O objetivo deste trabalho é investigar se os multiplicadores de gastos do governo diferem de acordo com o estado do ciclo de negócios para o período 1999: I- 2016: II. Para tanto é utilizado o Método de Projeção Local de Jordà para estimar as funções resposta ao impulso e os multiplicadores fiscais sob dois regimes diferentes: recessão e expansão. Para definir os diferentes regimes foram utilizadas as variáveis comumente usadas na literatura (o hiato do produto, o nível de utilização da capacidade instalada, a taxa de crescimento do PIB, a taxa de desemprego), além da datação oficial de ciclos do CODACE. A estimação do modelo não linear resulta em multiplicadores de gastos do governo, após um e dois anos, maiores nos períodos de recessão do que nos períodos de expansão, independentemente da variável escolhida para diferenciar os regimes. Porém, os multiplicadores obtidos não parecem ser diferentes estatisticamente entre os regimes. Infelizmente, como observado por Ramey e Zubairy (2017) a existência de séries históricas é fundamental para a estimação dos multiplicadores fiscais e sua ausência para a economia brasileira limita muito o que é possível dizer sobre o assunto / This paper aims to investigate whether government spending multipliers are different according to the state of the business cycle for the Brazilian economy during the period 1999:I-2016:II. In order to do so we use Jordà\'s Local Projection Method to estimate impulse response functions and fiscal multipliers under two different regimes: recession and expansion. To define the different regimes we use several variables commonly used in the literature: the output gap, the capacity utilization level, the GDP growth rate, the unemployment rate and CODACE. The nonlinear model estimations result in larger multipliers, after one and two years, in periods of economic recession than in periods of economic expansion, regardless of the variable chosen to differentiate regimes. However, the multipliers do not seem to be statistically different between regimes. Unfortunately, as observed by Ramey and Zubairy (2017), long historical series are fundamental for the adequate estimation of fiscal multipliers and their absence for the Brazilian economy does not allow anyone to say much about the subject.

This diploma thesis deals with the influence of geometric abstraction and op art on art and the use of new media in video art. Above all, it focuses on selected Czech artists of these directions and their work. The thesis is divided into two main parts, theoretical and practical. The theoretical part of the thesis deals with the beginnings of geometric abstraction and its expansion, especially in the second half of the twentieth century in Bohemia. Important names of this direction are mentioned here, namely Jan Kubíček, Hugo Demartini, Zdeněk Sýkora and Milan Grygar. Following the geometric abstraction, there are tendencies to create geometric optical illusions outlined in the chapter devoted to op art. The work of Vladislav Mirvald and Radoslav Kratina is highlighted here. In addition, it devotes itself mainly to the penetration of new media into video art and overall to the arts as such. Mr and Mrs Vasulka are mentioned as representatives of video art. They have contributed to the development of this direction, primarily through their creativity and inventiveness during their creative work. The text describes the issue not only from a global point of view, but also focuses on the development of Czech art. The practical part reflects the knowledge of the theoretical part and unifies the elements of the above-mentioned directions by creating an authorial video using mainly the principles of geometric abstraction.

Nesta tese estudamos a geometria diferencial do cross-cap usando ferramentas da teoria de singularidades. Estudamos curvas definidas sobre uma superfície regular que captam o contato da superfície com planos e esferas e estendemos o estudo para o cross-cap. Consideramos os fenômenos locais que ocorrem genericamente na família de projeções ortogonais do cross-cap e obtemos informações detalhadas sobre as bifurcações da projeção do conjuntos dos pontos duplos juntamente com a do contorno aparente. Estudamos as simetrias reflexõais infinitesimais do cross-cap através das singularidades da família da aplicações dobra e damos uma caracterização geométrica das mesmas. Finalmente, consideramos dualidade nas equações diferenciais binárias que definem as curvas assintóticas e as linhas de curvatura sobre o cross-cap. Estudamos o conjunto dos pontos onde ocorrem as inflexões de tais curvas e a relação deste conjunto com o conjunto sub-parabólico e flecnodal. / In this thesis we study the differential geometry of the cross-cap using singularity theory. We study curves on a regular surface that capture the contact of the surface with planes and spheres and extend our study to the cross-cap. We deal with local phenomena that occur generically in the family of orthogonal projection of the cross-cap and obtain detailed information about the bifurcations of the projection of double point curve together with the profile. We study the infinitesimal reflectional symmetry of a cross-cap via the singularities of the fold maps and give a geometrical characterization of these maps. Finally, we consider the duality in the binary differential equations of the asymptotic curves and of the curvature lines on a cross-cap. We study the inflection set of this curves and their relation with the subparabolic set and the flecnodal curve.

Animal home range estimations are important for conservation planning and protecting the habitat of threatened species. The accuracy of home range calculations is influenced by the map projection chosen in a geographic information system (GIS) for data analysis. Different methods of projection will distort spatial data in different ways, so it is important to choose a projection that meets the needs of the research. The large number of projections in use today and the lack of distortion comparison between the various types make selecting the most appropriate projection a difficult decision. The purpose of this study is to quantify and compare the amount of area distortion in animal home range estimations when projected into a number of projected coordinate systems in order to understand how the chosen projection influences analysis. The objectives of this research are accomplished by analyzing the tracking data of four species from different regions in North and South America. The home range of each individual from the four species datasets is calculated using the Characteristic Hull Polygon method for home range estimation and then projected into eight projected coordinate systems of various scales and projection type, including equal area, conformal, equidistant, and compromise projections. A continental Albers Equal Area projection is then used as a baseline area for the calculation of a distortion measurement ratio and magnitude of distortion statistic. The distortion measurement ratio and magnitude calculations provide a measurement of the quantity of area distortion caused by a projection. Results show the amount distortion associated with each type of projection method and how the amount of distortion changes for a projection based on geographic location. These findings show how the choice of map projection can have a large influence on data analysis and illustrate the importance of using an appropriate PCS for the needs of a given study. Distorted perceptions can influence decision-making, so it is important to recognize how a map projection can influence the analysis and interpretation of spatial data.

Durant cette thèse nous avons proposé une approche temps réel, générique et fonctionnelle pour reconnaître la posture des personnes filmées par une caméra statique. Notre approche est conçue pour être complètement automatique et indépendante du point de vue de la caméra. La reconnaissance de posture à partir de séquence vidéo est un problème difficile. Ce problème s'inscrit dans le champ de recherche plus général de l'interprétation de séquence vidéo. L'approche proposée prend en entrée des informations provenant d'algorithmes de vision telles que la silhouette de la personne observée (une image binaire où une couleur représente la personne et l'autre le fond) ou sa position dans la scène. La première contribution est la modélisation d'un avatar 3D de posture. Un avatar 3D de posture est composé d'un modèle 3D humain (définissant les relations entre les différentes parties du corps), d'un ensemble de paramètre (définissant les positions des différentes parties du corps) et d'un ensemble de primitive (définissant l'aspect visuel des parties du corps). La seconde contribution est la proposition d'une approche hybride combinant l'utilisation de modèles 3D et de techniques 2D. Les avatars 3D de postures sont utilisés dans le processus de reconnaissance pour avoir une certaine indépendance du point de vue de la caméra. Les techniques 2D représentent les silhouettes des personnes détectées pour garder un temps réel de calcul. Cette thèse montre comment les avatars 3D peuvent être utilisés pour obtenir une approche générique et fonctionnelle pour reconnaître les postures. Cette approche est composée de deux parties : la détection de postures qui reconnaît la posture de la personne détectée en utilisant seulement l'information calculée sur l'image considérée, et le filtrage temporel de posture qui reconnaît la posture en utilisant l'information provenant des images précédentes. Une troisième contribution a été faite en comparant différentes représentations 2D des silhouettes au niveau du temps de calcul nécessaire et de leur dépendance à la qualité de la silhouette. Quatre représentations ont été retenues : une représentation combinant différentes valeurs géométriques, les moment de Hu, la skeletonisation et les projections horizontale et verticale. Une quatrième contribution est la caractérisation des cas ambigus. Des ambiguïtés au niveau de la reconnaissance peuvent se produire en utilisant seulement une caméra statique. Une posture ambiguë est définie par plusieurs postures vii qui ont des silhouettes visuellement similaires. Des données de synthèse sont générées pour évaluer l'approche proposée pour différents points de vue. Ainsi, les postures ambiguës sont identifiées en considérant la posture et son orientation. L'approche est aussi évaluée pour des données réelles en proposant un modèle de vérité terrain pour la reconnaissance de posture. Une cinquième contribution a été proposée en appliquant le résultat de notre approche à la reconnaissance d'action. Une méthode utilisant des machines à états finis a ainsi été proposée pour reconnaître des actions faisant intervenir une seule personne. Chaque état de la machine est composé d'une ou plusieurs postures. Cette méthode est appliquée avec succès pour détecter les chutes et la marche. Bien que notre approche donne de très bon taux de reconnaissance, il subsiste quelques limitations. La principale limitation de l'approche est qu'elle est limitée en nombre de postures d'intérêt pour des raisons de temps de calcul et de discrimination entre les postures considérées. La seconde limitation est le temps nécessaire à la génération des silhouettes des avatars 3D de posture. En utilisant l'information sur le déplacement de la personne dans la scène, l'algorithme de reconnaissance de posture traite entre 5 et 6 images par seconde. Des améliorations peuvent être faites pour résoudre ces limitations. En particulier, nous pourrions adapter automatiquement l'ensemble des postures d'intérêt au cas considéré, en utilisant par exemple la posture reconnue précédemment pour restreindre les postures 3D dont nous voulons extraire les silhouettes.

<p>Long term care and social services (LTCaS) for older people are an important part of the Scandinavian welfare state. The fast growing number of elderly people in Sweden has caused many concerns about increases in future needs (and particularly costs) of age-related social programs such as LTCaS. The general aim of this dissertation is to examine how projected demographic changes may affect future needs for long-term care and services in Sweden assuming different trends in morbidity and mortality. The following data sources are used: national population registers, register data on inpatient/outpatient health care from region Skåne, the Swedish National Survey on Living Conditions (SNSLC) for the period 1975-1999. Three alternative methods to inform simple demographic extrapolations of needs for health and social care for the elderly are presented. Furthermore, a new method for demographic projections has been developed. According to our studies, the health of older people (measured as the prevalence of severe ill-health) has improved during the study period. Taking into account health status, when projecting future needs for LTCaS, will result in a fairly substantial reduction of the rate of the demographically influenced increase in projected LTCaS needs. The changes in population composition regarding education and mortality differentials per educational level may have a significant impact on the number of the elderly in the future. On the other hand, the projected increase in the number of older people suffering from severe ill-health, as a consequence of population ageing, may be counterbalanced to a large extent by changes in the educational composition towards a higher proportion of the population having a high educational level and lower prevalence of severe ill-health. We need to improve our planning tools in order to support policy-makers to plan for uncertainty concerning future needs and demand for LTCaS.</p>

J'aborderai l'étude géologique des hautes vallées de la Santaire, de l'Impradine et de la Petite Rhue dans l'ordre chronostratigraphique, à savoir: l - Formations non voleaniques (socle et sédiments oligocènes) II - Basaltes miocènes III - Formations acides inférieures IV - Complexe bréchique V - Basaltes terminaux VI - Terrains de couverture. La partie la plus importante de ce mémoire est consacrée aux formations acides inférieures et au complexe bréchique, généralement délaissés dans la plupart des travaux antérieurs à 1974. Pour chacun de ces deux ensembles, l'accent est mis sur leur étude stratigraphique détaillée qui, seule, peut permettre de découvrir des niveaux repères, si précieux dans des formations apparemment très homogènes. En tenant compte des données pétrographiques, j'essaierai d'apporter une interprétation dynamique aux différents phénomènes observés et, dans la mesure du possible, d'aborder des problèmes plus généraux dépassant le cadre de la région étudiée. Le dernier chapitre sera consacré à la magmatologie.

Long term care and social services (LTCaS) for older people are an important part of the Scandinavian welfare state. The fast growing number of elderly people in Sweden has caused many concerns about increases in future needs (and particularly costs) of age-related social programs such as LTCaS. The general aim of this dissertation is to examine how projected demographic changes may affect future needs for long-term care and services in Sweden assuming different trends in morbidity and mortality. The following data sources are used: national population registers, register data on inpatient/outpatient health care from region Skåne, the Swedish National Survey on Living Conditions (SNSLC) for the period 1975-1999. Three alternative methods to inform simple demographic extrapolations of needs for health and social care for the elderly are presented. Furthermore, a new method for demographic projections has been developed. According to our studies, the health of older people (measured as the prevalence of severe ill-health) has improved during the study period. Taking into account health status, when projecting future needs for LTCaS, will result in a fairly substantial reduction of the rate of the demographically influenced increase in projected LTCaS needs. The changes in population composition regarding education and mortality differentials per educational level may have a significant impact on the number of the elderly in the future. On the other hand, the projected increase in the number of older people suffering from severe ill-health, as a consequence of population ageing, may be counterbalanced to a large extent by changes in the educational composition towards a higher proportion of the population having a high educational level and lower prevalence of severe ill-health. We need to improve our planning tools in order to support policy-makers to plan for uncertainty concerning future needs and demand for LTCaS.

With the increasing availability of high-throughput systems for parallel monitoring of multiple variables, e.g. levels of large numbers of transcripts in functional genomics experiments, massive amounts of data are being collected even from single experiments. Extracting useful information from such systems is a non-trivial task that requires powerful computational methods to identify common trends and to help detect the underlying biological patterns. This thesis deals with the general computational problems of classifying and integrating high-dimensional empirical data using a latent variable based modeling approach. The underlying principle of this approach is that a complex system can be characterized by a few independent components that characterize the systematic properties of the system. Such a strategy is well suited for handling noisy, multivariate data sets with strong multicollinearity structures, such as those typically encountered in many biological and chemical applications. The main foci of the studies this thesis is based upon are applications and extensions of the orthogonal projections to latent structures (OPLS) method in life science contexts. OPLS is a latent variable based regression method that separately describes systematic sources of variation that are related and unrelated to the modeling aim (for instance, classifying two different categories of samples). This separation of sources of variation can be used to pre-process data, but also has distinct advantages for model interpretation, as exemplified throughout the work. For classification cases, a probabilistic framework for OPLS has been developed that allows the incorporation of both variance and covariance into classification decisions. This can be seen as a unification of two historical classification paradigms based on either variance or covariance. In addition, a non-linear reformulation of the OPLS algorithm is outlined, which is useful for particularly complex regression or classification tasks. The general trend in functional genomics studies in the post-genomics era is to perform increasingly comprehensive characterizations of organisms in order to study the associations between their molecular and cellular components in greater detail. Frequently, abundances of all transcripts, proteins and metabolites are measured simultaneously in an organism at a current state or over time. In this work, a generalization of OPLS is described for the analysis of multiple data sets. It is shown that this method can be used to integrate data in functional genomics experiments by separating the systematic variation that is common to all data sets considered from sources of variation that are specific to each data set. / Funktionsgenomik är ett forskningsområde med det slutgiltiga målet att karakterisera alla gener i ett genom hos en organism. Detta inkluderar studier av hur DNA transkriberas till mRNA, hur det sedan translateras till proteiner och hur dessa proteiner interagerar och påverkar organismens biokemiska processer. Den traditionella ansatsen har varit att studera funktionen, regleringen och translateringen av en gen i taget. Ny teknik inom fältet har dock möjliggjort studier av hur tusentals transkript, proteiner och små molekyler uppträder gemensamt i en organism vid ett givet tillfälle eller över tid. Konkret innebär detta även att stora mängder data genereras även från små, isolerade experiment. Att hitta globala trender och att utvinna användbar information från liknande data-mängder är ett icke-trivialt beräkningsmässigt problem som kräver avancerade och tolkningsbara matematiska modeller. Denna avhandling beskriver utvecklingen och tillämpningen av olika beräkningsmässiga metoder för att klassificera och integrera stora mängder empiriskt (uppmätt) data. Gemensamt för alla metoder är att de baseras på latenta variabler: variabler som inte uppmätts direkt utan som beräknats från andra, observerade variabler. Detta koncept är väl anpassat till studier av komplexa system som kan beskrivas av ett fåtal, oberoende faktorer som karakteriserar de huvudsakliga egenskaperna hos systemet, vilket är kännetecknande för många kemiska och biologiska system. Metoderna som beskrivs i avhandlingen är generella men i huvudsak utvecklade för och tillämpade på data från biologiska experiment. I avhandlingen demonstreras hur dessa metoder kan användas för att hitta komplexa samband mellan uppmätt data och andra faktorer av intresse, utan att förlora de egenskaper hos metoden som är kritiska för att tolka resultaten. Metoderna tillämpas för att hitta gemensamma och unika egenskaper hos regleringen av transkript och hur dessa påverkas av och påverkar små molekyler i trädet poppel. Utöver detta beskrivs ett större experiment i poppel där relationen mellan nivåer av transkript, proteiner och små molekyler undersöks med de utvecklade metoderna.

In this paper we use the long-term empirical relationship among primary energy consumption, real income, physical capital, population and technology, obtained by averaged panel error correction models, to project the long-term primary energy consumption of 56 countries up to 2100. In forecasting long-term primary energy consumption, we work with four different Shared Socioeconomic Pathway Scenarios (SSPs) developed for the Intergovernmental Panel on Climate Change (IPCC) framework, assuming different challenges to adaptation and mitigation. We find that in all scenarios, China, the United States and India will be the largest energy consumers, while highly growing countries will also significantly contribute to energy use. We observe for most scenarios a sharp increase in global energy consumption, followed by a levelling-out and a decrease towards the second half of the century. The reasons behind this pattern are not only slower population growth, but also infrastructure saturation and increased total factor productivity. This means, as countries move towards more knowledge based societies, and higher energy efficiency, their primary energy usage is likely to decrease as a result. Global primary energy consumption is expected however to increase significantly in the coming decades, thus increasing the pressure on policy makers to cope with the questions of energy security and greenhouse gas mitigation at the same time. (authors' abstract) / Series: Department of Economics Working Paper Series