Magnetic Field Amplification by Small-Scale Dynamo Action: Dependence on Turbulence Models and Reynolds and Prandtl Numbers

The small-scale dynamo is a process by which turbulent kinetic energy is converted into magnetic energy, and thus is expected to depend crucially on the nature of turbulence. In this work, we present a model for the small-scale dynamo that takes into account the slope of the turbulent velocity spectrum v(l) ~ l^theta, where l and v(l) are the size of a turbulent fluctuation and the typical velocity on that scale. The time evolution of the fluctuation component of the magnetic field, i.e., the small-scale field, is described by the Kazantsev equation. We solve this linear differential equation for its eigenvalues with the quantum-mechanical WKB-approximation. The validity of this method is estimated as a function of the magnetic Prandtl number Pm. We calculate the minimal magnetic Reynolds number for dynamo action, Rm_crit, using our model of the turbulent velocity correlation function. For Kolmogorov turbulence (theta=1/3), we find that the critical magnetic Reynolds number is approximately 110 and for Burgers turbulence (theta=1/2) approximately 2700. Furthermore, we derive that the growth rate of the small-scale magnetic field for a general type of turbulence is Gamma ~ Re^((1-theta)/(1+theta)) in the limit of infinite magnetic Prandtl numbers. For decreasing magnetic Prandtl number (down to Pm approximately larger than 10), the growth rate of the small-scale dynamo decreases. The details of this drop depend on the WKB-approximation, which becomes invalid for a magnetic Prandtl number of about unity.Comment: 13 pages, 8 figures; published in Phys. Rev. E 201

Analysis of the 24-Hour Activity Cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought (ACT) Study

The 24-hour activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We illustrate and compare the use of three popular approaches, namely isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) for modeling outcome associations with the 24HAC. We apply these approaches to assess an association with a cognitive outcome, measured by CASI item response theory (IRT) score, in a cohort of 1034 older adults (mean [range] age = 77 [65-100]; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7 days. We highlight differences in assumptions between the three approaches, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. ISM is easiest to apply and interpret; however, the typical ISM model assumes a linear association. CoDA specifies a non-linear association through isometric logratio transformations that are more challenging to apply and interpret. LPA can classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications which is often ignored. The selection of the most appropriate method should be guided by the scientific questions of interest and the applicability of each model's assumptions. The analytic results did not suggest that less time spent on SB and more in PA was associated with better cognitive function. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.Comment: 51 pages, 11 tables, 8 figure

Resting heart rate as a low tech predictor of coronary events in women: prospective cohort study

Objective To evaluate resting heart rate as an independent predictor of cardiovascular risk in women

Flavor Physics in an SO(10) Grand Unified Model

In supersymmetric grand-unified models, the lepton mixing matrix can possibly affect flavor-changing transitions in the quark sector. We present a detailed analysis of a model proposed by Chang, Masiero and Murayama, in which the near-maximal atmospheric neutrino mixing angle governs large new b -> s transitions. Relating the supersymmetric low-energy parameters to seven new parameters of this SO(10) GUT model, we perform a correlated study of several flavor-changing neutral current (FCNC) processes. We find the current bound on B(tau -> mu gamma) more constraining than B(B -> X_s gamma). The LEP limit on the lightest Higgs boson mass implies an important lower bound on tan beta, which in turn limits the size of the new FCNC transitions. Remarkably, the combined analysis does not rule out large effects in B_s-B_s-bar mixing and we can easily accomodate the large CP phase in the B_s-B_s-bar system which has recently been inferred from a global analysis of CDF and DO data. The model predicts a particle spectrum which is different from the popular Constrained Minimal Supersymmetric Standard Model (CMSSM). B(tau -> mu gamma) enforces heavy masses, typically above 1 TeV, for the sfermions of the degenerate first two generations. However, the ratio of the third-generation and first-generation sfermion masses is smaller than in the CMSSM and a (dominantly right-handed) stop with mass below 500 GeV is possible.Comment: 44 pages, 5 figures. Footnote and references added, minor changes, Fig. 2 corrected; journal versio

Ecological Homogenization of Urban USA

A visually apparent but scientifically untested outcome of land-use change is homogenization across urban areas, where neighborhoods in different parts of the country have similar patterns of roads, residential lots, commercial areas, and aquatic features. We hypothesize that this homogenization extends to ecological structure and also to ecosystem functions such as carbon dynamics and microclimate, with continental-scale implications. Further, we suggest that understanding urban homogenization will provide the basis for understanding the impacts of urban land-use change from local to continental scales. Here, we show how multi-scale, multi-disciplinary datasets from six metropolitan areas that cover the major climatic regions of the US (Phoenix, AZ; Miami, FL; Baltimore, MD; Boston, MA; Minneapolis–St Paul, MN; and Los Angeles, CA) can be used to determine how household and neighborhood characteristics correlate with land-management practices, land-cover composition, and landscape structure and ecosystem functions at local, regional, and continental scales

Ubiquitous outflows in DEEP2 spectra of star-forming galaxies at z=1.4

Galactic winds are a prime suspect for the metal enrichment of the intergalactic medium and may have a strong influence on the chemical evolution of galaxies and the nature of QSO absorption line systems. We use a sample of 1406 galaxy spectra at z~1.4 from the DEEP2 redshift survey to show that blueshifted Mg II 2796, 2803 A absorption is ubiquitous in starforming galaxies at this epoch. This is the first detection of frequent outflowing galactic winds at z~1. The presence and depth of absorption are independent of AGN spectral signatures or galaxy morphology; major mergers are not a prerequisite for driving a galactic wind from massive galaxies. Outflows are found in coadded spectra of galaxies spanning a range of 30x in stellar mass and 10x in star formation rate (SFR), calibrated from K-band and from MIPS IR fluxes. The outflows have column densities of order N_H ~ 10^20 cm^-2 and characteristic velocities of ~ 300-500 km/sec, with absorption seen out to 1000 km/sec in the most massive, highest SFR galaxies. The velocities suggest that the outflowing gas can escape into the IGM and that massive galaxies can produce cosmologically and chemically significant outflows. Both the Mg II equivalent width and the outflow velocity are larger for galaxies of higher stellar mass and SFR, with V_wind ~ SFR^0.3, similar to the scaling in low redshift IR-luminous galaxies. The high frequency of outflows in the star-forming galaxy population at z~1 indicates that galactic winds occur in the progenitors of massive spirals as well as those of ellipticals. The increase of outflow velocity with mass and SFR constrains theoretical models of galaxy evolution that include feedback from galactic winds, and may favor momentum-driven models for the wind physics.Comment: Accepted by ApJ. 25 pages, 17 figures. Revised to add discussions of intervening absorbers and AGN-driven outflows; conclusions unchange

Introduction to A Compendium of Strategies to Prevent Healthcare-Associated Infections In Acute-Care Hospitals: 2022 Updates.

Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients, leading to substantial morbidity, mortality, and excess healthcare expenditures, and persistent gaps remain between what is recommended and what is practiced.The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others

Climate and lawn management interact to control C4 plant distribution in residential lawns across seven U.S. cities.

Author Posting. © Ecological Society of America, 2019. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Trammell, T. L. E., Pataki, D. E., Still, C. J., Ehleringer, J. R., Avolio, M. L., Bettez, N., Cavender-Bares, J., Groffman, P. M., Grove, M., Hall, S. J., Heffernan, J., Hobbie, S. E., Larson, K. L., Morse, J. L., Neill, C., Nelson, K. C., O'Neil-Dunne, J., Pearse, W. D., Chowdhury, R. R., Steele, M., & Wheeler, M. M. Climate and lawn management interact to control C4 plant distribution in residential lawns across seven U.S. cities. Ecological Applications, 29(4), (2019): e01884, doi: 10.1002/eap.1884.In natural grasslands, C4 plant dominance increases with growing season temperatures and reflects distinct differences in plant growth rates and water use efficiencies of C3 vs. C4 photosynthetic pathways. However, in lawns, management decisions influence interactions between planted turfgrass and weed species, leading to some uncertainty about the degree of human vs. climatic controls on lawn species distributions. We measured herbaceous plant carbon isotope ratios (δ13C, index of C3/C4 relative abundance) and C4 cover in residential lawns across seven U.S. cities to determine how climate, lawn plant management, or interactions between climate and plant management influenced C4 lawn cover. We also calculated theoretical C4 carbon gain predicted by a plant physiological model as an index of expected C4 cover due to growing season climatic conditions in each city. Contrary to theoretical predictions, plant δ13C and C4 cover in urban lawns were more strongly related to mean annual temperature than to growing season temperature. Wintertime temperatures influenced the distribution of C4 lawn turf plants, contrary to natural ecosystems where growing season temperatures primarily drive C4 distributions. C4 cover in lawns was greatest in the three warmest cities, due to an interaction between climate and homeowner plant management (e.g., planting C4 turf species) in these cities. The proportion of C4 lawn species was similar to the proportion of C4 species in the regional grass flora. However, the majority of C4 species were nonnative turf grasses, and not of regional origin. While temperature was a strong control on lawn species composition across the United States, cities differed as to whether these patterns were driven by cultivated lawn grasses vs. weedy species. In some cities, biotic interactions with weedy plants appeared to dominate, while in other cities, C4 plants were predominantly imported and cultivated. Elevated CO2 and temperature in cities can influence C3/C4 competitive outcomes; however, this study provides evidence that climate and plant management dynamics influence biogeography and ecology of C3/C4 plants in lawns. Their differing water and nutrient use efficiency may have substantial impacts on carbon, water, energy, and nutrient budgets across cities.This research was funded by a series of collaborative grants from the U.S. National Science Foundation Macrosystems Biology Program (EF‐1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 121238320). The authors thank La'Shaye Ervin, William Borrowman, Moumita Kundu, and Barbara Uhl for field and laboratory assistance