New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The ‘explosive’ outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading—when data are insufficient to make an estimate by adopting SIR model—a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the ‘so-called’ second wave with respect to the previous epidemic peak

Halo Mass Functions in Early Dark Energy Cosmologies

We examine the linear density contrast at collapse time, $\delta_c$ for large-scale structure in dynamical dark energy cosmologies, including models with early dark energy. Contrary to previous results, we find that as long as dark energy is homogeneous on small scales, $\delta_c$ is insensitive to dark energy properties for parameter values fitting current data, including the case of early dark energy. This is significant since using the correct $\delta_c$ is crucial for accurate Press-Schechter prediction of the halo mass function. Previous results have found an apparent failing of the extended Press-Schechter approach (Sheth-Tormen) for early dark energy. Our calculations demonstrate that with the correct $\delta_c$ the accuracy of this approach is restored. We discuss the significance of this result for the halo mass function and examine what dark energy physics would be needed to cause significant change in $\delta_c$, and the observational signatures this would leave.Comment: 5 pages, 2 figures. Accepted for MNRAS Letter

Photonics and electronics integration in the HELIOS project

The objective of the European project HELIOS is to combine a photonic layer with a CMOS circuit by different innovative means, using microelectronics processes. Bonding of AWG + Ge Photodiodes on CMOS wafer is achieved

The Halo Bispectrum in N-body Simulations with non-Gaussian Initial Conditions

We present measurements of the bispectrum of dark matter halos in numerical simulations with non-Gaussian initial conditions of the local type. We show, in the first place, that the overall effect of primordial non-Gaussianity on the halo bispectrum is larger than on the halo power spectrum when all measurable configurations are taken into account. We then compare our measurements with a tree-level perturbative prediction finding good agreement at large scale when the constant Gaussian bias parameter, both linear and quadratic, and their constant non-Gaussian corrections are fitted for. The best-fit values of the Gaussian bias factors and their non-Gaussian, scale-independent corrections are in qualitative agreement with the peak-background split expectations. In particular, we show that the effect of non-Gaussian initial conditions on squeezed configurations is fairly large (up to 30% for f_NL=100 at redshift z=0.5) and results from contributions of similar amplitude induced by the initial matter bispectrum, scale-dependent bias corrections as well as from nonlinear matter bispectrum corrections. We show, in addition, that effects at second order in f_NL are irrelevant for the range of values allowed by CMB and galaxy power spectrum measurements, at least on the scales probed by our simulations. Finally, we present a Fisher matrix analysis to assess the possibility of constraining primordial non-Gaussianity with future measurements of the galaxy bispectrum. We find that a survey with a volume of about 10 cubic Gpc at mean redshift z ~ 1 could provide an error on f_NL of the order of a few. This shows the relevance of a joint analysis of galaxy power spectrum and bispectrum in future redshift surveys.Comment: 37 pages, 15 figure

Medical-grade silicone coated with rhamnolipid R89 is effective against Staphylococcus spp. Biofilms

Staphylococcus aureus and Staphylococcus epidermidis are considered two of the most important pathogens, and their biofilms frequently cause device-associated infections. Microbial biosurfactants recently emerged as a new generation of anti-adhesive and anti-biofilm agents for coating implantable devices to preserve biocompatibility. In this study, R89 biosurfactant (R89BS) was evaluated as an anti-biofilm coating on medical-grade silicone. R89BS is composed of homologues of the mono- (75%) and di-rhamnolipid (25%) families, as evidenced by mass spectrometry analysis. The antimicrobial activity against Staphylococcus spp. planktonic and sessile cells was evaluated by microdilution and metabolic activity assays. R89BS inhibited S. aureus and S. epidermidis growth with minimal inhibitory concentrations (MIC99) of 0.06 and 0.12 mg/mL, respectively and dispersed their pre-formed biofilms up to 93%. Silicone elastomeric discs (SEDs) coated by R89BS simple adsorption significantly counteracted Staphylococcus spp. biofilm formation, in terms of both built-up biomass (up to 60% inhibition at 72 h) and cell metabolic activity (up to 68% inhibition at 72 h). SEM analysis revealed significant inhibition of the amount of biofilm-covered surface. No cytotoxic effect on eukaryotic cells was detected at concentrations up to 0.2 mg/mL. R89BS-coated SEDs satisfy biocompatibility requirements for leaching products. Results indicate that rhamnolipid coatings are effective anti-biofilm treatments and represent a promising strategy for the prevention of infection associated with implantable devices