An Automated Approach to the Study and Classification of Colliding and Interacting Galaxies

Colliding galaxies are perhaps the greatest events changing and evolving our Universe. Consequently, the need for an understanding of how that interaction originated is very important. This thesis presents a framework in which the study of these events can be conducted in a timely and efficient manner. A genetic algorithm coupled with an initial conditions generator, a physics engine and an analysis package performs an automated search to visually match an unknown galactic interaction with a known event, thus providing the starting conditions that created such an interaction

The Role of Bulge Formation in the Homogenization of Stellar Populations at z∼2z\sim2 as revealed by Internal Color Dispersion in CANDELS

We use data from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey to study how the spatial variation in the stellar populations of galaxies relate to the formation of galaxies at $1.5 < z < 3.5$. We use the Internal Color Dispersion (ICD), measured between the rest-frame UV and optical bands, which is sensitive to age (and dust attenuation) variations in stellar populations. The ICD shows a relation with the stellar masses and morphologies of the galaxies. Galaxies with the largest variation in their stellar populations as evidenced by high ICD have disk-dominated morphologies (with S\'{e}rsic indexes $< 2$) and stellar masses between $10 < \mathrm{Log~M/ M_\odot}< 11$. There is a marked decrease in the ICD as the stellar mass and/or the S\'ersic index increases. By studying the relations between the ICD and other galaxy properties including sizes, total colors, star-formation rate, and dust attenuation, we conclude that the largest variations in stellar populations occur in galaxies where the light from newly, high star-forming clumps contrasts older stellar disk populations. This phase reaches a peak for galaxies only with a specific stellar mass range, $10 < \mathrm{Log~M/ M_\odot} < 11$, and prior to the formation of a substantial bulge/spheroid. In contrast, galaxies at higher or lower stellar masses, and/or higher S\'{e}rsic index ($n > 2$) show reduced ICD values, implying a greater homogeneity of their stellar populations. This indicates that if a galaxy is to have both a quiescent bulge along with a star forming disk, typical of Hubble Sequence galaxies, this is most common for stellar masses $10 < \mathrm{Log~M/M_\odot} < 11$ and when the bulge component remains relatively small ($n<2$).Comment: 15 pages, 14 figure

Measuring the Scatter in the Cluster Optical Richness-Mass Relation with Machine Learning

The distribution of massive clusters of galaxies depends strongly on the total cosmic mass density, the mass variance, and the dark energy equation of state. As such, measures of galaxy clusters can provide constraints on these parameters and even test models of gravity, but only if observations of clusters can lead to accurate estimates of their total masses. Here, we carry out a study to investigate the ability of a blind spectroscopic survey to recover accurate galaxy cluster masses through their line-of- sight velocity dispersions (LOSVD) using probability based and machine learning methods. We focus on the Hobby Eberly Telescope Dark Energy Experiment (HETDEX), which will employ new Visible Integral-Field Replicable Unit Spectrographs (VIRUS), over 420 degree2 on the sky with a 1/4.5 fill factor. VIRUS covers the blue/optical portion of the spectrum (3500 - 5500 Å), allowing surveys to measure redshifts for a large sample of galaxies out to z < 0.5 based on their absorption or emission (e.g., [O II], Mg II, Ne V) features. We use a detailed mock galaxy catalog from a semi-analytic model to simulate surveys observed with VIRUS, including: (1) Survey, a blind, HETDEX-like survey with an incomplete but uniform spectroscopic selection function; and (2) Targeted, a survey which targets clusters directly, obtaining spectra of all galaxies in a VIRUS-sized field. For both surveys, we include realistic uncertainties from galaxy magnitude and line-flux limits. We benchmark both surveys against spectroscopic observations with \perfect" knowledge of galaxy line-of-sight velocities. With Survey observations, we can recover cluster masses to ~ 0.1 dex which can be further improved to < 0.1 dex with Targeted observations. This level of cluster mass recovery provides important measurements of the intrinsic scatter in the optical richness-cluster mass relation, and enables constraints on the key cosmological parameter, σ8, to < 20%. As a demonstration of the methods developed previously, we present a pilot survey with integral field spectroscopy of ten galaxy clusters optically selected from the Sloan Digital Sky Survey's DR8 at z = 0.2 – 0.3. Eight of the clusters are rich (λ > 60) systems with total inferred masses (1.58 -17.37) ×1014 Mʘ (M200c), and two are poor (λ < 15) systems with inferred total masses ~ 0.5 × 1014 Mʘ (M200c). We use the Mitchell Spectrograph, (formerly the VIRUS-P spectrograph, a prototype of the HETDEX VIRUS instrument) located on the McDonald Observatory 2.7m telescope, to measure spectroscopic redshifts and line-of-sight velocities of the galaxies in and around each cluster, determine cluster membership and derive LOSVDs. We test both a LOSVD-cluster mass scaling relation and a machine learning based approach to infer total cluster mass. After comparing the cluster mass estimates to the literature, we use these independent cluster mass measurements to estimate the absolute cluster mass scale, and intrinsic scatter in the optical richness-mass relationship. We measure the intrinsic scatter in richness at fixed cluster mass to be σMǀλ = 0.27 ± 0.07 dex in excellent agreement with previous estimates of σMǀλ ~ 0.2 – 0.3 dex. We discuss the importance of the data used to train the machine learning methods and suggest various strategies to import the accuracy of the bias (offset) and scatter in the optical richness-cluster mass relation. This demonstrates the power of blind spectroscopic surveys such as HETDEX to provide robust cluster mass estimates which can aid in the determination of cosmological parameters and help to calibrate the observable-mass relation for future photometric large area-sky surveys

Low Rank plus Sparse Decomposition of ODFs for Improved Detection of Group-level Differences and Variable Correlations in White Matter

A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF). Recent advances in MRI acquisition make it possible to use high quality diffusion weighted protocols (multi-shell, large number of gradient directions) for routine in vivo study of white matter architecture. The dimensionality of these data sets is however often reduced to simplify statistical analysis. While these approaches may detect large group differences, they do not fully capitalize on all acquired image volumes. Incorporation of all available diffusion information in the analysis however risks biasing the outcome by outliers. Here we propose a statistical analysis method operating on the ODF, either the diffusion ODF or fiber ODF. To avoid outlier bias and reliably detect voxelwise group differences and correlations with demographic or behavioral variables, we apply the Low-Rank plus Sparse (L + S) matrix decomposition on the voxelwise ODFs which separates the sparse individual variability in the sparse matrix S whilst recovering the essential ODF features in the low-rank matrix L. We demonstrate the performance of this ODF L + S approach by replicating the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset. The volume of positive findings agrees with and expands on the volume found by TBSS, Connectivity based fixel enhancement and Connectometry. In the same dataset we further localize the correlations of brain structure with neurocognitive measures such as fluid intelligence and episodic memory. The presented ODF L + S approach will aid in the full utilization of all acquired diffusion weightings leading to the detection of smaller group differences in clinically relevant settings as well as in neuroscience applications.Comment: 20 pages, 11 figures, 5 supplementary figure

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics

Analysis of the oral and dental hygiene habits of school children.

El objetivo de la siguiente investigación es analizar el desarrollo que han tenido los conocimientos y hábitos de los estudiantes en la higiene bucodental. Para el desarrollo de este trabajo, se utilizó un estudio descriptivo, estableciendo un programa de prevención de salud oral. Los datos se obtuvieron mediante un cuestionario de conocimientos, analizados de forma descriptiva. Se pudo concluir que los niños que recibieron solo una charla no obtuvieron los resultados esperados, en comparación con aquellos niños en los cuales se utilizó herramientas interactivas para enseñar, los cuales aprendieron de mejor manera y disminuyendo sus lesiones dentales. Los resultados del programa parecen ser más positivos que negativos, demostrando que los niños aprenden mejor cuando se utiliza la didáctica para enseñar.The objective of the following investigation is to analyze the development of students' knowledge and habits in oral hygiene. For the development of this work, a descriptive study was used, establishing an oral health prevention program. Data were obtained through a knowledge questionnaire, analyzed descriptively. It was concluded that the children who received only one talk did not obtain the expected results, compared to those children in whom interactive tools were used to teach, who learned better, and their dental injuries decreased. The results of the program seem to be more positive than negative, showing that children learn better when didactics are used to teach

The Role of Bulge Formation in the Homogenization of Stellar Populations at \u3cem\u3eZ\u3c/em\u3e ~ 2 as Revealed by Internal Color Dispersion in CANDELS

We use data from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey to study how the spatial variation in the stellar populations of galaxies relates to the formation of galaxies at 1.5 \u3c z \u3c 3.5. We use the internal color dispersion (ICD), measured between the rest-frame UV and optical bands, which is sensitive to age (and dust attenuation) variations in stellar populations. The ICD shows a relation with the stellar masses and morphologies of the galaxies. Galaxies with the largest variation in their stellar populations as evidenced by high ICD have disk-dominated morphologies (with Sérsic indexes M/M⊙) \u3c 11. There is a marked decrease in the ICD as the stellar mass and/or the Sérsic index increases. By studying the relations between the ICD and other galaxy properties including size, total color, star formation rate, and dust attenuation, we conclude that the largest variations in stellar populations occur in galaxies where the light from newly, high star-forming clumps contrasts older stellar disk populations. This phase reaches a peak for galaxies only with a specific stellar mass range, 10 \u3c log(M/M⊙) \u3c 11, and prior to the formation of a substantial bulge/spheroid. In contrast, galaxies at higher or lower stellar masses and/or higher Sérsic index (n \u3e 2) show reduced ICD values, implying a greater homogeneity of their stellar populations. This indicates that if a galaxy is to have a quiescent bulge along with a star-forming disk, typical of Hubble sequence galaxies, this is most common for stellar masses 10 \u3c log(M/M⊙) \u3c 11 and when the bulge component remains relatively small (n \u3e 2)