SM Higgs mass bounds from theory

The two-loop Higgs mass upper bounds are reanalyzed. Previous results for a cutoff scale $\Lambda\approx$ few TeV are found to be too stringent. For $\Lambda=10^{19}$ GeV we find $M_H < 180 \pm 4\pm 5$ GeV, the first error indicating the theoretical uncertainty, the second error reflecting the experimental uncertainty due to $m_t = 175 \pm 6$ GeV. We also summarize the lower bounds on $M_H$. We find that a SM Higgs mass in the range of 160 to 170 GeV will certainly allow for a perturbative and well-behaved SM up to the Planck-mass scale $\Lambda_{Pl}\simeq 10^{19}$ GeV, with no need for new physics to set in below this scale.Comment: 6 pages; to appear in the Proceedings of the ``ECFA/DESY Study on Physics and Detectors for the Linear Collider'', ed. R. Settle

Implications of probabilistic data modeling for rule mining

Mining association rules is an important technique for discovering meaningful patterns in transaction databases. In the current literature, the properties of algorithms to mine associations are discussed in great detail. In this paper we investigate properties of transaction data sets from a probabilistic point of view. We present a simple probabilistic framework for transaction data and its implementation using the R statistical computing environment. The framework can be used to simulate transaction data when no associations are present. We use such data to explore the ability to filter noise of confidence and lift, two popular interest measures used for rule mining. Based on the framework we develop the measure hyperlift and we compare this new measure to lift using simulated data and a real-world grocery database.Series: Research Report Series / Department of Statistics and Mathematic

Importance driven environment map sampling

In this paper we present an automatic and efficient method for supporting Image Based Lighting (IBL) for bidirectional methods which improves both the sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves this by taking into account view importance, and modifies the lighting distribution to use light transport information. This also automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling. Results are presented when our method is applied to bidirectional rendering techniques, in particular we show results for Bidirectional Path Tracing, Metropolis Light Transport and Progressive Photon Mapping. Efficiency results demonstrate speed up of orders of magnitude (depending on the rendering method used), when compared to other methods

A near-field study on the transition from localized to propagating plasmons on 2D nano-wedges

In this manuscript we report on a near-feld study of two-dimensional plasmonic gold nano-wedges using electron energy loss spectroscopy in combination with scanning transmission electron microscopy, as well as discontinuous Galerkin time-domain computations. With increasing nano-wedge size, we observe a transition from localized surface plasmons on small nano-wedges to non-resonant propagating surface plasmon polaritons on large nano-wedges. Furthermore we demonstrate that nano-wedges with a groove cut can support localized as well as propagating plasmons in the same energy range

Exploring the Architecture of the Human GABA(A) Receptor Ligand Binding Pocket via Mutational, Electrophysiological, and Kinetic Analysis

The gamma-aminobutyric acid type A (GABAA) receptor is a member of the cys-loop family of ligand-gated ion channels, and plays a crucial role in normal brain function by providing inhibitory neurotransmission. The objective of my research is to establish the mechanisms that underlie the interaction between the GABAA receptor and GABA during binding, as well as to provide direct information about the architecture of the ligand binding pocket. To achieve this, a multitude of amino acid residues surrounding the GABA binding pocket were individually mutated and structure-function relationships were explored. Changes in EC50-GABA, macroscopic kinetics, GABA binding rates and GABA unbinding rates were assessed using patch-clamp recording, rapid-ligand application, and kinetic modeling techniques. A state-dependent interaction bridging the β/α inter-subunit interface was identified between α1R120 and β2D163 by characterizing GABA binding and unbinding rates for alanine mutations at each residue. These results were subjected to double-mutant cycle analysis. Intriguingly, the residues appear to be completely independent when considering the binding of GABA, but they are coupled when looking at the unbinding of GABA. These results suggest that β2D163 and α1R120 do not interact in the unbound state but form an interaction upon binding of GABA. A role for β2F200 at the GABA binding site was also revealed. Mutation of β2F200 to alanine caused a dramatic reduction in GABA affinity. This was the result of both an increase in the rate of GABA unbinding and a decrease in the GABA binding rate. β2F200 fits the profile of a residue that could directly interact with GABA. Finally, three mutations of the β2 subunit (Y97A, Y157A, and D163A) have interesting effects on the functional expression of receptors. Mutation of these residues allowed the assembly of functional receptors when expressed with α1 and γ2, but not when expressed with α1 only. The aligned residues on the γ2 subunit were also mutated and found to have unique expression patterns. Each of the residues appears to be required for the assembly of the β(+)/β(-) interface, which is only present in αβ receptors; however, only the residue homologous to β2Y97 (γ2F112) is critical for assembly at the γ/β interface

P4CEP: Towards In-Network Complex Event Processing

In-network computing using programmable networking hardware is a strong trend in networking that promises to reduce latency and consumption of server resources through offloading to network elements (programmable switches and smart NICs). In particular, the data plane programming language P4 together with powerful P4 networking hardware has spawned projects offloading services into the network, e.g., consensus services or caching services. In this paper, we present a novel case for in-network computing, namely, Complex Event Processing (CEP). CEP processes streams of basic events, e.g., stemming from networked sensors, into meaningful complex events. Traditionally, CEP processing has been performed on servers or overlay networks. However, we argue in this paper that CEP is a good candidate for in-network computing along the communication path avoiding detouring streams to distant servers to minimize communication latency while also exploiting processing capabilities of novel networking hardware. We show that it is feasible to express CEP operations in P4 and also present a tool to compile CEP operations, formulated in our P4CEP rule specification language, to P4 code. Moreover, we identify challenges and problems that we have encountered to show future research directions for implementing full-fledged in-network CEP systems.Comment: 6 pages. Author's versio

Multi-party privacy risks in social networks

As the popularity of social networks expands, the information users expose to the public has potentially dangerous implications for individual privacy. While social networks allow users to restrict access to their personal data, there is currently no mechanism to enforce privacy concerns over content uploaded by other users. As group photos and stories are shared by friends and family, personal privacy goes beyond the discretion of what a user uploads about himself and becomes an issue of what every network participant reveals. In this paper, we examine how the lack of joint privacy controls over content can inadvertently reveal sensitive information about a user including preferences, relationships, conversations, and photos. Specifically, we analyze Facebook to identify scenarios where conflicting privacy settings between friends will reveal information that at least one user intended to keep private. By aggregating the information exposed in this manner, we demonstrate how a user's private attributes can be inferred from simply being listed as a friend or mentioned in a story. To mitigate this threat, we show how Facebook's privacy model can be adapted to enforce multi-party privacy. We present a proof of concept application built into Facebook that automatically ensures mutually acceptable privacy restrictions are enforced on group content