Analysis Of Nociceptive Evoked Potentials During Multi-Stimulus Experiments Using Linear Mixed Models

Neural processing of sensory stimuli can be studied using EEG by estimation of the evoked potential using the averages of large sets of trials. However, it is not always possible to include all stimulus parameters in a conventional analysis, since this would lead to an insufficient amount of trials to obtain the evoked potential by averaging. Linear mixed models use dependencies within the data to combine information from all data for the estimation of the evoked potential. In this work, it is shown that in multi-stimulus EEG data the quality of an evoked potential estimate can be improved by using a linear mixed model. Furthermore, the linear mixed model effectively deals with correlation between parameters in the data and reveals the influence of individual stimulus parameters

Ground-state properties of tubelike flexible polymers

In this work we investigate structural properties of native states of a simple model for short flexible homopolymers, where the steric influence of monomeric side chains is effectively introduced by a thickness constraint. This geometric constraint is implemented through the concept of the global radius of curvature and affects the conformational topology of ground-state structures. A systematic analysis allows for a thickness-dependent classification of the dominant ground-state topologies. It turns out that helical structures, strands, rings, and coils are natural, intrinsic geometries of such tubelike objects

Back-flow ripples in troughs downstream of unit bars: Formation, preservation and value for interpreting flow conditions

Back-flow ripples are bedforms created within the lee-side eddy of a larger bedform with migration directions opposed or oblique to that of the host bedform. In the flume experiments described in this article, back-flow ripples formed in the trough downstream of a unit bar and changed with mean flow velocity; varying from small incipient back-flow ripples at low velocities, to well-formed back-flow ripples with greater velocity, to rapidly migrating transient back-flow ripples formed at the greatest velocities tested. In these experiments back-flow ripples formed at much lower mean back-flow velocities than predicted from previously published descriptions. This lower threshold mean back-flow velocity is attributed to the pattern of velocity variation within the lee-side eddy of the host bedform. The back-flow velocity variations are attributed to vortex shedding from the separation zone, wake flapping and increases in the size of, and turbulent intensity within, the flow separation eddy controlled by the passage of superimposed bedforms approaching the crest of the bar. Short duration high velocity packets, whatever their cause, may form back-flow ripples if they exceed the minimum bed shear stress for ripple generation for long enough or, if much faster, may wash them out. Variation in back-flow ripple cross-lamination has been observed in the rock record and, by comparison with flume observations, the preserved back-flow ripple morphology may be useful for interpreting formative flow and sediment transport dynamics

On the detectability of the CMSSM light Higgs boson at the Tevatron

We examine the prospects of detecting the light Higgs h^0 of the Constrained MSSM at the Tevatron. To this end we explore the CMSSM parameter space with \mu>0, using a Markov Chain Monte Carlo technique, and apply all relevant collider and cosmological constraints including their uncertainties, as well as those of the Standard Model parameters. Taking 50 GeV < m_{1/2}, m_0 < 4 TeV, |A_0| < 7 TeV and 2 < tan(beta) < 62 as flat priors and using the formalism of Bayesian statistics we find that the 68% posterior probability region for the h^0 mass lies between 115.4 GeV and 120.4 GeV. Otherwise, h^0 is very similar to the Standard Model Higgs boson. Nevertheless, we point out some enhancements in its couplings to bottom and tau pairs, ranging from a few per cent in most of the CMSSM parameter space, up to several per cent in the favored region of tan(beta)\sim 50 and the pseudoscalar Higgs mass of m_A\lsim 1 TeV. We also find that the other Higgs bosons are typically heavier, although not necessarily much heavier. For values of the h^0 mass within the 95% probability range as determined by our analysis, a 95% CL exclusion limit can be set with about 2/fb of integrated luminosity per experiment, or else with 4/fb (12/fb) a 3 sigma evidence (5 sigma discovery) will be guaranteed. We also emphasize that the alternative statistical measure of the mean quality-of-fit favors a somewhat lower Higgs mass range; this implies even more optimistic prospects for the CMSSM light Higgs search than the more conservative Bayesian approach. In conclusion, for the above CMSSM parameter ranges, especially m_0, either some evidence will be found at the Tevatron for the light Higgs boson or, at a high confidence level, the CMSSM will be ruled out.Comment: JHEP versio

Minimizing the stabbing number of matchings, trees, and triangulations

The (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. This paper deals with finding perfect matchings, spanning trees, or triangulations of minimum stabbing number for a given set of points. The complexity of these problems has been a long-standing open question; in fact, it is one of the original 30 outstanding open problems in computational geometry on the list by Demaine, Mitchell, and O'Rourke. The answer we provide is negative for a number of minimum stabbing problems by showing them NP-hard by means of a general proof technique. It implies non-trivial lower bounds on the approximability. On the positive side we propose a cut-based integer programming formulation for minimizing the stabbing number of matchings and spanning trees. We obtain lower bounds (in polynomial time) from the corresponding linear programming relaxations, and show that an optimal fractional solution always contains an edge of at least constant weight. This result constitutes a crucial step towards a constant-factor approximation via an iterated rounding scheme. In computational experiments we demonstrate that our approach allows for actually solving problems with up to several hundred points optimally or near-optimally.Comment: 25 pages, 12 figures, Latex. To appear in "Discrete and Computational Geometry". Previous version (extended abstract) appears in SODA 2004, pp. 430-43