University of Trento

About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Context (language use). The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.

A Fully Digital 8 $\,\times\,$ 16 SiPM Array for PET Applications With Per-Pixel TDCs and Real-Time Energy Output

Abstract: An 8 × 16 pixel array based on CMOS small-area silicon photomultipliers (mini-SiPMs) detectors for PET applications is reported. Each pixel is 570 × 610 μm2 in size and contains four digital mini-SiPMs, for a total of 720 SPADs, resulting in a full chip fill-factor of 35.7%. For each gamma detection, the pixel provides the total detected energy and a timestamp, obtained through two 7-b counters and two 12-b 64-ps TDCs. An adder tree overlaid on top of the pixel array sums the sensor total counts at up to 100 Msamples/s, which are then used for detecting the asynchronous gamma events on-chip, while also being output in real-time. Characterization of gamma detection performance with an 3 × 3 × 5 mm3 LYSO scintillator at 20°C is reported, showing a 511-keV gamma energy resolution of 10.9% and a coincidence timing resolution of 399 ps.

Mitigation measures for pandemic influenza in Italy: an individual based model considering different scenarios.

Abstract: Background Individual-based models can provide the most reliable estimates of the spread of infectious diseases. In the present study, we evaluated the diffusion of pandemic influenza in Italy and the impact of various control measures, coupling a global SEIR model for importation of cases with an individual based model (IBM) describing the Italian epidemic. Methodology/Principal Findings We co-located the Italian population (57 million inhabitants) to households, schools and workplaces and we assigned travel destinations to match the 2001 census data. We considered different R0 values (1.4; 1.7; 2), evaluating the impact of control measures (vaccination, antiviral prophylaxis -AVP-, international air travel restrictions and increased social distancing). The administration of two vaccine doses was considered, assuming that first dose would be administered 1-6 months after the first world case, and different values for vaccine effectiveness (VE). With no interventions, importation would occur 37–77 days after the first world case. Air travel restrictions would delay the importation of the pandemic by 7–37 days. With an R0 of 1.4 or 1.7, the use of combined measures would reduce clinical attack rates (AR) from 21–31% to 0.3–4%. Assuming an R0 of 2, the AR would decrease from 38% to 8%, yet only if vaccination were started within 2 months of the first world case, in combination with a 90% reduction in international air traffic, closure of schools/workplaces for 4 weeks and AVP of household and school/work close contacts of clinical cases. Varying VE would not substantially affect the results. Conclusions This IBM, which is based on country-specific demographic data, could be suitable for the real-time evaluation of measures to be undertaken in the event of the emergence of a new pandemic influenza virus. All preventive measures considered should be implemented to mitigate the pandemic.

Normal state of a polarized fermi gas at unitarity.

Abstract: We study the Fermi gas at unitarity and at $T=0$ by assuming that, at high polarizations, it is a normal Fermi liquid composed of weakly interacting quasiparticles associated with the minority spin atoms. With a quantum Monte Carlo approach we calculate their effective mass and binding energy, as well as the full equation of state of the normal phase as a function of the concentration $x={n}_{\ensuremath{\downarrow}}/{n}_{\ensuremath{\uparrow}}$ of minority atoms. We predict a first order phase transition from normal to superfluid at ${x}_{c}=0.44$ corresponding, in the presence of harmonic trapping, to a critical polarization ${P}_{c}=({N}_{\ensuremath{\uparrow}}\ensuremath{-}{N}_{\ensuremath{\downarrow}})/({N}_{\ensuremath{\uparrow}}+{N}_{\ensuremath{\downarrow}})=77%$. We calculate the radii and the density profiles in the trap and predict that the frequency of the spin dipole mode will be increased by a factor of 1.23 due to interactions.