Abstract:
We generated arrays of silver wires with a height of one atom and an average width of 11 atoms on the Si(557) surface via self assembly with local $\sqrt{3}\times\sqrt{3}$ order, and investigated the 1D plasmon formation in them using a combination of high resolution electron loss spectroscopy with low energy electron diffraction. As it turned out by a series of thermal desorption experiments followed by adding small concentrations of Ag, pure Ag-$\sqrt{3}$ ordered arrays of nanowires, separated by (113) facets, are intrinsically semi-metallic or semiconducting. Added Ag atoms in the range up to few percent of a monolayer result in 1D plasmon formation without any concentration threshold. The quantitative Ag concentration dependence of the plasmonic losses is clearly non-linear and fully compatible with a $\sqrt{n_e}$ dependence of the 1D plasmon. Adsorption of traces of residual gas can have a qualitatively similar doping effect.

Abstract:
This thesis discusses the phenomenological parton recombination approach to describe hadronization in heavy ion collisions. The very good agreement to RHIC data for the flow coefficients v_2 and v_4 is shown and extrapolations are used to make predictions for the LHC.

Abstract:
Almost every monocrystalline silicon solar cell design includes a wet chemical process step for the alkaline texturing of the wafer surface in order to reduce the reflection of the front side. The alkaline texturing solution contains hydroxide, an organic additive usually 2-propanol and as a reaction product silicate. The hydroxide is consumed due to the reaction whereas 2-propanol evaporates during the process. Therefore, the correct replenishment for both components is required in order to achieve constant processing conditions. This may be simplified by using analytical methods for controlling the main components of the alkaline bath. This study gives an overview for a successful analytical method of the main components of an alkaline texturing bath by titration, HPLC, surface tension and NIR spectrometry.

Abstract:
A recent study from Deng et al at the University of G？teborg in Sweden provides new insight into a previously overlooked potential etiologic factor in septic arthritis [3]. These investigators showed that the mere introduction of bacterial DNA into the knee joints of mice triggered rapid and severe inflammatory arthritis with an influx of monocytes and the production of intra-articular tumor necrosis factor-α. Joint damage was independent of B or T cells, suggesting that it involved instead the activation of the more evolutionarily primitive innate immune system.At first glance, it may seem quite surprising that highly purified bacterial DNA could trigger such profound immune effects in the absence of infection, especially since injection of vertebrate DNA into the joints had no pro-inflammatory activity. However, in recent years it has become clear that DNA serves not just as the genetic material for encoding genes, but also can have direct immunostimulatory effects (reviewed in [4]). In vertebrate DNA, the combination of bases in which a cytosine is followed by a guanine, termed a CpG dinucleotide (the 'p' refers to the phosphate bond linking the C and the G), occurs less frequently than would be predicted assuming a random combination of all possible bases in the genome. Moreover, when CpGs occur in vertebrate genomes, the C is almost always modified by the addition of a methyl cap. In contrast, bacterial DNA generally has the expected frequency of CpG dinucleotides that are not methylated. This subtle structural difference in the DNA of vertebrates and bacterial pathogens is apparently used by our immune system as a 'danger signal' indicating the presence of infection. Indeed, recent studies showed that immune recognition of this elegantly simple unmethylated 'CpG motif' has evolved as a relatively simple way for the immune system to detect the presence of bacteria or other pathogens without necessarily recognising the identity of the specific pathogen [5]. CpG

Abstract:
Long-term synaptic plasticity is fundamental to learning and network function. It has been studied under various induction protocols and depends on firing rates, membrane voltage, and precise timing of action potentials. These protocols show different facets of a common underlying mechanism but they are mostly modeled as distinct phenomena. Here, we show that all of these different dependencies can be explained from a single computational principle. The objective is a sparse distribution of excitatory synaptic strength, which may help to reduce metabolic costs associated with synaptic transmission. Based on this objective we derive a stochastic gradient ascent learning rule which is of differential-Hebbian type. It is formulated in biophysical quantities and can be related to current mechanistic theories of synaptic plasticity. The learning rule accounts for experimental findings from all major induction protocols and explains a classic phenomenon of metaplasticity. Furthermore, our model predicts the existence of metaplasticity for spike-timing-dependent plasticity Thus, we provide a theory of long-term synaptic plasticity that unifies different induction protocols and provides a connection between functional and mechanistic levels of description.

Abstract:
We apply the parton recombination approach to study the energy dependence of the elliptic flow, v_2 in heavy ion collisions from AGS to LHC energies. The relevant input quantities ($T, \mu_B, \eta_T$) at the various center of mass energies are obtained from fits to the available data. The model yields a good description of the integrated v_2 data for charged particles at midrapidity from AGS to RHIC energies. In stark contrast to the current expectations, we observe a decrease of the integrated v_2 values above the highest RHIC energy. Thus, we predict a decrease of v_2 at LHC energies compared to the RHIC results. This drop is attributed to negative v_2 values for the underlying parton distributions at low to moderate transverse momenta that develops if the transverse flow velocity is high enough. At energies above the LHC regime, the present approach predicts even negative values for the integrated v_2.

Abstract:
We discuss one of the most prominent features of the very recent preliminary elliptic flow data of $J/\Psi$ meson from the PHENIX collaboration \cite{Silvestre:2008tw}. Even within the the rather large error bars of the measured data a negative elliptic flow parameter ($v_2$) for $J/\Psi$ in the range of $p_T=0.5-2.5 \GeV/c$ is visible. We argue that this negative elliptic flow at intermediate $p_T$ is a clear and qualitative signature for the collectivity of charm quarks produced in nucleus-nucleus reactions at RHIC. Within a parton recombination approach we show that a negative elliptic flow puts a lower limit on the collective transverse velocity of heavy quarks. The numerical value of the transverse flow velocity $\beta_T$ for charm quarks that is necessary to reproduce the data is $\beta_T(charm)\sim 0.55-0.6c$ and therefore compatible with the flow of light quarks.

Abstract:
We prove the functional equation for the twisted spinor L-series of a cuspidal, holomorphic Siegel eigenform for the full modular group of genus 2. It follows from a more general functional equation, valid for Rankin convolutions of paramodular cuspforms. A non-vanishing result for Fourier-Jacabi coefficients of the eigenforms in question is the central pillar of the deduction of the former from the latter functional equation.

Abstract:
Circle packings with specified patterns of tangencies form a discrete counterpart of analytic functions. In this paper we study univalent packings (with a combinatorial closed disk as tangent graph) which are embedded in (or fill) a bounded, simply connected domain. We introduce the concept of crosscuts and investigate the rigidity of circle packings with respect to maximal crosscuts. The main result is a discrete version of an indentity theorem for analytic functions (in the spirit of Schwarz' Lemma), which has implications to uniqueness statements for discrete conformal mappings.