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.

Measurements of CP violation in the three-body phase space of charmless B-+/- decays

Abstract: The charmless three-body decay modes B±→K±π+π−, B±→K±K+K−, B±→π±K+K− and B±→π±π+π− are reconstructed using data, corresponding to an integrated luminosity of 3.0 fb−1, collected by the LHCb detector. The inclusive CP asymmetries of these modes are measured to be ACP(B±→K±π+π−)=+0.025±0.004±0.004±0.007,ACP(B±→K±K+K−)=−0.036±0.004±0.002±0.007,ACP(B±→π±π+π−)=+0.058±0.008±0.009±0.007,ACP(B±→π±K+K−)=−0.123±0.017±0.012±0.007, where the first uncertainty is statistical, the second systematic, and the third is due to the CP asymmetry of the B±→J/ψK± reference mode. The distributions of these asymmetries are also studied as functions of position in the Dalitz plot and suggest contributions from rescattering and resonance interference processes.

Optimal Meter Placement for Robust Measurement Systems in Active Distribution Grids

Abstract: Future active distribution grids are characterized by rapid and significant changes of operation and behavior due to, for example, intermittent power injections from renewable sources and the load-generation characteristic of the so-called prosumers. The design of a robust measurement infrastructure is critical for safe and effective grid control and operation. We had earlier proposed a placement procedure that allows finding an optimal robust measurement location incorporating phasor measurement units and smart metering devices for distribution system state estimation. In this paper, the lack of detailed information on distributed generation is also considered in the optimal meter placement procedure, so that the distributed measurement system can provide accurate estimates even with limited knowledge of the profile of the injected power. Possible non-Gaussian distribution of the distributed power generation has been taken into account. With this aim, the Gaussian mixture model has been incorporated into the placement optimization by means of the so-called Gaussian component combination method. The occurrence of either loss of data or degradation of metrological performance of the measurement devices is also considered. Tests performed on a UKGDS 16-bus distribution network are presented and discussed.

Efficacy of antidepressants in juvenile depression: meta-analysis

Abstract: Background The safety of antidepressants in children and adolescents is being questioned and the efficacy of these drugs in juvenile depression remains uncertain. Aims To assess antidepressant efficacy in juvenile depression. Method Systematic review and meta-analysis of randomised controlled trials (RCTs) comparing responses to antidepressants, overall and by type, v . placebo in young people with depression. Results Thirty drug–placebo contrasts in RCTs lasting 8 weeks (median) involved 3069 participants (512 person-years) of average age 13.5 years. Meta-analysis yielded a modest pooled drug/placebo response rate ratio (RR=1.22, 95% CI 1.15–1.31), with little separation between antidepressant types. Findings were similar for response rate differences and corresponding number needed to treat (NNT): overall NNT=9; tricyclic antidepressants NNT=14 > serotonin reuptake inhibitors NNT=9 > other antidepressants NNT=8. Numbers needed to treat decreased with increasing age: children (NNT=21) > mixed ages (NNT=10) > adolescents (NNT=8). Conclusions Antidepressants of all types showed limited efficacy in juvenile depression, but fluoxetine might be more effective, especially in adolescents. Studies in children and in severely depressed, hospitalised or suicidal juvenile patients are needed, and effective, safe and readily accessible treatments for juvenile depression are urgently required.

Causal beliefs of the public and social acceptance of persons with mental illness: a comparative analysis of schizophrenia, depression and alcohol dependence

Abstract: Background There is an ongoing debate whether biological illness explanations improve tolerance towards persons with mental illness or not. Several theoretical models have been proposed to predict the relationship between causal beliefs and social acceptance. This study uses path models to compare different theoretical predictions regarding attitudes towards persons with schizophrenia, depression and alcohol dependence. Method In a representative population survey in Germany (n = 3642), we elicited agreement with belief in biogenetic causes, current stress and childhood adversities as causes of either disorder as described in an unlabelled case vignette. We further elicited potentially mediating attitudes related to different theories about the consequences of biogenetic causal beliefs (attribution theory: onset responsibility, offset responsibility; genetic essentialism: differentness, dangerousness; genetic optimism: treatability) and social acceptance. For each vignette condition, we calculated a multiple mediator path model containing all variables. Results Biogenetic beliefs were associated with lower social acceptance in schizophrenia and depression, and with higher acceptance in alcohol dependence. In schizophrenia and depression, perceived differentness and dangerousness mediated the largest indirect effects, the consequences of biogenetic causal explanations thus being in accordance with the predictions of genetic essentialism. Psychosocial causal beliefs had differential effects: belief in current stress as a cause was associated with higher acceptance in schizophrenia, while belief in childhood adversities resulted in lower acceptance of a person with depression. Conclusions Biological causal explanations seem beneficial in alcohol dependence, but harmful in schizophrenia and depression. The negative correlates of believing in childhood adversities as a cause of depression merit further exploration.