University of Arizona

About: University of Arizona is a education organization based out in Tucson, Arizona, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 63805 authors who have published 155998 publications receiving 6854915 citations. The organization is also known as: UA & U of A.

Galaxies in a simulated $\Lambda$CDM Universe I: cold mode and hot cores

Abstract: We study the formation of galaxies in a (50 Mpc/h)^3 cosmological simulation (2x288^3 particles), evolved using the entropy conserving SPH code Gadget-2. Most of the baryonic mass in galaxies of all masses is originally acquired through filamentary "cold mode" accretion of gas that was never shock heated to its halo virial temperature, confirming the key feature of our earlier results obtained with a different SPH code (Keres et al. 2005). Atmospheres of hot, virialized gas develop in halos above ~2.5e11 Msun, a transition mass that is nearly constant from z=3 to z=0. Cold accretion persists in halos above the transition mass, especially at z>=2. It dominates the growth of galaxies in low mass halos at all times, and it is the main driver of the cosmic star formation history. Satellite galaxies have accretion rates similar to central galaxies of the same baryonic mass at high redshifts, but they have less accretion than comparable central galaxies at low redshift. Relative to our earlier results, the Gadget-2 simulations predict much lower rates of "hot mode" accretion from the virialized gas component of massive halos. At z<=1, typical hot accretion rates in halos above 5e12 Msun are below 1 Msun/yr, even though our simulation does not include AGN heating or other forms of "preventive" feedback. The inner density profiles of hot gas in these halos are shallow, with long associated cooling times. The cooling recipes typically used in semi-analytic models can overestimate the accretion rates in these halos by orders of magnitude, so such models may overemphasize the role of preventive feedback in producing observed galaxy masses and colors. A fraction of the massive halos develop cuspy profiles and significant cooling rates between z=1 and z=0, a redshift trend similar to the observed trend in the frequency of cooling flow clusters.

Policy Uncertainty and Corporate Investment

Abstract: Using a news-based index of policy uncertainty, we document a strong negative relationship between firm-level capital investment and the aggregate level of uncertainty associated with future policy and regulatory outcomes. More importantly, we find evidence that the relation between policy uncertainty and capital investment is not uniform in the cross-section, being significantly stronger for firms with a higher degree of investment irreversibility and for firms that are more dependent on government spending. Our results lend empirical support to the notion that policy uncertainty can depress corporate investment by inducing precautionary delays due to investment irreversibility.

Missing Data: A Gentle Introduction

Abstract: Part 1. A Gentle Introduction to Missing Data. The Concept of Missing Data. The Prevalence of Missing Data. Why Data Might Be Missing. The Impact of Missing Data. What's Missing in the Missing Data Literature? A Cost-Benefit Approach to Missing Data. Missing Data - Not Just for Statisticians Anymore. Part 2. Consequences of Missing Data. Three General Consequences of Missing Data. Consequences of Missing Data on Construct Validity. Consequences of Missing Data on Internal Validity. Consequences on Causal Generalization. Summary. Part 3. Classifying Missing Data. "The Silence That Betokens". The Current Classification System: Mechanisms of Missing Data. Expanding the Classification System. Summary. Part 4. Preventing Missing Data by Design. Overall Study Design. Characteristics of the Target Population and the Sample. Data Collection and Measurement. Treatment Implementation. Data Entry Process. Summary. Part 5. Diagnostic Procedures. Traditional Diagnostics. Dummy Coding Missing Data. Numerical Diagnostic Procedures. Graphical Diagnostic Procedures. Summary. Part 6. The Selection of Data Analytic Procedures. Preliminary Steps. Decision Making. Summary. Part 7. Data Deletion Methods for Handling Missing Data. Data Sets. Complete Case Method. Available Case Method. Available Item Method. Individual Growth Curve Analysis. Multisample Analyses. Summary. Part 8. Data Augmentation Procedures. Model-Based Procedures. Markov Chain Monte Carlo. Adjustment Methods. Summary. Part 9. Single Imputation Procedures. Constant Replacement Methods. Random Value Imputation. Nonrandom Value Imputation: Single Condition. Nonrandom Value Imputation: Multiple Conditions. Summary. Part 10. Multiple Imputation. The MI Process. Summary. Part 11. Reporting Missing Data and Results. APA Task Force Recommendations. Missing Data and Study Stages. TFSI Recommendations and Missing Data. Reporting Format. Summary. Part 12. Epilogue.

Innate Immunity and Asthma Risk in Amish and Hutterite Farm Children

Abstract: BackgroundThe Amish and Hutterites are U.S. agricultural populations whose lifestyles are remarkably similar in many respects but whose farming practices, in particular, are distinct; the former follow traditional farming practices whereas the latter use industrialized farming practices. The populations also show striking disparities in the prevalence of asthma, and little is known about the immune responses underlying these disparities. MethodsWe studied environmental exposures, genetic ancestry, and immune profiles among 60 Amish and Hutterite children, measuring levels of allergens and endotoxins and assessing the microbiome composition of indoor dust samples. Whole blood was collected to measure serum IgE levels, cytokine responses, and gene expression, and peripheral-blood leukocytes were phenotyped with flow cytometry. The effects of dust extracts obtained from Amish and Hutterite homes on immune and airway responses were assessed in a murine model of experimental allergic asthma. ResultsDespite the...

Relationships between body size and abundance in ecology.

Abstract: Body size is perhaps the most fundamental property of an organism and is related to many biological traits, including abundance. The relationship between abundance and body size has been extensively studied in an attempt to quantify the form of the relationship and to understand the processes that generate it. However, progress has been impeded by the underappreciated fact that there are four distinct, but interrelated, relationships between size and abundance that are often confused in the literature. Here, we review and distinguish between these four patterns, and discuss the linkages between them. We argue that a synthetic understanding of size–abundance relationships will result from more detailed analyses of individual patterns and from careful consideration of how and why the patterns are related.