(g−2)μ from noncommutative geometry

AbstractThis brief Letter demonstrates that effects from a noncommutative spacetime geometry will measurably affect the value of (g−2)μ inferred from the decay of the muon to an electron plus two neutrinos. If the scale of noncommutativity is O (TeV), the alteration of the V–A structure of the lepton–lepton–W vertex is sufficient to shift the inferred value of (g−2)μ to one part in 108. This may account for the recently reported 2.6σ discrepancy between the BNL measurement aexpt=11659202(14)(6)×10−10 and the Standard Model prediction aSM=11659159.6(6.7)×10−10

A Simple Mass Reconstruction Technique for SUSY particles at the LHC

It is often true that an invariant mass constructed from visible decay products of a heavy particle may attain a maximum(or minimum) for a certain kinematic configuration only -- this fact can be used to reconstruct relevant particle masses from observed decay product momenta of events near the invariant mass endpoint. MSSM neutralino and chargino mass reconstruction at the LHC from multi-lepton endstates is illustrated by way of example.Comment: 14 pages, 5 figures. PRD versio

Beyond 2D-grids: a dependence maximization view on image browsing

Ideally, one would like to perform image search using an intuitive and friendly approach. Many existing image search engines, however, present users with sets of images arranged in some default order on the screen, typically the relevance to a query, only. While this certainly has its advantages, arguably, a more flexible and intuitive way would be to sort images into arbitrary structures such as grids, hierarchies, or spheres so that images that are visually or semantically alike are placed together. This paper focuses on designing such a navigation system for image browsers. This is a challenging task because arbitrary layout structure makes it difficult -- if not impossible -- to compute cross-similarities between images and structure coordinates, the main ingredient of traditional layouting approaches. For this reason, we resort to a recently developed machine learning technique: kernelized sorting. It is a general technique for matching pairs of objects from different domains without requiring cross-domain similarity measures and hence elegantly allows sorting images into arbitrary structures. Moreover, we extend it so that some images can be preselected for instance forming the tip of the hierarchy allowing to subsequently navigate through the search results in the lower levels in an intuitive way

Factors of Influence on the Performance of a Short-Latency Non-Invasive Brain Switch: Evidence in Healthy Individuals and Implication for Motor Function Rehabilitation.

Brain-computer interfacing (BCI) has recently been applied as a rehabilitation approach for patients with motor disorders, such as stroke. In these closed-loop applications, a brain switch detects the motor intention from brain signals, e.g., scalp EEG, and triggers a neuroprosthetic device, either to deliver sensory feedback or to mimic real movements, thus re-establishing the compromised sensory-motor control loop and promoting neural plasticity. In this context, single trial detection of motor intention with short latency is a prerequisite. The performance of the event detection from EEG recordings is mainly determined by three factors: the type of motor imagery (e.g., repetitive, ballistic), the frequency band (or signal modality) used for discrimination (e.g., alpha, beta, gamma, and MRCP, i.e., movement-related cortical potential), and the processing technique (e.g., time-series analysis, sub-band power estimation). In this study, we investigated single trial EEG traces during movement imagination on healthy individuals, and provided a comprehensive analysis of the performance of a short-latency brain switch when varying these three factors. The morphological investigation showed a cross-subject consistency of a prolonged negative phase in MRCP, and a delayed beta rebound in sensory-motor rhythms during repetitive tasks. The detection performance had the greatest accuracy when using ballistic MRCP with time-series analysis. In this case, the true positive rate (TPR) was ~70% for a detection latency of ~200 ms. The results presented here are of practical relevance for designing BCI systems for motor function rehabilitation