The impact of compact binary confusion noise on tests of fundamental physics with next-generation gravitational-wave detectors

Next-generation ground-based gravitational-wave observatories such as the Einstein Telescope and Cosmic Explorer will detect $O(10^{5}-10^{6})$ signals from compact binary coalescences every year, the exact number depending on uncertainties in the binary merger rate. Several overlapping signals will be present in band at any given time, generating a confusion noise background. We study how this confusion noise affects constraints on possible deviations from general relativity induced by modified gravity and environmental effects. Confusion noise impacts only the signals that last longer in band. Even for a "golden" GW170817-like signal, the constraints broaden by a factor in the range $[10\%,40\%]$ $([70\%,110\%])$ for the fiducial (highest) value of the local binary neutron star merger rate. Our ability to test general relativity or constrain environmental effects will be limited by systematic errors, and not by confusion noise.Comment: 11 pages, 5 figure

Mapping by spatial predictors exploiting remotely sensed and ground data: a comparative design-based perspective

This study was designed to compare the performance – in terms of bias and accuracy – of four different parametric,semiparametric and nonparametric methods in spatially predicting a forest response variable using auxiliary information from remote sensing. The comparison was carried out in simulated and real populations where the value of response variable was known for each pixel of the study region. Sampling was simulated through a tessellation stratified design. Universal kriging and cokriging were considered among parametric methods based on the spatial autocorrelation of the forest response variable. Locallyweighted regression and k-nearest neighbor predictors were considered among semiparametric and nonparametricmethods based on the information from neighboring sites in the auxiliary variable space. The study was performed from a design-based perspective, taking the populations as fixed and replicating the sampling procedurewith 1000Monte Carlo simulation runs. On the basis of the empirical values of relative bias and relative root mean squared error it was concluded that universal kriging and cokriging were more suitable in the presence of strong spatial autocorrelation of the forest variable, while locally weighted regression and k-nearest neighbors were more suitable when the auxiliary variables were well correlated with the response variable. Results of the study advise that attention should be paid when mapping forest variables characterized by highly heterogeneous structures. The guidelines of this study can be adopted even for mapping environmental attributes beside forestry

SULLA DIPENDENZA DEL PREZZO DEGLI IMMOBILI RESIDENZIALI DAI LIVELLI DI ACCESSIBILITÀ A SERVIZI E INFRASTRUTTURE DI TRASPORTO

Intrinsic characteristics and urban facilities significantly influence residential property prices. However, among the effects of city facilities, those related to accessibility to the urban system services and activities have not yet been sufficiently investigated and their spatial heterogeneity is often overlooked. The aim of the paper is to define a methodology to analyse the impact of accessibility to services and infrastructures on property values. It is a three-step methodology: (i) characterisation of the price function; (ii) verifying the goodness of the model; (iii) autocorrelation analysis and implementation of spatial econometric models. A new element of this research is the construction of a panel of input variables useful for setting the price function. In fact, in addition to intrinsic characteristics and zonal characteristics, local accessibility indicators and systemwide accessibility indicators, usually not included in evaluations, are introduced. In addition, the last step of the model demonstrates the necessity of implementing spatial econometric models in cases where the levels of spatial heterogeneity are not negligible. The implementation of the model to real case studies will allow to quantify the impact of local and systemwide accessibility on residential property values

Preoperative very short-term, high-dose erythropoietin administration diminishes blood transfusion rate in off-pump coronary artery bypass: A randomized blind controlled study

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Southern Italian wild boar population, hotspot of genetic diversity

The wild boar, Sus scrofa, is an important game species widely distributed in Eurasia. Whereas the genetic variability of most European wild boar populations is well known, the status of wild boar living in Southern Italy is not as clear. We evaluated the present and past genetic diversity (D-loop, mtDNA) of the South Italian population, comparing it with that observed in other Mediterranean glacial refugia. Italian population showed highest genetic variability, if compared to other two European refugia (Iberian and Balkan). Most of samples from Italy carried sequences belonging to the European E1 haplogroup (80.9%) with a small proportion of the private Italian E2 (10.2%) and of the Asian (8.9%) ones. Italian samples carrying an Asian haplotype were genotyped by MC1R nuclear gene, failing to disclose a recent introgression from domestic pigs. Mismatch distribution analysis of the Italian population was affected by secondary contacts between these different lin- eages. This genetic melting pot was detected since the Mesolithic and the Neolithic age, during which we found samples belonging to the indigenous Italian and European haplogroups. Further, a Near-Eastern haplotype was found in 1,800 AD samples from Southern and Central Italy. Our res- ults can be in agreement with post-glacial recolonization theories, as well as with the long history of human-mediated translocations of Sus scrofa in the Mediterranean basi