Today’s competitive global market has placed companies under great pressure and the focus on production systems has been more prominent. Although there are several claimed benefits with using frameworks in the development of production systems, companies are reluctant to use these. Consequently, a relevant question formulation is: Are frameworks in the development of production systems usable? The purpose with this thesis work was therefore to evaluate the usability of production system development frameworks (PSDFs) in practice. In order to achieve this purpose, two research questions were established: RQ1.  How can usability of frameworks be evaluated? RQ2.  How does the use of a framework contribute to the development of a new production system? In order to answer the posed research questions, Bellgran and Säfsten’s PSDF was used in the production system development (PSD) process of a new production system at Xylem. Based on the PSD process, a meta-study was performed to evaluate the practical usability of the PSDF. Usability was defined and evaluated based on the five usability terms learnability, memorability, efficiency, effectiveness, and satisfaction. The result showed that all the five usability terms contribute to the usability evaluation of PSDFs. However, memorability was considered difficult to use on only one study since the user has to think a step further and make a qualified guess to answer if it is possible to memorize a framework. Therefore, it was considered memorability is only appropriate to use in a multiple study. The results also showed that Bellgran and Säfsten’s PSDF contributed most in the beginning of the PSD process by putting emphasis on the planning phase and providing a structure to follow. Due to the nature of a framework (i.e., to serve as a guide for structures to follow), this was not unexpected. However, the contributions from a structure or plan are hard to exactly distinguish. Since companies most often want tangible and accurate evidences, frameworks’ vague contributions are considered to be a major reason to why companies do not use frameworks more frequently.

This research is a meta-analytic review of the effects of transformational school leadership (TSL)-- a systematic, comprehensive synthesis of the quantitative research on transformational school leadership. The review method used in this research is standard meta-analysis supplemented by narrative synthesis and vote-counting methods. The types of effect sizes involved in meta-analytical calculations are correlation coefficients rs. The evidence reviewed was provided exclusively by unpublished theses or dissertations that were completed between 1996 and 2008. This study identified 33 dimensions of transformational leadership as developed by various scholars and captured by a variety of leadership measures, which were synthesized into 11 core leadership dimensions. This study meta-analyzed the effects of transformational school leadership and its dimensions on a large range of school outcomes, including 17 school conditions (e.g., school culture, shared decision-making processes), 23 teacher-related outcomes (e.g., teacher satisfaction), and five types of student outcomes. Transformational school leadership was most influential on teachers’ emotions and inner states. TSL had large effects on teachers’ individual inner states and their practices while it had small effects on their group inner states. Leaders effectively influence teachers’ psychological inner states and practices mainly through modeling good practices themselves, providing support and intellectual stimulation to teachers individually and setting shared school goals. TSL was also very influential on school conditions. It had large effects on four key school conditions. This review detected significant, positive small direct effects of TSL on student achievements. The indirect effects of TSL on student learning vary when different school or teacher variables are controlled. This review identified seven important moderators and three mediators that significantly contributed to student learning along with TSL. Specific leadership practices that effectively influenced school and student outcomes were also examined and discussed. Regarding the moderating effects of contextual and methodological factors, school level and leadership measures were found to moderate leadership impacts significantly in some cases. The findings of this study provide guidance for school administrators and policy makers who want to improve school leadership as a means of improving school quality.

Background: The use of meta-analysis to combine the results of observational studies is controversial. Despite its common use, methodological work in this area is lacking. Because of the diversity of study designs, exposure and outcome measures, and differential adjustment for confounding variables, the identification of sources of heterogeneity among study effect estimates is particularly important when combining data from observational studies. This thesis presents the results of a study that examines the relative ability of individual participant data (IPD) meta-analysis (which was considered a “gold standard”) and traditional aggregate data (AD) meta-analysis to identify sources of heterogeneity among studies examining mechanical exposure and low back pain (LBP) in workers. Materials and Methods: A systematic literature search was conducted to identify relevant articles. The corresponding author of each article was contacted to request their individual-level data. Because the outcome definitions and exposure measures were not uniform across studies, two sub-studies were conducted 1) to identify sets of outcome definitions that could be combined in a meta-analysis and 2) to develop methods to translate mechanical exposure onto a common metric. IPD analyses were conducted using generalized estimating equation (GEE) regression to identify variables that acted as strong confounders and effect modifiers. Traditional AD meta-analysis was also conducted and potential sources of heterogeneity were tested using meta-regression. Key Findings: (1) Overall, we found an association between both forces and postures on LBP, although the magnitude varied depending on the exposure-outcome combination. Among the outcomes, the ORs tended to be highest for sick leave due to LBP. (2) There was very little evidence of strong confounders in the relationship between mechanical exposure and LBP; thus differential adjustment for confounders in studies would not likely be an important source of heterogeneity in an AD meta-analysis. (3) AD meta-analysis was able to identify the same study-level effect modifiers as IPD meta-analysis, but did not consistently identify individual-level effect modifiers. Both individual-level characteristics (older age and being male), and study-level characteristics (population-based studies and self-reported mechanical exposure), were associated with an increased OR for many of the LBP outcome and mechanical exposure combinations. Conclusion: AD meta-analysis is likely sufficient to detect heterogeneity for study-level factors but is not sufficient to identify individual-level effect modifiers. When the primary source of evidence in a research area is observational studies and when there is controversy despite several systematic reviews, IPD meta-analysis can be used to better understand sources of heterogeneity and provide context

This research is a meta-analytic review of the effects of transformational school leadership (TSL)-- a systematic, comprehensive synthesis of the quantitative research on transformational school leadership. The review method used in this research is standard meta-analysis supplemented by narrative synthesis and vote-counting methods. The types of effect sizes involved in meta-analytical calculations are correlation coefficients rs. The evidence reviewed was provided exclusively by unpublished theses or dissertations that were completed between 1996 and 2008. This study identified 33 dimensions of transformational leadership as developed by various scholars and captured by a variety of leadership measures, which were synthesized into 11 core leadership dimensions. This study meta-analyzed the effects of transformational school leadership and its dimensions on a large range of school outcomes, including 17 school conditions (e.g., school culture, shared decision-making processes), 23 teacher-related outcomes (e.g., teacher satisfaction), and five types of student outcomes. Transformational school leadership was most influential on teachers’ emotions and inner states. TSL had large effects on teachers’ individual inner states and their practices while it had small effects on their group inner states. Leaders effectively influence teachers’ psychological inner states and practices mainly through modeling good practices themselves, providing support and intellectual stimulation to teachers individually and setting shared school goals. TSL was also very influential on school conditions. It had large effects on four key school conditions. This review detected significant, positive small direct effects of TSL on student achievements. The indirect effects of TSL on student learning vary when different school or teacher variables are controlled. This review identified seven important moderators and three mediators that significantly contributed to student learning along with TSL. Specific leadership practices that effectively influenced school and student outcomes were also examined and discussed. Regarding the moderating effects of contextual and methodological factors, school level and leadership measures were found to moderate leadership impacts significantly in some cases. The findings of this study provide guidance for school administrators and policy makers who want to improve school leadership as a means of improving school quality.

The data delivery architectures in most enterprises are complex and under documented. Conceptual business models and business analytics applications are created to provide a simplified, and easy to navigate view of enterprise data for analysts. But the construction of such interfaces is tedious, manually intensive to build, requiring specialized technical expertise, and it is especially difficult to map exactly where data came from in the organization. In this paper we investigate how two aspects (lineage and requests for data i.e. semantics and new reports) can be addressed by tying metadata documentation to a systematic data delivery architecture in order to support business analytics applications. We propose a tool framework that includes a metadata repository for each step in the data delivery architecture, a web based interface to access and manage that repository and mapping tools that capture data lineage to support step by step automation of data delivery.

Antiplatelet therapy with clopidogrel is widely used in patients with coronary artery disease, but the recent development of the new P2Y12 receptor antagonists prasugrel and ticagrelor will increase treatment options. An overview of systematic reviews was performed to summarize available evidence on clopidogrel. Current data on prasugrel and ticagrelor were identified by a systematic review and used for an indirect treatment comparison (ITC) of the drugs against each other and versus placebo in the absence of head-to-head clinical trials. Adjusted indirect comparison according to Bucher, Bayesian methods for mixed treatment comparisons using Winbugs, and generalized linear mixed models using SAS were employed for ITC, yielding almost identical results: prasugrel was favored regarding stent thrombosis and ticagrelor regarding major bleeding. However, substantial differences in trial design were identified, demanding caution when interpreting these results. On the basis of the obtained results, a randomized controlled trial was designed within the gap of current evidence.

At the beginning of the 21st century, primary liver cancer (PLC) remains the fifth most common malignancy in men worldwide, and the eighth in women. Central Africa and South East of Asia are high risk geographic areas for PLC, whereas developed countries appear to be generally low risk. Infections with hepatitis B (HBV) and C (HCV) viruses are the main risk factors for PLC, accounting for well over 80% of PLC cases detected worldwide. The recently detected increase in both incidence and mortality by PLC in developed countries is strongly related to these viral infections. The evaluation of PLC time trends needs to take into consideration the geographic distribution and effect of these viruses. This thesis presents three studies which the aim to describe PLC incidence and mortality issues in different geographic areas, each addressing several epidemiological and methodological issues. For each study, different statistical methods on the basis of the Bayesian inference have been proposed, evaluated and discussed in order to cope with extra-Poisson variability. The first study, entitled "Meta-analysis of cohort studies of risk of liver cancer death among HBV carriers", evaluates the variability in PLC mortality reported in 11 cohort studies of male HBV carriers, taking into consideration the effects of geographic area and the choice of the general population versus a more comparable group such as HBV-negative workers or blood donors as the comparison group. The statistical methods of this study focuses on mixtures of Poisson distributions. The "stickbreaking" method has been used to estimate the number of components of the mixture of Poisson distributions, and, thus to obtain a pooled relative risk (RR) of death for PLC among male HBV carriers. The pooled RR of death by PLC related to HBV infection was 23.5 (95% Credibility Interval (CRI): 14.9 - 44.5). Studies carried out in high risk areas for PLC (China and Taiwan) showed RRs 2 to 5-fold higher than those of studies carried out in Europe, Japan and the U.S.. In low risk areas for PLC, studies which used workers or blood donors as comparison groups had RRs 1.9-fold higher (95% CRI: 1.2 - 3.1) than studies which used the general population. However, in high risk areas, the ratio of RRs was 5.3-fold (95% CRI: 3.4 - 7.9). This is the first time that a "healthy donor effect" has been quantified in longitudinal studies. The second study, entitled "Geographic distribution of primary liver cancer in Europe in 2002" evaluates the effect of HBV and HCV seroprevalence in 38 European countries on PLC incidence and mortality. Mixed Poisson models based on Bayesian inference have been used to smooth Standardized Incidence (SIR) and Mortality (SMR) ratios for PLC accounting for the effect of HBV and HCV prevalences. This approach enabled us to both examine the effect of different levels of HBV and HCV, and to identify remaining variability in PLC after accounting for infection rates. Bayesian inference allowed the determination of posterior probabilities for the somoothed SIRs and SMRs (hereafter RRs). The Deviance Information Criterion (DIC) and the "effective number of parameters" (pD) have been used as tools for model choice. The highest mortality and incidence PLC RRs were found in Southern European countries (RR range 0.9-2.4), whereas Northern European countries showed the lowest RRs (RR range: 0.3-0.9). The effect of HBV infection was not found to be statistically significant in the model which accounted for both HBV and HCV prevalence. Countries with a prevalence of HCV higher than 2% (e.g.: Italy and Spain) had a higher risk of incidence and mortality (RR range: 1.28 - 1.78) than countries with HCV prevalence below 1%. Thus, the high risk of PLC detected in Southern Europe appears to be explained, in part, by HCV infection. The high HCV seroprevalence in this area could be associated with exposure 30-50 years ago. There may be an underestimation of PLC incidence and mortality rates in Eastern European countries given the low PLC RRs reported, despite high HBV and HCV seroprevalences observed. The implementation of population-based cancer registries in Eastern European countries is warranted, as well as HCV prevalence studies across Europe, to better determine the distribution of PLC in Europe and its relationship with that virus. The last study, entitled "Time trends in liver disease in Spain during the period 198397", describes incidence and mortality trends in hepatocellular carcinoma and cholangiocarcinoma as well as mortality trends in liver cirrhosis in Spain. Autoregressive age-period-cohort (APC) models have been used to evaluate the time trends. We found that APC models performed well for those liver diseases with large number of cases, whereas the age-period models did for those liver diseases with low number of cases. We found an increase in incidence and mortality of hepatocellular carcinoma in Spain (annual percent change (APCH) in men's incidence: 6.6%, 95% CRI: 5.8, 8.1: APCH in women's incidence: 4.5%, 95% CRI: 1.4%, 7.3%; APCH in men's mortality: 6.8%, 95% CRI: 5.8%, 8.1%; APCH in women's mortality: 5.1%, 95% CRI: 3.5%, 6.3%), that appear to be related to HCV exposure 30 years ago, as described in other studies of PLC. We also found an increasing trend in cholangiocarcinoma mortality (APCH in men: 17.1%, 95% CRI: 13.5%, 21.2%; APCH in women: 15.0%, 95% CRI: 11.5%, 19.5%) similar to that found in some developed countries, that could be attributed to improvement in diagnosis resulting from better imaging and diagnostic techniques. However, we did not detect a significant increasing trend in cholangiocarcinoma incidence, perhaps due to the low number of cases reported by the Spanish cancer registries. We have observed a decreasing trend in cirrhosis mortality in both sexes during the study period (APCH in men: -3.1%, 95% CRI: -5.1, -1.9%; APCH in women: -2.9%; 95% CRI: -6.2%, -1.3%), although younger cohorts did not show this pattern. This cohort effect suggests the possibility that younger cohorts could be exposed to some additional risk factors besides alcohol consumption. HIV and HCV or HBV co-infection and intravenous drug addiction could explain the increase in liver cirrhosis mortality among younger cohorts. The flexibility of the Bayesian approach allowed us to cope with extra-Poisson variability in three statistical analyses, applying different models, and addressing relevant methodological aspects specific to each problem. Challenging statistical issues in the framework of Bayesian applied modelling are: i) the selection of prior distributions for model parameters, which is related to convergence of the model; and ii) model selection procedures, and these remain important considerations for future research.

When solving partial differential equations using finite difference methods on structured meshes, adaptive refinement can be used to increase the accuracy of the solution in an efficient manner. When implementing solvers using structured adaptive mesh refinement for modern parallel computer systems, an important task is the partitioning of the grid hierarchy over the available processors. The Meta-partitioner is an autonomic framework which can dynamically select between a large number of grid-partitioning algorithms at run time. In this thesis we investigate which modifications that are necessary in order to connect the Meta-partitioner to the existing SAMR-framework Chombo, and begin the process of performing this connection. We conclude that although significant changes to both Chombo and the Meta-partitioner are necessary, a connection definitely seams feasible. We estimate that that the major work of the connection has been done, and that with the experience gained from this project, the continuation is straightforward. We also connect a patch-based partitioning algorithm to Chombo and evaluate it for the first time as part of a real SAMR-based simulation. The results are promising and we conclude that it is a viable candidate for inclusion in the Meta-partitioner.

This thesis aims to produce a novel multi-objective algorithm that is based on Cuckoo Search by Dr. Xin-She Yang. Cuckoo Search is a promising nature-inspired meta-heuristic optimization algorithm, which currently is only able to solve single-objective optimization problems. After an introduction, a number of theoretical points are presented as a basis for the decision of which algorithms to hybridize Cuckoo Search with. These are then reviewed in detail and verified against current benchmark algorithms to evaluate their efficiency. To test the proposed algorithm in a new setting, a real-world combinatorial problem is used. The proposed algorithm is then used as an optimization engine for a simulation-based system and compared against a current implementation.

Determining the relative roles of top-down vs. bottom-up forces in controlling the structure of ecological communities is of primary importance because anthropogenic nutrient loading, overharvesting of consumers, and potential interactions of these forces are pervasively changing ecosystems throughout the world. Here I use both field experimentation and meta-analyses to investigate the role of predators in controlling community composition, the relative roles of herbivores vs. nutrient enrichment in controlling the abundance of benthic primary producers, and the influence of herbivore diversity on the community structure of coral reefs. On a coral reef in the Florida Keys, I showed that release from predation by large fishes and invertebrates via exclusion cages allowed population increases in the gorgonian-eating gastropod Cyphoma gibbosum which increased predation rates on gorgonian corals. To directly address the relative roles of top-down and bottom-up forces in controlling primary producers in benthic marine habitats, I used factorial meta-analysis of 54 field experiments that orthogonally manipulated herbivore pressure and nutrient loading to quantify the effects of consumers and nutrient enrichment on community structure. The relative effects of herbivores vs. nutrient enrichment were context dependant, varying with latitude, the type of primary producer, and the nutrient status of the system. To address the influence of herbivore diversity on the community structure of Caribbean coral reefs, I used manipulative field experiments over two years to show that a Caribbean reef changes dramatically as a function of herbivorous fish diversity. The effects of herbivore diversity on community structure were strong in both years of the experiment due to different diet preferences among herbivores. Higher herbivore diversity suppressed macroalgal abundance, increased abundance of crustose coralline algae, reduced coral mortality, and increased coral growth when compared to treatments with lower herbivore diversity. Complementary feeding by different fishes drove these patterns because macroalgae were unable to effectively deter feeding by fishes with different attack strategies. Thus, herbivore diversity appears to play an important role in the healthy function of coral reef ecosystems via complementary feeding of different herbivore species.