On Markovian solutions to Markov Chain BSDEs

We study (backward) stochastic differential equations with noise coming from a finite state Markov chain. We show that, for the solutions of these equations to be `Markovian', in the sense that they are deterministic functions of the state of the underlying chain, the integrand must be of a specific form. This allows us to connect these equations to coupled systems of ODEs, and hence to give fast numerical methods for the evaluation of Markov-Chain BSDEs

Mutiprocessor Adaptation of a Texture Segmentation Scheme for Satellite Radar Images

This paper presents a scheme for segmenting images on the basis of differences in localised measures of spatial texture. The scheme used was originally proposed by Wilson and Spann [1] but incorporates a new clustering algorithm which gives improved overall segmentation performance. The Wilson and Spann [1] algorithm uses a clustering algorithm which proved susceptible to initial input parameters and gave poor segmentation on our images. Our algorithm uses a modification of the Koontz, Narendra and Fukunaga [2] clustering algorithm. By linking the clustering to the resolution of the image, significant clusters were able to be realised, yielding a more robust segmentation scheme. The adaptation also resulted in a significant reduction in run-time. The paper is directed towards the problem of segmenting satellite synthetic aperture radar (SAR) images and we give comparisons of the techniques on SAR and other images

Texture Classification Using Nonparametric Random Fields

We present a nonparametric Markov Random Field model for classifying texture images. This model can capture the characteristics of a wide variety of textures, varying from the highly structured to the stochastic. The power of our modelling technique is evident in that only a small training image is required, even when the training texture contains long range characteristics. We show how this model can be used for unsupervised segmentation and classification of images containing textures for which we have no prior knowledge of the constituent texture types. This technique can therefore be used to find a specific texture in a background of unknown textures

Classification Of Cervical Cell Nuclei Using Morphological Segmentation And Texture Feature Extraction

This paper presents preliminary results for the classification of Pap smear cell nuclei, using Gray Level Co-occurrence Matrix (GLCM) textual features. We outline a method of nuclear segmentation using fast morphological gray-scale transforms. For each segmented nucleus, features derived from a modified form of the GLCM are extracted over several angle and distance measures. Linear Discriminant Analysis is preformed on these features to reduce the dimensionality of the feature space, and a classifier with hyper quadric decision surface is implemented to classify a small set of normal and abnormal cell nuclei. Using 2 features, we achieve a misclassification rate of 3.3% on a data set of 61 cells

Functional cyclophilin D moderates platelet adhesion, but enhances the lytic resistance of fibrin

In the course of thrombosis, platelets are exposed to a variety of activating stimuli classified as ‘strong’ (e.g. thrombin and collagen) or ‘mild’ (e.g. ADP). In response, activated platelets adhere to injured vasculature, aggregate, and stabilise the three-dimensional fibrin scaffold of the expanding thrombus. Since ‘strong’ stimuli also induce opening of the mitochondrial permeability transition pore (MPTP) in platelets, the MPTP-enhancer Cyclophilin D (CypD) has been suggested as a critical pharmacological target to influence thrombosis. However, it is poorly understood what role CypD plays in the platelet response to ‘mild’ stimuli which act independently of MPTP. Furthermore, it is unknown how CypD influences platelet-driven clot stabilisation against enzymatic breakdown (fibrinolysis). Here we show that treatment of human platelets with Cyclosporine A (a cyclophilin-inhibitor) boosts ADP-induced adhesion and aggregation, while genetic ablation of CypD in murine platelets enhances adhesion but not aggregation. We also report that platelets lacking CypD preserve their integrity in a fibrin environment, and lose their ability to render clots resistant against fibrinolysis. Our results indicate that CypD has opposing haemostatic roles depending on the stimulus and stage of platelet activation, warranting a careful design of any antithrombotic strategy targeting CypD

Precision luminosity measurements at LHCb

Measuring cross-sections at the LHC requires the luminosity to be determined accurately at each centre-of-mass energy √s. In this paper results are reported from the luminosity calibrations carried out at the LHC interaction point 8 with the LHCb detector for √s = 2.76, 7 and 8 TeV (proton-proton collisions) and for √sNN = 5 TeV (proton-lead collisions). Both the "van der Meer scan" and "beam-gas imaging" luminosity calibration methods were employed. It is observed that the beam density profile cannot always be described by a function that is factorizable in the two transverse coordinates. The introduction of a two-dimensional description of the beams improves significantly the consistency of the results. For proton-proton interactions at √s = 8 TeV a relative precision of the luminosity calibration of 1.47% is obtained using van der Meer scans and 1.43% using beam-gas imaging, resulting in a combined precision of 1.12%. Applying the calibration to the full data set determines the luminosity with a precision of 1.16%. This represents the most precise luminosity measurement achieved so far at a bunched-beam hadron collider

Measurement of the CKM angle γ from a combination of B±→Dh± analyses

A combination of three LHCb measurements of the CKM angle γ is presented. The decays B±→D K± and B±→Dπ± are used, where D denotes an admixture of D0 and D0 mesons, decaying into K+K−, π+π−, K±π∓, K±π∓π±π∓, K0Sπ+π−, or K0S K+K− final states. All measurements use a dataset corresponding to 1.0 fb−1 of integrated luminosity. Combining results from B±→D K± decays alone a best-fit value of γ =72.0◦ is found, and confidence intervals are set γ ∈ [56.4,86.7]◦ at 68% CL, γ ∈ [42.6,99.6]◦ at 95% CL. The best-fit value of γ found from a combination of results from B±→Dπ± decays alone, is γ =18.9◦, and the confidence intervals γ ∈ [7.4,99.2]◦ ∪ [167.9,176.4]◦ at 68% CL are set, without constraint at 95% CL. The combination of results from B± → D K± and B± → Dπ± decays gives a best-fit value of γ =72.6◦ and the confidence intervals γ ∈ [55.4,82.3]◦ at 68% CL, γ ∈ [40.2,92.7]◦ at 95% CL are set. All values are expressed modulo 180◦, and are obtained taking into account the effect of D0–D0 mixing

Differential branching fraction and angular analysis of the decay B0→K∗0μ+μ−

The angular distribution and differential branching fraction of the decay B 0→ K ∗0 μ + μ − are studied using a data sample, collected by the LHCb experiment in pp collisions at s√=7 TeV, corresponding to an integrated luminosity of 1.0 fb−1. Several angular observables are measured in bins of the dimuon invariant mass squared, q 2. A first measurement of the zero-crossing point of the forward-backward asymmetry of the dimuon system is also presented. The zero-crossing point is measured to be q20=4.9±0.9GeV2/c4 , where the uncertainty is the sum of statistical and systematic uncertainties. The results are consistent with the Standard Model predictions