University of Cagliari

About: University of Cagliari is a education organization based out in Cagliari, Italy. It is known for research contribution in the topics: Population & Dopamine. The organization has 11029 authors who have published 29046 publications receiving 771023 citations. The organization is also known as: Università degli Studi di Cagliari & Universita degli Studi di Cagliari.

Technical design report for the upgrade of the ALICE inner tracking system

Abstract: ALICE (A Large Ion Collider Experiment) is studying the physics of strongly interacting matter, and in particular the properties of the Quark–Gluon Plasma (QGP), using proton–proton, proton–nucleus and nucleus–nucleus collisions at the CERN LHC (Large Hadron Collider). The ALICE Collaboration is preparing a major upgrade of the experimental apparatus, planned for installation in the second long LHC shutdown in the years 2018–2019. A key element of the ALICE upgrade is the construction of a new, ultra-light, high- resolution Inner Tracking System (ITS) based on monolithic CMOS pixel detectors. The primary focus of the ITS upgrade is on improving the performance for detection of heavy-flavour hadrons, and of thermal photons and low-mass di- electrons emitted by the QGP. With respect to the current detector, the new Inner Tracking System will significantly enhance the determination of the distance of closest approach to the primary vertex, the tracking efficiency at low transverse momenta, and the read-out rate capabilities. This will be obtained by seven concentric detector layers based on a 50 μm thick CMOS pixel sensor with a pixel pitch of about 30×30 μm2. This document, submitted to the LHCC (LHC experiments Committee) in September 2013, presents the design goals, a summary of the R&D activities, with focus on the technical implementation of the main detector components, and the projected detector and physics performance.

The development of candidate composite disease activity and responder indices for psoriatic arthritis (GRACE project)

Abstract: Objective To develop new composite disease activity indices for psoriatic arthritis (PsA). Methods Data from routine clinic visits at multiple centres were collected in a systematic manner. Data included all domains identified as important in randomised controlled trials in PsA. Decisions to change treatment were used as surrogates for high disease activity. New indices were developed by multiple linear regression (psoriatic arthritis disease activity score: PASDAS) and empirically, utilising physician-defined cut-offs for disease activity (arithmetic mean of desirability functions: AMDF). These were compared with existing composite measures: Composite Psoriatic arthritis Disease Activity Index (CPDAI), Disease Activity for PSoriatic Arthritis (DAPSA), and Disease Activity Score for rheumatoid arthritis (DAS28). Results 161/503 (32%) subjects had treatment changes. Although all measures performed well, compared with existing indices, PASDAS was better able to discriminate between high and low disease activity (area under receiver operating curves (ROC)) curve with 95% CI: PASDAS 0.773 (0.723, 0.822); AMDF 0.730 (0.680, 0.780); CPDAI 0.719 (0.668, 0.770); DAPSA 0.710 (0.654, 0.766); DAS28 0.736 (0.680, 0.792). All measures were able to discriminate between disease activity states in patients with oligoarthritis, although area under the receiver operating curves (AUC) were generally smaller. In patients with severe skin disease (psoriasis area and severity index >10) both nonparametric and AUC curve statistics were nonsignificant for all measures. Conclusions Two new composite measures to assess disease activity in PsA have been developed. Further testing in other datasets, including comparison with existing measures, is required to validate these instruments.