Topology, edge states, and zero-energy states of ultracold atoms in 1D optical superlattices with alternating onsite potentials or hopping coefficients

One-dimensional superlattices with periodic spatial modulations of onsite potentials or tunneling coefficients can exhibit a variety of properties associated with topology or symmetry. Recent developments of ring-shaped optical lattices allow a systematic study of those properties in superlattices with or without boundaries. While superlattices with additional modulating parameters are shown to have quantized topological invariants in the augmented parameter space, we also found localized or zero-energy states associated with symmetries of the Hamiltonians. Probing those states in ultracold-atoms is possible by utilizing recently proposed methods analyzing particle depletion or the local density of states. Moreover, we summarize feasible realizations of configurable optical superlattices using currently available techniques.Comment: 11 pages, 10 figure

RPGR protein complex regulates proteasome activity and mediates store-operated calcium entry

Ciliopathies are a group of genetically heterogeneous disorders, characterized by defects in cilia genesis or maintenance. Mutations in the RPGR gene and its interacting partners, RPGRIP1 and RPGRIP1L, cause ciliopathies, but the function of their proteins remains unclear. Here we show that knockdown (KD) of RPGR, RPGRIP1 or RPGRIP1L in hTERT-RPE1 cells results in abnormal actin cytoskeleton organization. The actin cytoskeleton rearrangement is regulated by the small GTPase RhoA via the planar cell polarity (PCP) pathway. RhoA activity was upregulated in the absence of RPGR, RPGRIP1 or RPGRIP1L proteins. In RPGR, RPGRIP1 or RPGRIP1L KD cells, we observed increased levels of DVl2 and DVl3 proteins, the core components of the PCP pathway, due to impaired proteasomal activity. RPGR, RPGRIP1 or RPGRIP1L KD cells treated with thapsigargin (TG), an inhibitor of sarcoendoplasmic reticulum Ca2+ - ATPases, showed impaired store-operated Ca2+ entry (SOCE), which is mediated by STIM1 and Orai1 proteins. STIM1 was not localized to the ER-PM junction upon ER store depletion in RPGR, RPGRIP1 or RPGRIP1L KD cells. Our results demonstrate that the RPGR protein complex is required for regulating proteasomal activity and for modulating SOCE, which may contribute to the ciliopathy phenotype

The influence of halides in polyoxotitanate cages; dipole moment, splitting and expansion of d-orbitals and electron-electron repulsion

Metal-doped polyoxotitanate (M-POT) cages have been shown to be efficient single-source precursors to metal-doped titania [TiO$_2$(M)] (state-of-the-art photocatalytic materials) as well as molecular models for the behaviour of dopant metal ions in bulk titania. Here we report the influence halide ions have on the optical and electronic properties of a series of halide-only, and cobalt halide-‘doped’ POT cages. In this combined experimental and computational study we show that halide ions can have several effects on the band gaps of halide-containing POT cages, influencing the dipole moment (hole–electron separation) and the structure of the valance band edge. Overall, the band gap behaviour stems from the effects of increasing orbital energy moving from F to I down Group 17, as well as crystal-field splitting of the d-orbitals, the potential effects of the Nephelauxetic influence of the halides and electron–electron repulsion.We thank the EPSRC (Doctoral Prize for P. D. M.), A*STAR Singapore (Scholarship for N. L.), the Studienstiftung des deutschen Volkes, Fonds of the Chemical Industry (S. H.) for funding. The authors would like to acknowledge the use of the EPSRC UK National Service for Computational Chemistry Software (NSCCS) at Imperial College London and contributions from its staff in carrying out this work

Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition

Here, we develop an audiovisual deep residual network for multimodal apparent personality trait recognition. The network is trained end-to-end for predicting the Big Five personality traits of people from their videos. That is, the network does not require any feature engineering or visual analysis such as face detection, face landmark alignment or facial expression recognition. Recently, the network won the third place in the ChaLearn First Impressions Challenge with a test accuracy of 0.9109

Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion

Surface solitons in trilete lattices

Fundamental solitons pinned to the interface between three semi-infinite one-dimensional nonlinear dynamical chains, coupled at a single site, are investigated. The light propagation in the respective system with the self-attractive on-site cubic nonlinearity, which can be implemented as an array of nonlinear optical waveguides, is modeled by the system of three discrete nonlinear Schr\"{o}dinger equations. The formation, stability and dynamics of symmetric and asymmetric fundamental solitons centered at the interface are investigated analytically by means of the variational approximation (VA) and in a numerical form. The VA predicts that two asymmetric and two antisymmetric branches exist in the entire parameter space, while four asymmetric modes and the symmetric one can be found below some critical value of the inter-lattice coupling parameter -- actually, past the symmetry-breaking bifurcation. At this bifurcation point, the symmetric branch is destabilized and two new asymmetric soliton branches appear, one stable and the other unstable. In this area, the antisymmetric branch changes its character, getting stabilized against oscillatory perturbations. In direct simulations, unstable symmetric modes radiate a part of their power, staying trapped around the interface. Highly unstable asymmetric modes transform into localized breathers traveling from the interface region across the lattice without significant power loss.Comment: Physica D in pres

Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation

In this paper, we present the optimization formulation of the Kalman filtering and smoothing problems, and use this perspective to develop a variety of extensions and applications. We first formulate classic Kalman smoothing as a least squares problem, highlight special structure, and show that the classic filtering and smoothing algorithms are equivalent to a particular algorithm for solving this problem. Once this equivalence is established, we present extensions of Kalman smoothing to systems with nonlinear process and measurement models, systems with linear and nonlinear inequality constraints, systems with outliers in the measurements or sudden changes in the state, and systems where the sparsity of the state sequence must be accounted for. All extensions preserve the computational efficiency of the classic algorithms, and most of the extensions are illustrated with numerical examples, which are part of an open source Kalman smoothing Matlab/Octave package.Comment: 46 pages, 11 figure

The liver X receptor pathway is highly upregulated in rheumatoid arthritis synovial macrophages and potentiates TLR-driven cytokine release

<p>Objectives: Macrophages are central to the inflammatory processes driving rheumatoid arthritis (RA) synovitis. The molecular pathways that are induced in synovial macrophages and thereby promote RA disease pathology remain poorly understood.</p> <p>Methods: We used microarray to characterise the transcriptome of synovial fluid (SF) macrophages compared with matched peripheral blood monocytes from patients with RA (n=8).</p> <p>Results: Using in silico pathway mapping, we found that pathways downstream of the cholesterol activated liver X receptors (LXRs) and those associated with Toll-like receptor (TLR) signalling were upregulated in SF macrophages. Macrophage differentiation and tumour necrosis factor α promoted the expression of LXRα. Furthermore, in functional studies we demonstrated that activation of LXRs significantly augmented TLR-driven cytokine and chemokine secretion.</p> <p>Conclusions: The LXR pathway is the most upregulated pathway in RA synovial macrophages and activation of LXRs by ligands present within SF augments TLR-driven cytokine secretion. Since the natural agonists of LXRs arise from cholesterol metabolism, this provides a novel mechanism that can promote RA synovitis.</p&gt

XRCC2 R188H (rs3218536), XRCC3 T241M (rs861539) and R243H (rs77381814) single nucleotide polymorphisms in cervical cancer risk

Human Papillomavirus (HPV) is the main cause of cervical cancer and its precursor lesions. Transformation may be induced by several mechanisms, including oncogene activation and genome instability. Individual differences in DNA damage recognition and repair have been hypothesized to influence cervical cancer risk. The aim of this study was to evaluate whether the double strand break gene polymorphisms XRCC2 R188H G>A (rs3218536), XRCC3 T241M C>T (rs861539) and R243H G>A (rs77381814) are associated to cervical cancer in Argentine women. A case control study consisting of 322 samples (205 cases and 117 controls) was carried out. HPV DNA detection was performed by PCR and genotyping of positive samples by EIA (enzyme immunoassay). XRCC2 and 3 polymorphisms were determined by pyrosequencing. The HPV-adjusted odds ratio (OR) of XRCC2 188 GG/AG genotypes was OR = 2.4 (CI = 1.1-4.9, p = 0.02) for cervical cancer. In contrast, there was no increased risk for cervical cancer with XRCC3 241 TT/CC genotypes (OR = 0.48; CI = 0.2-1; p = 0.1) or XRCC3 241 CT/CC (OR = 0.87; CI = 0.52-1.4; p = 0.6). Regarding XRCC3 R243H, the G allele was almost fixed in the population studied. In conclusion, although the sample size was modest, the present data indicate a statistical association between cervical cancer and XRCC2 R188H polymorphism. Future studies are needed to confirm these findings.Fil: Perez, Luis Orlando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; ArgentinaFil: Crivaro, Andrea Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; ArgentinaFil: Barbisan, Gisela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; ArgentinaFil: Poleri, Lucía Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; ArgentinaFil: Golijow, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentin

Structured Sparsity: Discrete and Convex approaches

Compressive sensing (CS) exploits sparsity to recover sparse or compressible signals from dimensionality reducing, non-adaptive sensing mechanisms. Sparsity is also used to enhance interpretability in machine learning and statistics applications: While the ambient dimension is vast in modern data analysis problems, the relevant information therein typically resides in a much lower dimensional space. However, many solutions proposed nowadays do not leverage the true underlying structure. Recent results in CS extend the simple sparsity idea to more sophisticated {\em structured} sparsity models, which describe the interdependency between the nonzero components of a signal, allowing to increase the interpretability of the results and lead to better recovery performance. In order to better understand the impact of structured sparsity, in this chapter we analyze the connections between the discrete models and their convex relaxations, highlighting their relative advantages. We start with the general group sparse model and then elaborate on two important special cases: the dispersive and the hierarchical models. For each, we present the models in their discrete nature, discuss how to solve the ensuing discrete problems and then describe convex relaxations. We also consider more general structures as defined by set functions and present their convex proxies. Further, we discuss efficient optimization solutions for structured sparsity problems and illustrate structured sparsity in action via three applications.Comment: 30 pages, 18 figure