Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior information of feature appearances. The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods. SDF also includes two original elements, i.e., a deterministic sampling algorithm and a novel model selection algorithm. The two algorithms are tightly coupled to boost the performance of SDF in both speed and accuracy. Specifically, the proposed sampling algorithm leverages the grouping cues of superpixels to generate reliable and consistent hypotheses. The proposed model selection algorithm further makes use of desirable properties of the generated hypotheses, to improve the conventional fit-and-remove framework for more efficient and effective performance. The key characteristic of SDF is that it can efficiently and deterministically estimate the parameters of model instances in multi-structure data. Experimental results demonstrate that the proposed SDF shows superiority over several state-of-the-art fitting methods for real images with single-structure and multiple-structure data.Comment: Accepted by European Conference on Computer Vision (ECCV

Spontaneous R-Parity Violation, A4A_4 Flavor Symmetry and Tribimaximal Mixing

We explore the possibility of spontaneous R parity violation in the context of $A_4$ flavor symmetry. Our model contains $SU(3)_c \times SU(2)_L \times U(1)_Y$ singlet matter chiral superfields which are arranged as triplet of $A_4$ and as well as few additional Higgs chiral superfields which are singlet under MSSM gauge group and belong to triplet and singlet representation under the $A_4$ flavor symmetry. R parity is broken spontaneously by the vacuum expectation values of the different sneutrino fields and hence we have neutrino-neutralino as well as neutrino-MSSM gauge singlet higgsino mixings in our model, in addition to the standard model neutrino- gauge singlet neutrino, gaugino-higgsino and higgsino-higgsino mixings. Because all of these mixings we have an extended neutral fermion mass matrix. We explore the low energy neutrino mass matrix for our model and point out that with some specific constraints between the sneutrino vacuum expectation values as well as the MSSM gauge singlet Higgs vacuum expectation values, the low energy neutrino mass matrix will lead to a tribimaximal mixing matrix. We also analyze the potential minimization for our model and show that one can realize a higher vacuum expectation value of the $SU(3)_c \times SU(2)_L \times U(1)_Y$ singlet sneutrino fields even when the other sneutrino vacuum expectation values are extremely small or even zero.Comment: 18 page

The Interplay Between GUT and Flavour Symmetries in a Pati-Salam x S4 Model

Both Grand Unified symmetries and discrete flavour symmetries are appealing ways to describe apparent structures in the gauge and flavour sectors of the Standard Model. Both symmetries put constraints on the high energy behaviour of the theory. This can give rise to unexpected interplay when building models that possess both symmetries. We investigate on the possibility to combine a Pati-Salam model with the discrete flavour symmetry $S_4$ that gives rise to quark-lepton complementarity. Under appropriate assumptions at the GUT scale, the model reproduces fermion masses and mixings both in the quark and in the lepton sectors. We show that in particular the Higgs sector and the running Yukawa couplings are strongly affected by the combined constraints of the Grand Unified and family symmetries. This in turn reduces the phenomenologically viable parameter space, with high energy mass scales confined to a small region and some parameters in the neutrino sector slightly unnatural. In the allowed regions, we can reproduce the quark masses and the CKM matrix. In the lepton sector, we reproduce the charged lepton masses, including bottom-tau unification and the Georgi-Jarlskog relation as well as the two known angles of the PMNS matrix. The neutrino mass spectrum can present a normal or an inverse hierarchy, and only allowing the neutrino parameters to spread into a range of values between $\lambda^{-2}$ and $\lambda^2$, with $\lambda\simeq0.2$. Finally, our model suggests that the reactor mixing angle is close to its current experimental bound.Comment: 62 pages, 4 figures; references added, version accepted for publication in JHE

Implications of Recent Data on Neutrino Mixing and Lepton Flavour Violating Decays for the Zee Model

We study implications of recent data on neutrino mixing from T2K, MINOS, Double Chooz and $\mu \to e \gamma$ from MEG for the Zee model. The simplest version of this model has been shown to be ruled out by experimental data some time ago. The general Zee model is still consistent with recent data. We demonstrate this with a constrained Zee model based on naturalness consideration. In this constrained model, only inverted mass hierarchy for neutrino masses is allowed, and $\theta_{13}$ must be non-zero in order to have correct ratio for neutrino mass-squared differences and for mixing in solar and atmospherical neutrino oscillations. The best fit value of our model for $\theta_{13}$ is $8.91\deg$ from T2K and MINOS data, very close to the central value obtained by Double Chooz experiment. There are solutions with non-zero CP violation with the Jarlskog parameter predicted in the range $\pm 0.039$, $\pm 0.044$ and $\pm 0.048$ respectively for a 1$\sigma$, 2$\sigma$ and 3$\sigma$ ranges of other input parameters. However, without any constraint on the $\theta_{13}$-parameter above respective ranges become $\pm 0.049$, $\pm 0.053$ and $\pm 0.056$. We analyse different cases to obtain a branching ratio for $\mu \to e \gamma$ close to the recent MEG bound. We also discuss other radiative as well as the charged trilepton flavour violating decay modes of the $\tau$-lepton.Comment: References added, one extra figure added, typos corrected, few more related phenomenology discussion added/modified; 25 pages, 10 figure

Structural Annotation of Mycobacterium tuberculosis Proteome

Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well

Different SO(10) Paths to Fermion Masses and Mixings

Recently SO(10) models with type-II see-saw dominance have been proposed as a promising framework for obtaining Grand Unification theories with approximate Tri-bimaximal (TB) mixing in the neutrino sector. We make a general study of SO(10) models with type-II see-saw dominance and show that an excellent fit can be obtained for fermion masses and mixings, also including the neutrino sector. To make this statement more significant we compare the performance of type-II see-saw dominance models in fitting the fermion masses and mixings with more conventional models which have no built-in TB mixing in the neutrino sector. For a fair comparison the same input data and fitting procedure is adopted for all different theories. We find that the type-II dominance models lead to an excellent fit, comparable with the best among the available models, but the tight structure of this framework implies a significantly larger amount of fine tuning with respect to other approaches.Comment: 24 pages, References and minor wording changes adde

Superpixel-based two-view deterministic fitting for multiple-structure data

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior information of feature appearances. The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods. SDF also includes two original elements, i.e., a deterministic sampling algorithm and a novel model selection algorithm. The two algorithms are tightly coupled to boost the performance of SDF in both speed and accuracy. The key characteristic of SDF is that it can efficiently and deterministically estimate the parameters of model instances in multi-structure data. Experimental results demonstrate that the proposed SDF shows superiority over several state-of-the-art fitting methods for real images with singlestructure and multiple-structure data.Guobao Xiao, Hanzi Wang, B, Yan Yan, and David Sute