On the photon polarization in radiative B -> phi K gamma decay

The photon polarization in radiative decays B -> Y gamma is known to be a subtle probe of the effective Lagrangian structure and possible New Physics effects. We discuss exclusive decay mode B -> phi K gamma where the experimentally distinct final state makes analysis especially promising. The possibility to extract information on the photon polarization out of the data entirely depends on the partial waves interference pattern in the phi K system.Comment: RevTeX, 6 pages, 1 figure; the journal versio

Star-forming galaxies at very high redshifts

Analysis of the deepest available images of the sky, obtained by the Hubble Space Telescope, reveals a large number of candidate high-redshift galaxies. A catalogue of 1,683 objects is presented, with estimated redshifts ranging from $z=0$ to $z>6$. The high-redshift objects are interpreted as regions of star formation associated with the progenitors of present-day normal galaxies at epochs reaching to 95\% of the time to the Big Bang.Comment: 10 pages, LaTeX type, aaspp4.sty macro provided. Supplementary information, including the full catalog, plots of spectra and redshift likelihood functions for all the objects, and composite spectra, are available at ftp://ftp.ess.sunysb.edu/pub/hd

Non-canonical generalizations of slow-roll inflation models

We consider non-canonical generalizations of two classes of simple single-field inflation models. First, we study the non-canonical version of "ultra-slow roll" inflation, which is a class of inflation models for which quantum modes do not freeze at horizon crossing, but instead evolve rapidly on superhorizon scales. Second, we consider the non-canonical generalization of the simplest "chaotic" inflation scenario, with a potential dominated by a quartic (mass) term for the inflaton. We find a class of related non-canonical solutions with polynomial potentials, but with varying speed of sound. These solutions are characterized by a constant field velocity, and we dub such models {\it isokinetic} inflation. As in the canonical limit, isokinetic inflation has a slightly red-tilted power spectrum, consistent with current data. Unlike the canonical case, however, these models can have an arbitrarily small tensor/scalar ratio. Of particular interest is that isokinetic inflation is marked by a correlation between the tensor/scalar ratio and the amplitude of non-Gaussianity such that parameter regimes with small tensor/scalar ratio have {\it large} associated non-Gaussianity, which is a distinct observational signature.Comment: 12 pages, 3 figures, LaTeX; V2: version submitted to JCAP. References adde

Estimating PM\u3csub\u3e2.5\u3c/sub\u3ein Southern California using satellite data: Factors that affect model performance

Background: Studies of PM2.5 health effects are influenced by the spatiotemporal coverage and accuracy of exposure estimates. The use of satellite remote sensing data such as aerosol optical depth (AOD) in PM2.5 exposure modeling has increased recently in the US and elsewhere in the world. However, few studies have addressed this issue in southern California due to challenges with reflective surfaces and complex terrain. Methods: We examined the factors affecting the associations with satellite AOD using a two-stage spatial statistical model. The first stage estimated the temporal PM2.5/AOD relationships using a linear mixed effects model at 1 km resolution. The second stage accounted for spatial variation using geographically weighted regression. Goodness of fit for the final model was evaluated by comparing the daily PM2.5 concentrations generated by cross-validation (CV) with observations. These methods were applied to a region of southern California spanning from Los Angeles to San Diego. Results: Mean predicted PM2.5 concentration for the study domain was 8.84 µg m-3. Linear regression between CV predicted PM2.5 concentrations and observations had an R 2 of 0.80 and RMSE 2.25 µg m-3. The ratio of PM2.5 to PM10 proved an important variable in modifying the AOD/PM2.5 relationship (β = 14.79, p ≤ 0.001). Including this ratio improved model performance significantly (a 0.10 increase in CV R 2 and a 0.56 µg m-3 decrease in CV RMSE). Discussion: Utilizing the high-resolution MAIAC AOD, fine-resolution PM2.5 concentrations can be estimated where measurements are sparse. This study adds to the current literature using remote sensing data to achieve better exposure data in the understudied region of Southern California. Overall, we demonstrate the usefulness of MAIAC AOD and the importance of considering coarser particles in dust prone areas

Spatial particulate fields during highwinds in the imperial valley, California

We examined windblown dust within the Imperial Valley (CA) during strong springtime west-southwesterly (WSW) wind events. Analysis of routine agency meteorological and ambient particulate matter (PM) measurements identified 165 high WSW wind events between March and June 2013 to 2019. The PM concentrations over these days are higher at northern valley monitoring sites, with daily PM mass concentration of particles less than 10 micrometers aerodynamic diameter (PM10) at these sites commonly greater than 100 μg/m3 and reaching around 400 μg/m3, and daily PM mass concentration of particles less than 2.5 micrometers aerodynamic diameter (PM2.5) commonly greater than 20 μg/m3 and reaching around 60 μg/m3. A detailed analysis utilizing 1 km resolution multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD), Identifying Violations Affecting Neighborhoods (IVAN) low-cost PM2.5 measurements and 500 m resolution sediment supply fields alongside routine ground PM observations identified an area of high AOD/PM during WSW events spanning the northwestern valley encompassing the Brawley/Westmorland through the Niland area. This area shows up most clearly once the average PM10 at northern valley routine sites during WSW events exceeds 100 μg/m3. The area is consistent with high soil sediment supply in the northwestern valley and upwind desert, suggesting local sources are primarily responsible. On the basis of this study, MAIAC AOD appears able to identify localized high PM areas during windblown dust events provided the PM levels are high enough. The use of the IVAN data in this study illustrates how a citizen science effort to collect more spatially refined air quality concentration data can help pinpoint episodic pollution patterns and possible sources important for PM exposure and adverse health effects

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.Comment: 9 pages, 6 figures. Supporting information files available at http://filrad.homelinux.or

The association of cold weather and all-cause and cause-specific mortality in the island of Ireland between 1984 and 2007

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background This study aimed to assess the relationship between cold temperature and daily mortality in the Republic of Ireland (ROI) and Northern Ireland (NI), and to explore any differences in the population responses between the two jurisdictions. Methods A time-stratified case-crossover approach was used to examine this relationship in two adult national populations, between 1984 and 2007. Daily mortality risk was examined in association with exposure to daily maximum temperatures on the same day and up to 6 weeks preceding death, during the winter (December-February) and cold period (October-March), using distributed lag models. Model stratification by age and gender assessed for modification of the cold weather-mortality relationship. Results In the ROI, the impact of cold weather in winter persisted up to 35 days, with a cumulative mortality increase for all-causes of 6.4% (95%CI=4.8%-7.9%) in relation to every 1oC drop in daily maximum temperature, similar increases for cardiovascular disease (CVD) and stroke, and twice as much for respiratory causes. In NI, these associations were less pronounced for CVD causes, and overall extended up to 28 days. Effects of cold weather on mortality increased with age in both jurisdictions, and some suggestive gender differences were observed. Conclusions The study findings indicated strong cold weather-mortality associations in the island of Ireland; these effects were less persistent, and for CVD mortality, smaller in NI than in the ROI. Together with suggestive differences in associations by age and gender between the two Irish jurisdictions, the findings suggest potential contribution of underlying societal differences, and require further exploration. The evidence provided here will hope to contribute to the current efforts to modify fuel policy and reduce winter mortality in Ireland

Assessing the impact of biomedical research in academic institutions of disparate sizes

Abstract Background The evaluation of academic research performance is nowadays a priority issue. Bibliometric indicators such as the number of publications, total citation counts and h-index are an indispensable tool in this task but their inherent association with the size of the research output may result in rewarding high production when evaluating institutions of disparate sizes. The aim of this study is to propose an indicator that may facilitate the comparison of institutions of disparate sizes. Methods The Modified Impact Index (MII) was defined as the ratio of the observed h-index (h) of an institution over the h-index anticipated for that institution on average, given the number of publications (N) it produces i.e. (α and β denote the intercept and the slope, respectively, of the line describing the dependence of the h-index on the number of publications in log10 scale). MII values higher than 1 indicate that an institution performs better than the average, in terms of its h-index. Data on scientific papers published during 2002–2006 and within 36 medical fields for 219 Academic Medical Institutions from 16 European countries were used to estimate α and β and to calculate the MII of their total and field-specific production. Results From our biomedical research data, the slope β governing the dependence of h-index on the number of publications in biomedical research was found to be similar to that estimated in other disciplines (≈0.4). The MII was positively associated with the average number of citations/publication (r = 0.653, p Conclusion The MII should complement the use of h-index when comparing the research output of institutions of disparate sizes. It has a conceptual interpretation and, with the data provided here, can be computed for the total research output as well as for field-specific publication sets of institutions in biomedicine.</p

The Family Health Promotion Project (FHPP): Design and baseline data from a randomized trial to increase colonoscopy screening in high risk families

Colorectal cancer (CRC) is a significant cause of mortality and morbidity in the United States, much of which could be prevented through adequate screening. Consensus guidelines recommend that high-risk groups initiate screening earlier with colonoscopy and more frequently than average risk persons. However, a large proportion of high risk individuals do not receive regular colonoscopic screening. The Family Health Promotion Project (FHPP) is a randomized-controlled trial to test the effectiveness of a telephone-based counseling intervention to increase adherence to risk-appropriate colonoscopy screening in high risk individuals. Unaffected members of CRC families from two national cancer family registries were enrolled (n=632) and randomized to receive either a single session telephone counseling intervention using Motivational Interviewing techniques or a minimal mail-out intervention. The primary endpoint, rate of colonoscopy screening, was assessed at 6, 12 and 24 months post-enrollment. In this paper, we describe the research design and telephone counseling intervention of the FHPP trial, and report baseline data obtained from the two high risk cohorts recruited into this trial. Results obtained at baseline confirm the need for interventions to promote colonoscopy screening among these high risk individuals, as well as highlighting several key opportunities for intervention, including increasing knowledge about risk-appropriate screening guidelines, and providing both tailored risk information and barriers counseling