Background: Diarrhea is the passage of 3 or more loose or liquid stools per day. Globally, it is the second-leading cause of death among under-five children, accounting for 9% of all under-five deaths, and kills more young children than Acquired Immunodeficiency Syndrome (AIDS), malaria and measles combined. In developing countries, an estimated 1.8 million people die annually due to diarrheal diseases, and more than 80% of them are children under 5 years, while 88% of these deaths are in South Asia and Sub-Saharan Africa (SSA). There are limited studies that investigate the prevalence and factors associated with diarrhea in SSA despite the health burden. Method: The Demographic and Health Survey (DHS) children’s recode dataset of 2015 for Chad was used for this study. The predictor variables were; age of child, source of drinking water, maternal highest level of education, drank from bottle with nipple, and the outcome variable was diarrhea recently. Descriptive statistics for all variables were completed, and Chi-square analyses were conducted to determine associations between predictor variables and the outcome, diarrhea recently. Simple and multiple logistic regressions were completed to determine factors that predict diarrhea in the last two weeks. Odds ratios, 95% confidence intervals, and p-values were reported. Results: The total sample size was (N=16,710). About 3292 (19.70%) children had diarrhea, 13418 (80.30%) children had no diarrhea. A high prevalence of diarrhea in under-five children was observe particularly in those who drink water from unprotected well (1070 cases), had mothers with only primary level of education (796 cases), and did not drink from bottles with nipple (2961 cases). Based on the age of child, the odds of having diarrhea were over 60% lower in children 3 years old and below [aOR = 0.39, C.I (0.279-0.538), p <.0001] compared to 4 years old and above. Based on the source of drinking water, children that drank from a protected spring were 74% less likely to have diarrhea [0.26, 0.084-0.827, p=0.0223] compared to those that drank from other sources. The study also showed that children that drank from bottles with nipple were 16% less likely of having diarrhea [0.84, 0.726-0.968, p=0.0166] compared to those that did not drink from bottles with nipple. However, maternal highest level of education had no significant association with the odds of having diarrhea in these children. Conclusion: Caregivers should ensure absolute hygiene and provide safe drinking water to under-five children, especially those above 3 years who may easily access contaminated water sources themselves. We also encourage the use of bottles with nipple heads for drinking in children. Further studies are needed in SSA on other factors influencing diarrhea risk in those under five.

Measuring levels of childhood mortality is important for low and middle-income countries to monitor overall development and progress towards improved child health. The overall aim of this research is to estimate the level and trend of childhood mortality in South Africa over time, and to examine the factors associated with and the determinants of childhood mortality. The study discovered that significant progress has been made to reduce the levels of childhood mortality in the country. The estimates derived through direct estimation using the 2016 South African Demographic and Health Survey (SADHS) for the period between 2012-2016 revealed age-specific mortality rates were: Neonatal Mortality Rate (NMR) was 22.0 per 1 000 live births, Post-neonatal Mortality Rate (PNMR) 13.1, 1q0 34.9, 1q4 5.5 and 5q0 40.2 per 1 000 live births. Investigation of the factors associated with childhood mortality revealed significant differentials in age group, sex, population group, province, socio-economic status and household characteristics. Overall, children aged less than one month and those aged between one to two months had a higher mortality risk than the other age groups; male children had an increased risk of dying than females; Black and Coloured children had an increased risk of dying compared to children in other population groups; children in Mpumalanga, Eastern Cape and North West had a higher risk of dying compared to children in other provinces; children whose mothers had below secondary education had higher risks of mortality; and children with poor water source and toilet facility were more likely to die than other children with better facilities. The results were generally in agreement with the existing literature. Although the study found significant improvement in the level of childhood mortality over the period 1996-2016, further progress is achievable as many children still continue to die of preventable or treatable causes. The findings of this study may assist government, policymakers and researchers to plan, and implement targeted interventions that will further reduce the levels of childhood mortality in South Africa.

Skogen är en mångfacetterad resurs och är nödvändig i omställningen till ett fossilfritt samhälle. Den agerar kolsänka och producerar träd vilket ses som en förnyelsebar resurs. Intresset för förnyelsebara resurser ökar vilket medför att allt fler tarskogen i anspråk. Sverige är ett av Europas skogrikaste länder med 28 miljoner hektar skog vilkentäcker två tredjedelar av landets yta. Syftet med att skydda skog är att värna om naturmiljöer med ett betydelsefullt värde för djur, växter och människor. Drygt 13procent av Sveriges produktiva skogsmark är skyddad. Gävleborgs län är ett av delänen med minst skyddad skog och är samtidigt ett av Sveriges skogstätaste län. Avden produktiva skogsmarken är åtta procent skyddad. Syftet med studien var att undersöka enskilda skogsägares attityd till skyddad skogoch identifiera miljönyttan med ökad mängd skyddad skog i Gävleborg. För att besvara studiens syfte och frågeställning har en semistrukturerad kvalitativ intervjustudie utförts för att identifiera enskilda skogsägares attityder till insatser inom hållbartskogsbruk. Hälften av respondenterna ansåg att skogen gör störst klimatnytta genom att agerakolsänka. Dock var intresset att avsätta ytterligare arealer skog inte in de enskildaägarnas intresse. Inställningen till att skydda mer skog kan öka genom ekonomiskkompensation. Att skydda större områden i den svenska skogen skulle ha betydandeeffekter. Det skulle gynna ekosystemen, flertalet av Sveriges miljömål och Gävleborgs miljömål. Det skulle också vara ett effektivt verktyg mot klimatförändringar.

The advancement in data acquiring technology continues to see survival data sets with many covariates. This has posed a new challenge for researchers in identifying important covariates for inference and prediction for a time-to-event response variable. In this dissertation, common Cox proportional hazards model selection techniques and a random survival forest technique were compared using five performance criteria measures. These performance measures were concordance index, integrated area under the curve, and , and R2 . To carry out this exercise, a multicentre clinical trial data set was used. A simulation study was also implemented for this comparison. To develop a Cox proportional model, a training dataset of 75% of the observations was used and the model selection techniques were implemented to select covariates. Full Cox PH models containing all covariates were also incorporated for analysis for both the clinical trial data set and simulations. The clinical trial data set showed that the full model and forward selection technique performed better with the performance metrics employed, though they do not reduce the complexity of the model as much as the Lasso technique does. The simulation studies also showed that the full model performed better than the other techniques, with the Lasso technique overpenalising the model from the simulation with the smaller data set and many covariates. AIC and BIC were less effective in computation than the rest of the variable selection techniques, but effectively reduced model complexity than their counterparts for the simulations. The integrated area under the curve was the performance metric of choice for choosing the final model for analysis on the real data set. This performance metric gave more efficient outcomes unlike the other metrics on all selection techniques. This dissertation hence showed that variable selection techniques differ according to the study design of the research as well as the performance measure used. Hence, to have a good model, it is important to not use a model selection technique in isolation. There is therefore need for further research and publish techniques that work generally well for different study designs to make the process shorter for most researchers.

Capturing protein dynamics in biological crowded environments is essential for under- standing cellular function. In this project, we have explored the dynamic properties of apoferritin in aqueous solutions under varying conditions, including different temper- ature, solvent viscosity and protein concentrations. Dynamic light scattering (DLS) was applied here at various scattering angles from 90 to 150 degrees and at temperatures 295 K and 263 K on three different samples, including one with 19.5 mg/ml apo- ferritin, 6 mg/ml NaCl and 50% glycerol in volume fraction, one with 20 mg/ml apoferritin and 6 mg/ml NaCl, and one with 196.7 mg/ml apoferritin, 6 mg/ml NaCl and 50% glycerol in volume fraction. With the intensity autocorrelation func- tions from DLS measurements, the corresponding diffusion coefficients, hydrodynamic radii and relaxation time constants for each sample under varying conditions were ex- tracted. By comparing with the previous studies, unexpectedly large hydrodynamic radii were noticed and were attributed to undissolved protein crystallites. Still, it can be indicated from our experiment that applying smaller momentum transfer, decreas- ing temperature, increasing solvent viscosity and increasing protein concentration in the solutions can slow down the diffusion dynamics of protein molecules and clusters. Especially by increasing protein concentration, the slowing down of dynamics may be due to crowding effects, as well as increased size of the crystallites. In addition, the data indicate that in all cases, larger solution viscosity can lead to slower diffusivity of proteins.

Computer simulation is a popular method that is often used as a decision support tool in industry to estimate the performance of systems too complex for analytical solutions. It is a tool that assists decision-makers to improve organizational performance and achieve performance objectives in which simulated conditions can be randomly varied so that critical situations can be investigated without real-world risk. Due to the stochastic nature of many of the input process variables in simulation models, the output from the simulation model experiments are random. Thus, experimental runs of computer simulations yield only estimates of the values of performance objectives, where these estimates are themselves random variables. Most real-world decisions involve the simultaneous optimization of multiple, and often conflicting, objectives. Researchers and practitioners use various approaches to solve these multiobjective problems. Many of the approaches that integrate the simulation models with stochastic multiple objective optimization algorithms have been proposed, many of which use the Pareto-based approaches that generate a finite set of compromise, or tradeoff, solutions. Nevertheless, identification of the most preferred solution can be a daunting task to the decisionmaker and is an order of magnitude harder in the presence of stochastic objectives. However, to the best of this researcher’s knowledge, there has been no focused efforts and existing work that attempts to reduce the number of tradeoff solutions while considering the stochastic nature of a set of objective functions. In this research, two approaches that consider multiple stochastic objectives when reducing the set of the tradeoff solutions are designed and proposed. The first proposed approach is an a posteriori approach, which uses a given set of Pareto optima as input. The second iv approach is an interactive-based approach that articulates decision-maker preferences during the optimization process. A detailed description of both approaches is given, and computational studies are conducted to evaluate the efficacy of the two approaches. The computational results show the promise of the proposed approaches, in that each approach effectively reduces the set of compromise solutions to a reasonably manageable size for the decision-maker. This is a significant step beyond current applications of decision-making process in the presence of multiple stochastic objectives and should serve as an effective approach to support decisionmaking under uncertainty

Interdisciplinary education is something that has become much more common in schools over the years. Jan Nilsson (2007) describes Interdisciplinary education as thematic education. He points out how interdisciplinary education tends to mix multiple subjects – like arts, biology and English – together to create a whole. In this study focus has been placed on two novels written by French author Jules Verne, and how these two novels can be used in interdisciplinary education where Swedish as a subject is included. The two novels are 2000 leagues under the sea and Journey to the centre of the Earth. Subject areas discussed together with Swedish are mankind’s relationship with Mother Nature and science, as well as how the two novels can be connected to the basic values of the school system. The study has concluded that the two selected novels by Jules Verne are applicable together with interdisciplinary education, both in regard to the subject “Nature” and “Science,” as well “the basic values the of school system.” This is because 2000 leagues under the sea and Journey to the centre of the Earth, on multiple occasions throughout the novels, include scenes, quotes and plot twists where subjects like “Nature” and “basic values” which can provide material for classroom discussion.

Uncertainty is prevalent throughout the design, analysis, and optimization of aerospace products. When scientific computing is used to support these tasks, sources of uncertainty may include the freestream flight conditions of a vehicle, physical modeling parameters, geometric fidelity, numerical error, and model-form uncertainty, among others. Moreover, while some uncertainties may be treated as probabilistic, aleatory sources, other uncertainties are non-probabilistic and epistemic due to a lack of knowledge, and cannot be rigorously treated using classical statistics or Bayesian approaches. An additional complication for propagating uncertainty is that many aerospace scientific computing tools may be computationally expensive; for example, a single high-fidelity computational fluid dynamics solution may require several days or even weeks to complete. It is therefore necessary to employ uncertainty propagation strategies that require as few solutions as possible. The Non-Intrusive Polynomial Chaos (NIPC) method has grown in popularity in recent decades due to its ability to propagate both aleatory and epistemic parametric sources of uncertainty in a computationally efficient manner. While traditional Monte Carlo methods might require thousands to millions of function evaluations to achieve statistical convergence, NIPC typically requires tens to hundreds for problems with similar numbers of uncertain dimensions. Despite this efficiency, NIPC is limited in one important aspect: it can only propagate uncertainty at a particular point in a design space or flight envelope. For optimization or aerodynamic database problems that require uncertainty estimates at many more than one point, the use of NIPC quickly becomes computationally intractable. This dissertation introduces a new method entitled Spatially Accurate Polynomial Chaos (SAPC) that extends the original NIPC approach for the spatial regression of aleatory and epistemic parametric sources of uncertainty. Throughout the dissertation, the SAPC method is applied to various aerospace problems of interest. These include the regression of aerodynamic force and moment uncertainties throughout the flight envelope of a commercial aircraft, the design under uncertainty of a two-stream propulsive mixer device, and the robust design of a low-boom supersonic demonstrator aircraft. Collectively the results suggest that SAPC may be useful for a large variety of engineering applications. / Doctor of Philosophy / Uncertainty is prevalent throughout the design, analysis, and optimization of aerospace products. When scientific computer simulations are used to support these tasks, sources of uncertainty may include the speed of an aerospace vehicle, the direction of the wind, physical modeling constants or assumptions, and the vehicle shape, among others. As a result of these sources uncertainty, assessments of vehicle performance are also uncertain. For example, if the speed of a vehicle is not known precisely, then computer simulations will predict a lift force which is also imprecisely known. A challenge when assessing the uncertainty in aerospace vehicle performance is that the computer simulations which predict performance may take a long time to run, even on state-of-the-art super computers. Traditional statistical methods may require thousands or millions of simulations for the prediction of uncertainty, which does not fit within the computational budget of most aerospace analyses. A newer method called Non-Intrusive Polynomial Chaos (NIPC) is more efficient, typically requiring only tens to hundreds of simulations; however, NIPC only provides uncertainty estimates at a single point in an aircraft flight envelope or design condition. In this dissertation, a new method called Spatially Accurate Polynomial Chaos (SAPC) is developed. The SAPC method combines desirable features of NIPC with regression methods for an efficient estimation of uncertainty throughout a vehicle flight envelope or design space. Throughout the dissertation, the SAPC method is applied to various aerospace problems of interest. These include the regression of aerodynamic force and moment uncertainties throughout the flight envelope of a commercial aircraft, the design under uncertainty of a two-stream propulsive mixer device, and the robust design of a low-boom supersonic demonstrator aircraft. Collectively the results suggest that SAPC may be useful for a large variety of engineering applications.

As agents are built for ever more complex environments, methods that consider the uncertainty in the system have strong advantages. This uncertainty is common in domains such as robot navigation, medical diagnosis and treatment, inventory management, sensor networks and e-commerce. When a single decision maker is present, the partially observable Markov decision process (POMDP) model is a popular and powerful choice. When choices are made in a decentralized manner by a set of decision makers, the problem can be modeled as a decentralized partially observable Markov decision process (DEC-POMDP). While POMDPs and DEC-POMDPs offer rich frameworks for sequential decision making under uncertainty, the computational complexity of each model presents an important research challenge. As a way to address this high complexity, this thesis develops several solution methods based on utilizing domain structure, memory-bounded representations and sampling. These approaches address some of the major bottlenecks for decision-making in real-world uncertain systems. The methods include a more efficient optimal algorithm for DEC-POMDPs as well as scalable approximate algorithms for POMDPs and DEC-POMDPs. Key contributions include optimizing compact representations as well as automatic structure extraction and exploitation. These approaches increase the scalability of algorithms, while also increasing their solution quality.

No description available.