Nonminimal Couplings in the Early Universe: Multifield Models of Inflation and the Latest Observations

Models of cosmic inflation suggest that our universe underwent an early phase of accelerated expansion, driven by the dynamics of one or more scalar fields. Inflationary models make specific, quantitative predictions for several observable quantities, including particular patterns of temperature anistropies in the cosmic microwave background radiation. Realistic models of high-energy physics include many scalar fields at high energies. Moreover, we may expect these fields to have nonminimal couplings to the spacetime curvature. Such couplings are quite generic, arising as renormalization counterterms when quantizing scalar fields in curved spacetime. In this chapter I review recent research on a general class of multifield inflationary models with nonminimal couplings. Models in this class exhibit a strong attractor behavior: across a wide range of couplings and initial conditions, the fields evolve along a single-field trajectory for most of inflation. Across large regions of phase space and parameter space, therefore, models in this general class yield robust predictions for observable quantities that fall squarely within the "sweet spot" of recent observations.Comment: 17pp, 2 figs. References added to match the published version. Published in {\it At the Frontier of Spacetime: Scalar-Tensor Theory, Bell's Inequality, Mach's Principle, Exotic Smoothness}, ed. T. Asselmeyer-Maluga (Springer, 2016), pp. 41-57, in honor of Carl Brans's 80th birthda

Probing Density Fluctuations using the FIRST Radio Survey

We use results of angular clustering measurements in 3000 sq. deg's of the FIRST radio survey to infer information on spatial clustering. Measurements are compared with CDM-model predictions. Clustering of FIRST sources with optical ID's in the APM catalog are also investigated. Finally, we outline a preliminary search for a weak lensing signal in the survey.Comment: 6 pages latex, 2 figures, to appear in Cosmology with the New Radio Surveys (Kluwer

Detection of virus-specific intrathecally synthesised immunoglobulin G with a fully automated enzyme immunoassay system

<p>Abstract</p> <p>Background</p> <p>The determination of virus-specific immunoglobulin G (IgG) antibodies in cerebrospinal fluid (CSF) is useful for the diagnosis of virus associated diseases of the central nervous system (CNS) and for the detection of a polyspecific intrathecal immune response in patients with multiple sclerosis. Quantification of virus-specific IgG in the CSF is frequently performed by calculation of a virus-specific antibody index (AI). Determination of the AI is a demanding and labour-intensive technique and therefore automation is desirable. We evaluated the precision and the diagnostic value of a fully automated enzyme immunoassay for the detection of virus-specific IgG in serum and CSF using the analyser BEP2000 (Dade Behring).</p> <p>Methods</p> <p>The AI for measles, rubella, varicella-zoster, and herpes simplex virus IgG was determined from pairs of serum and CSF samples of patients with viral CNS infections, multiple sclerosis and of control patients. CSF and serum samples were tested simultaneously with reference to a standard curve. Starting dilutions were 1:6 and 1:36 for CSF and 1:1386 and 1:8316 for serum samples.</p> <p>Results</p> <p>The interassay coefficient of variation was below 10% for all parameters tested. There was good agreement between AIs obtained with the BEP2000 and AIs derived from the semi-automated reference method.</p> <p>Conclusion</p> <p>Determination of virus-specific IgG in serum-CSF-pairs for calculation of AI has been successfully automated on the BEP2000. Current limitations of the assay layout imposed by the analyser software should be solved in future versions to offer more convenience in comparison to manual or semi-automated methods.</p

Ecosystem restoration strengthens pollination network resilience and function.

Land degradation results in declining biodiversity and the disruption of ecosystem functioning worldwide, particularly in the tropics. Vegetation restoration is a common tool used to mitigate these impacts and increasingly aims to restore ecosystem functions rather than species diversity. However, evidence from community experiments on the effect of restoration practices on ecosystem functions is scarce. Pollination is an important ecosystem function and the global decline in pollinators attenuates the resistance of natural areas and agro-environments to disturbances. Thus, the ability of pollination functions to resist or recover from disturbance (that is, the functional resilience) may be critical for ensuring a successful restoration process. Here we report the use of a community field experiment to investigate the effects of vegetation restoration, specifically the removal of exotic shrubs, on pollination. We analyse 64 plant-pollinator networks and the reproductive performance of the ten most abundant plant species across four restored and four unrestored, disturbed mountaintop communities. Ecosystem restoration resulted in a marked increase in pollinator species, visits to flowers and interaction diversity. Interactions in restored networks were more generalized than in unrestored networks, indicating a higher functional redundancy in restored communities. Shifts in interaction patterns had direct and positive effects on pollination, especially on the relative and total fruit production of native plants. Pollinator limitation was prevalent at unrestored sites only, where the proportion of flowers producing fruit increased with pollinator visitation, approaching the higher levels seen in restored plant communities. Our results show that vegetation restoration can improve pollination, suggesting that the degradation of ecosystem functions is at least partially reversible. The degree of recovery may depend on the state of degradation before restoration intervention and the proximity to pollinator source populations in the surrounding landscape. We demonstrate that network structure is a suitable indicator for pollination quality, highlighting the usefulness of interaction networks in environmental management

Don't spin the pen: two alternative methods for second-stage sampling in urban cluster surveys

In two-stage cluster surveys, the traditional method used in second-stage sampling (in which the first household in a cluster is selected) is time-consuming and may result in biased estimates of the indicator of interest. Firstly, a random direction from the center of the cluster is selected, usually by spinning a pen. The houses along that direction are then counted out to the boundary of the cluster, and one is then selected at random to be the first household surveyed. This process favors households towards the center of the cluster, but it could easily be improved. During a recent meningitis vaccination coverage survey in Maradi, Niger, we compared this method of first household selection to two alternatives in urban zones: 1) using a superimposed grid on the map of the cluster area and randomly selecting an intersection; and 2) drawing the perimeter of the cluster area using a Global Positioning System (GPS) and randomly selecting one point within the perimeter. Although we only compared a limited number of clusters using each method, we found the sampling grid method to be the fastest and easiest for field survey teams, although it does require a map of the area. Selecting a random GPS point was also found to be a good method, once adequate training can be provided. Spinning the pen and counting households to the boundary was the most complicated and time-consuming. The two methods tested here represent simpler, quicker and potentially more robust alternatives to spinning the pen for cluster surveys in urban areas. However, in rural areas, these alternatives would favor initial household selection from lower density (or even potentially empty) areas. Bearing in mind these limitations, as well as available resources and feasibility, investigators should choose the most appropriate method for their particular survey context

Long-term effects of chronic light pollution on seasonal functions of European blackbirds (turdus merula)

Light pollution is known to affect important biological functions of wild animals, including daily and annual cycles. However, knowledge about long-term effects of chronic exposure to artificial light at night is still very limited. Here we present data on reproductive physiology, molt and locomotor activity during two-year cycles of European blackbirds (Turdus merula) exposed to either dark nights or 0.3 lux at night. As expected, control birds kept under dark nights exhibited two regular testicular and testosterone cycles during the two-year experiment. Control urban birds developed testes faster than their control rural conspecifics. Conversely, while in the first year blackbirds exposed to light at night showed a normal but earlier gonadal cycle compared to control birds, during the second year the reproductive system did not develop at all: both testicular size and testosterone concentration were at baseline levels in all birds. In addition, molt sequence in light-treated birds was more irregular than in control birds in both years. Analysis of locomotor activity showed that birds were still synchronized to the underlying light-dark cycle. We suggest that the lack of reproductive activity and irregular molt progression were possibly the results of i) birds being stuck in a photorefractory state and/or ii) chronic stress. Our data show that chronic low intensities of light at night can dramatically affect the reproductive system. Future studies are needed in order to investigate if and how urban animals avoid such negative impact and to elucidate the physiological mechanisms behind these profound long-term effects of artificial light at night. Finally we call for collaboration between scientists and policy makers to limit the impact of light pollution on animals and ecosystems

Stress induced polarization of immune-neuroendocrine phenotypes in Gallus gallus

Immune-neuroendocrine phenotypes (INPs) stand for population subgroups differing in immune-neuroendocrine interactions. While mammalian INPs have been characterized thoroughly in rats and humans, avian INPs were only recently described in Coturnix coturnix (quail). To assess the scope of this biological phenomenon, herein we characterized INPs in Gallus gallus (a domestic hen strain submitted to a very long history of strong selective breeding pressure) and evaluated whether a social chronic stress challenge modulates the individuals’ interplay affecting the INP subsets and distribution. Evaluating plasmatic basal corticosterone, interferon-γ and interleukin-4 concentrations, innate/acquired leukocyte ratio, PHA-P skin-swelling and induced antibody responses, two opposite INP profiles were found: LEWIS-like (15% of the population) and FISCHER-like (16%) hens. After chronic stress, an increment of about 12% in each polarized INP frequency was found at expenses of a reduction in the number of birds with intermediate responses. Results show that polarized INPs are also a phenomenon occurring in hens. The observed inter-individual variation suggest that, even after a considerable selection process, the population is still well prepared to deal with a variety of immune-neuroendocrine challenges. Stress promoted disruptive effects, leading to a more balanced INPs distribution, which represents a new substrate for challenging situations.Fil: Nazar, Franco Nicolas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Estevez, Inma. Centro de Investigación. Neiker - Tecnalia; EspañaFil: Correa, Silvia Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Marin, Raul Hector. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentin

Legal determinants of external finance revisited : the inverse relationship between investor protection and societal well-being

This paper investigates relationships between corporate governance traditions and quality of life as measured by a number of widely reported indicators. It provides an empirical analysis of indicators of societal health in developed economies using a classification based on legal traditions. Arguably the most widely cited work in the corporate governance literature has been the collection of papers by La Porta et al. which has shown, inter alia, statistically significant relationships between legal traditions and various proxies for investor protection. We show statistically significant relationships between legal traditions and various proxies for societal health. Our comparative evidence suggests that the interests of investors may not be congruent with the interests of wider society, and that the criteria for judging the effectiveness of approaches to corporate governance should not be restricted to financial metrics

The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure