Optimised dose titration for Duodopatreatment based on simulation experiments– implementation in a decision supportsystem

The aim of this work was to design a set of rules for levodopa infusion dose adjustment in Parkinson’s disease based on a simulation experiments. Using this simulator, optimal infusions dose in different conditions were calculated. There are seven conditions (-3 to +3)appearing in a rating scale for Parkinson’s disease patients. By finding mean of the differences between conditions and optimal dose, two sets of rules were designed. The set of rules was optimized by several testing. Usefulness for optimizing the titration procedure of new infusion patients based on rule-based reasoning was investigated. Results show that both of the number of the steps and the errors for finding optimal dose was shorten by new rules. At last, the dose predicted with new rules well on each single occasion of majority of patients in simulation experiments.

Performance determinants For Swedish Financial Monetary Institutions: Panel Data evidence between 2010-2014.

Due to the rapid changes that governs the Swedish financial sector such as financial deregulations and technological innovations, it is imperative to examine the extent to which the Swedish Financial institutions had performed amid these changes. For this to be accomplish, the work investigates what are the determinants of performance for Swedish Financial Monetary Institutions? Assumptions were derived from theoretical and empirical literatures to investigate the authenticity of this research question using seven explanatory variables. Two models were specified using Returns on Asset (ROA) and Return on Equity (ROE) as the main performance indicators and for the sake of reliability and validity, three different estimators such as Ordinary Least Square (OLS), Generalized Least Square (GLS) and Feasible Generalized Least Square (FGLS) were employed. The Akaike Information Criterion (AIC) was also used to verify which specification explains performance better while performing robustness check of parameter estimates was done by correcting for standard errors. Based on the findings, ROA specification proves to have the lowest Akaike Information Criterion (AIC) and Standard errors compared to ROE specification. Under ROA, two variables; the profit margins and the Interest coverage ratio proves to be statistically significant while under ROE just the interest coverage ratio (ICR) for all the estimators proves significant. The result also shows that the FGLS is the most efficient estimator, then follows the GLS and the last OLS. when corrected for SE robust, the gearing ratio which measures the capital structure becomes significant under ROA and its estimate become positive under ROE robust. Conclusions were drawn that, within the period of study three variables (ICR, profit margins and gearing) shows significant and four variables were insignificant. The overall findings show that the institutions strive to their best to maximize returns but these returns were just normal to cover their costs of operation. Much should be done as per the ASC theory to avoid liquidity and credit risks problems. Again, estimated values of ICR and profit margins shows that a considerable amount of efforts with sound financial policies are required to increase performance by one percentage point. Areas of further research could be how the individual stochastic factors such as the Dupont model, repo rates, inflation, GDP etc. can influence performance.