153 research outputs found

    Columnar cells necessary for motion responses of wide-field visual interneurons in Drosophila

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    Wide-field motion-sensitive neurons in the lobula plate (lobula plate tangential cells, LPTCs) of the fly have been studied for decades. However, it has never been conclusively shown which cells constitute their major presynaptic elements. LPTCs are supposed to be rendered directionally selective by integrating excitatory as well as inhibitory input from many local motion detectors. Based on their stratification in the different layers of the lobula plate, the columnar cells T4 and T5 are likely candidates to provide some of this input. To study their role in motion detection, we performed whole-cell recordings from LPTCs in Drosophila with T4 and T5 cells blocked using two different genetically encoded tools. In these flies, motion responses were abolished, while flicker responses largely remained. We thus demonstrate that T4 and T5 cells indeed represent those columnar cells that provide directionally selective motion information to LPTCs. Contrary to previous assumptions, flicker responses seem to be largely mediated by a third, independent pathway. This work thus represents a further step towards elucidating the complete motion detection circuitry of the fly

    Photonic Analogue of Two-dimensional Topological Insulators and Helical One-Way Edge Transport in Bi-Anisotropic Metamaterials

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    Recent progress in understanding the topological properties of condensed matter has led to the discovery of time-reversal invariant topological insulators. Because of limitations imposed by nature, topologically non-trivial electronic order seems to be uncommon except in small-band-gap semiconductors with strong spin-orbit interactions. In this Article we show that artificial electromagnetic structures, known as metamaterials, provide an attractive platform for designing photonic analogues of topological insulators. We demonstrate that a judicious choice of the metamaterial parameters can create photonic phases that support a pair of helical edge states, and that these edge states enable one-way photonic transport that is robust against disorder.Comment: 13 pages, 3 figure

    Deep learning of the retina enables phenome- and genome-wide analyses of the microvasculature.

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    Background: The microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health as well as tumorigenesis. The retinal fundus is a window for human in vivo non-invasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease. Methods: We utilized 97,895 retinal fundus images from 54,813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated fractal dimension (FD) as a measure of vascular branching complexity, and vascular density. We associated these indices with 1,866 incident ICD-based conditions (median 10y follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. Results: Low retinal vascular FD and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular FD and density identified 7 and 13 novel loci respectively, which were enriched for pathways linked to angiogenesis (e.g., VEGF, PDGFR, angiopoietin, and WNT signaling pathways) and inflammation (e.g., interleukin, cytokine signaling). Conclusions: Our results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights on genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health records, biomarker, and genetic data to inform risk prediction and risk modification

    Artificial graphene as a tunable Dirac material

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    Artificial honeycomb lattices offer a tunable platform to study massless Dirac quasiparticles and their topological and correlated phases. Here we review recent progress in the design and fabrication of such synthetic structures focusing on nanopatterning of two-dimensional electron gases in semiconductors, molecule-by-molecule assembly by scanning probe methods, and optical trapping of ultracold atoms in crystals of light. We also discuss photonic crystals with Dirac cone dispersion and topologically protected edge states. We emphasize how the interplay between single-particle band structure engineering and cooperative effects leads to spectacular manifestations in tunneling and optical spectroscopies.Comment: Review article, 14 pages, 5 figures, 112 Reference

    Topological Photonics

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    Topology is revolutionizing photonics, bringing with it new theoretical discoveries and a wealth of potential applications. This field was inspired by the discovery of topological insulators, in which interfacial electrons transport without dissipation even in the presence of impurities. Similarly, new optical mirrors of different wave-vector space topologies have been constructed to support new states of light propagating at their interfaces. These novel waveguides allow light to flow around large imperfections without back-reflection. The present review explains the underlying principles and highlights the major findings in photonic crystals, coupled resonators, metamaterials and quasicrystals.Comment: progress and review of an emerging field, 12 pages, 6 figures and 1 tabl

    Fiber guiding at the Dirac frequency beyond photonic bandgaps

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    Light trapping within waveguides is a key practice of modern optics, both scientifically and technologically. Photonic crystal fibers traditionally rely on total internal reflection (index-guiding fibers) or a photonic bandgap (photonic-bandgap fibers) to achieve field confinement. Here, we report the discovery of a new light trapping within fibers by the so-called Dirac point of photonic band structures. Our analysis reveals that the Dirac point can establish suppression of radiation losses and consequently a novel guided mode for propagation in photonic crystal fibers. What is known as the Dirac point is a conical singularity of a photonic band structure where wave motion obeys the famous Dirac equation. We find the unexpected phenomenon of wave localization at this point beyond photonic bandgaps. This guiding relies on the Dirac point rather than total internal reflection or photonic bandgaps, thus providing a sort of advancement in conceptual understanding over the traditional fiber guiding. The result presented here demonstrates the discovery of a new type of photonic crystal fibers, with unique characteristics that could lead to new applications in fiber sensors and lasers. The Dirac equation is a special symbol of relativistic quantum mechanics. Because of the similarity between band structures of a solid and a photonic crystal, the discovery of the Dirac-point-induced wave trapping in photonic crystals could provide novel insights into many relativistic quantum effects of the transport phenomena of photons, phonons, and electrons

    Research Article A New Informatics Framework for Evaluating the Codon Usage Metrics, Evolutionary Models and Phylogeographic Reconstruction of Tomato Yellow Leaf Curl Virus (TYLCV) in Different Regions of Asian Countries

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    Not AvailableTomato yellow leaf curl virus (TYLCV) is a major devastating viral disease, majorly affecting the tomato production globally. The disease is majorly transmitted by the Whitefly. The Begomovirus (TYLCV) having a six major protein coding genes, among them the C1/AC1 is evidently associated with viral replication. Owing to immense role of C1/AC1 gene, the present study is an initial effort to elucidate the factors shaping the codon usage bias and evolutionary pattern of TYLCV-C1/AC1 gene in five major Asian countries. Based on publicly available nucleotide sequence data the Codon usage pattern, Evolutionary and Phylogeographic reconstruction was carried out. The study revealed the presence of significant variation between the codon bias indices in all the selected regions. Implying that the codon usage pattern indices (eNC, CAI, RCDI, GRAVY, Aromo) are seriously affected by selection and mutational pressure, taking a supremacy in shaping the codon usage bias of viral gene. Further, the tMRCA age was 1853, 1939, 1855, 1944, 1828 for China, India, Iran, Oman and South Korea, respectively for TYLCV-C1/AC1 gene. The integrated analysis of Codon usage bias, Evolutionary rate and Phylogeography analysis in viruses signifies the positive role of selection and mutational pressure among the selected regions for TYLCV (C1/AC1) gene.Not Availabl

    Two-Particle-Self-Consistent Approach for the Hubbard Model

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    Even at weak to intermediate coupling, the Hubbard model poses a formidable challenge. In two dimensions in particular, standard methods such as the Random Phase Approximation are no longer valid since they predict a finite temperature antiferromagnetic phase transition prohibited by the Mermin-Wagner theorem. The Two-Particle-Self-Consistent (TPSC) approach satisfies that theorem as well as particle conservation, the Pauli principle, the local moment and local charge sum rules. The self-energy formula does not assume a Migdal theorem. There is consistency between one- and two-particle quantities. Internal accuracy checks allow one to test the limits of validity of TPSC. Here I present a pedagogical review of TPSC along with a short summary of existing results and two case studies: a) the opening of a pseudogap in two dimensions when the correlation length is larger than the thermal de Broglie wavelength, and b) the conditions for the appearance of d-wave superconductivity in the two-dimensional Hubbard model.Comment: Chapter in "Theoretical methods for Strongly Correlated Systems", Edited by A. Avella and F. Mancini, Springer Verlag, (2011) 55 pages. Misprint in Eq.(23) corrected (thanks D. Bergeron
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