Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); The objective of this study was to estimate (co)variance components and genetic parameters for live weight (LW) and daily live weight gain (LWG) of Nellore bulls in a test station using multi-trait and random regression models. In addition, breeding values for these traits were predicted by multi-trait and random regression analyses, and the rank of animals based on breeding values was compared with the current selection criterion of the test station (own performance). A total of 4758 Nellore bulls tested in a central station of the Beef Cattle Research Center (CPPC) between 1978 and 2007, including 2211 bulls from the CPPC herd and 2547 from commercial herds, were used. During the test, four LWs were recorded at intervals of 56 days (LW1d, LW56d. LW112d and LW168d). LWG was calculated as the difference between two consecutive weights for three periods: 1 to 55 (LWG(1)), 56 to 111 (LWG(2)), and 112 to 168 (LWG(3)) days on test. For LW and LWG, the multi-trait model included the fixed effects of contemporary group (year-month of birth), dam age class, and animal age at recording as covariate. For random regression analysis...

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML).

During the past two decades, a major outgrowth of efforts by our research group at St. Luke’s-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively ‘stable’, for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

The understanding of multiphase multi-component transport in capillary porous media plays an important role in scientific and engineering disciplines such as the petroleum and environmental industries. The two most commonly used tools to model multiphase multi-component flow are finite difference and finite volume methods. While these are well-established methods, they either fail to provide stability on unstructured meshes or they yield low order approximation. In this thesis, a presentation of both fully coupled and sequential discontinuous Galerkin (DG) formulations for the multiphase multi-component flow is given. Two physical models are examined: the black oil model and the CO2 sequestration model. The attractive attribute of using DG is that it permits the use of unstructured meshes while maintaining high order accuracy. Furthermore, the method can be structured to ensure mass conservation, which is another appealing feature when one is dealing with fluid dynamic problems.

Addressing complex chronic disease prevention, like childhood obesity, requires a multi-level, multi-component culturally relevant approach with broad reach. Models are lacking to guide fidelity monitoring across multiple levels, components, and sites engaged in such interventions. The aim of this study is to describe the fidelity-monitoring approach of The Children’s Healthy Living (CHL) Program, a multi-level multi-component intervention in five Pacific jurisdictions. A fidelity-monitoring rubric was developed. About halfway during the intervention, community partners were randomly selected and interviewed independently by local CHL staff and by Coordinating Center representatives to assess treatment fidelity. Ratings were compared and discussed by local and Coordinating Center staff. There was good agreement between the teams (Kappa = 0.50, p < 0.001), and intervention improvement opportunities were identified through data review and group discussion. Fidelity for the multi-level, multi-component, multi-site CHL intervention was successfully assessed, identifying adaptations as well as ways to improve intervention delivery prior to the end of the intervention.

The critical cooling rate $\mathcal{R}_c$, below which liquids crystallize upon cooling, characterizes the glass-forming ability (GFA) of the system. While pure metals are typically poor glass formers with $\mathcal {R}_c>10^{12}\, {\rm K/s}$, specific multi-component alloys can form bulk metallic glasses (BMGs) even at cooling rates below $\mathcal {R}\sim 1\, {\rm K/s}$. Conventional wisdom asserts that metal alloys with three or more components are better glass formers (with smaller ${\cal R}_c$) than binary alloys. However, there is currently no theoretical framework that provides quantitative predictions for $\mathcal{R}_c$ for multi-component alloys. We perform simulations of ternary hard-sphere systems, which have been shown to be accurate models for the glass-forming ability of BMGs, to understand the roles of geometric frustration and demixing in determining $\mathcal {R}_c$. Specifically, we compress ternary hard sphere mixtures into jammed packings and measure the critical compression rate, below which the system crystallizes, as a function of the diameter ratios $\sigma_B/\sigma_A$ and $\sigma_C/\sigma_A$ and number fractions $x_A$, $x_B$, and $x_C$. We find two distinct regimes for the GFA in parameter space for ternary hard spheres. When the diameter ratios are close to $1$...

We use multi-component decaying dark matter (DM) scenario to explain the possible cosmic ray excesses in the positron fraction recently confirmed by AMS-02 and the total $e^+ +e^-$ flux observed by Fermi-LAT. In the two-component DM models, we find an interesting variation of the flavor structure along with the cutoff of the heavy DM. For the three-component DM case, we focus on a particular parameter range in which the best fits prefer to open only 2 DM decay channels with a third DM contributing nothing to the electron and positron spectra. We show that all models give the reasonable fits to both the AMS-02 positron fraction and the Fermi-LAT total $e^++e^-$ flux, which are also consistent with the measured diffuse $\gamma$-ray flux by Fermi-LAT.; Comment: 10 pages, 1 figures, submitted to the special issue of Mod. Phys. Lett.A "Indirect Dark Matter Searches"

We present multi-component photoionization models allowing for local density inhomogeneities in the NLR to interpret the emission line spectra of Seyfert 2 galaxies. This approach leads to a successful match of a large set of line intensities from the UV to the NIR. In particular, the hitherto elusive NIR features [SIII]9062+9531 as well as high-ionization lines like [FeVII] are consistently fitted. The predictions of CIII] and CIV are considerably improved. From the detailed analysis of single-component photoionization models we derive the minimal radial extent of the NLR and the necessary span in density. Furthermore, we determine constraints on suggestions made about the role of matter-bounded clouds, and on proposed explanations for large [OIII]4363/5007 ratios (the so-called `temperature problem'), and assess the usability of some emission-line ratios as indicators of the ionization parameter. We find that a systematic variation of the cloud column densities in a population of matter-bounded clouds is inconsistent with the trends and correlations exhibited by the emission lines in the diagnostic diagrams. Concerning the temperature problem, the only possibility that leads to an overall consistency with the strengths of all other observed emission lines is subsolar metal abundances (as compared to e.g. the presence of dust...

We introduce {\it conformal multi-matrix models} (CMM) as an alternative to conventional multi-matrix model description of two-dimensional gravity interacting with $c < 1$ matter. We define CMM as solutions to (discrete) extended Virasoro constraints. We argue that the so defined alternatives of multi-matrix models represent the same universality classes in continuum limit, while at the discrete level they provide explicit solutions to the multi-component KP hierarchy and by definition satisfy the discrete $W$-constraints. We prove that discrete CMM coincide with the $(p,q)$-series of 2d gravity models in a {\it well}-{\it defined} continuum limit, thus demonstrating that they provide a proper generalization of Hermitian one-matrix model.; Comment: 35 pages, preprint FIAN/TD-9/92 & ITEP-M-4/92

We critically discuss and review the general ideas behind single- and multi-site coarse-grained (CG) models as applied to macromolecular solutions in the dilute and semi-dilute regime. We first consider single-site models with zero-density and density-dependent pair potentials. We highlight advantages and limitations of each option in reproducing the thermodynamic behavior and the large-scale structure of the underlying reference model. As a case study we consider solutions of linear homopolymers in a solvent of variable quality. Secondly, we extend the discussion to multi-component systems presenting, as a test case, results for mixtures of colloids and polymers. Specifically, we found the CG model with zero-density potentials to be unable to predict fluid-fluid demixing in a reasonable range of densities for mixtures of colloids and polymers of equal size. For larger colloids, the polymer volume fractions at which phase separation occurs are largely overestimated. CG models with density-dependent potentials are somewhat less accurate than models with zero-density potentials in reproducing the thermodynamics of the system and, although they presents a phase separation, they significantly underestimate the polymer volume fractions along the binodal. Finally...

In this paper, gravothermal oscillations are investigated in multi-component star clusters which have power law initial mass functions (IMF). For the power law IMFs, the minimum masses ($m_{min}$) were fixed and three different maximum stellar masses ($m_{max}$) were used along with different power-law exponents ($\alpha$) ranging from 0 to -2.35 (Salpeter). The critical number of stars at which gravothermal oscillations first appear with increasing $N$ was found using the multi-component gas code SPEDI. The total mass ($M_{tot}$) is seen to give an approximate stability condition for power law IMFs with fixed values of $m_{max}$ and $m_{min}$ independent of $\alpha$. The value $M_{tot}/m_{max} \simeq 12000$ is shown to give an approximate stability condition which is also independent of $m_{max}$, though the critical value is somewhat higher for the steepest IMF that was studied. For appropriately chosen cases, direct N-body runs were carried out in order to check the results obtained from SPEDI. Finally, evidence of the gravothermal nature of the oscillations found in the N-body runs is presented.; Comment: 9 pages, 3 figures, 8 tables. Accepted for publication in MNRAS

In this review we try to capture some of the recent excitement induced by experimental developments, but also by a large volume of theoretical and computational studies addressing multi-component nonlinear Schrodinger models and the localized structures that they support. We focus on some prototypical structures, namely the dark-bright and dark-dark solitons. Although our focus will be on one-dimensional, two-component Hamiltonian models, we also discuss variants, including three (or more)-component models, higher-dimensional states, as well as dissipative settings. We also offer an outlook on interesting possibilities for future work on this theme.; Comment: 23 pages, 9 figures

The Spitzer Survey of Stellar Structure in Galaxies (S$^4$G, Sheth et. al. 2010) is a deep 3.6 and 4.5 $\mu$m imaging survey of 2352 nearby ($< 40$ Mpc) galaxies. We describe the S$^4$G data analysis pipeline 4, which is dedicated to 2-dimensional structural surface brightness decompositions of 3.6 $\mu$m images, using GALFIT3.0 \citep{peng2010}. Besides automatic 1-component S\'ersic fits, and 2-component S\'ersic bulge + exponential disk fits, we present human supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge S\'ersic index and bulge-to-total light ratio ($B/T$), confirming earlier results \citep{laurikainen2007, gadotti2008, weinzirl2009}. In this first paper, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page ({\bf \tt www.oulu.fi/astronomy/S4G\_PIPELINE4/MAIN}). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions...

We revisit the multi-component leptonically decaying dark matter (DM) scenario to explain the possible electron/positron excesses with the recently updated AMS-02 data. We find that both the single- and two-component DM models can fit the positron fraction and $e^+/e^-$ respective fluxes, in which the two-component ones provide better fits. However, for the single-component models, the recent AMS-02 data on the positron fraction limit the DM cutoff to be smaller than 1 TeV, which conflicts with the high-energy behavior of the AMS-02 total $e^++e^-$ flux spectrum, while the two-component DM models do not possess such a problem. We also discuss the constraints from the Fermi-LAT measurement of the diffuse $\gamma$-ray spectrum. We show that the two-component DM models are consistent with the current DM lifetime bounds. In contrast, the best-fit DM lifetimes in the single-component models are actually excluded.; Comment: 18 pages, 2 figures, revised version accepted for publication in PRD

The fraction of star-forming to quiescent dwarf galaxies varies from almost infinity in the field to zero in the centers of rich galaxy clusters. What is causing this pronounced morphology-density relation? What do quiescent dwarf galaxies look like when studied in detail, and what conclusions can be drawn about their formation mechanism? Here we study a nearly magnitude-complete sample (-19 < M_r < -16 mag) of 121 Virgo cluster early types with deep near-infrared images from the SMAKCED project. We fit two-dimensional models with optional inner and outer components, as well as bar and lens components (in ~15% of the galaxies), to the galaxy images. While a single S\'ersic function may approximate the overall galaxy structure, it does not entirely capture the light distribution of two-thirds of our galaxies, for which multi-component models provide a better fit. This fraction of complex galaxies shows a strong dependence on luminosity, being larger for brighter objects. We analyze the global and component-specific photometric scaling relations of early-type dwarf galaxies and discuss similarities with bright early and late types. The dwarfs' global galaxy parameters show scaling relations that are similar to those of bright disk galaxies. The inner components are mostly fitted with S\'ersic n values close to 1. At a given magnitude they are systematically larger than the bulges of spirals...

We explore multi-component dark matter models where the dark sector consists of multiple stable states with different mass scales, and dark forces coupling these states further enrich the dynamics. The multi-component nature of the dark matter naturally arises in supersymmetric models, where both R parity and an additional symmetry, such as a $Z_2$, is preserved. We focus on a particular model where the heavier component of dark matter carries lepton number and annihilates mostly to leptons. The heavier component, which is essentially a sterile neutrino, naturally explains the PAMELA, ATIC and synchrotron signals, without an excess in antiprotons which typically mars other models of weak scale dark matter. The lighter component, which may have a mass from a GeV to a TeV, may explain the DAMA signal, and may be visible in low threshold runs of CDMS and XENON, which search for light dark matter.; Comment: 4 pages, no figures. v2: paper shortened to letter length; modified dark matter spectrum

Abstract—Computed Tomography (CT) is a noninvasive medical test obtained via a series of X-ray exposures resulting in 3D images that aid medical diagnosis. Previous approaches for coding such 3D images propose to employ multi-component transforms to exploit correlation among CT slices, but these approaches do not always improve coding performance with respect to a simpler slice-by-slice coding approach. In this work, we propose a novel analysis which accurately predicts when the use of a multi-component transform is profitable. This analysis models the correlation coefficient r based on image acquisition parameters readily available at acquisition time. Extensive experimental results from multiple image sensors suggest that multi-component transforms are appropriate for images with correlation coefficient r in excess of 0.87.

Fossil fuel reserves are projected to be decreasing, and emission regulations are becoming more stringent due to increasing atmospheric pollution. Alternative fuels for power generation in industrial gas turbines are thus required able to meet the above demands. Examples of such fuels are synthetic gas, blast furnace gas and coke oven gas. A common characteristic of these fuels is that they are multi-component fuels, whose composition varies greatly depending on their production process. This implies that their combustion characteristics will also vary significantly. Thus, accurate and yet flexible enough combustion sub-models are required for such fuels, which are used during the design stage, to ensure optimum performance during practical operating conditions. Most combustion sub-model development and validation is based on Direct Numerical Simulation (DNS) studies. DNS however is computationally expensive. This, has so far limited DNS to single-component fuels such as methane and hydrogen. Furthermore, the majority of DNS conducted to date used one-step chemistry in 3D, and skeletal chemistry in 2D only. The need for 3D DNS using skeletal chemistry is thus apparent. In this study, an accurate reduced chemical mechanism suitable for multi-component fuel-air combustion is developed from a skeletal mechanism. Three-dimensional DNS of a freely propagating turbulent premixed flame is then conducted using both mechanisms to shed some light into the flame structure and turbulence-scalar interaction of such multi-component fuel flames. It is found that for the multi-component fuel flame heat is released over a wider temperature range contrary to a methane flame. This...

The Spitzer Survey of Stellar Structure in Galaxies (S^4G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S^4G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G_PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions...