix) despite the focus on fewer sectors contribute to the quality of accuracy, the same does not occur with the focus on assets. So it is possible that analysts may have economies of scale when cover more assets within the same industry; and finally, (x) was possible to develop a proposal for classification analysts to consider both returns and the consistency of these predictions, called Analysis coefficient. This ranking resulted better results, considering the return / standard deviation.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

Constraint-force-based approach of modelling compliant mechanisms: principle and application

Numerous works have been conducted on modelling basic compliant elements such as wire beams, and closed-form analytical models of most basic compliant elements have been well developed. However, the modelling of complex compliant mechanisms is still a challenging work. This paper proposes a constraint-force-based (CFB) modelling approach to model compliant mechanisms with a particular emphasis on modelling complex compliant mechanisms. The proposed CFB modelling approach can be regarded as an improved free-body- diagram (FBD) based modelling approach, and can be extended to a development of the screw-theory-based design approach. A compliant mechanism can be decomposed into rigid stages and compliant modules. A compliant module can offer elastic forces due to its deformation. Such elastic forces are regarded as variable constraint forces in the CFB modelling approach. Additionally, the CFB modelling approach defines external forces applied on a compliant mechanism as constant constraint forces. If a compliant mechanism is at static equilibrium, all the rigid stages are also at static equilibrium under the influence of the variable and constant constraint forces. Therefore, the constraint force equilibrium equations for all the rigid stages can be obtained, and the analytical model of the compliant mechanism can be derived based on the constraint force equilibrium equations. The CFB modelling approach can model a compliant mechanism linearly and nonlinearly, can obtain displacements of any points of the rigid stages, and allows external forces to be exerted on any positions of the rigid stages. Compared with the FBD based modelling approach, the CFB modelling approach does not need to identify the possible deformed configuration of a complex compliant mechanism to obtain the geometric compatibility conditions and the force equilibrium equations. Additionally, the mathematical expressions in the CFB approach have an easily understood physical meaning. Using the CFB modelling approach, the variable constraint forces of three compliant modules, a wire beam, a four-beam compliant module and an eight-beam compliant module, have been derived in this paper. Based on these variable constraint forces, the linear and non-linear models of a decoupled XYZ compliant parallel mechanism are derived, and verified by FEA simulations and experimental tests.

n-alkane carbon isotope ratios in plants and recent lake sediments from Cameroon

Trees and shrubs in tropical Africa use the C3 cycle as a carbon fixation pathway during photosynthesis, while grasses and sedges mostly use the C4 cycle. Leaf-wax lipids from sedimentary archives such as the long-chain n-alkanes (e.g., n-C27 to n-C33) inherit carbon isotope ratios that are representative of the carbon fixation pathway. Therefore, n-alkane d13C values are often used to reconstruct past C3/C4 composition of vegetation, assuming that the relative proportions of C3 and C4 leaf waxes reflect the relative proportions of C3 and C4 plants. We have compared the d13C values of n-alkanes from modern C3 and C4 plants with previously published values from recent lake sediments and provide a framework for estimating the fractional contribution (areal-based) of C3 vegetation cover (fC3) represented by these sedimentary archives. Samples were collected in Cameroon, across a latitudinal transect that accommodates a wide range of climate zones and vegetation types, as reflected in the progressive northward replacement of C3-dominated rain forest by C4-dominated savanna. The C3 plants analysed were characterised by substantially higher abundances of n-C29 alkanes and by substantially lower abundances of n-C33 alkanes than the C4 plants. Furthermore, the sedimentary d13C values of n-C29 and n-C31 alkanes from recent lake sediments in Cameroon (-37.4 per mil to -26.5 per mil) were generally within the range of d13C values for C3 plants, even when from sites where C4 plants dominated the catchment vegetation. In such cases simple linear mixing models fail to accurately reconstruct the relative proportions of C3 and C4 vegetation cover when using the d13C values of sedimentary n-alkanes, overestimating the proportion of C3 vegetation, likely as a consequence of the differences in plant wax production, preservation, transport, and/or deposition between C3 and C4 plants. We therefore tested a set of non-linear binary mixing models using d13C values from both C3 and C4 vegetation as end-members. The non-linear models included a sigmoid function (sine-squared) that describes small variations in the fC3 values as the minimum and maximum d13C values are approached, and a hyperbolic function that takes into account the differences between C3 and C4 plants discussed above. Model fitting and the estimation of uncertainties were completed using the Monte Carlo algorithm and can be improved by future data addition. Models that provided the best fit with the observed d13C values of sedimentary n-alkanes were either hyperbolic functions or a combination of hyperbolic and sine-squared functions. Such non-linear models may be used to convert d13C measurements on sedimentary n-alkanes directly into reconstructions of C3 vegetation cover.

Phonic skills mediate improved literacy outcomes in at-risk primary school children: results from the Ready-to-Learn Programme

Background
Learning to read is a key goal during primary school: reading difficulties may curtail children’s learning trajectories. Controversy remains regarding what types of interventions are effective for children at risk for academic failure, such as children in disadvantaged areas. We present data from a complex intervention to test the hypothesis that phonic skills and word recognition abilities are a pivotal and specific causal mechanism for the development of reading skills in children at risk for poorer literacy outcomes.
Method
Over 500 pupils across 16 primary schools took part in a Cluster Randomised Controlled Trial from school year 1 to year 3. Schools were randomly allocated to the intervention or the control arm. The intervention involved a literacy-rich after-school programme. Children attending schools in the control arm of the study received the curriculum normally provided. Children in both arms completed batteries of language, phonic skills, and reading tests every year. We used multilevel mediation models to investigate mediating processes between intervention and outcomes.
Findings
Children who took part in the intervention displayed improvements in reading skills compared to those in the control arm. Results indicated a significant indirect effect of the intervention via phonics encoding.
Discussion
The results suggest that the intervention was effective in improving reading abilities of children at risk, and this effect was mediated by improving children’s phonic skills. This has relevance for designing interventions aimed at improving literacy skills of children exposed to socio-economic disadvantage. Results also highlight the importance of methods to investigate causal pathways from intervention to outcomes.

Effect of a Mediterranean Diet Intervention on Dietary Glycemic Load and Dietary Glycemic Index: The PREDIMED Study

[EN]To compare the one year effect of two dietary interventions with MeDiet on GL and GI in the PREDIMED trial. Methods. Participants were older subjects at high risk for cardiovascular disease. This analysis included 2866 nondiabetic subjects. Diet was assessed with a validated 137-item food frequency questionnaire (FFQ). The GI of each FFQ item was assigned by a 5-step methodology using the International Tables of GI and GL Values. Generalized linear models were fitted to assess the relationship between the intervention group and dietary GL and GI at one year of follow-up, using control group as reference.

Une étude sur les déterminants biologiques, psychologiques et du travail de l'épuisement professionnel

Cette thèse de doctorat s’intéresse à mieux comprendre, d’une part, ce qui influence la sécrétion de cortisol salivaire, et d’autre part, ce qui influence l’épuisement professionnel. Plusieurs objectifs en découlent. D’abord, elle vise à mieux cerner la contribution des conditions de l’organisation du travail (utilisation des compétences, autorité décisionnelle, demandes psychologiques, demandes physiques, horaire de travail irrégulier, nombre d’heures travaillées, soutien social des collègues, soutien social des superviseurs, insécurité d’emploi) sur la sécrétion de cortisol salivaire, ainsi que le rôle modérateur de certains traits de personnalité (extraversion, agréabilité, névrosisme, conscience, ouverture d’esprit, estime de soi, centre de contrôle) sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Par ailleurs, cette thèse vise à établir la contribution des conditions de l’organisation du travail sur l’épuisement professionnel, ainsi que le rôle modérateur des traits de personnalité sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. Finalement, cette thèse vise à vérifier si la sécrétion de cortisol salivaire joue un rôle médiateur sur la relation entre les conditions de l’organisation du travail et l’épuisement professionnel, ainsi qu’à identifier les effets de médiation modérés par les traits de personnalité sur la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire. Ces objectifs sont inspirés de nombreuses limites observées dans la littérature, principalement l’intégration de déterminants à la fois biologiques, psychologiques et du travail dans la compréhension de l’épuisement professionnel. La thèse propose un modèle conceptuel qui tente de savoir comment ces différents stresseurs entraînent une dérégulation de la sécrétion de cortisol dans la salive des travailleurs. Ensuite, ce modèle conceptuel vise à voir si cette dérégulation s’associe à l’épuisement professionnel. Finalement, ce modèle conceptuel cherche à expliquer comment la personnalité peut influencer la manière dont ces variables sont reliées entre elles, c’est-à-dire de voir si la personnalité joue un rôle modérateur. Ce modèle découle de quatre théories particulières, notamment la perspective biologique de Selye (1936). Les travaux de Selye s’orientent sur l’étude de la réaction physiologique d’un organisme soumis à un stresseur. Dans ces circonstances, l’organisme est en perpétuel effort de maintien de son équilibre (homéostasie) et ne tolère que très peu de modifications à cet équilibre. En cas de modifications excessives, une réponse de stress est activée afin d’assurer l’adaptation en maintenant l’équilibre de base de l’organisme. Ensuite, le modèle conceptuel s’appuie sur le modèle de Lazarus et Folkman (1984) qui postule que la réponse de stress dépend plutôt de l’évaluation que font les individus de la situation stressante, et également sur le modèle de Pearlin (1999) qui postule que les individus exposés aux mêmes stresseurs ne sont pas nécessairement affectés de la même manière. Finalement, le modèle conceptuel de cette thèse s’appuie sur le modèle de Marchand (2004) qui postule que les réactions dépendent du décodage que font les acteurs des contraintes et ressources qui les affectent. Diverses hypothèses émergent de cette conceptualisation théorique. La première est que les conditions de l’organisation du travail contribuent directement aux variations de la sécrétion de cortisol salivaire. La deuxième est que les conditions de l’organisation du travail contribuent directement à l’épuisement professionnel. La troisième est que la sécrétion de cortisol salivaire médiatise la relation entre les conditions de l’organisation du travail et l’épuisement professionnel. La quatrième est que la relation entre les conditions de l’organisation du travail et la sécrétion de cortisol salivaire est modérée par les traits de personnalité. La cinquième est que la relation entre les conditions de l’organisation du travail, la sécrétion de cortisol salivaire et l’épuisement professionnel est modérée par les traits de personnalité. Des modèles de régression multiniveaux et des analyses de cheminement de causalité ont été effectués sur un échantillon de travailleurs canadiens provenant de l’étude SALVEO. Les résultats obtenus sont présentés sous forme de trois articles, soumis pour publication, lesquels constituent les chapitres 4 à 6 de cette thèse. Dans l’ensemble, le modèle intégrateur biopsychosocial proposé dans le cadre de cette thèse de doctorat permet de mieux saisir la complexité de l’épuisement professionnel qui trouve une explication biologique, organisationnelle et individuelle. Ce constat permet d’offrir une compréhension élargie et multiniveaux et assure l’avancement des connaissances sur une problématique préoccupante pour les organisations, la société ainsi que pour les travailleurs. Effectivement, la prise en compte des traits de personnalité et de la sécrétion du cortisol salivaire dans l’étude de l’épuisement professionnel assure une analyse intégrée et plus objective. Cette thèse conclue sur les implications de ces résultats pour la recherche, et sur les retombées qui en découlent pour les milieux de travail.

Estimates of genetic parameters for growth and wood properties in Eucalyptus pellita F. Muell. to support tree breeding in Vietnam

Eucalyptus pellita demonstrated good growth and wood quality traits in this study, with young plantation grown timber being suitable for both solid and pulp wood products. All traits examined were under moderate levels of genetic control with little genotype by environment interaction when grown on two contrasting sites in Vietnam. Eucalyptus pellita currently has a significant role in reforestation in the tropics. Research to support expanded of use of this species is needed: particularly, research to better understand the genetic control of key traits will facilitate the development of genetically improved planting stock. This study aimed to provide estimates of the heritability of diameter at breast height over bark, wood basic density, Kraft pulp yield, modulus of elasticity and microfibril angle, and the genetic correlations among these traits, and understand the importance of genotype by environment interactions in Vietnam. Data for diameter and wood properties were collected from two 10-year-old, open-pollinated progeny trials of E. pellita in Vietnam that evaluated 104 families from six native range and three orchard sources. Wood properties were estimated from wood samples using near-infrared (NIR) spectroscopy. Data were analysed using mixed linear models to estimate genetic parameters (heritability, proportion of variance between seed sources and genetic correlations). Variation among the nine sources was small compared to additive variance. Narrow-sense heritability and genetic correlation estimates indicated that simultaneous improvements in most traits could be achieved from selection among and within families as the genetic correlations among traits were either favourable or close to zero. Type B genetic correlations approached one for all traits suggesting that genotype by environment interactions were of little importance. These results support a breeding strategy utilizing a single breeding population advanced by selecting the best individuals across all seed sources. Both growth and wood properties have been evaluated. Multi-trait selection for growth and wood property traits will lead to more productive populations of E. pellita both with improved productivity and improved timber and pulp properties.

Influence of environmental variability and age on the body condition of small pelagic fish in the Gulf of Lions

Endogenous and environmental variables are fundamental in explaining variations in fish condition. Based on more than 20 yr of fish weight and length data, relative condition indices were computed for anchovy and sardine caught in the Gulf of Lions. Classification and regression trees (CART) were used to identify endogenous factors affecting fish condition, and to group years of similar condition. Both species showed a similar annual cycle with condition being minimal in February and maximal in July. CART identified 3 groups of years where the fish populations generally showed poor, average and good condition and within which condition differed between age classes but not according to sex. In particular, during the period of poor condition (mostly recent years), sardines older than 1 yr appeared to be more strongly affected than younger individuals. Time-series were analyzed using generalized linear models (GLMs) to examine the effects of oceanographic abiotic (temperature, Western Mediterranean Oscillation [WeMO] and Rhone outflow) and biotic (chlorophyll a and 6 plankton classes) factors on fish condition. The selected models explained 48 and 35% of the variance of anchovy and sardine condition, respectively. Sardine condition was negatively related to temperature but positively related to the WeMO and mesozooplankton and diatom concentrations. A positive effect of mesozooplankton and Rhone runoff on anchovy condition was detected. The importance of increasing temperatures and reduced water mixing in the NW Mediterranean Sea, affecting planktonic productivity and thus fish condition by bottom-up control processes, was highlighted by these results. Changes in plankton quality, quantity and phenology could lead to insufficient or inadequate food supply for both species.

Interaction between mercury (Hg), arsenic (As) and selenium (Se) affects the activity of glutathione S-transferase in breast milk: possible relationship with fish and shellfish intake

Breast milk is regarded as an ideal source of nutrients for the growth and development of neonates, but it can also be a potential source of pollutants. Mothers can be exposed to different contaminants as a result of their lifestyle and environmental pollution. Mercury (Hg) and arsenic (As) could adversely affect the development of fetal and neonatal nervous system. Some fish and shellfish are rich in selenium (Se), an essential trace element that forms part of several enzymes related to the detoxification process, including glutathione S-transferase (GST). The goal of this study was to determine the interaction between Hg, As and Se and analyze its effect on the activity of GST in breast milk. Milk samples were collected from women between day 7 and 10 postpartum. The GST activity was determined spectrophotometrically; total Hg, As and Se concentrations were measured by atomic absorption spectrometry. To explain the possible association of Hg, As and Se concentrations with GST activity in breast milk, generalized linear models were constructed. The model explained 44% of the GST activity measured in breast milk. The GLM suggests that GST activity was positively correlated with Hg, As and Se concentrations. The activity of the enzyme was also explained by the frequency of consumption of marine fish and shellfish in the diet of the breastfeeding women.

Investigating bias in recreational fishing surveys: Fishers listed in public telephone directories fish similarly to their unlisted counterparts

Several recent offsite recreational fishing surveys have used public landline telephone directories as a sampling frame. Sampling biases inherent in this method are recognised, but are assumed to be corrected through demographic data expansion. However, the rising prevalence of mobile-only households has potentially increased these biases by skewing raw samples towards households that maintain relatively high levels of coverage in telephone directories. For biases to be corrected through demographic expansion, both the fishing participation rate and fishing activity must be similar among listed and unlisted fishers within each demographic group. In this study, we tested for a difference in the fishing activity of listed and unlisted fishers within demographic groups by comparing their avidity (number of fishing trips per year), as well as the platform used (boat or shore) and species targeted on their most recent fishing trip. 3062 recreational fishers were interviewed at 34 tackle stores across 12 residential regions of Queensland, Australia. For each fisher, data collected included their fishing avidity, the platform used and species targeted on their most recent trip, their gender, age, residential region, and whether their household had a listed telephone number. Although the most avid fishers were younger and less likely to have a listed phone number, cumulative link models revealed that avidity was not affected by an interaction of phone listing status, age group and residential region (p > 0.05). Likewise, binomial generalized linear models revealed that there was no interaction between phone listing, age group and avidity acting on platform (p > 0.05), and platform was not affected by an interaction of phone listing status, age group, and residential region (p > 0.05). Ordination of target species using Bray-Curtis dissimilarity indices found a significant but irrelevant difference (i.e. small effect size) between listed and unlisted fishers (ANOSIM R < 0.05, p < 0.05). These results suggest that, at this time, the fishing activity of listed and unlisted fishers in Queensland is similar within demographic groups. Future research seeking to validate the assumptions of recreational fishing telephone surveys should investigate fishing participation rates of listed and unlisted fishers within demographic groups.

Prevalence and associations of Trypanosoma spp. and Sodalis glossinidius with intrinsic factors of tsetse flies

Trypanosomiasis has been identified as a neglected tropical disease in both humans and animals in many regions of sub-Saharan Africa. Whilst assessments of the biology of trypanosomes, vectors, vertebrate hosts and the environment have provided useful information about life cycles, transmission, and pathogenesis of the parasites that could be used for treatment and control, less information is available about the effects of interactions among multiple intrinsic factors on trypanosome presence in tsetse flies from different sites. It is known that multiple species of tsetse flies can transmit trypanosomes but differences in their vector competence has normally been studied in relation to individual factors in isolation, such as: intrinsic factors of the flies (e.g. age, sex); habitat characteristics; presence of endosymbionts (e.g. Wigglesworthia glossinidia, Sodalis glossinidius); feeding pattern; host communities that the flies feed on; and which species of trypanosomes are transmitted. The purpose of this study was to take a more integrated approach to investigate trypanosome prevalence in tsetse flies. In chapter 2, techniques were optimised for using the Polymerase Chain Reaction (PCR) to identify species of trypanosomes (Trypanosoma vivax, T. congolense, T. brucei, T. simiae, and T. godfreyi) present in four species of tsetse flies (Glossina austeni, G. brevipalpis, G. longipennis and G. pallidipes) from two regions of eastern Kenya (the Shimba Hills and Nguruman). Based on universal primers targeting the internal transcribed spacer 1 region (ITS-1), T. vivax was the predominant pathogenic species detected in flies, both singly and in combination with other species of trypanosomes. Using Generalised Linear Models (GLMs) and likelihood ratio tests to choose the best-fitting models, presence of T. vivax was significantly associated with an interaction between subpopulation (a combination between collection sites and species of Glossina) and sex of the flies (X2 = 7.52, df = 21, P-value = 0.0061); prevalence in females overall was higher than in males but this was not consistent across subpopulations. Similarly, T. congolense was significantly associated only with subpopulation (X2 = 18.77, df = 1, P-value = 0.0046); prevalence was higher overall in the Shimba Hills than in Nguruman but this pattern varied by species of tsetse fly. When associations were analysed in individual species of tsetse flies, there were no consistent associations between trypanosome prevalence and any single factor (site, sex, age) and different combinations of interactions were found to be significant for each. The results thus demonstrated complex interactions between vectors and trypanosome prevalence related to both the distribution and intrinsic factors of tsetse flies. The potential influence of the presence of S. glossinidius on trypanosome presence in tsetse flies was studied in chapter 3. A high number of Sodalis positive flies was found in the Shimba Hills, while there were only two positive flies from Nguruman. Presence or absence of Sodalis was significantly associated with subpopulation while trypanosome presence showed a significant association with age (X2 = 4.65, df = 14, P-value = 0.0310) and an interaction between subpopulation and sex (X2 = 18.94, df = 10, P-value = 0.0043). However, the specific associations that were significant varied across species of trypanosomes, with T. congolense and T. brucei but not T. vivax showing significant interactions involving Sodalis. Although it has previously been concluded that presence of Sodalis increases susceptibility to trypanosomes, the results presented here suggest a more complicated relationship, which may be biased by differences in the distribution and intrinsic factors of tsetse flies, as well as which trypanosome species are considered. In chapter 4 trypanosome status was studied in relation to blood meal sources, feeding status and feeding patterns of G. pallidipes (which was the predominant fly species collected for this study) as determined by sequencing the mitochondrial cytochrome B gene using DNA extracted from abdomen samples. African buffalo and African elephants were the main sources of blood meals but antelopes, warthogs, humans, giraffes and hyenas were also identified. Feeding on multiple hosts was common in flies sampled from the Shimba Hills but most flies from Nguruman had fed on single host species. Based on Multiple Correspondence Analysis (MCA), host-feeding patterns showed a correlation with site of sample collection and Sodalis status, while trypanosome status was correlated with sex and age of the flies, suggesting that recent host-feeding patterns from blood meal analysis cannot predict trypanosome status. In conclusion, the complexity of interactions found suggests that strategies of tsetse fly control should be specific to particular epidemic areas. Future studies should include laboratory experiments that use local colonies of tsetse flies, local strains of trypanosomes and local S. glossinidius under controlled environmental conditions to tease out the factors that affect vector competence and the relative influence of external environmental factors on the dynamics of these interactions.

Nuevo método de identificación usando la respuesta escalón para sistemas de fase no mínima de segundo orden

Este artículo presenta un nuevo método de identificación para sistemas de fase no mínima basado en la respuesta escalón. El enfoque propuesto provee un modelo aproximado de segundo orden evitando diseños experimentales complejos. El método propuesto es un algoritmo de identificación cerrado basado en puntos característicos de la respuesta escalón de sistemas de fase no mínima de segundo orden. Él es validado usando diferentes modelos lineales. Ellos tienen respuesta inversa entre 3,5% y 38% de la respuesta en régimen permanente. En simulaciones, ha sido demostrado que resultados satisfactorios pueden ser obtenidos usando el procedimiento de identificación propuesto, donde los parámetros identificados presentan errores relativos medios, menores que los obtenidos mediante el método de Balaguer.

A study on independent component analysis over galois fields

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.