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The dissertation is concerned with the numerical solution of Fokker-Planck equations in high dimensions arising in the study of dynamics of polymeric liquids. Traditional methods based on tensor product structure are not applicable in high dimensions for the number of nodes required to yield a fixed accuracy increases exponentially with the dimension; a phenomenon often referred to as the curse of dimension. Particle methods or finite point set methods are known to break the curse of dimension. The Monte Carlo method (MCM) applied to such problems are 1/sqrt(N) accurate, where N is the cardinality of the point set considered, independent of the dimension. Deterministic version of the Monte Carlo method called the quasi Monte Carlo method (QMC) are quite effective in integration problems and accuracy of the order of 1/N can be achieved, up to a logarithmic factor. However, such a replacement cannot be carried over to particle simulations due to the correlation among the quasi-random points. The method proposed by Lecot (C.Lecot and F.E.Khettabi, Quasi-Monte Carlo simulation of diffusion, Journal of Complexity, 15 (1999), pp.342-359) is the only known QMC approach, but it not only leads to large particle numbers but also the proven order of convergence is 1/N^(2s) in dimension s. We modify the method presented there, in such a way that the new method works with reasonable particle numbers even in high dimensions and has better order of convergence. Though the provable order of convergence is 1/sqrt(N), the results show less variance and thus the proposed method still slightly outperforms standard MCM.

This thesis builds a bridge between singularity theory and computer algebra. To an isolated hypersurface singularity one can associate a regular meromorphic connection, the Gauß-Manin connection, containing a lattice, the Brieskorn lattice. The leading terms of the Brieskorn lattice with respect to the weight and V-filtration of the Gauß-Manin connection define the spectral pairs. They correspond to the Hodge numbers of the mixed Hodge structure on the cohomology of the Milnor fibre and belong to the finest known invariants of isolated hypersurface singularities. The differential structure of the Brieskorn lattice can be described by two complex endomorphisms A0 and A1 containing even more information than the spectral pairs. In this thesis, an algorithmic approach to the Brieskorn lattice in the Gauß-Manin connection is presented. It leads to algorithms to compute the complex monodromy, the spectral pairs, and the differential structure of the Brieskorn lattice. These algorithms are implemented in the computer algebra system Singular.

In the last decade, injection molding of long-fiber reinforced thermoplastics
(LFT) has been established as a low-cost, high volume technique for manufacturing
parts with complex shape without any post-treatment [1–3]. Applications
are mainly found in the automotive industry with a volume annually
growing by 10% to 15% [4].
While first applications were based on polyamide (PA6 and PA6.6), the market
share of glass fiber reinforced polypropylene (PP) is growing due to cost savings
and ease of processing. With the use of polypropylene, different processing
techniques such as gas-assisted injection molding [5] or injection compression
molding [6] have emerged in addition to injection molding [7, 8].
In order to overcome or justify higher materials costs when compared to short
fiber reinforced thermoplastics, the manufacturing techniques for LFT pellets
with fiber length greater than 10mm have evolved starting from pultrusion by
improving impregnation and throughput [9] or by direct addition of fiber strands
in the mold [10–12].
The benefit of long glass fiber reinforcement either in PP or PA is mainly due
to the enhanced resistance to fiber pull-out resulting in an increase in impact
properties and strength [13–19], even at low temperature levels [20]. Creep
and fatigue resistance are also substantially improved [21, 22].
The performance of fiber reinforced thermoplastics manufactured by injection
molding strongly depends on the flow-induced microstructure which is
driven by materials composition, processing conditions and part geometry.
The anisotropic microstructure is characterized by fiber fraction and dispersion,
fiber length and fiber orientation.
Facing the complexity of this processing technique, simulation becomes a precious
tool already in the concept phase for parts manufactured by injection
molding. Process simulation supports decisions with respect to choice of concepts
and materials. The part design is determined in terms of mold filling
including location of gates, vents and weld lines. Tool design requires the
determination of melt feeding, logistics and mold heating. Subsequently, performance
including prediction of shrinkage and warpage as well as structural
analysis is evaluated [23].
While simulation based on two-dimensional representation of three-dimensional
part geometry has been extensively used during the last two decades, the
complexity of the parts as well as the trend towards solid modelling in CAD
and CAE demands the step towards three-dimensional process simulation. The scope of this work is the prediction of flow-induced microstructure during
injection molding of long glass fiber reinforced polypropylene using threedimensional
process simulation. Modelling of the injection molding process in
three dimensions is supported experimentally by rheological characterization
in both shear and extensional flow and by two- and three-dimensional evaluation
of microstructure.
In chapter 2 the fundamentals of rheometry and rheology are presented with
respect to long fiber reinforced thermoplastics. The influence of parameters
on microstructure is described and approaches for modelling the state of microstructure
and its dynamics are discussed.
Chapter 3 introduces a rheometric technique allowing for rheological characterization
of polymer melts at processing conditions as encountered during
manufacturing. Using this rheometer, both shear and extensional viscosity of
long glass fiber reinforced polypropylene are measured with respect to composition
of materials, processing conditions and geometry of the cavity.
Chapter 4 contains the evaluation of microstructure of long glass fiber reinforced
polypropylene in terms of two-dimensional fiber orientation and its dependence
on materials parameters and processing condition. For the evaluation
of three-dimensional microstructure, a technique based on x-ray tomography
is introduced.
In chapter 5, modelling of microstructural dynamics is addressed. One-way
coupling of interactions between fluid and fibers is described macroscopically.
The flow behavior of fibers in the vicinity of cavity walls is evaluated experimentally.
From these observations, a model for treatment of fiber-wall interaction
with respect to numerical simulation is proposed.
Chapter 6 presents the application of three-dimensional simulation of the injection
molding process. Mold filling simulation is performed using a commercial
code while prediction of 3D fiber orientation is based on a proprietary module.
The rheological and thermal properties derived in chapter 3 are tested by
simulation of the experiments and comparison of predicted pressure and temperature
profile versus recorded results. The performance of fiber orientation
prediction is verified using analytical solutions of test examples from literature.
The capability of three-dimensional simulation is demonstrated based on the
simulation of mold filling and prediction of fiber orientation for an automotive
part.

Microsystem technology has been a fast evolving field over the last few years. Its ability to handle volumes in the sub-microliter range makes it very interesting for potential application in fields such as biology, medicine and pharmaceutical research. However, the use of micro-fabricated devices for the analysis of liquid biological samples still has to prove its applicability for many particular demands of basic research. This is particularly true for samples consisting of complex protein mixtures. The presented study therefore aimed at evaluating if a commonly used glass-coating technique from the field of micro-fluidic technology can be used to fabricate an analysis system for molecular biology. It was ultimately motivated by the demand to develop a technique that allows the analysis of biological samples at the single-cell level. Gene expression at the transcription level is initiated and regulated by DNA-binding proteins. To fully understand these regulatory processes, it is necessary to monitor the interaction of specific transcription factors with other elements - proteins as well as DNA sites - in living cells. One well-established method to perform such analysis is the Chromatin Immunoprecipitation (CHIP) assay. To map protein-DNA interactions, living cells are treated with formaldehyde in vivo to cross-link DNA-binding proteins to their resident sites. The chromatin is then broken into small fragments, and specific antibodies against the protein of interest are used to immunopurify the chromatin fragments to which those factors are bound. After purification, the associated DNA can be detected and analyzed using Polymerase Chain Reaction (PCR). Current CHIP technology is limited as it needs a relatively large number of cells while there is increasing interest in monitoring DNA-protein interactions in very few, if not single cells. Most notably this is the case in research on early organism development (embryogenesis). To investigate if microsystem technology can be used to analyze DNA-protein complexes from samples containing chromatin from only few cells, a new setup for fluid transport in glass capillaries of 75 µm inner diameter has been developed, forming an array of micro-columns for parallel affinity chromatography. The inner capillary walls were antibody-coated using a silane-based protocol. The remaining surface was made chemically inert by saturating free binding sites with suitable biomolecules. Variations of this protocol have been tested. Furthermore, the sensitivity of the PCR method to detect immunoprecipitated protein-DNA complexes was improved, resulting in the reliable detection of about 100 DNA fragments from chromatin. The aim of the study was to successively decrease the amount of analyzed chromatin in order to investigate the lower limits of this technology in regard to sensitivity and specificity of detection. The Drosophila GAGA transcription factor was used as an established model system. The protein has already been analyzed in several large-scale CHIP experiments and antibodies of excellent specificity are available. The results of the study revealed that this approach is not easily applicable to "real-world" biological samples in regard to volume reduction and specificity. Particularly, material that non-specifically adsorbed to capillary surfaces outweighed the specific antibody-antigen interaction, the system was designed for. It became clear that complex biological structures, such as chromatin-protein compositions, are not as easily accessible by techniques based on chemically modified glass surfaces as pre-purified samples. In the case of the investigated system, it became evident that there is a need for more research that goes beyond the scope of this work. It is necessary to develop novel coatings and materials to prevent non-specific adsorption. In addition to improving existing techniques, fundamentally new concepts, such as microstructures in biocompatible polymers or liquid transport on hydrophobic stripes on planar substrates to minimize surface contact, may also help to advance the miniaturization of biological experiments.

Contributions to the application of adaptive antennas and CDMA code pooling in the TD CDMA downlink
(2002)

TD (Time Division)-CDMA is one of the partial standards adopted by 3GPP (3rd Generation Partnership Project) for 3rd Generation (3G) mobile radio systems. An important issue when designing 3G mobile radio systems is the efficient use of the available frequency spectrum, that is the achievement of a spectrum efficiency as high as possible. It is well known that the spectrum efficiency can be enhanced by utilizing multi-element antennas instead of single-element antennas at the base station (BS). Concerning the uplink of TD- CDMA, the benefits achievable by multi-element BS antennas have been quantitatively studied to a satisfactory extent. However, corresponding studies for the downlink are still missing. This thesis has the goal to make contributions to fill this lack of information. For near-to-reality directional mobile radio scenarios TD-CDMA downlink utilizing multi-element antennas at the BS are investigated both on the system level and on the link level. The system level investigations show how the carrier-to-interference ratio can be improved by applying such antennas. As the result of the link level investigations, which rely on the detection scheme Joint Detection (JD), the improvement of the bit er- ror rate by utilizing multi-element antennas at the BS can be quantified. Concerning the link level of TD-CDMA, a number of improvements are proposed which allow considerable performance enhancement of TD-CDMA downlink in connection with multi-element BS antennas. These improvements include * the concept of partial joint detection (PJD), in which at each mobile station (MS) only a subset of the arriving CDMA signals including those being of interest to this MS are jointly detected, * a blind channel estimation algorithm, * CDMA code pooling, that is assigning more than one CDMA code to certain con- nections in order to offer these users higher data rates, * maximizing the Shannon transmission capacity by an interleaving concept termed CDMA code interleaving and by advantageously selecting the assignment of CDMA codes to mobile radio channels, * specific power control schemes, which tackle the problem of different transmission qualities of the CDMA codes. As a comprehensive illustration of the advantages achievable by multi-element BS anten- nas in the TD-CDMA downlink, quantitative results concerning the spectrum efficiency for different numbers of antenna elements at the BS conclude the thesis.

thesis deals with the investigation of the dynamics of optically excited (hot) electrons in thin and ultra-thin layers. The main interests concern about the time behaviour of the dissipation of energy and momentum of the excited electrons. The relevant relaxation times occur in the femtosecond time region. The two-photon photoemission is known to be an adequate tool in order to analyse such dynamical processes in real-time. This work expands the knowledge in the fields of electron relaxation in ultra-thin silver layers on different substrates, as well as in adsorbate states in a bandgap of a semiconductor. It contributes facts to the comprehension of spin transport through an interface between a metal and a semiconductor. The primary goal was to prove the predicted theory by reducing the observed crystal in at least one direction. One expects a change of the electron relaxation behaviour while altering the crystal’s shape from a 3d bulk to a 2d (ultra-thin) layer. This is due to the fact that below a determined layer thickness, the electron gas transfers to a two-dimensional one. This behaviour could be proven in this work. In an about 3nm thin silver layer on graphite, the hot electrons show a jump to longer relaxation time all over the whole accessible energy range. It is the first time that the temporal evolution of the relaxation of excited electrons could be observed during the transition from a 3d to a 2d system. In order to reduce or even eliminate the influence coming from the substrate, the system of silver on the semiconductor GaAs, which has a bandgap of 1.5eV at the Gamma-point, was investigated. The observations of the relaxation behaviour of hot electron in different ultra-thin silver layers on this semiconductor could show, that at metal-insulator-junctions, plasmons in the silver and in the interface, as well as cascading electrons from higher lying energies, have a huge influence to the dissipation of momentum and energy. This comes mainly from the band bending of the semiconductor, and from the electrons, which are excited in GaAs. The limitation of the silver layer on GaAs in one direction led to the expected generation of quantum well states (QWS) in the bandgap. Those adsorbate states have quantised energy- and momentum values, which are directly connected to the layer thickness and the standing electron wave therein. With the experiments of this work, published values could not only be completed and proved, but it could also be determined the time evolution of such a QWS. It came out that this QWS might only be filled by electrons, which are moving from the lower edge of the conduction band of the semiconductor to the silver and suffer cascading steps there. By means of the system silver on GaAs, and of the known fact that an excitation of electrons in GaAs with circularly polarised light of the energy 1.5eV does produce spin polarised electrons in the conduction band, it became possible to bring a contribution to the hot topic of spin injection. The main target of spin injection is the transfer of spin polarised electrons out of a ferromagnet into a semiconductor, in order to develop spin dependent switches and memories. It could be demonstrated here that spin polarised electrons from GaAs can move through the interface into silver, could be photoemitted from there and their spin was still being detectable. As a third investigation system, ultra-thin silver layers were deposited on the insulator MgO, which has a bandgap of 7.8eV. Also in this system, one could recognize a change in the relaxation time while reducing the dimension of the silver layer from thick to ultra-thin. Additionally, it came out an extreme large relaxation time at a layer thickness of 0.6 – 1.2nm. This time is an order of magnitude longer than at thick films, and this is a consequence of two factors: first, the reduction of the phase space due to the confined electron gas in the z-direction, and second, the slowlier thermalisation of the electron gas due to less accessible scattering partners.

Lung cancer, mainly caused by tobacco smoke, is the leading cause of cancer mortality. Large efforts in prevention and cessation have reduced smoking rates in the U.S. and other countries. Nevertheless, since 1990, rates have remained constant and it is believed that most of those currently smoking (~25%) are addicted to nicotine, and therefore are unable to stop smoking. An alternative strategy to reduce lung cancer mortality is the development of chemopreventive mixtures used to reduce cancer risk. Before entering clinical trails, it is crucial to know the efficacy, toxicity and the molecular mechanism by which the active compounds prevent carcinogenesis. 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), N-nitrosonornicotine (NNN) and benzo[a]pyrene (B[a]P) are among the most carcinogenic compounds in tobacco smoke. All have been widely used as model carcinogens and their tumorigenic activities are well established. It is believed that formation of DNA adducts is a crucial step in carcinogenesis. NNK and NNN form 4-hydroxy-1-(3-pyridyl)-1-butanone releasing and methylating adducts, while B[a]P forms B[a]P-tetraol-releasing adducts. Different isothiocyanates (ITCs) are able to prevent NNK-, NNN- or B[a]P-induced tumor formation, but relative little is know about the mechanism of these preventive effects. In this thesis, the influence of different ITCs on adduct formation from NNK plus B[a]P and NNN were evaluated. Using an A/J mouse lung tumor model, it was first shown that the formation of HPB-releasing, O6-mG and B[a]P-tetraol-releasing adducts were not affected when NNK and B[a]P were given individually or in combination, of by gavage. Using the same model, the effects of different mixtures of PEITC and BITC, given by gavage or in the diet, on DNA adduct formation were evaluated. Dietary treatment with phenethyl isothiocyanate (PEITC) or PEITC plus benzyl isothiocyanate (BITC) reduced levels of HPB-releasing adducts by 40*50%. This is consistent with a previously shown 40% inhibition of tumor multiplicity for the same treatment. In the gavage treatments with ITCs it seemed that PEITC reduced HPB-releasing DNA adducts, while levels of BITC counteracted these effects. Levels of O6-mG were minimally affected by any of the treatments. Levels of B[a]P-tetraol releasing adducts were reduced by gavaged PEITC Summary Page XII and BITC, 120 h after the last carcinogen treatment, while dietary treatment had no effects. We then extended our investigation to F-344 rats by using a similar ITC treatment protocol as in the mouse model. NNK was given in the drinking water and B[a]P in diet. Dietary PEITC reduced the formation of HPB-releasing globin and DNA adducts in lung but not in liver, while levels of B[a]P-tetraol-releasing adducts were unaffected. Additionally, the effects of PEITC, 3-phenlypropyl isothiocyanate, and their N-acetylcystein conjugates in diet on adducts from NNN in drinking water were evaluated in rat esophageal DNA and globin. Using a protocol known to inhibit NNNinduced esophageal tumorigenesis, the levels of HPB-releasing adduct levels were unaffected by the ITCs treatment. The observations that dietary PEITC inhibited the formation of HPB-releasing DNA adducts only in mice where the control levels were above 1 fmol/µg DNA and adduct levels in rat lung were reduced to levels seen in liver, lead to the conclusion that in mice and rats, there are at least two activation pathway of NNK. One is PEITC-sensitive and responsible for the high adduct levels in lung and presumably also for higher carcinogenicity of NNK in lung. The other is PEITC-insensitive and responsible for the remaining adduct levels and tumorigenicity. In conclusion, our results demonstrated that the preventive mechanism by which ITCs inhibit carcinogenesis is only in part due to inhibition of DNA adduct formation and that other mechanisms are involved. There is a large body of evidence indicating that induction of apoptosis may be a mechanism by which ITCs prevent tumor formation, but further studies are required.

In the present work, we investigated how to correct the questionable normality, linear and quadratic assumptions underlying existing Value-at-Risk methodologies. In order to take also into account the skewness, the heavy tailedness and the stochastic feature of the volatility of the market values of financial instruments, the constant volatility hypothesis widely used by existing Value-at-Risk appproches has also been investigated and corrected and the tails of the financial returns distributions have been handled via Generalized Pareto or Extreme Value Distributions. Artificial Neural Networks have been combined by Extreme Value Theory in order to build consistent and nonparametric Value-at-Risk measures without the need to make any of the questionable assumption specified above. For that, either autoregressive models (AR-GARCH) have been used or the direct characterization of conditional quantiles due to Bassett, Koenker [1978] and Smith [1987]. In order to build consistent and nonparametric Value-at-Risk estimates, we have proved some new results extending White Artificial Neural Network denseness results to unbounded random variables and provide a generalisation of the Bernstein inequality, which is needed to establish the consistency of our new Value-at-Risk estimates. For an accurate estimation of the quantile of the unexpected returns, Generalized Pareto and Extreme Value Distributions have been used. The new Artificial Neural Networks denseness results enable to build consistent, asymptotically normal and nonparametric estimates of conditional means and stochastic volatilities. The denseness results uses the Sobolev metric space L^m (my) for some m >= 1 and some probability measure my and which holds for a certain subclass of square integrable functions. The Fourier transform, the new extension of the Bernstein inequality for unbounded random variables from stationary alpha-mixing processes combined with the new generalization of a result of White and Wooldrige [1990] have been the main tool to establich the extension of White's neural network denseness results. To illustrate the goodness and level of accuracy of the new denseness results, we were able to demonstrate the applicability of the new Value-at-Risk approaches by means of three examples with real financial data mainly from the banking sector traded on the Frankfort Stock Exchange.

The development of recombinant DNA techniques opened a new era for protein production both in scientific research and industrial application. However, the purification of recombinant proteins is very often quite difficult and inefficient. Therefore, we tried to employ novel techniques for the expression and purification of three pharmacologically interesting proteins: the plant toxin gelonin; a fusion protein of gelonin and the extracellular domain of the subunit of the acetylcholine receptor (gelonin-AchR) and human neurotrophin 3 (hNT3). Recombinant gelonin, acetylcholine receptor a subunit and their fusion product, gelonin-AchR were constructed and expressed. The gelonin gene, a 753 bp polynucleotide was chemically synthesized by Ya-Wei Shi et al. and was kindly provided to us. The gene was first inserted into the vector pUC118 yielding pUC-gel. It was subsequently transferred into pET28a and pET-gel was expressed in E. coli. The product, gelonin was soluble and was purified in two steps showing a homogeneous band corresponding to 28 kD on SDS-PAGE. The expression of the extracellular domain of the -subunit of AchR always led to insoluble aggregates and even upon coexpression with the chaperonin GroESL, very small and hardly reproducible amounts of soluble material were formed, only. Therefore, recombinant AchR- gelonin was cloned and expressed in the same host. The corresponding fusion protein, gelonin-AchR, again formed aggregates and it had to be solubilized in 6 M Gu-HCl for further purification and refolding. The final product, however, was recognized by several monoclonal antibodies directed against the extracellular domain of the -subunit of AchR as well as a polyclonal serum against gelonin. Expression and purification of recombinant hNT3 was achieved by the use of a protein self-splicing system. Based on the reported hNT3 DNA sequence, a 380 bp fragment corresponding to a 14 kD protein was amplified from genomal DNA of human whole blood by PCR. The DNA fragment was cloned into the pTXB1 vector, which contains a DNA fragment of intein and chintin binding domain (CBD). A further construct, pJLA-hNT3, is temperature-inducible. Both constructs expressed the target protein, hNT3-intein-CBD in E. coli by the induction with IPTG or temperature, however, as aggregates. After denaturation and renaturation, the soluble fusion protein was slowly loaded on an affinity column of chitin beads. A 14 kD hNT3 could be isolated after cleavage with DTT either at 4 °C or 25 °C for 48 h. Based on nerve fiber out-growth of the dorsal root ganglia of chicken embryos, both, hNT-3-intein-CBD and hNT3 itself exhibit almost the same biological activity.

Matrix Compression Methods for the Numerical Solution of Radiative Transfer in Scattering Media
(2002)

Radiative transfer in scattering media is usually described by the radiative transfer equation, an integro-differential equation which describes the propagation of the radiative intensity along a ray. The high dimensionality of the equation leads to a very large number of unknowns when discretizing the equation. This is the major difficulty in its numerical solution. In case of isotropic scattering and diffuse boundaries, the radiative transfer equation can be reformulated into a system of integral equations of the second kind, where the position is the only independent variable. By employing the so-called momentum equation, we derive an integral equation, which is also valid in case of linear anisotropic scattering. This equation is very similar to the equation for the isotropic case: no additional unknowns are introduced and the integral operators involved have very similar mapping properties. The discretization of an integral operator leads to a full matrix. Therefore, due to the large dimension of the matrix in practical applcation, it is not feasible to assemble and store the entire matrix. The so-called matrix compression methods circumvent the assembly of the matrix. Instead, the matrix-vector multiplications needed by iterative solvers are performed only approximately, thus, reducing, the computational complexity tremendously. The kernels of the integral equation describing the radiative transfer are very similar to the kernels of the integral equations occuring in the boundary element method. Therefore, with only slight modifications, the matrix compression methods, developed for the latter are readily applicable to the former. As apposed to the boundary element method, the integral kernels for radiative transfer in absorbing and scattering media involve an exponential decay term. We examine how this decay influences the efficiency of the matrix compression methods. Further, a comparison with the discrete ordinate method shows that discretizing the integral equation may lead to reductions in CPU time and to an improved accuracy especially in case of small absorption and scattering coefficients or if local sources are present.