Synchronization and modularity in complex networks

We investigate the connection between the dynamics of synchronization and the modularity on complex networks. Simulating the Kuramoto's model in complex networks we determine patterns of meta-stability and calculate the modularity of the partition these patterns provide. The results indicate that the more stable the patterns are, the larger tends to be the modularity of the partition defined by them. This correlation works pretty well in homogeneous networks (all nodes have similar connectivity) but fails when networks contain hubs, mainly because the modularity is never improved where isolated nodes appear, whereas in the synchronization process the characteristic of hubs is to have a large stability when forming its own community.Comment: To appear in the Proceedings of Workshop on Complex Systems: New Trends and Expectations, Santander, Spain, 5-9 June 200

New Image Statistics for Detecting Disturbed Galaxy Morphologies at High Redshift

Testing theories of hierarchical structure formation requires estimating the distribution of galaxy morphologies and its change with redshift. One aspect of this investigation involves identifying galaxies with disturbed morphologies (e.g., merging galaxies). This is often done by summarizing galaxy images using, e.g., the CAS and Gini-M20 statistics of Conselice (2003) and Lotz et al. (2004), respectively, and associating particular statistic values with disturbance. We introduce three statistics that enhance detection of disturbed morphologies at high-redshift (z ~ 2): the multi-mode (M), intensity (I), and deviation (D) statistics. We show their effectiveness by training a machine-learning classifier, random forest, using 1,639 galaxies observed in the H band by the Hubble Space Telescope WFC3, galaxies that had been previously classified by eye by the CANDELS collaboration (Grogin et al. 2011, Koekemoer et al. 2011). We find that the MID statistics (and the A statistic of Conselice 2003) are the most useful for identifying disturbed morphologies. We also explore whether human annotators are useful for identifying disturbed morphologies. We demonstrate that they show limited ability to detect disturbance at high redshift, and that increasing their number beyond approximately 10 does not provably yield better classification performance. We propose a simulation-based model-fitting algorithm that mitigates these issues by bypassing annotation.Comment: 15 pages, 14 figures, accepted for publication in MNRA

Prevalence and determinants of anxiety and depression in end stage renal disease (ESRD). A comparison between ESRD patients with and without coexisting diabetes mellitus

Objective: To compare anxiety and/or depressive symptoms between patients with end-stage renal disease with and without comorbid diabetes and identify factors associated with symptoms of distress in this population. Methods: Data from two studies (conducted between 2010 and 2014) were pooled. A total of 526 patients on hemodialysis (68.8% with diabetes) completed the Hospital Anxiety and Depression Scale (HADS). Elevated symptoms were defined as HADS-Anxiety or HADS-Depression ≥ 8. Univariate and multivariate logistic regressions were used to estimate associations between diabetic status, and other socio-demographic and clinical factors with baseline clinical anxiety and depression. Results: A total of 233 (45.4%) reported elevated anxiety symptoms and 256 (49.9%) reported elevated depressive symptoms sufficient for caseness. Rates were not different between patients with and without diabetes. Risk for clinical depression was higher in patients who were single/unpartnered (OR = 1.828), Chinese vs. Malay (OR = 2.05), or had lower albumin levels (OR = 0.932). None of the parameters were associated with anxiety caseness. Conclusion: Sociocultural factors rather than comorbid burden may help identify patients at risk for depression. The high rates of anxiety and depression underlie the importance for monitoring and intervention in dialysis care

Trajectory Mapping and Applications to Data from the Upper Atmosphere Research Satellite

The problem of creating synoptic maps from asynoptically gathered trace gas data has prompted the development of a number of schemes. Most notable among these schemes are the Kalman filter, the Salby-Fourier technique, and constituent reconstruction. This paper explores a new technique called trajectory mapping. Trajectory mapping creates synoptic maps from asynoptically gathered data by advecting measurements backward or forward in time using analyzed wind fields. A significant portion of this work is devoted to an analysis of errors in synoptic trajectory maps associated with the calculation of individual parcel trajectories. In particular, we have considered (1) calculational errors; (2) uncertainties in the values and locations of constituent measurements, (3) errors incurred by neglecting diabatic effects, and (4) sensitivity to differences in wind field analyses. These studies reveal that the global fields derived from the advection of large numbers of measurements are relatively insensitive to the errors in the individual trajectories. The trajectory mapping technique has been successfully applied to a variety of problems. In this paper, the following two applications demonstrate the usefulness of the technique: an analysis of dynamical wave-breaking events and an examination of Upper Atmosphere Research Satellite data accuracy

Boundary Conditions for the Einstein Evolution System

New boundary conditions are constructed and tested numerically for a general first-order form of the Einstein evolution system. These conditions prevent constraint violations from entering the computational domain through timelike boundaries, allow the simulation of isolated systems by preventing physical gravitational waves from entering the computational domain, and are designed to be compatible with the fixed-gauge evolutions used here. These new boundary conditions are shown to be effective in limiting the growth of constraints in 3D non-linear numerical evolutions of dynamical black-hole spacetimes.Comment: 21 pages, 12 figures, submitted to PR

Photometric Redshift Estimation Using Spectral Connectivity Analysis

The development of fast and accurate methods of photometric redshift estimation is a vital step towards being able to fully utilize the data of next-generation surveys within precision cosmology. In this paper we apply a specific approach to spectral connectivity analysis (SCA; Lee & Wasserman 2009) called diffusion map. SCA is a class of non-linear techniques for transforming observed data (e.g., photometric colours for each galaxy, where the data lie on a complex subset of p-dimensional space) to a simpler, more natural coordinate system wherein we apply regression to make redshift predictions. As SCA relies upon eigen-decomposition, our training set size is limited to ~ 10,000 galaxies; we use the Nystrom extension to quickly estimate diffusion coordinates for objects not in the training set. We apply our method to 350,738 SDSS main sample galaxies, 29,816 SDSS luminous red galaxies, and 5,223 galaxies from DEEP2 with CFHTLS ugriz photometry. For all three datasets, we achieve prediction accuracies on par with previous analyses, and find that use of the Nystrom extension leads to a negligible loss of prediction accuracy relative to that achieved with the training sets. As in some previous analyses (e.g., Collister & Lahav 2004, Ball et al. 2008), we observe that our predictions are generally too high (low) in the low (high) redshift regimes. We demonstrate that this is a manifestation of attenuation bias, wherein measurement error (i.e., uncertainty in diffusion coordinates due to uncertainty in the measured fluxes/magnitudes) reduces the slope of the best-fit regression line. Mitigation of this bias is necessary if we are to use photometric redshift estimates produced by computationally efficient empirical methods in precision cosmology.Comment: Resubmitted to MNRAS (11 pages, 8 figures

Coarsening Kinetics of a Two Dimensional O(2) Ginzburg-Landau Model: Effect of Reversible Mode Coupling

We investigate, via numerical simulations, the phase ordering kinetics of a two- dimensional soft-spin O(2) Ginzburg-Landau model when a reversible mode cou- pling is included via the conserved conjugate momentum of the spin order parameter (the model E). Coarsening of the system, when quenched from a dis- ordered state to zero temperature, is observed to be enhanced by the existence of the mode coupling terms. The growth of the characteristic length scale L(t) exhibits an effective super-diffusive growth exponent that can be interpreted as a positive logarithmic-like correction to a diffusive growth, i.e., L(t) ~ (t ln t)^{1/2}. In order to understand this behavior, we introduced a simple phenomenological model of coarsening based on the annihilation dynamics of a vortex-antivortex pair, incorporating the effect of vortex inertia and logarithmically divergent mobility of the vortex. With a suitable choice of the parameters, numerical solutions of the simple model can fit the full simulation results very adequately. The effective growth exponent in the early time stage is larger due to the effect of the vortex inertia, which crosses over into late time stage characterized by positive logarithmic correction to a diffusive growth. We also investigated the non-equilibrium autocorrelation function from which the so called {\lambda} exponent can be extracted. We get {\lambda} = 1.99(2) which is distinctively larger than the value of {\lambda} = 1.17 for the purely dissipative model-A dynamics of non-conserved O(2) models.Comment: 19 pages, 8 figure

Reaching beyond pregnant women to eliminate mother-to-child transmission of syphilis in Africa

Congenital syphilis is a devastating disease that can be prevented by screening and treatment of infected pregnant women. The WHO is leading a global initiative to eliminate mother-to-child-transmission of syphilis with a goal of 50 congenital syphilis cases per 100,000 live births and targets of 95% antenatal care, 95% syphilis testing, and 95% treatment coverage. We estimated current congenital syphilis rates for 43 African countries, and additional scenarios in a subset of 9 countries. Our analysis suggested that only 4 of 43 countries are likely to currently have a congenital syphilis rate 50 per 100,000 live births, and none of the 9 countries could reach this goal even in 5 different scenarios with improved services. To achieve the eliminate mother-to-child-transmission goal, it appears necessary to intervene beyond services for pregnant women, and decrease prevalence of syphilis in the general population as well

Sandpiles on multiplex networks

We introduce the sandpile model on multiplex networks with more than one type of edge and investigate its scaling and dynamical behaviors. We find that the introduction of multiplexity does not alter the scaling behavior of avalanche dynamics; the system is critical with an asymptotic power-law avalanche size distribution with an exponent $\tau = 3/2$ on duplex random networks. The detailed cascade dynamics, however, is affected by the multiplex coupling. For example, higher-degree nodes such as hubs in scale-free networks fail more often in the multiplex dynamics than in the simplex network counterpart in which different types of edges are simply aggregated. Our results suggest that multiplex modeling would be necessary in order to gain a better understanding of cascading failure phenomena of real-world multiplex complex systems, such as the global economic crisis.Comment: 7 pages, 7 figure

Structural insights into the autoregulation and cooperativity of the human transcription factor Ets-2

Ets-2, like its closely related homologue Ets-1, is a member of the Ets family of DNA binding transcription factors. Both proteins are subject to multiple levels of regulation of their DNA binding and transactivation properties. One such regulatory mechanism is the presence of an autoinhibitory module, which in Ets-1 allosterically inhibits the DNA binding activity. This inhibition can be relieved by interaction with protein partners or cooperative binding to closely separated Ets binding sites in a palindromic arrangement. In this study we describe the 2.5 Å resolution crystal structure of a DNA complex of the Ets-2 Ets domain. The Ets domain crystallized with two distinct species in the asymmetric unit, which closely resemble the autoinhibited and DNA bound forms of Ets-1. This discovery prompted us to re-evaluate the current model for the autoinhibitory mechanism and the structural basis for cooperative DNA binding. In contrast to Ets-1, in which the autoinhibition is caused by a combination of allosteric and steric mechanisms, we were unable to find clear evidence for the allosteric mechanism in Ets-2. We also demonstrated two possibly distinct types of cooperative binding to substrates with Ets binding motifs separated by four and six base pairs and suggest possible molecular mechanisms for this behavior