Using paired samples t-tests, this study examines attitudes toward government intervention to decrease the consumption of tobacco, alcohol, and sugar to improve public health in Sweden. The effects of the four sociodemographic variables gender, age, education, and income on attitudes toward health policies are tested using Ordinary Least Squares and ordered probit regressions. The research is performed using cross-sectional data which is supplied by a national survey. The results show that tobacco should be regulated the most, followed by alcohol and lastly sugar. According to the respondents, tobacco and alcohol consumption need clear societal restrictions while individuals should be responsible for their sugar consumption. This implies that tobacco and alcohol restrictions introduced by the government should be effective and should, therefore, reduce the consumption and subsequently decrease a country’s economic costs. The opposite is true for sugar policy. Women, younger people, highly educated people, and people with higher incomes are positively related to support toward tobacco restrictions. Women, younger people, and highly educated people show more support for alcohol restrictions. Lastly, respondents with higher levels of education are more supportive of sugar restrictions.

This paper concerns the ordinary stories. It is about the forgotten and the things that have gone unnoticed. It is about female history and is a political exploration into what and who is allowed to take space. I focus on everyday life in a domestic space, where I see these things that are discarded, often are overlooked and not talked about. I explore society from a kitchen point of view with a grandmother’s life in focus. It is a story about everyday rituals in the home, which are of an important cultural deed. The objects support her in these rituals, and they also help me to tell. I investigate the memorial space and with my artistic practice I create a room to remember those who are soon no longer with us. In this project I work within the craft-field of corpus. I use the tradition of corpus as a method of working but also as a tool to discuss my subject. As corpus is talking about class and hierarchies it creates a counterweight to my project.

NR 20140805

In this thesis we analyze parameter optimization problems governed by linear ordinary differential equations (ODEs) and develop computationally efficient numerical methods for their solution. In addition, a series of noise-robust finite difference formulas are given for the estimation of the derivatives in the ODEs. The suggested methods have been employed to identify Gene Regulatory Networks (GRNs). GRNs are responsible for the expression of thousands of genes in any given developmental process. Network inference deals with deciphering the complex interplay of genes in order to characterize the cellular state directly from experimental data. Even though a plethora of methods using diverse conceptual ideas has been developed, a reliable network reconstruction remains challenging. This is due to several reasons, including the huge number of possible topologies, high level of noise, and the complexity of gene regulation at different levels. A promising approach is dynamic modeling using differential equations. In this thesis we present such an approach to infer quantitative dynamic models from biological data which addresses inherent weaknesses in the current state-of-the-art methods for data-driven reconstruction of GRNs. The method is computationally cheap such that the size of the network (model complexity) is no longer a main concern with respect to the computational cost but due to data limitations; the challenge is a huge number of possible topologies. Therefore we embed a filtration step into the method to reduce the number of free parameters before simulating dynamical behavior. The latter is used to produce more information about the network’s structure. We evaluate our method on simulated data, and study its performance with respect to data set size and levels of noise on a 1565-gene E.coli gene regulatory network. We show the computation time over various network sizes and estimate the order of computational complexity. Results on five networks in the benchmark collection DREAM4 Challenge are also presented. Results on five networks in the benchmark collection DREAM4 Challenge are also presented and show our method to outperform the current state of the art methods on synthetic data and allows the reconstruction of bio-physically accurate dynamic models from noisy data. / I detta examensarbete analyserar vi parameteroptimeringsproblem som är beskrivna med ordinära differentialekvationer (ODEer) och utvecklar beräkningstekniskt effektiva numeriska metoder för att beräkna lösningen. Dessutom härleder vi brusrobusta finita-differens approximationer för uppskattning av derivator i ODEn. De föreslagna metoderna har tillämpats för regulatoriska gennätverk (RGN). RGNer är ansvariga för uttrycket av tusentals gener. Nätverksinferens handlar om att identifiera den komplicerad interaktionen mellan gener för att kunna karaktärisera cellernas tillstånd direkt från experimentella data. Tillförlitlig nätverksrekonstruktion är ett utmanande problem, trots att många metoder som använder många olika typer av konceptuella idéer har utvecklats. Detta beror på flera olika saker, inklusive att det finns ett enormt antal topologier, mycket brus, och komplexiteten av genregulering på olika nivåer. Ett lovande angreppssätt är dynamisk modellering från biologiska data som angriper en underliggande svaghet i den för tillfället ledande metoden för data-driven rekonstruktion. Metoden är beräkningstekniskt billig så att storleken på nätverket inte längre är huvudproblemet för beräkningen men ligger fortfarande i databegränsningar. Utmaningen är ett enormt antal av topologier. Därför bygger vi in ett filtreringssteg i metoder för att reducera antalet fria parameterar och simulerar sedan det dynamiska beteendet. Anledningen är att producera mer information om nätverkets struktur. Vi utvärderar metoden på simulerat data, och studierar dess prestanda med avseende på datastorlek och brusnivå genom att tillämpa den på ett regulartoriskt gennätverk med 1565-gen E.coli. Vi illustrerar beräkningstiden över olika nätverksstorlekar och uppskattar beräkningskomplexiteten. Resultat på fem nätverk från DREAM4 är också presenterade och visar att vår metod har bättre prestanda än nuvarande metoder när de tillämpas på syntetiska data och tillåter rekonstruktion av bio-fysikaliskt noggranna dynamiska modeller från data med brus.

Ertapenem is an antibiotic commonly used to treat a broad spectrum of infections, which is part of a broader class of antibiotics called carbapenem. Unlike other carbapenems, ertapenem has a longer half-life and thus only has to be administered once a day. A physiologically-based pharmacokinetic (PBPK) model was developed to investigate the uptake, distribution, and elimination of ertapenem following a single one gram dose. PBPK modeling incorporates known physiological parameters such as body weight, organ volumes, and blood ow rates in particular tissues. Furthermore, ertapenem is highly bound in human blood plasma; therefore, nonlinear binding is incorporated in the model since only the free portion of the drug can saturate tissues and, hence, is the only portion of the drug considered to be medicinally effective. Parameters in the model were estimated using a least squares inverse problem formulation with published data for blood concentrations of ertapenem for normal height, normal weight males. Finally, an uncertainty analysis of the parameter estimation and model predictions is presented.

Background – This study is an attempt to explore the relationship between microcredit and the socio-economic empowerment of women in rural Bangladesh. Microcredit is simply the extension of a small amount of collateral-free institutional loans to jointly liable poor group members to generate employment and income enhancing activities. As it is too difficult for poor members to get loan from the formal credit institutions, Grameen Bank (GB) or other Non-Government Organizations (NGOs) provide small loans to vulnerable groups of the society by which they are expected to empower over his counterparts. Research questions – RQ1: How does micro-credit affect different indicators of women empowerment in the rural areas of Bangladesh? RQ2– Is the impact different from the male counterparts in the sample households? Purpose – This study is an effort to find the impact of microcredit on a number of indicators of women’s empowerment in the rural areas in Bangladesh. Methodology – Quantitative Regression Techniques such as Ordinary Least Square (OLS) and Instrumental Variable (IV) method have been applied to get the relationship between microcredit and women empowerment. Conclusion – Applying nationally representative cross-section survey data, Bangladesh Integrated Household Survey (BIHS) 2015, this thesis is intended to find the causal linkage between microcredit and women empowerment’s with different dimensions of women’s decisions are taken as empowerment indicators: production, resources, income, leadership, savings and time. The analysis has been conducted at the household level. The study assumes that women empowerment is endogenous. After controlling for endogeneity in the estimation by using an instrumental variable (IV) ‘distance to the market’ this study finds a significant relationship between microcredit and different dimensions of women’s empowerment. Participation in the microcredit program is found to be significant in explaining some of the outcome indicators of empowerment for the sampled households.

Seasonal shifts in predation habits, from a generalist in the summer to a specialist in the winter, have been documented for the great horned owl (Bulbo virginialis) in the boreal forest. This shift occurs largely due to varying prey availability. There is little study of this switching behaviour in the current literature. Since season length is predicted to change under future climate scenarios, it is important to understand resulting effects on species dynamics. Previous work has been done on a two-species seasonal model for the great horned owl and its focal prey, the snowshoe hare (Lepus americanus). In this thesis, we extend the model by adding one of the hare's most important predators, the Canadian lynx (Lynx canadensis). We study the qualitative behaviour of this model as season length changes using tools and techniques from dynamical systems. Our main approach is to determine when the lynx and the owl may invade the system at low density and ask whether mutual invasion of the predators implies stable coexistence in the three-species model. We observe that, as summer length increases, mutual invasion is less likely, and we expect to see extinction of the lynx. However, in all cases where mutual invasion was satisfied, the three species stably coexist.

Many complex actions are precomposed, by sequencing simpler motor actions. For such a complex action to be executed accurately, those simpler actions must be planned in the desired order, held in working memory, and then enacted one-by-one until the sequence is complete. Examples of this phenomenon include writing, typing, and speaking. Under most circumstances, the ability to learn and reproduce novel motor sequences is hindered when additional information is presented. However, in cases where the motor sequence is musical in nature (e.g. a choreographed dance or a piano melody), one must learn two sequences at the same time, one of motor actions and one of the time intervals between actions. Despite this added complexity, humans learn and perform rhythm-based motor sequences regularly. It has been shown that people can learn motoric and rhythmic sequences separately and then combine them with little trouble (Ullén & Bengtsson 2003). Also, functional MRI data suggest that there are distinct sets of neural regions responsible for the two different sequence types (Bengtsson et al. 2004). Although research on musical rhythm is extensive, few computational models exist to extend and inform our understanding of its neural bases. To that end, this dissertation introduces the TAMSIN (Timing And Motor System Integration Network) model, a systems-level neural network model designed to replicate rhythm-based motor sequence performance. TAMSIN utilizes separate Competitive Queuing (CQ) modules for motoric and temporal sequences, as well as modules designed to coordinate these sequence types into a cogent output performance consistent with a perceived beat and tempo. Chapters 1-4 explore prior literature on CQ architectures, rhythmic perception/production, and computational modeling, thereby illustrating the need for a model to tie those research areas together. Chapter 5 details the structure of the TAMSIN model and its mathematical specification. Chapter 6 presents and discusses the results of the model simulated under various circumstances. Chapter 7 compares the simulation results to behavioral and imaging results from the experimental literature. The final chapter discusses future modifications that could be made to TAMSIN to simulate aspects of rhythm learning, rhythm perception, and disordered productions, such as those seen in Parkinson’s disease.

Cette recherche vise à mettre en rapport les effets du néolibéralisme sur le corps. En 2012 le Brésil a atteint la première place dans le classement international du pourcentage d'interventions plastiques par habitant. Durant ces dernières années, la proportion d’hommes ayant eu recours à la chirurgie esthétique à finalité non réparatrice a très fortement augmenté et reflète un changement dans les formes d’utilisation du corps masculin dans la contemporanéité. Le néolibéralisme a débordé les limites du monde économique pour envahir les modes d’agir et de désirer et faire du corps un bien de plus à produire et à consommer. Le marché triomphe sur les autres formes de croyance, dans une sorte de religion à laquelle le sujet devient dévot face au risque et marques de la castration. L'impact des discours de la science et de la marchandisation généralisée conduit à la promotion d’un homo economicus dans ses rapports à la jouissance. En prenant appui sur la théorie des discours de Jacques Lacan, la recherche a interrogé des hommes ayant recours à des interventions médicales à finalités esthétiques, (chirurgies plastiques, injections de botox, lifting facial, etc.) et qui font un usage particulier de leur corps. Deux cas cliniques sont distingués : l’un diagnostiqué comme névrotique et l’autre relevant de la psychose ordinaire. L'étude s’achève sur les implications au plan culturel de ces nouveaux modes de subjectivation et du privilège accordé sur un mode érotique à l'identification à l'objet. / This research aimed at relating the effects of neoliberal ideology on the body. In 2012 Brazil reached the first place in the international ranking of plastic surgery proportionally per citizen. During the last years there has been a leap in the number of men who undergo plastic surgery with aesthetic and not reparatory purpose, which reflects a change in the forms of use of the masculine body in contemporaneity. Neoliberal ideology has extrapolated the economy limits, has invaded the forms of acting and desiring and has made the body one more asset to be produced and consumed. The market prevails over other forms of belief, serving as a kind of religion to which the subject becomes obedientiary as they face castration. The impact of the discourse of science The impact of science discourse and widespread commoditization leads to the promotion of a homo economicus as to its relation to fruition. Based on to the discourses theory of Jacques Lacan, the research interviewed men who used medical interventions with aesthetic purpose (plastic surgeries, filling with botox, facelift, etc.) and make a peculiar usage of the body. Two cases stood out: one being diagnosed as neurotic and the other as an “ordinary psychotic”. The research ends with the implications on the cultural field of these new ways of subjectivation that priviledge identification to the object rather than its erotical use.

L'étude des systèmes aux équations différentielles ordinaires vise à prédire le futur des systèmes considérés. La connaissance de l'évolution dans le temps de toutes les variables d' état du modèle permet de prédire de possibles changements radicaux des variables ou des défaillances, par exemple, un moteur peut exploser, un pont peut s'écrouler, une voiture peut se mettre à consommer plus d'essence. De plus, les systèmes dynamiques peuvent contenir des dérivées spatiales et leur discrétisation peut ajouter un très grand nombre d'équations. La résolution des équations différentielles ordinaires est alors une étape essentielle dans la construction des systèmes physiques en terme de dimensionnement et de faisabilité. Le solveur de tels systèmes EDOs doit être rapide, précis et pertinent.En pratique, il n'est pas possible de trouver une fonction continue qui soit solution exacte du problème EDO. C'est pourquoi, des méthodes numériques sont utilisées afin de donner des solutions discrèes qui approchent la solution continue avec une erreur contrôlable. La gestion précise de ce contrôle est très importante afin d'obtenir une solution pertinente en un temps raisonnable.Cette thèse développe un nouveau solveur qui utilise plusieurs méthodes d'amélioration de la vitesse d'exécution des systèmes EDOs. La première méthode est l'utilisation d'un nouveau schéma numérique. Le but est de minimiser le coût de l'intégration en produisant une erreur qui soit le plus proche possible de la tolérance maximale permise par l'utilisateur du solveur. Une autre méthode pour améliorer la vitesse d'exécution est de paralléliser le solveur EDO en utilisant une architecture multicoeur et multiprocesseur. Enfin, le solveur a été testé avec différentes applications d'OpenModelica. / The study of systems of Ordinary Differential Equations aims at predicting the future of the considered systems. The access to the evolution of all states of a system's model allows us to predict possible drastic shifts of the states or failures, e.g. an engine blowing up, a bridge collapsin, a car consuming more gasoline etc. Solving ordinary differential equations is then an essential step of building industrial physical systems in regard to dimensioning and reliability. The solver of such ODE systems needs to be fast, accurate and relevant.In practice, it is not possible to find a continuous function as the exact solution of the real ODE problem. Consequently numerical methods are used to give discrete solutions which approximates the continuous one with a controllable error. The correct handline of this control is very important to get a relevant solution within an acceptable recovery time. Starting from existing studies of local and global errors, this thesis work goes more deeply and adjusts the time step of the integration time algorithm and solves the problem in a very efficient manner.A new scheme is proposed is this thesis, to minimize the cost of integration. Another method to improve the execution speed is to parallelize the ODE solver by using a multicore and a multiprocessor architecture. Finally, the solver has been tested with different applications from OpenModelica.