<p>Previous studies of agricultural conditions in the Mekong Delta (MD) have identified soil compaction as an obstacle to sustainable production. A conceptual model for soil formation was presented to demonstrate the link between soil hydrology and plant response. Detailed studies of soil moisture dynamics in agricultural fields were conducted using a dynamic process-orientated model. Pressure head and water flow were simulated for three selected sites during a year for which empirical data were available. Daily meteorological data were used as dynamic input and measured pressure head was used to estimate parameter values that satisfied various acceptance criteria. The Generalised Likelihood Uncertainty Estimation (GLUE) approach was applied for calibration procedures with 10,000 runs, each run using random values within the chosen range of parameter values. To evaluate model performance and uncertainty estimation, re-sampling was carried out using coefficient of determination (R2) and mean error (ME) as the criteria. Correlations between parameters and R2 (and ME) and among parameters were also considered to analyse the relationship of the selected parameter set in response to increases/decreases in the acceptable simulations. The method was successful for two of the three sites, with many accepted simulations. For these sites, the uncertainty was reduced and it was possible to quantify the importance of the different parameters.</p><p> </p>

Let G be a reductive algebraic group defined over an algebraically closed field of characteristic p. A subgroup H of G is called G-complete reducible whenever H is contained in a parabolic subgroup P of G, it is contained in some Levi subgroup of P. In this thesis, we present a pair of reductive subgroups H and M of G of type E_7 such that H<M and H is G-completely reducible but not M-completely reducible.

The aim of this study is to analyze factors that affecting consumers to drink coffee, based on two case studies in University of Gävle in Sweden and Zhuhai College of Jilin University in China.The study was conducted with mixed research methods. A questionnaire survey was designed as a pre-study to get a general idea and the interviews were designed based on the result of survey in order to gain more detailed information and explanations from the respondents. All the data are shown by tables or diagrams or histograms. University students in two different culture participated in survey and interviews, a comparison perspective for cross culture was mentioned in this study. As for Result &amp; Conclusions, both external factors (culture, price and people around) as well as internal factors (personality, psychological influence, learning and knowledge) impact the consumer‟s behaviors that are shown in different consumption characteristics. Take all in account, these factors could have an effect on university students to drink (or not drink) coffee in Jilin University and University of Gävle. And Contribution &amp; implication, the comparison of coffee drink between Chinese culture and Swedish culture is the most attractive contributions, supplementing the related study. Price issue was considered as the important factor that affecting the consumer to choose coffee, thus suggesting the managers to focus on the coffee price. In addition, the effective way to explore coffee market in China or Sweden is to know better of the consumers. Suggestions for future research, other consumer groups are missing given the study only focus on the university students. Also tested with more sample sizes of survey andIIinterviews are recommended in the future research so as to make it even valid and reliable.

The thesis deals with Luxembourg and its position in the European Union. It contains description of the economic characteristics and development of basic macroeconomic indicators of the country in the last decade. The thesis also evaluates the status of Luxembourg in the entire EU-27 based on a comparison of basic macroeconomic indicators. Finally, it sums up history of the European Communities in Luxembourg and subsequently in the European Union. Reader can find out information about last Luxembourg Presidency of the Council of the European Union and country's attitude to highly debated issues in the EU.

Doctor of Philosophy / Department of Statistics / Wei-Wen Hsu / The classification methods based on a linear combination of multiple biomarkers have been widely used to improve the accuracy in disease screening and diagnosis. However, it is seldom to include covariates such as gender and age at diagnosis into these classification procedures. It is known that biomarkers or patient outcomes are often associated with some covariates in practice, therefore the inclusion of covariates may further improve the power of prediction as well as the classification accuracy. In this study, we focus on the classification methods for multiple biomarkers adjusting for covariates. First, we proposed a covariate-adjusted classification model for multiple cross-sectional biomarkers. Technically, it is a two-stage method with a parametric or non-parametric approach to combine biomarkers first, and then incorporating covariates with the use of the maximum rank correlation estimators. Specifically, these parameter coefficients associated with covariates can be estimated by maximizing the area under the receiver operating characteristic (ROC) curve. The asymptotic properties of these estimators in the model are also discussed. An intensive simulation study is conducted to evaluate the performance of this proposed method in finite sample sizes. The data of colorectal cancer and pancreatic cancer are used to illustrate the proposed methodology for multiple cross-sectional biomarkers. We further extend our classification method to longitudinal biomarkers. With the use of a natural cubic spline basis, each subject's longitudinal biomarker profile can be characterized by spline coefficients with a significant reduction in the dimension of data. Specifically, the maximum reduction can be achieved by controlling the number of knots or degrees of freedom in the spline approach, and its coefficients can be obtained by the ordinary least squares method. We consider each spline coefficient as ``biomarker'' in our previous method, then the optimal linear combination of those spline coefficients can be acquired using Stepwise method without any distributional assumption. Afterward, covariates are included by maximizing the corresponding AUC as the second stage. The proposed method is applied to the longitudinal data of Alzheimer's disease and the primary biliary cirrhosis data for illustration. We conduct a simulation study to assess the finite-sample performance of the proposed method for longitudinal biomarkers.

The study examined gender differences in fashion consumption in reflecting to retailing-store characteristics. Observation was conducted in the five different retailing-stores to notice various store displays and consumer behaviors between women and men. Information from various sources including journals, books, stores’ magazines, and stores’ websites were used as additional data in complementing to observation technique. The study found that female were gather shoppers who went shopping for reasons of enjoyment and relaxation. Thus, they like spending time browsing for comparing price, products, and quality. On the other hand, men were hunter shoppers who went shopping for need-driven. As a result, men preferred shop where they can search for their intended items easily. Similarly, shop characteristics were found to reflect and adapt to consumer behavior by gender. / Program: Magisterutbildning i företagsekonomi

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Aluminosilicate inorganic polymers (AIPs) are network heteropolymers consisting of Si04 and AlO4 tetrahedra linked by a shared oxygen. The use of these materials as a cementing agent, toxic waste storage and fibre reinforced material, amongst a multitude of prospective applications, has grown in recent years. The utilisation of AIPs is hampered by a lack of knowledge about their formation and structure. In order to allow the materials to achieve their full potential, the way in which the material behaves and forms under different conditions must be elucidated. The basic questions that this study aimed to answer were: 1) How does the structure of these AIPs change with composition? and 2) Can this change in structure explain the material properties of the AIP? The AIPs investigated in the study covered the molar composition ranges Si:Al ratio = 1 - 3 and Na:Al ratio = 0.5 - 2. They were made by the sodium hydroxide activation of metakaolinite, derived from the dehydroxylation of kaolinite. The Si content of the AIP was altered by the addition of amorphous silica fume via the activation solution. The study considered the structural nature of the AIPs at the macro, micro and nanoscales, and found that the structure changed at all scales and with all compositions. The nature of the AIP structure was studied at the macroscale utilising compressive strength testing. The results from this work showed that the compressive strength of the AIPs varied systematically with the chemical composition. The strengths recorded ranged from 0.4 ± 0.2 MPa for a sample with Si:Al:Na molar ratios = 1.08:1:0.5, to 64 ± 3 MPa for a sample with Si:Al:Na molar ratios = 2.5:1:1.3. The higher strengths measured exceed those exhibited by Portland cement pastes. The microstructure of the AIPs was investigated by scanning electron microscopy and energy dispersive spectroscopy. / Microscopy showed that the microstructure variations correlated with the compressive strength. In general, AIPs with low compressive strengths exhibited an inhomogeneous two-phase microstructure; grain and matrix. The grain phase consisted of undissolved metakaolinite, whilst the matrix was the fully formed inorganic polymer. AIPs with high compressive strengths exhibited a microstructure that was more homogeneous than the samples with low compressive strength. The compressive strength of the AIPs depended on both the chemical composition and the level of residual MK present in the microstructure. EDS microanalysis showed that the composition of the two phases was significantly different, and that the differences depended on the overall composition of the AIP. EDS results also demonstrated that the impurity elements present in the metakaolinite were affected by the polymerisation process. Soluble elements such as Ca and Mg were found primarily in the matrix, indicating that they had leached out of the metakaolinite grains, whereas insoluble elements such as Fe and Ti were found primarily in the grains. The nanoscale structure of the AIPs was examined by solid-state nuclear magnetic resonance (NMR) and x-ray scattering (XRS). The NMR measurements revealed that the average coordination of Si varied according to the composition of the AIP, whereas the coordination of Al was constant. Na is present in the network in both hydrated and non-hydrated forms. It is postulated that the variation in the Si coordination can be explained by the formation of Si-O-Na bonds with Na forming an ionic bond with 0 in the polymer network. Radial distribution function (RDF) analysis of the XRS patterns revealed little difference in the structure of the different AIPs beyond ~2.5 Å. / Unfortunately, the data were of insufficient resolution to allow for a full evaluation of the differences in the Si-O and Al-O bonds between different AIPs. However, the trends present in the shape and position of the RDF peak corresponding to the Si-O and Al-O bonds do follow the composition of the AIP. It has been shown that a variety of experimental techniques can be used in concert to obtain information on the structural nature of AIPs. To this end, it has been found that the compressive strength of AIPs can be optimised, and that the microstructure of the AIPs changes systematically with variations in the compressive strength. An improved model for the structure of AIPs has also been proposed.

Thesis (Ph.D.)--McMaster University, 2005. / Supervisor: Manfred Kolster. Includes bibliographical references (leaves 93-96).

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