E-government e participação política em Portugal

Dissertação de Mestrado em MPA - Administração Pública

Human capital as a factor of growth and employment at the regional level. The case of Spain

We use statistical techniques to quantify the effects of school attainment on individual wages, participation rates and employment probabilities in Spain, and to measure the contribution of education to labour productivity at the regional level. These estimates are then combined with data on private and public expenditure on education and with information on taxes and social benefits to construct measures of the private and social returns to schooling, to explore the effects of public policies on private incentives to invest in human capital, and to analyse the long-term effects of schooling on public finances. The results are used, together with estimates of the returns to alternative assets, to draw some tentative conclusions regarding the adequacy of the aggregate investment patterns observed in the regions of Spain, and to identify changes in the design of national and EU cohesion and growth policies that may help enhance their effectiveness.

Distinction of males of the Lutzomyia intermedia (Lutz & Neiva, 1912) species complex by ratios between dimensions and by an artificial neural network (Diptera: Psychodidae, Phlebotominae)

The females of the two species of the Lutzomyia intermedia complex can be easily distinguished, but the males of each species are quite similar. The ratios between the extra-genital and the genital structures of L. neivai are larger than those of L. intermedia s. s., according to ANOVA. An artificial neural network was trained with a set of 300 examples, randomly taken from a sample of 358 individuals. The input vectors consisted of several ratios between some structures of each insect. The model was tested on the remaining 58 insects, 56 of which (96.6%) were correctly identified. This ratio of success can be considered remarkable if one takes into account the difficulty of attaining comparable results using traditional statistical techniques.

A Picture of breastfeeding in Ireland: Evidence from the Growing Up in Ireland study

Objectives: Describe the main patterns in breastfeeding Measure some of the predictors of “ Measure some of the consequences of “ Introduce some useful statistical techniques

Mejora diagnóstica de hepatopatías de afectación difusa mediante técnicas de inteligencia artificial

The automatic diagnostic discrimination is an application of artificial intelligence techniques that can solve clinical cases based on imaging. Diffuse liver diseases are diseases of wide prominence in the population and insidious course, yet early in its progression. Early and effective diagnosis is necessary because many of these diseases progress to cirrhosis and liver cancer. The usual technique of choice for accurate diagnosis is liver biopsy, an invasive and not without incompatibilities one. It is proposed in this project an alternative non-invasive and free of contraindications method based on liver ultrasonography. The images are digitized and then analyzed using statistical techniques and analysis of texture. The results are validated from the pathology report. Finally, we apply artificial intelligence techniques as Fuzzy k-Means or Support Vector Machines and compare its significance to the analysis Statistics and the report of the clinician. The results show that this technique is significantly valid and a promising alternative as a noninvasive diagnostic chronic liver disease from diffuse involvement. Artificial Intelligence classifying techniques significantly improve the diagnosing discrimination compared to other statistics.

Exploration of geological variability and possible processes through the use of compositional data analysis: an example using scottish metamorphosed

Developments in the statistical analysis of compositional data over the last twodecades have made possible a much deeper exploration of the nature of variability,and the possible processes associated with compositional data sets from manydisciplines. In this paper we concentrate on geochemical data sets. First we explainhow hypotheses of compositional variability may be formulated within the naturalsample space, the unit simplex, including useful hypotheses of subcompositionaldiscrimination and specific perturbational change. Then we develop through standardmethodology, such as generalised likelihood ratio tests, statistical tools to allow thesystematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require specialconstruction. We comment on the use of graphical methods in compositional dataanalysis and on the ordination of specimens. The recent development of the conceptof compositional processes is then explained together with the necessary tools for astaying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland.Finally we point out a number of unresolved problems in the statistical analysis ofcompositional processes

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets

Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of beingcompositional data and, for a given level of significance, are likely to be beyond thecapabilities of laboratories to distinguish between minute concentrations and completeabsence, thus preventing laboratories from reporting extremely low concentrations of theanalyte. Instead, what is reported is the detection limit, which is the minimumconcentration that conclusively differentiates between presence and absence of theelement. A spatially distributed exhaustive sample is employed in this study to generateunbiased sub-samples, which are further censored to observe the effect that differentdetection limits and sample sizes have on the inference of population distributionsstarting from geochemical analyses having specimens below detection limit (nondetects).The isometric logratio transformation is used to convert the compositional data in thesimplex to samples in real space, thus allowing the practitioner to properly borrow fromthe large source of statistical techniques valid only in real space. The bootstrap method isused to numerically investigate the reliability of inferring several distributionalparameters employing different forms of imputation for the censored data. The casestudy illustrates that, in general, best results are obtained when imputations are madeusing the distribution best fitting the readings above detection limit and exposes theproblems of other more widely used practices. When the sample is spatially correlated, itis necessary to combine the bootstrap with stochastic simulation

Seeds of distrust: conflict in Uganda

We study the effect of civil conflict on social capital, focusing on Uganda's experience during the last decade. Using individual and county-level data, we document large causal effects on trust and ethnic identity of an exogenous outburst of ethnic conflicts in 2002-2005. We exploit two waves of survey data from Afrobarometer (Round 4 Afrobarometer Survey in Uganda, 2000, 2008), including information on socioeconomic characteristics at the individual level, and geo-referenced measures of fighting events from ACLED. Our identification strategy exploits variations in the both the spatial and ethnic intensity of fighting. We find that more intense fighting decreases generalized trust and increases ethnic identity. The effects are quantitatively large and robust to a number of control variables, alternative measures of violence, and different statistical techniques involving ethnic and spatial fixed effects and instrumental variables. Controlling for the intensity of violence during the conflict, we also document that post-conflict economic recovery is slower in ethnically fractionalized counties. Our findings are consistent with the existence of a self-reinforcing process between conflicts and ethnic cleavages.

Exploring unfrequent events with accelerated molecular dynamics simulations: from photochemistry to drug design

La meva incorporació al grup de recerca del Prof. McCammon (University of California San Diego) en qualitat d’investigador post doctoral amb una beca Beatriu de Pinós, va tenir lloc el passat 1 de desembre de 2010; on vaig dur a terme les meves tasques de recerca fins al darrer 1 d’abril de 2012. El Prof. McCammon és un referent mundial en l’aplicació de simulacions de dinàmica molecular (MD) en sistemes biològics d’interès humà. La contribució més important del Prof. McCammon en la simulació de sistemes biològics és el desenvolupament del mètode de dinàmiques moleculars accelerades (AMD). Les simulacions MD convencionals, les quals estan limitades a l’escala de temps del nanosegon (~10-9s), no son adients per l’estudi de sistemes biològics rellevants a escales de temps mes llargues (μs, ms...). AMD permet explorar fenòmens moleculars poc freqüents però que son clau per l’enteniment de molts sistemes biològics; fenòmens que no podrien ser observats d’un altre manera. Durant la meva estada a la “University of California San Diego”, vaig treballar en diferent aplicacions de les simulacions AMD, incloent fotoquímica i disseny de fàrmacs per ordinador. Concretament, primer vaig desenvolupar amb èxit una combinació dels mètodes AMD i simulacions Car-Parrinello per millorar l’exploració de camins de desactivació (interseccions còniques) en reaccions químiques fotoactivades. En segon lloc, vaig aplicar tècniques estadístiques (Replica Exchange) amb AMD en la descripció d’interaccions proteïna-lligand. Finalment, vaig dur a terme un estudi de disseny de fàrmacs per ordinador en la proteïna-G Rho (involucrada en el desenvolupament de càncer humà) combinant anàlisis estructurals i simulacions AMD. Els projectes en els quals he participat han estat publicats (o estan encara en procés de revisió) en diferents revistes científiques, i han estat presentats en diferents congressos internacionals. La memòria inclosa a continuació conté més detalls de cada projecte esmentat.

Mirror me : the effect of the voting advice application smartvote on voting preferences and behavior of Swiss voters

Voting Advice Applications (VAAs) have become a central component of election campaigns worldwide. Through matching political preferences of voters to parties and candidates, the web application grants voters a look into their political mirror and reveals the most suitable political choices to them in terms of policy congruence. Both the dense and concise information on the electoral offer and the comparative nature of the application make VAAs an unprecedented information source for electoral decision making. In times where electoral choices are found to be highly individualized and driven by political issue positions, an ever increasing number of voters turn to VAAs before casting their ballots. With VAAs in high demand, the question of their effects on voters has become a pressing research topic. In various countries, survey research has been used to proclaim an impact of VAAs on electoral behavior, yet practically all studies fail to provide the scientific evidence that would allow for making such claims. In this thesis, I set out to systematically establish the causal link between VAA use and electoral behavior, using various data sources and appropriate statistical techniques in doing so. The focus lies on the Swiss VAA smartvote, introduced in the forefront of the 2003 Swiss federal elections and meanwhile an integral part of the national election campaign, smartvote has produced over a million voting recommendations in the last Swiss federal elections to an active electorate of two million, potentially guiding a vast amount of voters in their choices on the ballot. In order to determine the effect of the VAA on electoral behavior, I analyze both voting preferences and choice among Swiss voters during two consecutive election periods. First, I introduce statistical techniques to adequately examine VAA effects in observational studies and use them to demonstrate that voters who used smartvote prior to the 2007 Swiss federal elections were significantly more likely to swing vote in the elections than non- users. Second, I analyze preference voting during the same election and show that the smartvote voting recommendation inclines politically knowledgeable voters to modify their ballots and cast candidate specific preference votes. Third, to further tackle the indication that smartvote use affects the preference structure of voters, I employ an experimental research design to demonstrate that voters who use the application tend to strengthen their vote propensities for their most preferred party and adapt their overall party preferences in a way that they consider more than one party as eligible vote options after engaging with the application. Finally, vote choice is examined for the 2011 Swiss federal election, showing once more that the VAA initiated a change of party choice among voters. In sum, this thesis presents empirical evidence for the transformative effect of the Swiss VAA smartvote on the electoral behavior.

Comparison of the site distribution of melanoma in New Zealand and Canada

A comparison of the site distribution of cutaneous malignant melanoma in New Zealand and Canada was performed. This series deals with 41,331 incident cases registered between 1968 and 1990 and is the largest to date to evaluate the influence of age and gender on the site distribution of melanoma. Site-specific, age-standardized rates per unit surface area and relative tumour density were assessed by gender and country and differences compared with statistical techniques adapted to this context. The age-standardized rates for all sites were higher in New Zealand than in Canada, the ratio being 3.2 for men and 3.8 for women. Occurrence of melanoma was denser for chronically than intermittently exposed sites in both New Zealand and Canada. The highest incidence rate per unit area was for the ears in men which was more than 5 times the rate for the entire body in each country. For each gender, melanomas were relatively commoner on the trunk and the face in Canada, and on the lower limbs in New Zealand. The variations in the site distribution were similar in each country and consistent with the effect of differential patterns of sun exposure between genders. Our results show that the levels of risk of melanoma between phenotypically comparable populations exposed to different amount of UV radiation vary in a site-specific manner, especially for intermittently exposed sites. This suggests that both environmental conditions and lifestyle factors influence the site distribution of melanoma in these two populations.

Factors that determine the evolution of high-growth businesses

The study herein discusses research aimed at elucidating the factors that contribute to a business' ability to maintain high growth. The database from the Iberian Balance Sheet Analysis System (SABI, from its initials in Spanish) was used to identify 250 industrial Catalonian businesses with high growth during 2004-2007. These companies participated in a survey on strategies and management practices; in 2013, they were re-analyzed to investigate the factors that contributed to continued growth for certain companies. Through diverse statistical techniques, business policies related to quality, innovation, internationalization and finance were shown to influence business growth and sustainability over time. High-growth businesses have been studied throughout the world, but this is the first study to investigate the evolution of businesses after a high-growth phase.

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

Quantifying Social Asymmetric Structures

Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations nor do they deal with dependency. This paper describes a mathematical procedure for analyzing dyadic interactions in a social system. The proposed method mainly consists of decomposing asymmetric data into their symmetrical and skew-symmetrical parts. A quantification of skew-symmetry for a social system can be obtained by dividing the norm of the skew-symmetrical matrix by the norm of the asymmetric matrix. This calculation makes available to researchers a quantity related to the amount of dyadic reciprocity. Regarding agents, the procedure enables researchers to identify those whose behavior is asymmetric with respect to all agents. It is also possible to derive symmetric measurements among agents and to use multivariate statistical techniques.