Bakgrund: De stora medicinska framstegen som åstadkommits inom förlossningsvården genom historien har varit revolutionerande för kvinnor och barn vilket bidragit till en minskad mödra- och barnadödlighet. Barnmorskan är expert på normal graviditet och födsel, och har både förr och nu en avgörande roll för folkhälsans positiva utveckling. Trots denna utveckling minskar antalet normala födslar och parallellt ses en ökning av onödiga interventioner inklusive en ökad andel kejsarsnitt. Syfte: Att klargöra vad som främjar en normal födsel från barnmorskans och kvinnans perspektiv. Metod: Litteraturöversikt med systematisk ansats utfördes genom databassökning i PubMed och CINAHL. Artiklarna kvalitetgranskades genom Caldwells kvalitetsgranskningsmall och dataanalysen utfördes genom en integrerad analys av fem kvantitativa respektive 11 kvalitativa artiklar som svarade på studiens syfte och frågeställningar. Resultat: Studiens resultat klargjorde vad som främjar normal födsel och redovisades genom fyra huvudkategorier. Kategorin stöd identifierade hur kontinuerlig närvaro, empowerment och mödravårdens förlossningsförberedelse främjade det normala. Kategorin omgivning redovisade hur vårdorganisationen och födelserummet antingen kunde främja eller hämma den normala födelseprocessen. Kategorin barnmorskans betydelse redovisades genom hur barnmorskans kompetens, handläggande och egenskaper kunde påverka förloppet. Slutligen visade kategorin kvinnans individuella förutsättningar hur medicinska faktorer, den egna förberedelsen samt copingstrategier underlättade eller hindrade en normal födsel. Slutsats: För att främja normal födsel krävs en genuin tro på den normala födelseprocessen av både barnmorskan och kvinnan. Studien visar på hur barnmorskan självständigt kan främja processen genom sitt förhållningssätt där stöd är avgörande. Ytterligare huvudfynd visar dock på hur vårdorganisationen kan ha en hämmande inverkan. Kontinuitetsmodeller är den mest framgångsrika vårdformen för att främja normal födsel och trots detta är denna vårdform högst begränsad i Sverige. Istället visar studier på hur obstetrikerledda förlossningsenheter med utbredd riskkultur dominerar. Detta är problematisk då studier inklusive denna litteraturöversikt visar hur onödiga interventioner samt kejsarsnitt minskar med kontinuitetsmodeller. / Background: Medical advances throughout history have been revolutionary contributing to a reduction in maternal and child mortality. Midwives are experts in normal pregnancy and birth, having a decisive role in the positive development of public health. Despite this development, the number of normal births are decreasing while there is an increase in unnecessary interventions, including caesarean sections. Aim: To clarify what promotes a normal birth from a midwife and woman's perspective. Method: Literature review with a systematic approach was carried out by database search in PubMed and CINAHL. The articles were quality reviewed using the Caldwell quality framework. The data analysis was performed through an integrated analysis of five quantitative and 11 qualitative articles that answered the aim of the study. Results: The findings clarified factors promoting normal birth and were presented through four main categories: Support identified how continuous presence, empowerment and maternity care's birth preparation promoted normality. Environment reported how care organizations and delivery rooms could either inhibit or promote normal birth. Midwife's importance was reported through how midwife's experience, competence, handling and characteristics could influence the process. Finally woman's individual conditions showed how medical factors, own preparation and coping strategies facilitated or hindered normal birth. Conclusion: To promote normal birth, a genuine belief in normal birth is required by midwives and women. Findings show how midwives independently can promote normal birth through her approach where support was crucial. However, further findings show how care organizations could have an inhibiting impact. Continuity of care models has proven to be the most successful care in promoting normal birth. Despite this, these models are highly limited in Sweden. Instead, studies show how obstetrician-led delivery units with a widespread culture of risk are dominant. This is problematic as studies show how unnecessary interventions and cesarean sections are reduced with continuity of care models.

The main purpose of the study is to investigate if Boverkets supplement BEN is reasonable for apartment buildings with individual metering and charging for hot water. But also if there is any connection between hot water consumption, number of residents, bathtub and number of rooms in the apartments. Finally, it is investigated whether the residents make any active choice to reduce their consumption of hot water and if so why.In total, measurement data has been obtained from 2097 apartments distributed among 21 tenant-owned associations in Stockholm and Uppsala where Riksbyggen is the estate manager. The study also includes a comprehensive survey that was sent out to 975 apartments distributed among nine tenant-owned associations. The purpose of the survey is to get a better picture of how households reason about their hot water consumption. Through the database provided by Infometric, the work has had access to the apartments' actual hot water consumption. Thus, it has been possible to retrieve measurement data from all associations and to pair individual survey responses with the apartments' unique meter ID.The results presented in the study show that the associations are 27.1% below Boverkets supplement BEN for ordinary fixtures. At BEN for low-flush fixtures, the associations are 19.6% below the supplement. The study shows that factors such as the number of residents and the number of rooms and kitchens have a major impact on hot water consumption. Indications also show that bathtubs affect consumption to the negative to the extent that hot water consumption tends to increase. It also appears that residents are actively trying to minimize their hot water consumption where environmental reasons are stated as the main cause.

In this paper, we prove that the joint distribution of random vectors Z 1 and Z 2 and the distribution of Z 2 are skew normal provided that Z 1 is skew normally distributed and Z 2 conditioning on Z 1 is distributed as closed skew normal. Also, we extend the main results to the matrix variate case.

Neste trabalho apresentamos várias demonstrações do Teorema da Base Normal para certos tipos de extensões galoisianas de corpos, algumas existenciais e outras construtivas, destacando as diferenças e dificuldades de cada situação. Apresentamos também generalizações de tal teorema e mostramos que toda extensão galoisiana de grau ímpar de corpos admite uma base normal autodual com respeito µa forma bilinear traço / In this work we present several demonstrations of The Normal Basis Theorem for certain kinds of galoisian extensions of fields, some of them existential and others constructive, pointing the diffculties and differences in each situation. We also present generalizations of such theorem and show that every odd degree galoisian extension of fields admits a self-dual normal base with respect to the trace bilinear map

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No. of bitstreams: 1 TeseEAMms.pdf: 1490434 bytes, checksum: e7a807666b453630ffb423774d2539b9 (MD5) Previous issue date: 2016-03-23 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / From the generalized normal distribution and concepts of the generalized autoregressive moving averages models we introduce the generalized normal-ARMA model as an alternative way to model time series exhibiting symmetry and tails that may be lighter or heavier when compared the normal distribution. We present application for proposed model using three time series in the hydrology, economy and publics policy areas. The proposed model is presented as good alternative when compared to ARMA model with normal distribution. We extended this model the case of the asymmetric time series. In this case we used the Box-Cox transformation, denoted by Box-Cox generalized normal ARMA. The particular case, when we use the logarithmic transformation is called generalized log-normal ARMA. We adjusted the models with transformation to the series on monthly average affluent streamflow of the Furnas and Sobradinho hydroelectric plants. We obtain the prediction values for the model with transformation, that are better when compared with the model without transformation. To treat time series that exhibit periodic in the correlation function we defined three extensions for periodic autoregressive model, called generalized normal periodic autoregressive model, generalized log-normal periodic autoregressive model and Box-Cox generalized normal periodic autoregressive model. We can observed that the series on monthly average affluent streamflow of the Furnas and Sobradinho hydroelectric plants have periodic correlation. We present two applications of periodic models from these series. In the models, we note that is not necessary the use of generalized normal distribution in every months, just in some the generalized normal distribution presented better results than the normal distribution. Finally, we define the generalized normal zero inflated distribution and the generalized normal zero inflated ARMA model for time series. Adopting the model for series that have zero inflation and the maximum likelihood method for estimation of parameters, we analyze the serie of the amount of rainfall in the city of São Carlos. / A partir da distribuição normal generalizada e dos conceitos do modelo autorregressivo e de médias móveis generalizado, introduzimos o modelo normal generalizada- ARMA, como alternativa para modelar séries temporais, que exibem simetria e caudas mais leves ou mais pesadas quando comparadas com a distribuição normal. Apresentamos aplicações do modelo proposto, usando três séries temporais, das áreas de hidrologia, políticas públicas e economia. O modelo proposto se apresentou como uma boa alternativa ao modelo ARMA com distribuição normal. Estendemos o modelo para o caso de séries que apresentam assimetria. Neste caso, utilizamos a transformação de Box-Cox, denotado por Box-Cox normal generalizada-ARMA. O caso particular quando utilizamos a transformação logarítmica é chamado de log-normal generalizada-ARMA. Ajustamos os modelos com transformação à séries de vazões das usinas hidrelétricas de Furnas e Sobradinho. Calculamos predições, que para o modelo com transformação, foram melhores, quando comparado ao modelo sem transformação. Com o objetivo de tratar séries que apresentam periodicidade na função de correlação, definimos três extensões do modelo autorregressivo periódico, chamando-os de modelo normal generalizada autorregressivo periódico, modelo log-normal generalizada autorregressivo periódico e modelo Box-Cox normal generalizada autorregressivo periódico. Constatamos que as séries de vazões das usinas hidrelétricas de Furnas e Sobradinho apresentam correlação periódica. Apresentamos duas aplicações dos modelos periódicos propostos usando estas séries. Nos ajustes dos modelos, notamos que não há necessidade da utilização da distribuição normal generalizada em todos os meses, mas em alguns a distribuição normal generalizada se sobressaiu em relação a distribuição normal. Por último, definimos a distribuição normal generalizada zero inflacionada e o modelo para séries temporais normal generalizada zero inflacionada-ARMA. Adotando o método de máxima verossimilhança e o modelo para séries que apresentam inflação de zeros, analisamos a série da quantidade de precipitação pluviométrica da cidade de São Carlos.

Neste trabalho apresentamos várias demonstrações do Teorema da Base Normal para certos tipos de extensões galoisianas de corpos, algumas existenciais e outras construtivas, destacando as diferenças e dificuldades de cada situação. Apresentamos também generalizações de tal teorema e mostramos que toda extensão galoisiana de grau ímpar de corpos admite uma base normal autodual com respeito µa forma bilinear traço / In this work we present several demonstrations of The Normal Basis Theorem for certain kinds of galoisian extensions of fields, some of them existential and others constructive, pointing the diffculties and differences in each situation. We also present generalizations of such theorem and show that every odd degree galoisian extension of fields admits a self-dual normal base with respect to the trace bilinear map

Este trabalho apresenta um estudo de inferência e diagnósticos em modelos assimétricos. A análise de influência é baseada na metodologia para modelos com dados incompletos, que é relacionada ao algoritmo EM (Zhu e Lee, 2001). Além dos modelos de regressão Normal Assimétrico (Azzalini, 1999) e t-Normal Assimétrico (Gómez, Venegas e Bolfarine, 2007) existentes, são desenvolvidas duas novas classes de modelos, denominados modelos de misturas de escala normal assimétricos (englobando as distribuições Normal, t-Normal, Slash, Normal-Contaminada e Exponencial-potência Assimétricas) e modelos lineares mistos robustos assimétricos, utilizando distribuições de misturas de escalas normais assimétricas para o efeito aleatório e distribuições de misturas de escalas para o erro aleatório. Para o modelo misto, a matriz de informação de Fisher observada é calculada utilizando a aproximação de Louis (1982) para dados incompletos. Para todos os modelos, algoritmos tipo EM são desenvolvidos de forma a fornecer uma solução numérica para os parâmetros dos modelos de regressão. Para cada modelo de regressão, medidas de bondade de ajuste são realizadas via inspeção visual do gráfico de envelope simulado. Para os modelos de misturas de escalas normais assimétricos, um estudo de robustez do algoritmo EM proposto é desenvolvido, determinando a eficácia dos estimadores apresentados. Aplicações dos modelos estudados são realizadas para os conjuntos de dados do Australian Institute of Sports (AIS), para o conjunto de dados sobre qualidade de vida de pacientes (mulheres) com câncer de mama, em um estudo realizado pelo Centro de Atenção Integral à Saúde da Mulher (CAISM) em conjunto com a Faculdade de Ciências Médicas, da Universidade Estadual de Campinas e para o conjunto de dados de colesterol de Framingham. / This work presents a study of inference and diagnostic in asymmetric models. The influence analysis is based in the methodology for models with incomplete data, that is related to the algorithm EM (Zhu and Lee, 2001). Beyond of the existing asymmetric normal (Azzalini, 1999) and t-Normal asymmetric (Gómez, Venegas and Bolfarine, 2007) regression models, are developed two new classes of models, namely asymmetric normal scale mixture models (embodying the asymmetric Normal, t-Normal, Slash, Contaminated-Normal and Power-Exponential distributions) and asymmetric robust linear mixed models, utilizing asymmetric normal scale mixture distributions for the random effect and normal scale mixture distributions for the random error. For the mixed model, the observed Fisher information matrix is calculated using the Louis\' (1982) approach for incomplete data. For all models, EM algorithms are developed, that provide a numeric solution for the parameters of the regression models. For each regression model, measures of goodness of fit are realized through visual inspection of the graphic of simulated envelope. For the asymmetric normal scale mixture models, a study of robustness of the proposed EM algorithm is developed to determine the efficacy of the presented estimators. Applications of the studied models are made for the data set of the Australian Institute of Sports (AIS), for the data set about quality of life of patients (women) with breast cancer, in a study made by Centro de Atenção Integral à Saúde da Mulher (CAISM) in conjoint with the Medical Sciences Faculty, of the Campinas State\'s University and for the data set of Framingham\'s cholesterol study.

Este trabalho apresenta um estudo de inferência e diagnósticos em modelos assimétricos. A análise de influência é baseada na metodologia para modelos com dados incompletos, que é relacionada ao algoritmo EM (Zhu e Lee, 2001). Além dos modelos de regressão Normal Assimétrico (Azzalini, 1999) e t-Normal Assimétrico (Gómez, Venegas e Bolfarine, 2007) existentes, são desenvolvidas duas novas classes de modelos, denominados modelos de misturas de escala normal assimétricos (englobando as distribuições Normal, t-Normal, Slash, Normal-Contaminada e Exponencial-potência Assimétricas) e modelos lineares mistos robustos assimétricos, utilizando distribuições de misturas de escalas normais assimétricas para o efeito aleatório e distribuições de misturas de escalas para o erro aleatório. Para o modelo misto, a matriz de informação de Fisher observada é calculada utilizando a aproximação de Louis (1982) para dados incompletos. Para todos os modelos, algoritmos tipo EM são desenvolvidos de forma a fornecer uma solução numérica para os parâmetros dos modelos de regressão. Para cada modelo de regressão, medidas de bondade de ajuste são realizadas via inspeção visual do gráfico de envelope simulado. Para os modelos de misturas de escalas normais assimétricos, um estudo de robustez do algoritmo EM proposto é desenvolvido, determinando a eficácia dos estimadores apresentados. Aplicações dos modelos estudados são realizadas para os conjuntos de dados do Australian Institute of Sports (AIS), para o conjunto de dados sobre qualidade de vida de pacientes (mulheres) com câncer de mama, em um estudo realizado pelo Centro de Atenção Integral à Saúde da Mulher (CAISM) em conjunto com a Faculdade de Ciências Médicas, da Universidade Estadual de Campinas e para o conjunto de dados de colesterol de Framingham. / This work presents a study of inference and diagnostic in asymmetric models. The influence analysis is based in the methodology for models with incomplete data, that is related to the algorithm EM (Zhu and Lee, 2001). Beyond of the existing asymmetric normal (Azzalini, 1999) and t-Normal asymmetric (Gómez, Venegas and Bolfarine, 2007) regression models, are developed two new classes of models, namely asymmetric normal scale mixture models (embodying the asymmetric Normal, t-Normal, Slash, Contaminated-Normal and Power-Exponential distributions) and asymmetric robust linear mixed models, utilizing asymmetric normal scale mixture distributions for the random effect and normal scale mixture distributions for the random error. For the mixed model, the observed Fisher information matrix is calculated using the Louis\' (1982) approach for incomplete data. For all models, EM algorithms are developed, that provide a numeric solution for the parameters of the regression models. For each regression model, measures of goodness of fit are realized through visual inspection of the graphic of simulated envelope. For the asymmetric normal scale mixture models, a study of robustness of the proposed EM algorithm is developed to determine the efficacy of the presented estimators. Applications of the studied models are made for the data set of the Australian Institute of Sports (AIS), for the data set about quality of life of patients (women) with breast cancer, in a study made by Centro de Atenção Integral à Saúde da Mulher (CAISM) in conjoint with the Medical Sciences Faculty, of the Campinas State\'s University and for the data set of Framingham\'s cholesterol study.

I komplex analys finns det ett antal olika konvergenser varav vi tittar närmare på några här. Bland annat hur likformig konvergens medför punktvis konvergens men att det omvända ej gäller. Vi tittar också på vad de har för samband med lokal likformig konvergens och normal konvergens dvs. likformig konvergens på kompakta delmängder. Slutligen kommer vi att se på vad som gäller för familjer och kommer då in på lokalt begränsad, ekvikontinuitet, Arzela/Ascoli, Montels och Runges satser. Vi kommer här även se exempel på hur stort fel det egentligen kan bli för punktvisa konvergenta följder. De får normalt inte en gränsfunktion som är analytisk men vi ser både i Exempel 3.19 och Korollarium 3.23 att dessa ger resultat som är analytiska nästan överallt. / This report will describe four different types of convergence. The types described are pointwise, local uniformly, uniformly and normal convergence. The different convergences are explored in a way of how they relate to each other. Finally this report will also investigate how this applies to normal families and the theories of Arzela/Ascoli, Montel and Runge. We will here see examples of how wrong it really can go for pointwise convergent sequences. They do usually not have a limit that is analytic but from both Example 3.19 and Corollary 3.23 we will see that they give functions that in fact are analytic almost everywhere.

An NNF circuit is a directed acyclic graph (DAG), where each leaf is labelled with either true/false or a literal, and each inner node represents either a conjunction (∧) or a disjunction (∨). A decomposable NNF (DNNF) is an NNF satisfying the decomposabi- lity property for each conjunction node. The C-BDMC language generalizes the DNNF language. In a C-BDMC, the leaves can contain CNF formulae from a given base class C. In this paper, we focus only on renamable Horn formulae. We experimentally compare the sizes of d-BDMC and d-DNNF representations. We describe a new compilation langu- age, called cara DNNF (c-DNNF), that generalizes the DNNF language. A c-DNNF circuit can be considered as a compressed representation of a DNNF circuit. We present a new experimental knowledge compiler, called CaraCompiler, for converting a CNF formula into a d-BDMC or a (c)d-DNNF circuit. CaraCompiler is based on the state-of-the-art compiler D4. Also, we mention some extensions for the compiler D4, such as caching hypergraph cuts that can reduce the compilation times. 1