Isospin Considerations in Correlations of Pions and BB mesons

The correlations between a $B$ meson and a pion produced nearby in phase space should respect isospin reflection symmetry $I_3 \to -I_3$. Thus, one generally expects similar $\pi^+ B^0$ and $\pi^- B^+$ correlations (non-exotic channels), and similar $\pi^- B^0$ and $\pi^+ B^+$ correlations (exotic channels). Exceptions include (a) fragmentation processes involving exchange of quarks with the producing system, (b) misidentification of charged kaons as charged pions, and (c) effects of decay products of the associated $\overline{B}$. All of these can affect the apparent signal for correlations of charged $B$ mesons with charged hadrons. The identification of the flavor of neutral $B$ mesons through the decay $B^0 \to K^{*0} J/\psi$ requires good particle identification in order that the decay $K^{*0} \to K^+ \pi^-$ not be mistaken for $\overline{K}^{*0} \to K^- \pi^+$, in which case the correlations of neutral $B$ mesons with hadrons can be underestimated.Comment: LaTeX EPSF file; 8 uuencoded figures to be submitted separatel

c ○ 2001 Kluwer Academic Publishers. Manufactured in The Netherlands. Bayesian Object Localisation in Images

Abstract. A Bayesian approach to intensity-based object localisation is presented that employs a learned probabilistic model of image filter-bank output, applied via Monte Carlo methods, to escape the inefficiency of exhaustive search. An adequate probabilistic account of image data requires intensities both in the foreground (i.e. over the object), and in the background, to be modelled. Some previous approaches to object localisation by Monte Carlo methods have used models which, we claim, do not fully address the issue of the statistical independence of image intensities. It is addressed here by applying to each image a bank of filters whose outputs are approximately statistically independent. Distributions of the responses of individual filters, over foreground and background, are learned from training data. These distributions are then used to define a joint distribution for the output of the filter bank, conditioned on object configuration, and this serves as an observation likelihood for use in probabilistic inference about localisation. The effectiveness of probabilistic object localisation in image clutter, using Bayesian Localisation, is illustrated. Because it is a Monte Carlo method, it produces not simply a single estimate of object configuration, but an entire sample from the posterior distribution for the configuration. This makes sequential inference of configuration possible. Two examples are illustrated here: coarse to fine scale inference, and propagation of configuration estimates over time, in image sequences. Keywords: vision, object location, Monte Carlo, filter-bank, statistical independenc

Enhanced CP Violation with B→KD0(D‾0)B\to K D^0 (\overline D^0) Modes and Extraction of the CKM Angle gamma

The Gronau-London-Wyler (GLW) method extracts the CKM angle $\gamma$ by measuring $B^\pm$ decay rates involving $D^0/\overline D^0$ mesons. Since that method necessitates the interference between two amplitudes that are significantly different in magnitude, the resulting asymmetries tend to be small. CP violation can be greatly enhanced for decays to final states that are common to both D^0 and $\overline D^0$ and that are not CP eigenstates. In particular, large asymmetries are possible for final states f such that $D^0\to f$ is doubly Cabibbo suppressed while $\overline D^0\to f$ is Cabibbo allowed. The measurement of interference effects in two such modes allows the extraction of $\gamma$ without prior knowledge of $Br(B^-\to K^- \overline D^0)$, which may be difficult to determine due to backgrounds.Comment: 12 pages, LaTeX, no figure

Adaptative road lanes detection and classification

Proceeding of: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006This paper presents a Road Detection and Classification algorithm for Driver Assistance Systems (DAS), which tracks several road lanes and identifies the type of lane boundaries. The algorithm uses an edge filter to extract the longitudinal road markings to which a straight lane model is fitted. Next, the type of right and left lane boundaries (continuous, broken or merge line) is identified using a Fourier analysis. Adjacent lanes are searched when broken or merge lines are detected. Although the knowledge of the line type is essential for a robust DAS, it has been seldom considered in previous works. This knowledge helps to guide the search for other lanes, and it is the basis to identify the type of road (one-way, two-way or freeway), as well as to tell the difference between allowed and forbidden maneuvers, such as crossing a continuous line.Publicad

Adaptive Feature Selection for Object Tracking with Particle Filter

International audienceObject tracking is an important topic in the field of computer vision. Commonly used color-based trackers are based on a fixed set of color features such as RGB or HSV and, as a result, fail to adapt to changing illumination conditions and background clutter. These drawbacks can be overcome to an extent by using an adaptive framework which selects for each frame of a sequence the features that best discriminate the object from the background. In this paper, we use such an adaptive feature selection method embedded into a particle filter mechanism and show that our tracking method is robust to lighting changes and background distractions. Different experiments also show that the proposed method outperform other approaches

Leaf segmentation and tracking using probabilistic parametric active contours

Active contours or snakes are widely used for segmentation and tracking. These techniques require the minimization of an energy function, which is generally a linear combination of a data fit term and a regularization term. This energy function can be adjusted to exploit the intrinsic object and image features. This can be done by changing the weighting parameters of the data fit and regularization term. There is, however, no rule to set these parameters optimally for a given application. This results in trial and error parameter estimation. In this paper, we propose a new active contour framework defined using probability theory. With this new technique there is no need for ad hoc parameter setting, since it uses probability distributions, which can be learned from a given training dataset

Conformational Free-Energy Landscapes for a Peptide in Saline Environments

AbstractThe conformations that proteins adopt in solution are a function of both their primary structure and surrounding aqueous environment. Recent experimental and computational work on small peptides, e.g., polyK, polyE, and polyR, have highlighted an interesting and unusual behavior in the presence of aqueous ions such as ClO4−, Na+, and K+. Notwithstanding the aforementioned studies, as of this writing, the nature of the driving force induced by the presence of ions and its role on the conformational stability of peptides remains only partially understood. Molecular-dynamics simulations have been performed on the heptapeptide AEAAAEA in NaCl and KCl solutions at concentrations of 0.5, 1.0, and 2.0 M. Metadynamics in conjunction with a three-dimensional model reaction coordinate was used to sample the conformational space of the peptide. All simulations were run for 2 μs. Free-energy landscapes were computed over the model reaction coordinate for the peptide in each saline assay as well as in the absence of ions. Circular dichroism spectra were also calculated from each trajectory. In the presence of Na+ and K+ ions, no increase in helicity is observed with respect to the conformation in pure water

Decay constants of P and D-wave heavy-light mesons

We investigate decay constants of P and D-wave heavy-light mesons within the mock-meson approach. Numerical estimates are obtained using the relativistic quark model. We also comment on recent calculations of heavy-light pseudo-scalar and vector decay constants.Comment: REVTeX, 22 pages, uses epsf macro, 8 postscript figures include

In Pursuit of New Physics with B_s Decays

The presence of a sizeable CP-violating phase in B_s^0-B_s^0-bar mixing would be an unambiguous signal of physics beyond the Standard Model. We analyse various possibilities to detect such a new phase considering both tagged and untagged decays. The effects of a sizeable width difference Delta Gamma between the B_s mass eigenstates, on which the untagged analyses rely, are included in all formulae. A novel method to find this phase from simple measurements of lifetimes and branching ratios in untagged decays is proposed. This method does not involve two-exponential fits, which require much larger statistics. For the tagged decays, an outstanding role is played by the observables of the time-dependent angular distribution of the B_s -> J/psi [-> l^+ l^-] \phi [-> K^+K^-] decay products. We list the formulae needed for the angular analysis in the presence of both a new CP-violating phase and a sizeable Delta Gamma, and propose methods to remove a remaining discrete ambiguity in the new phase. This phase can therefore be determined in an unambiguous way.Comment: minor changes, lattice prediction of Delta Gamma updated, appears in PR