State Space Analysis of Dominant Structures in Dynamic Social Systems

Many systems involving human relationships are modeled as dynamic systems, as diverse as urban population growth, diffusion of innovations, spread of viruses, and supply chain management. A fundamental assumption is that these systems contain variables which accumulate and deplete over time (people, innovation adoptions, infections, and orders), and whose dynamics are determined by societal rules and human decision making processes. These assumptions allow the system to be formally expressed by ordinary differential equations which are often nonlinear and contain multiple state variables and feedback loops. Analytical methods have been developed to identify the dominant feedback loops which primarily influence the behavior of the system. However, these dominance methods can produce conflicting results and are often performed in the time-domain under specific initial conditions. This thesis takes a state-space approach to dominance analysis and, in the process, re-examines the definition of dominance. A formal, mathematical definition of dominance is proposed and an analytical procedure is developed and applied to previously studied models. The method produces results consistent with previous analyses and is able explain inconsistencies between other methods. The procedure is then applied in the state-domain and used to identify state-space regions in which certain feedback loops dominate behavior. The procedure is then used to identify the stability properties of equilibria, and a theorem is developed to provide a necessary condition for stability, based on the dominance of balancing (negative) feedback. Lastly, the method is applied to a problem in public health in which a model of the supply and demand of cancer control services is analyzed. The dominant feedback loops are identified for the purpose of revealing potential sources of health disparities between distinct population segments. The analysis revealed the existence of a tipping point condition associated with a single unstable equilibrium point which influences population health outcomes. Furthermore, trajectories near the unstable equilibrium point are dominated by reinforcing (positive) feedback loops which affect the proportion of people seeking cancer control services. These loops result in either virtuous or vicious cycles, depending on which side of the tipping point the system is operating in the state-space. The methods were then used to identify potential leverage points in the system in which small parameter changes cause significant behavior changes. Potential avenues for future dominance research are discussed as well as future transdisciplinary research in public health and implementation science

Tuning localized plasmons in nanostructured substrates for surface-enhanced Raman scattering

Comprehensive reflectivity mapping of the angular dispersion of nanostructured arrays comprising of inverted pyramidal pits is demonstrated. By comparing equivalently structured dielectric and metallic arrays, diffraction and plasmonic features are readily distinguished. While the diffraction features match expected theory, localised plasmons are also observed with severely flattened energy dispersions. Using pit arrays with identical pitch, but graded pit dimensions, energy scaling of the localised plasmon is observed. These localised plasmons are found to match a simple model which confines surface plasmons onto the pit sidewalls thus allowing an intuitive picture of the plasmons to be developed. This model agrees well with a 2D finite-difference time-domain simulation which shows the same dependence on pit dimensions. We believe these tuneable plasmons are responsible for the surface-enhancement of the Raman scattering (SERS) of an attached layer of benzenethiol molecules. Such SERS substrates have a wide range of applications both in security, chemical identification, environmental monitoring and healthcare

Spitzer Survey of the Large Magellanic Cloud, Surveying the Agents of a Galaxy's Evolution (SAGE) I: Overview and Initial Results

We are performing a uniform and unbiased, ~7x7 degrees imaging survey of the Large Magellanic Cloud (LMC), using the IRAC and MIPS instruments on board the Spitzer Space Telescope in order to survey the agents of a galaxy's evolution (SAGE), the interstellar medium (ISM) and stars in the LMC. The detection of diffuse ISM with column densities >1.2x10^21 H cm^-2 permits detailed studies of dust processes in the ISM. SAGE's point source sensitivity enables a complete census of newly formed stars with masses >3 solar masses that will determine the current star formation rate in the LMC. SAGE's detection of evolved stars with mass loss rates >1x10^-8 solar masses per year will quantify the rate at which evolved stars inject mass into the ISM of the LMC. The observing strategy includes two epochs in 2005, separated by three months, that both mitigate instrumental artifacts and constrain source variability. The SAGE data are non-proprietary. The data processing includes IRAC and MIPS pipelines and a database for mining the point source catalogs, which will be released to the community in support of Spitzer proposal cycles 4 and 5. We present initial results on the epoch 1 data with a special focus on the N79 and N83 region. The SAGE epoch 1 point source catalog has ~4 million sources. The point source counts are highest for the IRAC 3.6 microns band and decrease dramatically towards longer wavelengths consistent with the fact that stars dominate the point source catalogs and that the dusty objects, e.g. young stellar objects and dusty evolved stars that detected at the longer wavelengths, are rare in comparison. We outline a strategy for identifying foreground MW stars, that may comprise as much as 18% of the source list, and background galaxies, that may comprise ~12% of the source list.Comment: Accepted by the Astronomical Journa

Spitzer survey of the Large Magellanic Cloud, surveying the agents of a galaxy's evolution (SAGE). IV. Dust properties in the interstellar medium

The goal of this paper is to present the results of a preliminary analysis of the extended infrared (IR) emission by dust in the interstellar medium (ISM) of the Large Magellanic Cloud (LMC). We combine Spitzer Surveying the Agents of Galaxy Evolution (SAGE) and Infrared Astronomical Satellite (IRAS) data and correlate the infrared emission with gas tracers of H I, CO, and Hα. We present a global analysis of the infrared emission as well as detailed modeling of the spectral energy distribution (SED) of a few selected regions. Extended emission by dust associated with the neutral, molecular, and diffuse ionized phases of the ISM is detected at all IR bands from 3.6 μm to 160 μm. The relative abundance of the various dust species appears quite similar to that in the Milky Way (MW) in all the regions we have modeled. We construct maps of the temperature of large dust grains. The temperature map shows variations in the range 12.1-34.7 K, with a systematic gradient from the inner to outer regions, tracing the general distribution of massive stars and individual H II regions as well as showing warmer dust in the stellar bar. This map is used to derive the far-infrared (FIR) optical depth of large dust grains. We find two main departures in the LMC with respect to expectations based on the MW: (1) excess mid-infrared (MIR) emission near 70 μm, referred to as the 70 μm excess, and (2) departures from linear correlation between the FIR optical depth and the gas column density, which we refer to as FIR excess emission. The 70 μm excess increases gradually from the MW to the LMC to the Small Magellanic Cloud (SMC), suggesting evolution with decreasing metallicity. The excess is associated with the neutral and diffuse ionized gas, with the strongest excess region located in a loop structure next to 30 Dor. We show that the 70 μm excess can be explained by a modification of the size distribution of very small grains with respect to that in the MW, and a corresponding mass increase of ≃13% of the total dust mass in selected regions. The most likely explanation is that the 70 μm excess is due to the production of large very small grains (VSG) through erosion of larger grains in the diffuse medium. This FIR excess could be due to intrinsic variations of the dust/gas ratio, which would then vary from 4.6 to 2.3 times lower than the MW values across the LMC, but X_(CO) values derived from the IR emission would then be about three times lower than those derived from the Virial analysis of the CO data. We also investigate the possibility that the FIR excess is associated with an additional gas component undetected in the available gas tracers. Assuming a constant dust abundance in all ISM phases, the additional gas component would have twice the known H I mass. We show that it is plausible that the FIR excess is due to cold atomic gas that is optically thick in the 21 cm line, while the contribution by a pure H_2 phase with no CO emission remains a possible explanation

ISSCR standards for the use of human stem cells in basic research.

The laboratory culture of human stem cells seeks to capture a cellular state as an in vitro surrogate of a biological system. For the results and outputs from this research to be accurate, meaningful, and durable, standards that ensure reproducibility and reliability of the data should be applied. Although such standards have been previously proposed for repositories and distribution centers, no widely accepted best practices exist for laboratory research with human pluripotent and tissue stem cells. To fill that void, the International Society for Stem Cell Research has developed a set of recommendations, including reporting criteria, for scientists in basic research laboratories. These criteria are designed to be technically and financially feasible and, when implemented, enhance the reproducibility and rigor of stem cell research

The barley pan-genome reveals the hidden legacy of mutation breeding

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the ‘pan-genome’1). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley (Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions2. Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley—comprising landraces, cultivars and a wild barley—that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding

Asymmetric Wolbachia Segregation during Early Brugia malayi Embryogenesis Determines Its Distribution in Adult Host Tissues

Wolbachia are required for filarial nematode survival and fertility and contribute to the immune responses associated with human filarial diseases. Here we developed whole-mount immunofluorescence techniques to characterize Wolbachia somatic and germline transmission patterns and tissue distribution in Brugia malayi, a nematode responsible for lymphatic filariasis. In the initial embryonic divisions, Wolbachia segregate asymmetrically such that they occupy only a small subset of cells in the developing embryo, facilitating their concentration in the adult hypodermal chords and female germline. Wolbachia are not found in male reproductive tissues and the absence of Wolbachia from embryonic germline precursors in half of the embryos indicates Wolbachia loss from the male germline may occur in early embryogenesis. Wolbachia rely on fusion of hypodermal cells to populate adult chords. Finally, we detect Wolbachia in the secretory canal lumen suggesting living worms may release bacteria and/or their products into their host

Statistical HOmogeneous Cluster SpectroscopY (SHOCSY): an optimized statistical approach for clustering of ¹H NMR spectral data to reduce interference and enhance robust biomarkers selection.

We propose a novel statistical approach to improve the reliability of (1)H NMR spectral analysis in complex metabolic studies. The Statistical HOmogeneous Cluster SpectroscopY (SHOCSY) algorithm aims to reduce the variation within biological classes by selecting subsets of homogeneous (1)H NMR spectra that contain specific spectroscopic metabolic signatures related to each biological class in a study. In SHOCSY, we used a clustering method to categorize the whole data set into a number of clusters of samples with each cluster showing a similar spectral feature and hence biochemical composition, and we then used an enrichment test to identify the associations between the clusters and the biological classes in the data set. We evaluated the performance of the SHOCSY algorithm using a simulated (1)H NMR data set to emulate renal tubule toxicity and further exemplified this method with a (1)H NMR spectroscopic study of hydrazine-induced liver toxicity study in rats. The SHOCSY algorithm improved the predictive ability of the orthogonal partial least-squares discriminatory analysis (OPLS-DA) model through the use of "truly" representative samples in each biological class (i.e., homogeneous subsets). This method ensures that the analyses are no longer confounded by idiosyncratic responders and thus improves the reliability of biomarker extraction. SHOCSY is a useful tool for removing irrelevant variation that interfere with the interpretation and predictive ability of models and has widespread applicability to other spectroscopic data, as well as other "omics" type of data

MagAO Imaging of Long-period Objects (MILO). II. A Puzzling White Dwarf around the Sun-like Star HD 11112

The version of record, Rodigas, T. J. et al, 'MagAO Imaging of long-period objects (MILO). II. A puzzling white dwarf around the sun-like star HD 11112', The Astrophysical Journal, 831:177, November 2016, is available online via doi: 10.3847/0004-637X/831/2/177 © 2016. The American Astronomical Society. All rights reserved.HD 11112 is an old, Sun-like star that has a long-term radial velocity (RV) trend indicative of a massive companion on a wide orbit. Here we present direct images of the source responsible for the trend using the Magellan Adaptive Optics system. We detect the object (HD 11112B) at a separation of 2\fasec 2 (100 AU) at multiple wavelengths spanning 0.6-4 \microns ~and show that it is most likely a gravitationally-bound cool white dwarf. Modeling its spectral energy distribution (SED) suggests that its mass is 0.9-1.1 \msun, which corresponds to very high-eccentricity, near edge-on orbits from Markov chain Monte Carlo analysis of the RV and imaging data together. The total age of the white dwarf is $>2\sigma$ discrepant with that of the primary star under most assumptions. The problem can be resolved if the white dwarf progenitor was initially a double white dwarf binary that then merged into the observed high-mass white dwarf. HD 11112B is a unique and intriguing benchmark object that can be used to calibrate atmospheric and evolutionary models of cool white dwarfs and should thus continue to be monitored by RV and direct imaging over the coming years.Peer reviewedFinal Published versio

Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making

A common theoretical view is that attractor-like properties of neuronal dynamics underlie cognitive processing. However, although often proposed theoretically, direct experimental support for the convergence of neural activity to stable population patterns as a signature of attracting states has been sparse so far, especially in higher cortical areas. Combining state space reconstruction theorems and statistical learning techniques, we were able to resolve details of anterior cingulate cortex (ACC) multiple single-unit activity (MSUA) ensemble dynamics during a higher cognitive task which were not accessible previously. The approach worked by constructing high-dimensional state spaces from delays of the original single-unit firing rate variables and the interactions among them, which were then statistically analyzed using kernel methods. We observed cognitive-epoch-specific neural ensemble states in ACC which were stable across many trials (in the sense of being predictive) and depended on behavioral performance. More interestingly, attracting properties of these cognitively defined ensemble states became apparent in high-dimensional expansions of the MSUA spaces due to a proper unfolding of the neural activity flow, with properties common across different animals. These results therefore suggest that ACC networks may process different subcomponents of higher cognitive tasks by transiting among different attracting states