Observation and numerical simulation of a convective initiation during COHMEX

Under a synoptically undisturbed condition, a dual-peak convective lifecycle was observed with the COoperative Huntsville Meteorological EXperiment (COHMEX) observational network over a 24-hour period. The lifecycle included a multicell storm, which lasted about 6 hours, produced a peak rainrate exceeding 100 mm/hr, and initiated a downstream mesoscale convective system. The 24-hour accumulated rainfall of this event was the largest during the entire COHMEX. The downstream mesoscale convective system, unfortunately, was difficult to investigate quantitatively due to the lack of mesoscale observations. The dataset collected near the time of the multicell storm evolution, including its initiation, was one of the best datasets of COHMEX. In this study, the initiation of this multicell storm is chosen as the target of the numerical simulations

The Carnegie-Irvine Galaxy Survey. III. The Three-Component Structure of Nearby Elliptical Galaxies

Motivated by recent developments in our understanding of the formation and evolution of massive galaxies, we explore the detailed photometric structure of a representative sample of 94 bright, nearby elliptical galaxies, using high-quality optical images from the Carnegie-Irvine Galaxy Survey. The sample spans a range of environments and stellar masses, from M* = 10^{10.2} to 10^{12.0} solar mass. We exploit the unique capabilities of two-dimensional image decomposition to explore the possibility that local elliptical galaxies may contain photometrically distinct substructure that can shed light on their evolutionary history. Compared with the traditional one-dimensional approach, these two-dimensional models are capable of consistently recovering the surface brightness distribution and the systematic radial variation of geometric information at the same time. Contrary to conventional perception, we find that the global light distribution of the majority (>75%) of elliptical galaxies is not well described by a single Sersic function. Instead, we propose that local elliptical galaxies generically contain three subcomponents: a compact (R_e < 1 kpc) inner component with luminosity fraction f ~ 0.1-0.15; an intermediate-scale (R_e ~ 2.5 kpc) middle component with f ~ 0.2-0.25; and a dominant (f = 0.6), extended (R_e ~ 10 kpc) outer envelope. All subcomponents have average Sersic indices n ~ 1-2, significantly lower than the values typically obtained from single-component fits. The individual subcomponents follow well-defined photometric scaling relations and the stellar mass-size relation. We discuss the physical nature of the substructures and their implications for the formation of massive elliptical galaxies.Comment: To appear in The Astrophysical Journal; 36 pages, 2 tables, 38 figures; For the full resolution version, see: http://users.obs.carnegiescience.edu/shuang/PaperIII.pdf ; For the atlas of all selected models, see http://users.obs.carnegiescience.edu/shuang/AppendixE.pd

The Carnegie-Irvine Galaxy Survey. IV. A Method to Determine the Average Mass Ratio of Mergers That Built Massive Elliptical Galaxies

Many recent observations and numerical simulations suggest that nearby massive, early-type galaxies were formed through a "two-phase" process. In the proposed second phase, the extended stellar envelope was accumulated through many dry mergers. However, details of the past merger history of present-day ellipticals, such as the typical merger mass ratio, are difficult to constrain observationally. Within the context and assumptions of the two-phase formation scenario, we propose a straightforward method, using photometric data alone, to estimate the average mass ratio of mergers that contributed to the build-up of massive elliptical galaxies. We study a sample of nearby massive elliptical galaxies selected from the Carnegie-Irvine Galaxy Survey, using two-dimensional analysis to decompose their light distribution into an inner, denser component plus an extended, outer envelope, each having a different optical color. The combination of these two substructures accurately recovers the negative color gradient exhibited by the galaxy as whole. The color difference between the two components ( ~ 0.10 mag; ~ 0.14 mag), based on the slope of the M_stellar-color relation for nearby early-type galaxies, can be translated into an estimate of the average mass ratio of the mergers. The rough estimate, 1:5 to 1:10, is consistent with the expectation of the two-phase formation scenario, suggesting that minor mergers were largely responsible for building up to the outer stellar envelope of present-day massive ellipticals. With the help of accurate photometry, large sample size, and more choices of colors promised by ongoing and future surveys, the approach proposed here can reveal more insights into the growth of massive galaxies during the last few Gyr.Comment: Accepted by ApJ; 20 pages, 11 figures, 1 table; The high resolution figures and the full table can be downloaded from here: https://github.com/dr-guangtou/cgs_colorgra

Model studies on the role of moist convection as a mechanism for interaction between the mesoscales

A three year research effort is described which had as its goal the development of techniques to improve the numerical prediction of cumulus convection on the meso-beta and meso-gamma scales. Two MESO models are used, the MASS (mesoscale) and TASS (cloud scale) models. The primary meteorological situation studied is the 28-29 Jun. 1986 Cooperative Huntsville Meteorological Experiment (COHMEX) study area on a day with relatively weak large scale forcing. The problem of determining where and when convection should be initiated is considered to be a major problem of current approaches. Assimilation of moisture data from satellite, radar, and surface data is shown to significantly improve mesoscale simulations. The TASS model is shown to reproduce some observed mesoscale features when initialized with 3-D observational data. Convection evolution studies center on comparison of the Kuo and Fritsch-Chappell cumulus parameterization schemes to each other, and to cloud model results. The Fritsch-Chappell scheme is found to be superior at about 30 km resolution, while the Kuo scheme does surprisingly well in simulating convection down to 10 km in cases where convergence features are well-resolved by the model grid. Results from MASS-TASS interaction experiments are presented and discussed. A discussion of the future of convective simulation is given, with the conclusion that significant progress is possible on several fronts in the next few years

Symmetry Breaking with the SCAN Density Functional Describes Strong Correlation in the Singlet Carbon Dimer

The SCAN (strongly constrained and appropriately normed) meta-generalized gradient approximation (meta-GGA), which satisfies all 17 exact constraints that a meta-GGA can satisfy, accurately describes equilibrium bonds that are normally correlated. With symmetry breaking, it also accurately describes some sd equilibrium bonds that are strongly correlated. While sp equilibrium bonds are nearly always normally correlated, the C2 singlet ground state is known to be a rare case of strong correlation in an sp equilibrium bond. Earlier work that calculated atomization energies of the molecular sequence B2, C2, O2, and F2 in the local spin density approximation (LSDA), the Perdew-Burke-Ernzerhof (PBE) GGA, and the SCAN meta-GGA, without symmetry breaking in the molecule, found that only SCAN was accurate enough to reveal an anomalous under-binding for C2. This work shows that spin symmetry breaking in singlet C2, the appearance of net up- and down-spin densities on opposite sides (not ends) of the bond, corrects that under-binding, with a small SCAN atomization-energy error more like that of the other three molecules, suggesting that symmetry-breaking with an advanced density functional might reliably describe strong correlation. This article also discusses some general aspects of symmetry breaking, and the insights into strong correlation that symmetry-breaking can bring.Comment: 10 pages, 3 figures, 1 Tabl

Network-Based Analysis of Genetic Variants Associated with Hippocampal Volume in Alzheimer’S Disease: A Study of Adni Cohorts

Background: Alzheimer’s disease (AD) is a neurodegenerative disease that causes dementia. While molecular basis of AD is not fully understood, genetic factors are expected to participate in the development and progression of the disease. Our goal was to uncover novel genetic underpinnings of Alzheimer’s disease with a bioinformatics approach that accounts for tissue specificity. Findings: We performed genome-wide association studies (GWAS) for hippocampal volume in two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts. We used these GWAS in a subsequent tissue-specific network-wide association study (NetWAS), which applied nominally significant associations in the initial GWAS to identify disease relevant patterns in a functional network for the hippocampus. We compared prioritized gene lists from NetWAS and GWAS with literature curated AD-associated genes from the Online Mendelian Inheritance in Man (OMIM) database. In the ADNI-1 GWAS, where we also observed an enrichment of low p-values, NetWAS prioritized disease-gene associations in accordance with OMIM annotations. This was not observed in the ADNI-2 dataset. We provide source code to replicate these analyses as well as complete results under permissive licenses. Conclusions: We performed the first analysis of hippocampal volume using NetWAS, which uses machine learning algorithms applied to tissue-specific functional interaction network to prioritize GWAS results. Our findings support the idea that tissue-specific networks may provide helpful context for understanding the etiology of common human diseases and reveal challenges that network-based approaches encounter in some datasets. Our source code and intermediate results files can facilitate the development of methods to address these challenges

An effective route to the additive manufacturing of a mechanically gradient supramolecular polymer nanocomposite structure

3D Printing techniques are additive methods of fabricating parts directly from computer-aided designs. Whilst the clearest benefit is the realisation of geometrical freedom, multi-material printing allows the introduction of compositional variation and highly tailored product functionality. The paper reports a proof-of-concept additive manufacturing study to deposit a supramolecular polymer and a complementary organic filler to form composites with gradient composition to enable spatial distribution of mechanical properties and functionality by tuning the number of supramolecular interactions. We use a dual-feed extrusion 3D printing process, with feed stocks based on the supramolecular polymer and its organic composite, delivered at ratios predetermined. This allows for production of a graded specimen with varying filler concentration that dictates the mechanical properties. The printed specimen was inspected under dynamic load in a tensile test using digital image correlation to produce full-field deformation maps, which showed clear differences in deformation in regions with varying compositions, corresponding to the designed-in variations. This approach affords a novel method for printing material with graded mechanical properties which are not currently commercially available or easily accessible, however, the method can potentially be directly translated to the generation of biomaterial-based composites featuring gradients of mechanical properties