L'autonomia finanziaria delle Regioni nell'art. 119 della Costituzione - Il difficile cammino verso la sua effettività - Il caso della Regione Sardegna

L'autonomia finanziaria delle Regioni nella disciplina dell'art. 119 della Costituzione. La tesi si occupa di ricostruire, partendo dalla riforma del Titolo V, uno dei punti più problematici dell'intera riforma costituzionale del 2001, quello dell'allocazione delle risorse finanziarie delle Regioni e degli Enti Territoriali. Dopo la presentazione degli elementi di criticità della riforma del 2001 di opera una ricostruzione storica delle origini del regionalismo italiano. Si analizza, successivamente, con dettaglio l'art. 119 della Costituzione, anche alla luce degli interventi giurisprudenziali della Corte Costituzionale. Successivamente si analizza il caso della Regione Sardegna, che negli anni 2006 - 2009 si è dimostrata particolarmente attiva sul piano dell'elaborazione normativa in senso federalistico. L'ultimo capitolo presenta alcune considerazioni conclusive e indica le principali novità della legge 42/2009 che ha delegato il governo all'emanazione dei decreti legislativi per l'attuazione dell'art. 119 Cost

ONNX-to-Hardware Design Flow for the Generation of Adaptive Neural-Network Accelerators on FPGAs

Neural Networks (NN) provide a solid and reliable way of executing different types of applications, ranging from speech recognition to medical diagnosis, speeding up onerous and long workloads. The challenges involved in their implementation at the edge include providing diversity, flexibility, and sustainability. That implies, for instance, supporting evolving applications and algorithms energy-efficiently. Using hardware or software accelerators can deliver fast and efficient computation of the \acp{nn}, while flexibility can be exploited to support long-term adaptivity. Nonetheless, handcrafting an NN for a specific device, despite the possibility of leading to an optimal solution, takes time and experience, and that's why frameworks for hardware accelerators are being developed. This work-in-progress study focuses on exploring the possibility of combining the toolchain proposed by Ratto et al., which has the distinctive ability to favor adaptivity, with approximate computing. The goal will be to allow lightweight adaptable NN inference on FPGAs at the edge. Before that, the work presents a detailed review of established frameworks that adopt a similar streaming architecture for future comparison.Comment: Accepted for presentation at the CPS workshop 2023 (http://www.cpsschool.eu/cps-workshop

Testing the equality of two coefficients of variation: a new Bayesian approach

The use of testing procedures for comparing two coefficients of variation (CVs) of independent populations is not extensively explored in the Bayesian context. We propose to address this issue through a test based on a measure of evidence, the Bayesian Discrepancy Measure, recently introduced in the literature. Computing the Bayesian Discrepancy Measure is straightforward when the CVs depend on a single parameter of the distribution. In contrast, it becomes more difficult when this simplification does not occur since more parameters are involved, requiring often the use of MCMC methods. We derive the Bayesian Discrepancy Measure and the related test by considering a variety of distribution assumptions with multiparametric CVs and apply them to real datasets. As far as we know, some of the examined problems have not yet been covered in the literature

Optomechanical measurement of thermal transport in two-dimensional MoSe2 lattices

Nanomechanical resonators have emerged as sensors with exceptional sensitivities. These sensing capabilities open new possibilities in the studies of the thermodynamic properties in condensed matter. Here, we use mechanical sensing as a novel approach to measure the thermal properties of low-dimensional materials. We measure the temperature dependence of both the thermal conductivity and the specific heat capacity of a transition metal dichalcogenide (TMD) monolayer down to cryogenic temperature, something that has not been achieved thus far with a single nanoscale object. These measurements show how heat is transported by phonons in two-dimensional systems. Both the thermal conductivity and the specific heat capacity measurements are consistent with predictions based on first-principles

Relation of Secondhand Smoking to Mild Cognitive Impairment in Older Inpatients

Up to now, controversy still exists regarding the role of secondhand smoking (SHS) in developing cognitive impairment. This study aimed to evaluate the prevalence of SHS in hospitalized older patients with cognitive deficit, particularly in those with mild cognitive impairment (MCI). Smoking history was classified into four groups: never smokers, former-active smokers/no SHS, active smokers, and secondhand smokers, and cognitive function into three levels: normal cognition (C), MCI, and dementia. A total of 933 older subjects with diagnoses of MCI (n = 98), dementia (n = 124), or C (n = 711) were enrolled in this cross-sectional study. As expected, patients with dementia had significantly higher frequency of former-active smokers than cognitively normal. Moreover, patients with MCI showed a significantly higher frequency of active and secondhand smokers than patients with dementia or C. A smoking history is very frequent in older patients with dementia. Patients with MCI had even higher rate of exposure to active or secondhand smoking

Previous psychiatric hospitalizations as risk factors for single and multiple future alcohol-related hospitalizations in patients with alcohol use disorders

Background and aims: People with alcohol use disorder (AUD) often have co-occurring psychiatric conditions. The association between psychiatric conditions and AUD relapse has not yet been fully explored. This study aimed to quantify different psychiatric comorbidities as risk factors for first and multiple AUD rehospitalizations in patients already hospitalized once for AUD. Methods: We used a nation-wide routine health-care database in Scotland, UK, between 2010 and 2019. Individuals with a first hospitalization for AUD (codes F10.0-9 in the ICD-10 codes) were checked for previous hospitalizations where the main or co-occurring cause was a psychiatric condition (any other F0-F99 code in ICD-10). The final cohort included 23 529 patients, 18 620 of whom did not have a history of any other psychiatric comorbidity. First, individuals with a history of any previous psychiatric hospitalization were grouped and compared with those without on the basis of time to AUD rehospitalization. Then, individuals with different histories of psychiatric hospitalization were compared with each other. Cox and Prentice, Williams and Peterson gap-time models were used for single and multiple AUD rehospitalizations, respectively. Results: The AUD rehospitalization rate in individuals with a previous psychiatric hospitalization was 8% higher compared with those without [hazard ratio (HR) = 1.08, 95% confidence interval (CI) = 1.01–1.14]. The difference in rehospitalization rate reduced following the first rehospitalization (HR at second rehospitalization from first: 0.95, 95% CI = 0.87–1.04 and HR at third rehospitalization from second: 0.94, 95% CI = 0.84–1.07). Mood disorders and neurotic, stress-related and somatoform disorders were associated with a 54% (HR = 1.54, 95% CI = 1.38–1.72) and 39% (HR = 1.39, 95% CI = 1.17–1.66) increase in the risk of a first AUD rehospitalization. Other conditions, such as disorders due to psychoactive substance use or schizophrenia, were associated with decreases in future AUD rehospitalization (HR = 0.89, 95% CI = 0.82–0.97 and HR = 0.82, 95% CI = 0.58–1.16, respectively). Conclusions: Patients with AUD appear to have different rates of AUD rehospitalization based on different co-occurring psychiatric conditions. Addiction-related characteristics may be more relevant risk indicators for multiple AUD readmission than psychiatric comorbidities

Unlocking Onboard SAR Processing: Focusing and Ship Detection on Sentinel-1 IW Data

This work demonstrates the possibility of enabling onboard processing of SAR data in real-time through the adoption of an innovative focusing technology coupled with object detection, using limited computational resources. Our approach aims to provide a coarse focused product onboard to unlock real-time monitoring capabilities, complementing the ground-based detailed focusing algorithms. The focusing algorithm transforms the Level-0 raw signal into Level-1 Single-Look-Complex (SLC) data. It consists of a two-layers hybrid architecture: a traditional Fast-Fourier Transform (FFT) algorithm for range processing and a Deep Neural Network (DNN), trained to solved the azimuth processing task, which provides scalability and modularity benefits. After focusing, an object detection network is trained to detect the presence of ships in the SLC data. The whole processing chain has been optimized and deployed on different embedded devices, including NVIDIA Jetson Nano, and NVIDIA Jetson Xavier, to demonstrate the feasibility of running the overall pipeline onboard the future generations of SAR missions

Polyhedral separation via difference of convex (DC) programming

We consider polyhedral separation of sets as a possible tool in supervised classification. In particular, we focus on the optimization model introduced by Astorino and Gaudioso (J Optim Theory Appl 112(2):265–293, 2002) and adopt its reformulation in difference of convex (DC) form. We tackle the problem by adapting the algorithm for DC programming known as DCA. We present the results of the implementation of DCA on a number of benchmark classification datasets

Multifunctional bioinspired sol-gel coatings for architectural glasses

Although several multinational companies have recently released products incorporating bioinspired functional coatings, their practical integration in building envelopes is still an open issue. High production costs associated to the existing vacuum deposition technologies, as well as the difficulties in extending the number of functions achievable by a single coating, represent to date the main limitations to their diffusion on a large scale. This review summarizes the key topics in the field of functional coatings for architectural glasses, focusing in particular on the potential applications of sol-gel based antireflective and self-cleaning coatings, that have received a tremendous attention in the last years. It provides an overview of the recent research efforts aimed to improve their properties and to extend their range of applicability. The bioinspired principles, upon which such coatings are based, are also described and are related to the chemical and morphological properties of such surfaces. (C) 2009 Elsevier Ltd. All rights reserved