Dynamic fault tree analysis with PEWMA modeling of event rates and Bayesian updating of material balance parameters using MCMC

This research explores Bayesian updating as a tool for estimating parameters probabilistically by dynamic analysis of data sequences. Two distinct Bayesian updating methodologies are assessed. The first approach focuses on Bayesian updating of failure rates for primary events in fault trees. A Poisson Exponentially Moving Average (PEWMA) model is implemnented to carry out Bayesian updating of failure rates for individual primary events in the fault tree. To provide a basis for testing of the PEWMA model, a fault tree is developed based on the Texas City Refinery incident which occurred in 2005. A qualitative fault tree analysis is then carried out to obtain a logical expression for the top event. A dynamic Fault Tree analysis is carried out by evaluating the top event probability at each Bayesian updating step by Monte Carlo sampling from posterior failure rate distributions. It is demonstrated that PEWMA modeling is advantageous over conventional conjugate Poisson-Gamma updating techniques when failure data is collected over long time spans. The second approach focuses on Bayesian updating of parameters in non-linear forward models. Specifically, the technique is applied to the hydrocarbon material balance equation. In order to test the accuracy of the implemented Bayesian updating models, a synthetic data set is developed using the Eclipse reservoir simulator. Both structured grid and MCMC sampling based solution techniques are implemented and are shown to model the synthetic data set with good accuracy. Furthermore, a graphical analysis shows that the implemented MCMC model displays good convergence properties. A case study demonstrates that Likelihood variance affects the rate at which the posterior assimilates information from the measured data sequence. Error in the measured data significantly affects the accuracy of the posterior parameter distributions. Increasing the likelihood variance mitigates random measurement errors, but casuses the overall variance of the posterior to increase. Bayesian updating is shown to be advantageous over deterministic regression techniques as it allows for incorporation of prior belief and full modeling uncertainty over the parameter ranges. As such, the Bayesian approach to estimation of parameters in the material balance equation shows utility for incorporation into reservoir engineering workflows.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Effects of gust velocity spatial distributions on lateral-directional response of a VTOL aircraft

Mode of access: Internet.

Examining underlying determinants of fertility rates in Zambia: Evidence from the 2007 Zambia Demographic and Health Survey

Limited data exits on factors influencing fertility in Zambia. This study examined underlying determinants of fertility patterns and levels in Zambia. Data extracted from the 2007 Zambia Demographic and Health Survey was analysed using bivariate and multivariate logistic regression. Of 7146 women aged 15-49 years, age group 25-29 years experienced the highest prevalence of births (28.5%). Married women accounted for 27% of all births. Women with low education recorded more births (27%) than those with higher education (9.5%) (P<0.001). Fertility was higher among the poorest (28%) compared to the richest (12%) (P<0.001). Though not statistically significant, urban areas recorded more births (25%) than rural areas (15%). Education and wealth significantly influence fertility Zambia. Fertility management strategies should consider these factors and their fertility reducing effects. Improving education and wealth status of women can contribute to fertility reduction, particularly rural women. Lower fertility, with reduced mortality and migration, would provide less pressure on distribution of the limited economic resources of the country.

Logistics Cost Optimization of Road Freight Shipments in a Consumer Goods Company

In the industry of the case company, transportation and warehousing costs account for more than 10% of the total cost which is more than on average. A Finnish company has an understanding that by sending larger shipments in parcels, they could save tens of thousands of euros annually in freight costs in Finland’s domestic shipments. To achieve these savings and optimize total logistics cost, company’s interest is to find out which is the cost efficient way of shipping road shipments of certain volumes; in parcel boxes or on pallets, and what should be the split volume determining the shipment type. Distribution center (DC) costs affect this decision and therefore they need to be also evaluated to determine the total logistics cost savings. Main results were achieved by executing activity-based costing-calculations including DC and road freight costs to determine the ideal split volume with which the total logistics cost is optimal. Calculations were done for Finland’s DC, separately for two main road freight destinations, Finland and Sweden, which cover 50% of road shipment spend. Data for calculations was collected both manually and automatically from various internal and external sources, such as the company ERP system and logistics service providers’ (LSP) reporting. DC processes were studied in practice and compared to model processes. Currently used freight rates were compared to existing pricing models and freight service tendering process was evaluated by participating in the process and comparing it to the models based on literature. The results show that the potential savings are not as significant as the company hoped for, mainly because of packing work increasing DC labor cost. Annual savings by setting ideal split volume per country would account for 0,4 % of the warehousing and transportation costs of shipments in scope of this thesis. Split volume should be set separately for each route, mainly because the pricing model for road freight is different in each country. For some routes bigger parcels should be sent but for some routes pallets should be used more. Next step is to do these calculations for remaining routes to determine total savings potential. Other findings show that the processes in the DC are designed well and the company could achieve savings by executing tenders more efficiently. Company should also pay more attention to parcel pricing and packing the shipments accordingly.

MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.

Production of basic potato seed minitubers in substrate and different nitrogen rates

The optimal dose of nitrogen (N) in potato crop depends on the production system. The objective of this study was to determine the optimal dose of N for the production of basic potato seed minitubers and evaluate the effect of N rates on physiological and nitrogen indices in the youngest fully developed leaf (fourth leaf) and in the oldest leaf of the plants at 60 days after planting. The experiment was conducted in a greenhouse at the Departamento de Fitotecnia da Universidade Federal de Viçosa. The treatments consisted of five N rates (0, 45, 90, 180 and 360 mg dm-3), with 10% of each dose applied at planting and the remainder through irrigation water, daily, for 30 days. The nitrogen rates positively influenced the physiological indices (length, width, leaf area, number of leaves, fresh mass and dry mass) and nitrogen (level and content of N and N-NO³ in the dry mass and SPAD) both in the fourth leaf and in the oldest leaf. Likewise, the N rates positively influenced the number and mass of harvested tubers. The largest number (5.44 tubers/plant) and the maximum mass of tubers (243.5 g/plant) were obtained with 360.0 and 332.9 mg N dm-3, respectively. Therefore, the mass and number of tubers were not optimized by the same N rate. The critical SPAD index was 38.8 in the fourth leaf, which was more sensitive to the effect of N rates than the oldest leaf.

Carbohydrates Concentration in leaves of potato plants affected by nitrogen fertilization rates

ABSTRACT At poor conditions of nitrogen (N) in the soil, potato plants may accumulate starch in leaves and be indicative of N nutritional stress. The objective of this work was to determine the effects of N rates (0, 50, 100, 200 and 300 kg ha-1 of N) on the concentrations of carbohydrates (total soluble sugars-TSS, reducing sugars-RS, non-reducing sugars-NRS and starch) in the fourth leaf (FL) of two potato cultivars (Asterix and Atlantic) and their critical levels (CL) associated to the N fertilization rate necessary to obtain the maximum physical (MPE) and economic (MEE) efficiency of tubers. A randomized block design with four replications was used in both experiments. On day 21 after plant emergence, four FL were collected from four plants. Potatoes plants fertilized with low rates of N accumulated less TSS in leaves than those properly fertilized. The opposite occurred with content of starch. The cultivars showed similar responses to five doses of N in relation to contents of starch and TSS. However, the response to the increase in doses of N for RS, NRS and Starch/NRS is cultivar-specific. The correlations between contents of RS, NRS and Starch/NRS with the starch and TSS were dependent on the potato cultivar.

Effect of swine residue rates on corn, common bean, soybean and wheat yield

Swine residue (SR) applied as nutrient source of crops such as corn, bean, soybean and wheat, besides representing an environmental-friendly way of disposing of organic waste resulting from swine production, may significantly increase grain yields, replacing mineral fertilizer. The objective was to evaluate the effect of SR rates on corn, common bean, soybean and wheat yields from 2002 to 2007, in comparison with mineral fertilizer. The experiment was carried out at the Instituto Agronômico do Paraná - IAPAR, Pato Branco, PR and consisted of increasing SR rates (0, 15, 30, 45, and 60 m³ ha-1) and one treatment with mineral fertilizer (NPK 4-30-10), using 250 kg ha-1 for bean and 300 kg ha-1 for corn, soybean and wheat. Also, in the treatment with mineral fertilizer, 60, 120 and 90 kg ha-1 N was applied as topdressing to bean, corn and wheat, respectively. There were significant increases of grain yield in all evaluated years and crops with increasing SR rates, especially in the grass species under study. Also, with increasing SR rates applied every six months, K, P, Ca and Mg were accumulated in the soil and the pH increased. The application of 60 m³ ha-1 SR increased yields and exceeded the yield obtained with the recommended mineral fertilizer, indicating this amount as adequate for these crops.

Soluble carbon in oxisol under the effect of organic residue rates

The application of organic residues to the soil can increase soluble organic carbon (SOC) and affect the pH and electrolytic conductivity (EC) of the soil. However, the magnitude of these changes depends on the type of residue and the applied dose. This study aimed to evaluate the effect of increasing C rates contained in organic residue on the pH, EC, water-extractable total carbon (WETC), water-extractable organic carbon (WEOC), and water-extractable inorganic carbon (WEIC) in soil treated with manure (chicken, swine, and quail), sawdust, coffee husk, and sewage sludge. The levels of total C (TC- KH2PO4), organic carbon (OC- KH2PO4), and inorganic C (IC- KH2PO4) extractable by a 0.1 mol L-1 KH2PO4 solution were also quantified in soil under the effect of increasing rates of chicken and quail manures. The following rates of organic residue C were applied to a dystrophic Red Latosol (Oxisol) sample: 0, 2,000, 5,000, 10,000, and 20,000 mg kg-1. The addition of organic residues to the soil increased pH, except in the case of sewage sludge, which acidified the soil. The acidity correction potential of chicken and quail manure was highest, dependent on the manure rate applied; regardless of the dose used, sawdust barely alters the soil pH. At all tested rates, the EC of the soil treated with swine manure, coffee husk, and sawdust remained below 2.0 dS m-1, which is a critical level for salinity-sensitive crops. However, the application of chicken or quail manure and sewage sludge at certain rates increased the EC to values above this threshold level. Highest levels of WETC, WEOC, and WEIC were obtained when chicken and quail manure and coffee husk were applied to the Oxisol. The quantities of SOC extracted by KH2PO4 were higher than the quantities extracted by water, demonstrating the ability of soil to adsorb C into its colloids.

Do Rates and Splitting of Phosphogypsum Applications Influence the Soil and Annual Crops in a No-Tillage System?

ABSTRACT Applications of phosphogypsum (PG) provide nutrients to the soil and reduce Al3+ activity, favoring soil fertility and root growth, but allow Mg2+ mobilization through the soil profile, resulting in variations in the PG rate required to achieve the optimum crop yield. This study evaluated the effect of application rates and splitting of PG on soil fertility of a Typic Hapludox, as well as the influence on annual crops under no-tillage. Using a (4 × 3) + 1 factorial structure, the treatments consisted of four PG rates (3, 6, 9, and 12 Mg ha-1) and three split applications (P1 = 100 % in 2009; P2 = 50+50 % in 2009 and 2010; P3 = 33+33+33 % in 2009, 2010 and 2011), plus a control without PG. The soil was sampled six months after the last PG application, in stratified layers to a depth of 0.8 m. Corn, wheat and soybean were sown between November 2011 and December 2012, and leaf samples were collected for analysis when at least 50 % of the plants showed reproductive structures. The application of PG increased Ca2+ concentrations in all sampled soil layers and the soil pH between 0.2 and 0.8 m, and reduced the concentrations of Al3+ in all layers and of Mg2+ to a depth of 0.6 m, without any effect of splitting the applications. The soil Ca/Mg ratio increased linearly to a depth of 0.6 m with the rates and were found to be higher in the 0.0-0.1 m layer of the P2 and P3 treatments than without splitting (P1). Sulfur concentrations increased linearly by application rates to a depth of 0.8 m, decreasing in the order P3>P2>P1 to a depth of 0.4 m and were higher in the treatments P3 and P2 than P1 between 0.4-0.6 m, whereas no differences were observed in the 0.6-0.8 m layer. No effect was recorded for K, P and potential acidity (H+Al). The leaf Ca and S concentration increased, while Mg decreased for all crops treated with PG, and there was no effect of splitting the application. The yield response of corn to PG rates was quadratic, with the maximum technical efficiency achieved at 6.38 Mg ha-1 of PG, while wheat yield increased linearly in a growing season with a drought period. Soybean yield was not affected by the PG rate, and splitting had no effect on the yield of any of the crops. Phosphogypsum improved soil fertility in the profile, however, Mg2+ migrated downwards, regardless of application splitting. Splitting the PG application induced a higher Ca/Mg ratio in the 0.0-0.1 m layer and less S leaching, but did not affect the crop yield. The application rates had no effect on soybean yield, but were beneficial for corn and, especially, for wheat, which was affected by a drought period during growth.

Molecular dating, evolutionary rates, and the age of the grasses.

Many questions in evolutionary biology require an estimate of divergence times but, for groups with a sparse fossil record, such estimates rely heavily on molecular dating methods. The accuracy of these methods depends on both an adequate underlying model and the appropriate implementation of fossil evidence as calibration points. We explore the effect of these in Poaceae (grasses), a diverse plant lineage with a very limited fossil record, focusing particularly on dating the early divergences in the group. We show that molecular dating based on a data set of plastid markers is strongly dependent on the model assumptions. In particular, an acceleration of evolutionary rates at the base of Poaceae followed by a deceleration in the descendants strongly biases methods that assume an autocorrelation of rates. This problem can be circumvented by using markers that have lower rate variation, and we show that phylogenetic markers extracted from complete nuclear genomes can be a useful complement to the more commonly used plastid markers. However, estimates of divergence times remain strongly affected by different implementations of fossil calibration points. Analyses calibrated with only macrofossils lead to estimates for the age of core Poaceae ∼51-55 Ma, but the inclusion of microfossil evidence pushes this age to 74-82 Ma and leads to lower estimated evolutionary rates in grasses. These results emphasize the importance of considering markers from multiple genomes and alternative fossil placements when addressing evolutionary issues that depend on ages estimated for important groups.

Three essays on the determinants of output, inflation and interest rates

Résumé: Output, inflation and interest rates are key macroeconomic variables, in particular for monetary policy. In modern macroeconomic models they are driven by random shocks which feed through the economy in various ways. Models differ in the nature of shocks and their transmission mechanisms. This is the common theme underlying the three essays of this thesis. Each essay takes a different perspective on the subject: First, the thesis shows empirically how different shocks lead to different behavior of interest rates over the business cycle. For commonly analyzed shocks (technology and monetary policy errors), the patterns square with standard models. The big unknown are sources of inflation persistence. Then the thesis presents a theory of monetary policy, when the central bank can better observe structural shocks than the public. The public will then seek to infer the bank's extra knowledge from its policy actions and expectation management becomes a key factor of optimal policy. In a simple New Keynesian model, monetary policy becomes more concerned with inflation persistence than otherwise. Finally, the thesis points to the huge uncertainties involved in estimating the responses to structural shocks with permanent effects.

High rates of smoking especially in female Crohn's disease patients and low use of supportive measures to achieve smoking cessation : Data from the SwissIBD cohort study

BACKGROUND AND AIMS: Smoking is a crucial environmental factor in inflammatory bowel disease (IBD). However, knowledge on patient characteristics associated with smoking, time trends of smoking rates, gender differences and supportive measures to cease smoking provided by physicians is scarce. We aimed to address these questions in Swiss IBD patients. METHODS: Prospectively obtained data from patients participating in the Swiss IBD cohort study was analysed and compared to the general Swiss population (GSP) matched by age, sex and year. RESULTS: Among a total of 1770 IBD patients analysed (49.1% male), 29% are current smokers. More than twice as many patients with Crohn's disease (CD) are active smokers compared to ulcerative colitis (UC, 39.6% vs. 15.3%, p<0.001). In striking contrast to the GSP, significantly more women than men with CD smoke (42.8% vs. 35.8%, p=0.025), with also an overall significantly increased smoking rate compared to the GSP in women but not men. The vast majority of smoking IBD patients (90.5%) claim to never have received any support to achieve smoking cessation, significantly more in UC compared to CD. We identify a significantly negative association of smoking and primary sclerosing cholangitis, indicative of a protective effect. Psychological distress in CD is significantly higher in smokers compared to non-smokers, but does not differ in UC CONCLUSIONS: Despite well-established detrimental effects, smoking rates in CD are alarmingly high with persistent and stagnating elevations compared to the GSP, especially in female patients. Importantly, there appears to be an unacceptable underuse of supportive measures to achieve smoking cessation.