Two key events associated with a transposable element burst occurred during rice domestication

Transposable elements shape genome evolution through periodic bursts of amplification. In this study we exploited knowledge of the components of the mPing/Ping/Pong TE family in four rice strains undergoing mPing bursts to track their copy numbers and distribution in a large collection of genomes from the wild progenitor Oryza rufipogon and domesticated Oryza sativa (rice). We characterized two events that occurred to the autonomous Ping element and appear to be critical for mPing hyperactivity. First, a point mutation near the end of the element created a Ping variant ( Ping16A ) with reduced transposition. The proportion of strains with Ping16A has increased during domestication while the original Ping (Ping16G) has been dramatically reduced. Second, transposition of Ping16A into a Stowaway element generated a locus ( Ping16A_Stow ) whose presence correlates with strains that have high mPing copies. Finally, demonstration that Pong elements have been stably silenced in all strains analyzed indicates that sustained activity of the mPing/Ping family during domestication produced the components necessary for the mPing burst, not the loss of epigenetic regulation

Stochastic `Beads on a String' in the Accretion Tail of Arp 285

We present Spitzer infrared, GALEX UV, and SDSS and SARA optical images of the peculiar interacting galaxy pair Arp 285 (NGC 2856/4), and compare with a new numerical model of the interaction. We estimate the ages of clumps of star formation in these galaxies using population synthesis models, carefully considering the uncertainties on these ages. This system contains a striking example of `beads on a string': a series of star formation complexes ~1 kpc apart. These `beads' are found in a tail-like feature that is perpendicular to the disk of NGC 2856, which implies that it was formed from material accreted from the companion NGC 2854. The extreme blueness of the optical/UV colors and redness of the mid-infrared colors implies very young stellar ages (~4 - 20 Myrs) for these star forming regions. Spectral decomposition of these `beads' shows excess emission above the modeled stellar continuum in the 3.6 micron and 4.5 micron bands, indicating either contributions from interstellar matter to these fluxes or a second older stellar population. These clumps have -12.0 < M(B) < -10.6, thus they are less luminous than most dwarf galaxies. Our model suggests that bridge material falling into the potential of the companion overshoots the companion. The gas then piles up at apo-galacticon before falling back onto the companion, and star formation occurs in the pile-up. A luminous (M(B) ~ -13.6) extended (FWHM ~ 1.3 kpc) `bright spot' is visible at the northwestern edge of the NGC 2856 disk, with an intermediate stellar population (400 - 1500 Myrs). Our model suggests that this feature is part of a expanding ripple-like `arc' created by an off-center ring-galaxy-like collision between the two disks.Comment: Accepted by the Astronomical Journal. For color figures and appendix material, go tohttp://www.etsu.edu/physics/bsmith/research/sg/arp285/arp285.htm

Extracting an accurate river network: Stream burning re-revisited

Extracting river networks that are both accurate and topologically connected is important for applications that involve correct routing of material, for example water and sediment, through such networks. We combined water and sediment extraction using radar and multispectral imagery from Sentinel-1 and Sentinel-2 to create both water and sediment masks over a range of study areas. These were then used to condition topographic Digital Elevation Models (DEMs) by lowering the elevation of pixels with both water and sediment present, in a process known as stream burning. We examined how stream burning could improve accuracy of extracted networks and identified the most effective method of burning for optimal results. We find deeper burning depths improved accuracy, with diminishing returns: we suggest burning 40 to 50 meters. We find sediment burning improves accuracy in humid and temperate landscapes, but arid landscapes should be burned using only water pixels. We find accuracy of extracted networks is significantly better on the COP30 global topographic dataset compared to the NASADEM dataset, mainly due to the time of collection. The AW3D30 DEM and FABDEM datasets have accuracies just below that of the COP30 DEM

Empirical study of BIM implementation–based perceptions among Chinese practitioners

The global movement of building information modeling (BIM) is spreading the implementation of BIM from developed countries to other developing countries. Practitioners’ perceptions of BIM implementation in these developing countries, such as China, a giant building market that is increasing the application of BIM in the industry, have not been thoroughly understood. This research used the questionnaire method to survey 94 randomly recruited Chinese BIM professionals to investigate BIM practice and its related perceptions. Reductions in design errors and resultant construction rework were considered the top benefits of using BIM. The most important factor in achieving BIM value was noted as interoperability among various BIM tools. A comprehensive evaluation of BIM at the company level was considered a major difficulty of implementing BIM. The owner was considered the party that received the most benefits from BIM. Subgroup differences based on two major categories (i.e., participants’ profession and BIM proficiency level) were analyzed in the survey sections related to BIM implementation. Statistical analysis revealed that, generally, neither the profession nor BIM proficiency level affected participants’ perceptions of the benefits, factors, challenges, or benefited parties in BIM implementation

Depth-Based Subgraph Convolutional Neural Networks

This paper proposes a new graph convolutional neural network architecture based on a depth-based representation of graph structure deriving from quantum walks, which we refer to as the quantum-based subgraph convolutional neural network (QS-CNNs). This new architecture captures both the global topological structure and the local connectivity structure within a graph. Specifically, we commence by establishing a family of K-layer expansion subgraphs for each vertex of a graph by quantum walks, which captures the global topological arrangement information for substructures contained within a graph. We then design a set of fixed-size convolution filters over the subgraphs, which helps to characterise multi-scale patterns residing in the data. The idea is to apply convolution filters sliding over the entire set of subgraphs rooted at a vertex to extract the local features analogous to the standard convolution operation on grid data. Experiments on eight graph-structured datasets demonstrate that QS-CNNs architecture is capable of outperforming fourteen state-of-the-art methods for the tasks of node classification and graph classification

InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation

peer-reviewedInnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.This work was supported by Genome BC through the Pathogenomics of Innate Immunity (PI2) project and by the Foundation for the National Institutes of Health and the Canadian Institutes of Health Research under the Grand Challenges in Global Health Research Initiative [Grand Challenges ID: 419]. Further funding was also provided by AllerGen grants 12ASI1 and 12B&B2. D.J.L. was funded in part during this project by a postdoctoral trainee award from the Michael Smith Foundation for Health Research (MSFHR). F.S.L.B. is a MSFHR Senior Scholar and R.E.W.H. holds a Canada Research Chair (CRC). Funding to enable bovine systems biology in InnateDB is provided by Teagasc [RMIS6018] and the Teagasc Walsh Fellowship scheme. IMEx is funded by the European Commission under the PSIMEx project [contract number FP7-HEALTH-2007-223411]. Funding for open access charge: Teagasc [RMIS6018]

Unraveling the Nature of Charge Excitations in La2_2CuO4_4 with Momentum-Resolved Cu KK-edge Resonant Inelastic X-ray Scattering

Results of model calculations using exact diagonalization reveal the orbital character of states associated with different Raman loss peaks in Cu $K$-edge resonant inelastic X-ray scattering (RIXS) from La$_{2}$CuO$_{4}$. The model includes electronic orbitals necessary to highlight non-local Zhang-Rice singlet, charge transfer and $d$-$d$ excitations, as well as states with apical oxygen 2$p_z$ character. The dispersion of these excitations is discussed with prospects for resonant final state wave-function mapping. A good agreement with experiments emphasizes the substantial multi-orbital character of RIXS profiles in the energy transfer range 1-6 eV.Comment: Original: 4.5 pages. Replaced: 4 pages and 4 figures with updated content and reference

Single Image Super Resolution via Neighbor Reconstruction

Super Resolution (SR) is a complex, ill-posed problem where the aim is to construct the mapping between the low and high resolution manifolds of image patches. Anchored neighborhood regression for SR (namely A+  [27]) has shown promising results. In this paper we present a new regression-based SR algorithm that overcomes the limitations of A+ and benefits from an innovative and simple Neighbor Reconstruction Method (NRM). This is achieved by vector operations on an anchored point and its corresponding neighborhood. NRM reconstructs new patches which are closer to the anchor point in the manifold space. Our method is robust to NRM sparsely-sampled points: increasing PSNR by 0.5 dB compared to the next best method. We comprehensively validate our technique on standardised datasets and compare favourably with the state-of-the-art methods: we obtain PSNR improvement of up to 0.21 dB compared to previously-reported work