Association between TV viewing and heart disease mortality: observational study using negative control outcome

AIMS: Sedentary behaviour (particularly television (TV) viewing) is thought to be a risk factor for cardiovascular disease. We employed a negative control outcome to explore whether the association between TV viewing and heart disease mortality is explained by confounding. METHODS: The sample was drawn from the UK Biobank study and comprised 479 658 participants (aged 56.5±8.0 years; 45.7% men) followed up over a mean of 10.4 years. TV viewing was measured from self-report. RESULTS: There were 1437 ischaemic heart disease (IHD) deaths, and 214 accidental deaths (employed as the negative control outcome). TV viewing was related to the following confounding variables: age, smoking, alcohol, diet, obesity, physical inactivity, cardiovascular disease and education. The confounding structures were similar for both outcomes. TV viewing (per hour/d) was associated with IHD (hazard ratio (HR)=1.30, 95% CI, 1.27 to 1.33) and accidental death (HR=1.15, 95% CI, 1.07 to 1.24) in unadjusted models. Associations were attenuated for both outcomes and were considerably converged after adjustment for confounders; IHD (HR=1.09, 95% CI, 1.06 to 1.12) and accidental death (HR=1.06, 95% CI, 0.98 to 1.15). CONCLUSION: The pattern of results for TV with an implausible outcome mirrored that of IHD, suggesting that observed associations between TV and heart disease are likely to be driven by confounding

The impact of chromosomal translocation locus and fusion oncogene coding sequence in synovial sarcomagenesis.

Synovial sarcomas are aggressive soft-tissue malignancies that express chromosomal translocation-generated fusion genes, SS18-SSX1 or SS18-SSX2 in most cases. Here, we report a mouse sarcoma model expressing SS18-SSX1, complementing our prior model expressing SS18-SSX2. Exome sequencing identified no recurrent secondary mutations in tumors of either genotype. Most of the few mutations identified in single tumors were present in genes that were minimally or not expressed in any of the tumors. Chromosome 6, either entirely or around the fusion gene expression locus, demonstrated a copy number gain in a majority of tumors of both genotypes. Thus, by fusion oncogene coding sequence alone, SS18-SSX1 and SS18-SSX2 can each drive comparable synovial sarcomagenesis, independent from other genetic drivers. SS18-SSX1 and SS18-SSX2 tumor transcriptomes demonstrated very few consistent differences overall. In direct tumorigenesis comparisons, SS18-SSX2 was slightly more sarcomagenic than SS18-SSX1, but equivalent in its generation of biphasic histologic features. Meta-analysis of human synovial sarcoma patient series identified two tumor-gentoype-phenotype correlations that were not modeled by the mice, namely a scarcity of male hosts and biphasic histologic features among SS18-SSX2 tumors. Re-analysis of human SS18-SSX1 and SS18-SSX2 tumor transcriptomes demonstrated very few consistent differences, but highlighted increased native SSX2 expression in SS18-SSX1 tumors. This suggests that the translocated locus may drive genotype-phenotype differences more than the coding sequence of the fusion gene created. Two possible roles for native SSX2 in synovial sarcomagenesis are explored. Thus, even specific partial failures of mouse genetic modeling can be instructive to human tumor biology

Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network

Identification and extraction of singing voice from within musical mixtures is a key challenge in source separation and machine audition. Recently, deep neural networks (DNN) have been used to estimate 'ideal' binary masks for carefully controlled cocktail party speech separation problems. However, it is not yet known whether these methods are capable of generalizing to the discrimination of voice and non-voice in the context of musical mixtures. Here, we trained a convolutional DNN (of around a billion parameters) to provide probabilistic estimates of the ideal binary mask for separation of vocal sounds from real-world musical mixtures. We contrast our DNN results with more traditional linear methods. Our approach may be useful for automatic removal of vocal sounds from musical mixtures for 'karaoke' type applications

Characterizing quantum supremacy in near-term devices

© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. A critical question for quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of supercomputers. Such a demonstration of what is referred to as quantum supremacy requires a reliable evaluation of the resources required to solve tasks with classical approaches. Here, we propose the task of sampling from the output distribution of random quantum circuits as a demonstration of quantum supremacy. We extend previous results in computational complexity to argue that this sampling task must take exponential time in a classical computer. We introduce cross-entropy benchmarking to obtain the experimental fidelity of complex multiqubit dynamics. This can be estimated and extrapolated to give a success metric for a quantum supremacy demonstration. We study the computational cost of relevant classical algorithms and conclude that quantum supremacy can be achieved with circuits in a two-dimensional lattice of 7 × 7 qubits and around 40 clock cycles. This requires an error rate of around 0.5% for two-qubit gates (0.05% for one-qubit gates), and it would demonstrate the basic building blocks for a fault-tolerant quantum computer

A review of clustering techniques and developments

© 2017 Elsevier B.V. This paper presents a comprehensive study on clustering: exiting methods and developments made at various times. Clustering is defined as an unsupervised learning where the objects are grouped on the basis of some similarity inherent among them. There are different methods for clustering the objects such as hierarchical, partitional, grid, density based and model based. The approaches used in these methods are discussed with their respective states of art and applicability. The measures of similarity as well as the evaluation criteria, which are the central components of clustering, are also presented in the paper. The applications of clustering in some fields like image segmentation, object and character recognition and data mining are highlighted

Combined SEM-CL and STEM investigation of green InGaN quantum wells

Abstract The microstructure of green-emitting InGaN/GaN quantum well (QW) samples grown at different temperatures was studied using cross-section scanning transmission electron microscopy (STEM) and plan-view cathodoluminescence (CL). The sample with the lowest InGaN growth temperature exhibits microscale variations in the CL intensity across the sample surface. Using STEM analysis of such areas, the observed darker patches do not correspond to any observable extended defect. Instead, they are related to changes in the extent of gross-well width fluctuations in the QWs, with more brightly emitting regions exhibiting a high density of such fluctuations, whilst dimmer regions were seen to have InGaN QWs with a more uniform thickness.</jats:p

Combined SEM-CL and STEM investigation of green InGaN quantum wells

Abstract The microstructure of green-emitting InGaN/GaN quantum well (QW) samples grown at different temperatures was studied using cross-section scanning transmission electron microscopy (STEM) and plan-view cathodoluminescence (CL). The sample with the lowest InGaN growth temperature exhibits microscale variations in the CL intensity across the sample surface. Using STEM analysis of such areas, the observed darker patches do not correspond to any observable extended defect. Instead, they are related to changes in the extent of gross-well width fluctuations in the QWs, with more brightly emitting regions exhibiting a high density of such fluctuations, whilst dimmer regions were seen to have InGaN QWs with a more uniform thickness.</jats:p

Stacking fault-associated polarized surface-emitted photoluminescence from zincblende InGaN/GaN quantum wells

Zincblende InGaN/GaN quantum wells offer a potential improvement to the efficiency of green light emission by removing the strong electric fields present in similar structures. However, a high density of stacking faults may have an impact on the recombination in these systems. In this work, scanning transmission electron microscopy and energy-dispersive x-ray measurements demonstrate that one dimensional nanostructures form due to indium segregation adjacent to stacking faults. In photoluminescence experiments these structures emit visible light which is optically polarised up to 86% at 10K and up to 75% at room temperature. The emission redshifts and broadens as the well width increases from 2nm to 8nm. Photoluminescence excitation measurements indicate that carriers are captured by these structures from the rest of the quantum wells and recombine to emit light polarised along the length of these nanostructures

A two-dimensional type I superionic conductor

Superionic conductors possess liquid-like ionic diffusivity in the solid state, finding wide applicability from electrolytes in energy storage to materials for thermoelectric energy conversion. Type I superionic conductors (for example, AgI, Ag2Se and so on) are defined by a first-order transition to the superionic state and have so far been found exclusively in three-dimensional crystal structures. Here, we reveal a two-dimensional type I superionic conductor, α-KAg3Se2, by scattering techniques and complementary simulations. Quasi-elastic neutron scattering and ab initio molecular dynamics simulations confirm that the superionic Ag+ ions are confined to subnanometre sheets, with the simulated local structure validated by experimental X-ray powder pair-distribution-function analysis. Finally, we demonstrate that the phase transition temperature can be controlled by chemical substitution of the alkali metal ions that compose the immobile charge-balancing layers. Our work thus extends the known classes of superionic conductors and will facilitate the design of new materials with tailored ionic conductivities and phase transitions

Neighborhoods of trees in circular orderings

In phylogenetics, a common strategy used to construct an evolutionary tree for a set of species X is to search in the space of all such trees for one that optimizes some given score function (such as the minimum evolution, parsimony or likelihood score). As this can be computationally intensive, it was recently proposed to restrict such searches to the set of all those trees that are compatible with some circular ordering of the set X. To inform the design of efficient algorithms to perform such searches, it is therefore of interest to find bounds for the number of trees compatible with a fixed ordering in the neighborhood of a tree that is determined by certain tree operations commonly used to search for trees: the nearest neighbor interchange (nni), the subtree prune and regraft (spr) and the tree bisection and reconnection (tbr) operations. We show that the size of such a neighborhood of a binary tree associated with the nni operation is independent of the tree’s topology, but that this is not the case for the spr and tbr operations. We also give tight upper and lower bounds for the size of the neighborhood of a binary tree for the spr and tbr operations and characterize those trees for which these bounds are attained