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Religion, churches and religious communities have growing importance in the Law of the European Union. Since long a distinct law on religion of the European Union is developing.rnThis collection of those norms of European Union Law directly concerning religion mirrors today's status of this dynamic process.

The 23rd Annual Congress of the European Consortium for Church and State Research took place in Oxford, United Kingdom from 29 September to 2 October 2011. Founded in 1989, the Consortium unites experts in law and religion from Member States of the European Union. The Oxford conference took as its theme Religion and Discrimination Law focusing on the manner in which State governments had sought to implement the non-discrimination policy of the EU by legislation and through courts and tribunals. The proceedings comprise three introductory papers considering the historical, cultural and social background; the prohibition on discrimination, and the exemptions to the general prohibition. This is followed by national reports from twenty-three countries describing the reach of discrimination law in the field of religion. These are supplemented by further papers analysing the jurisprudence of the Strasbourg Court and the background to EU Directive 2000/78/EC and by some concluding reflections. The proceedings begin with the text of a public lecture given at the opening of the Congress by Sir Nicolas Bratza, President of the European Court of Human Rights on the subject of freedom of religion under Article 9 of the Convention.

The complicated human alternative GR promoter region plays a pivotal role in the regulation of GR levels. In this thesis, both genomic and environmental factors linked with GR expression are covered. This research showed that GR promoters were susceptible to silencing by methylation and the activity of the individual promoters was also modulated by SNPs. E2F1 is a major element to drive the expression of GR 1F transcripts and single CpG dinucleotide methylation cannot mediate the inhibition of transcription in vitro. Also, the distribution of GR first exons and 3" splice variants (GRα and GR-P) is expressed throughout the human brain with no region-specific alternative first exon usage. These data mirrored the consistently low levels of methylation in the brain, and the observed homogeneity throughout the studied regions. Taken together, the research presented in this thesis explored several layers of complexity in GR transcriptional regulation.

Effective Elements on E-Marketing strategy in Tourism Industry (Case study Germany and Iran Airlines, Tour Operator and Chain Hotels) By: Seyed Siamak Mousavi Supervisor: Prof. Dr. Andreas Kagermeier This dissertation focuses on e-marketing strategy's effective elements in tourism industry. As case study, research focus is on Airlines, tour operator, chain hotels in Iran and Germany. It aims to show various possibilities to enhance the company- e-marketing strategy and successfully performance e-marketing strategies with recognition effective elements and their important during the strategy designing and implementation process. For the purpose of this research due to the nature of the research, Explanatory -exploratory-applicable; after studying and consulting, Delphi technique has been chosen. In results, we have some effective elements and their important according the Delphi and AHP method. For example between elements "Tourists' Needs, Experience and Expects" with the importance coefficient of %204 is the most remarkable elements and "Customer satisfactions' elements group" with average value 5.54 according the research results have more important than other groups.

In this thesis, we mainly investigate geometric properties of optimal codebooks for random elements $X$ in a seperable Banach space $E$. Here, for a natural number $ N $ and a random element $X$ , an $N$-optimal codebook is an $ N $-subset in the underlying Banach space $E$ which gives a best approximation to $ X $ in an average sense. We focus on two types of geometric properties: The global growth behaviour (growing in $N$) for a sequence of $N$-optimal codebooks is described by the maximal (quantization) radius and a so-called quantization ball. For many distributions, such as central-symmetric distributions on $R^d$ as well as Gaussian distributions on general Banach spaces, we are able to estimate the asymptotics of the quantization radius as well as the quantization ball. Furthermore, we investigate local properties of optimal codebooks, in particular the local quantization error and the weights of the Voronoi cells induced by an optimal codebook. In the finite-dimensional setting, we are able to proof for many interesting distributions classical conjectures on the asymptotic behaviour of those properties. Finally, we propose a method to construct sequences of asymptotically optimal codebooks for random elements in infinite dimensional Banach spaces and apply this method to construct codebooks for stochastic processes, such as fractional Brownian Motions.

One of the main tasks in mathematics is to answer the question whether an equation possesses a solution or not. In the 1940- Thom and Glaeser studied a new type of equations that are given by the composition of functions. They raised the following question: For which functions Î¨ does the equation F(Î¨)=f always have a solution. Of course this question only makes sense if the right hand side f satisfies some a priori conditions like being contained in the closure of the space of all compositions with Î¨ and is easy to answer if F and f are continuous functions. Considering further restrictions to these functions, especially to F, extremely complicates the search for an adequate solution. For smooth functions one can already find deep results by Bierstone and Milman which answer the question in the case of a real-analytic function Î¨. This work contains further results for a different class of functions, namely those Î¨ that are smooth and injective. In the case of a function Î¨ of a single real variable, the question can be fully answered and we give three conditions that are both sufficient and necessary in order for the composition equation to always have a solution. Furthermore one can unify these three conditions to show that they are equivalent to the fact that Î¨ has a locally Hölder-continuous inverse. For injective functions Î¨ of several real variables we give necessary conditions for the composition equation to be solvable. For instance Î¨ should satisfy some form of local distance estimate for the partial derivatives. Under the additional assumption of the Whitney-regularity of the image of Î¨, we can give sufficient conditions for flat functions f on the critical set of Î¨ to possess a solution F(Î¨)=f.

Time series archives of remotely sensed data offer many possibilities to observe and analyse dynamic environmental processes at the Earth- surface. Based on these hypertemporal archives, which offer continuous observations of vegetation indices, typically at repetition rates from one to two weeks, sets of phenological parameters or metrics can be derived. Examples of such parameters are the beginning and end of the annual growing period, as well as its length. Even though these parameters do not correspond exactly to conventional observations of phenological events, they nevertheless provide indications of the dynamic processes occurring in the biosphere. The development of robust algorithms for the derivation of phenological metrics can be challenging. Currently, such algorithms are most commonly based on digital filters or the Fourier analysis of time series. Polynomial spline models offer a useful alternative to existing methods. The possibilities of using spline models in the analytical description of time series are numerous, and their specific mathematical properties may help to avoid known problems occurring with the more common methods for deriving phenological metrics. Based on a selection of different polynomial spline models suitable for the analysis of remotely sensed time series of vegetation indices, a method to derive various phenological parameters from such time series was developed and implemented in this work. Using an example data set from an intensively used agricultural area showing highly dynamic variations in vegetation phenology, the newly developed method was verified by a comparison of the results of the spline based approach to the results of two alternative, well established methods.

Magnet Resonance Imaging (MRI) and Electroencephalography (EEG) are tools used to investigate the functioning of the working brain in both humans and animal studies. Both methods are increasingly combined in separate or simultaneous measurements under the assumption to benefit from their individual strength while compensating their particular weaknesses. However, little attention has been paid to how statistical analyses strategies can influence the information that can be retrieved from a combined EEG fMRI study. Two independent studies in healthy student volunteers were conducted in the context of emotion research to demonstrate two approaches of combining MRI and EEG data of the same participants. The first study (N = 20) applied a visual search paradigm and found that in both measurements the assumed effects were absent by not statistically combining their results. The second study (N = 12) applied a novelty P300 paradigm and found that only the statistical combination of MRI and EEG measurements was able to disentangle the functional effects of brain areas involved in emotion processing. In conclusion, the observed results demonstrate that there are added benefits of statistically combining EEG-fMRI data acquisitions by assessing both the inferential statistical structure and the intra-individual correlations of the EEG and fMRI signal.

Optimal control problems are optimization problems governed by ordinary or partial differential equations (PDEs). A general formulation is given byrn \min_{(y,u)} J(y,u) with subject to e(y,u)=0, assuming that e_y^{-1} exists and consists of the three main elements: 1. The cost functional J that models the purpose of the control on the system. 2. The definition of a control function u that represents the influence of the environment of the systems. 3. The set of differential equations e(y,u) modeling the controlled system, represented by the state function y:=y(u) which depends on u. These kind of problems are well investigated and arise in many fields of application, for example robot control, control of biological processes, test drive simulation and shape and topology optimization. In this thesis, an academic model problem of the form \min_{(y,u)} J(y,u):=\min_{(y,u)}\frac{1}{2}\|y-y_d\|^2_{L^2(\Omega)}+\frac{\alpha}{2}\|u\|^2_{L^2(\Omega)} subject to -\div(A\grad y)+cy=f+u in \Omega, y=0 on \partial\Omega and u\in U_{ad} is considered. The objective is tracking type with a given target function y_d and a regularization term with parameter \alpha. The control function u takes effect on the whole domain \Omega. The underlying partial differential equation is assumed to be uniformly elliptic. This problem belongs to the class of linear-quadratic elliptic control problems with distributed control. The existence and uniqueness of an optimal solution for problems of this type is well-known and in a first step, following the paradigm 'first optimize, then discretize', the necessary and sufficient optimality conditions are derived by means of the adjoint equation which ends in a characterization of the optimal solution in form of an optimality system. In a second step, the occurring differential operators are approximated by finite differences and the hence resulting discretized optimality system is solved with a collective smoothing multigrid method (CSMG). In general, there are several optimization methods for solving the optimal control problem: an application of the implicit function theorem leads to so-called black-box approaches where the PDE-constrained optimization problem is transformed into an unconstrained optimization problem and the reduced gradient for these reduced functional is computed via the adjoint approach. Another possibilities are Quasi-Newton methods, which approximate the Hessian by a low-rank update based on gradient evaluations, Krylov-Newton methods or (reduced) SQP methods. The use of multigrid methods for optimization purposes is motivated by its optimal computational complexity, i.e. the number of required computer iterations scales linearly with the number of unknowns and the rate of convergence, which is independent of the grid size. Originally multigrid methods are a class of algorithms for solving linear systems arising from the discretization of partial differential equations. The main part of this thesis is devoted to the investigation of the implementability and the efficiency of the CSMG on commodity graphics cards. GPUs (graphic processing units) are designed for highly parallelizable graphics computations and possess many cores of SIMD-architecture, which are able to outperform the CPU regarding to computational power and memory bandwidth. Here they are considered as prototype for prospective multi-core computers with several hundred of cores. When using GPUs as streamprocessors, two major problems arise: data have to be transferred from the CPU main memory to the GPU main memory, which can be quite slow and the limited size of the GPU main memory. Furthermore, only when the streamprocessors are fully used to capacity, a remarkable speed-up comparing to a CPU is achieved. Therefore, new algorithms for the solution of optimal control problems are designed in this thesis. To this end, a nonoverlapping domain decomposition method is introduced which allows the exploitation of the computational power of many GPUs resp. CPUs in parallel. This algorithm is based on preliminary work for elliptic problems and enhanced for the application to optimal control problems. For the domain decomposition into two subdomains the linear system for the unknowns on the interface is solved with a Schur complement method by using a discrete approximation of the Steklov-Poincare operator. For the academic optimal control problem, the arising capacitance matrix can be inverted analytically. On this basis, two different algorithms for the nonoverlapping domain decomposition for the case of many subdomains are proposed in this thesis: on the one hand, a recursive approach and on the other hand a simultaneous approach. Numerical test compare the performance of the CSMG for the one domain case and the two approaches for the multi-domain case on a GPU and CPU for different variants.

The main topic of this treatise is the solution of two problems from the general theory of linear partial differential equations with constant coefficients. While surjectivity criteria for linear partial differential operators in spaces of smooth functions over an open subset of euclidean space and distributions were proved by B. Malgrange and L. Hörmander in 1955, respectively 1962, concrete evaluation of these criteria is still a highly non-trivial task. In particular, it is well-known that surjectivity in the space of smooth functions over an open subset of euclidean space does not automatically imply surjectivity in the space of distributions. Though, examples for this fact all live in three or higher dimensions. In 1966, F. Trèves conjectured that in the two dimensional setting surjectivity of a linear partial differential operator on the smooth functions indeed implies surjectivity on the space of distributions. An affirmative solution to this problem is presented in this treatise. The second main result solves the so-called problem of (distributional) parameter dependence for solutions of linear partial differential equations with constant coefficients posed by J. Bonet and P. Domanski in 2006. It is shown that, in dimensions three or higher, this problem in general has a negative solution even for hypoelliptic operators. Moreover, it is proved that the two dimensional case is again an exception, because in this setting the problem of parameter dependence always has a positive solution.