Indicatori per l’analisi delle ripartizioni interne al quartiere

Ai fini di caratterizzare le diverse sub-aree presentate nella figura n. 9 (sub-aree interne al quartiere), abbiamo costruito una pluralità di indici socio-demografici e socio-economici ricorrendo ai dati del XIV Censimento generale della popolazione e delle abitazioni condotto dall’Istat nel 2001. I dati individuali del Censimento ci hanno permesso di distinguere in maniera assai fine le cinque sub-aree del quartiere, di disegnarne con precisione i confini e comprenderne il significato sociale. I diversi indici utilizzati nel volume sono stati calcolati da Tommaso Vitale, Renato Carletti ed Enrico Claps. La maggior parte di loro è stata suggerita da Guido Cavalca, che li aveva approntanti per indagini precedenti (2005; 2006), e che nuovamente qui ringraziamo (...)

The Gelling Ability of Some Diimidazolium Salts: Effect of Isomeric Substitution of the Cation and Anion

The gelling ability of some geminal imidazolium salts was investigated both in organic solvents and in water solution. Organic salts differing either in the cation or anion structure were taken into account. In particular, the effects on the gelphase formation of isomeric substitution on the cation or anion as well as of the use of mono- or dianions were evaluated. As far as the cation structure is concerned, isomeric cations, such as 3,3’-di-n-octyl-1,1’-(1,4-phenylenedimethylene)diimidazolium and 3,3’-di-n-octyl-1,1’-(1,3-phenylenedimethylene) diimidazolium, were used. On the other hand, in addition to the bromide anion, isomeric dianions, such as the 1,5- and 2,6-naphthalenedisulfonate anions, were also examined. After preliminary gelation tests, different factors affecting the obtained gel phases, such as the nature of the solvent, organogelator concentrations, and action of external stimuli, were analyzed. The gel-phase formation was also studied as a function of time, by using resonance light scattering measurements. Gel morphologies were analyzed by scanning electron microscopy. To further support the understanding of the different behavior shown by the isomeric cations, some representative ion pairs were analyzed by DFT-based investigations. The collected data underline the significant role played by isomeric substitution of both cation and anion structures in determining the gelling capability of the investigated salts, as well as the properties of the gel phases. Finally, DFT investigations were helpful in the identification of the structural features affecting the self-assembly

Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations

Idiopathic Parkinson's Disease (iPD) is a common motor neurodegenerative disorder. It affects more frequently the elderly population, causing a significant emotional burden both for the patient and caregivers, due to the disease-related onset of motor and cognitive disabilities. iPD's clinical hallmark is the onset of cardinal motor symptoms such as bradykinesia, rest tremor, rigidity, and postural instability. However, these symptoms appear when the neurodegenerative process is already in an advanced stage. Furthermore, the greatest challenge is to distinguish iPD from other similar neurodegenerative disorders, "atypical parkinsonisms", such as Multisystem Atrophy, Progressive Supranuclear Palsy and Cortical Basal Degeneration, since they share many phenotypic manifestations, especially in the early stages. The diagnosis of these neurodegenerative motor disorders is essentially clinical. Consequently, the diagnostic accuracy mainly depends on the professional knowledge and experience of the physician. Recent advances in artificial intelligence have made it possible to analyze the large amount of clinical and instrumental information in the medical field. The application machine learning algorithms to the analysis of neuroimaging data appear to be a promising tool for identifying microstructural alterations related to the pathological process in order to explain the onset of symptoms and the spread of the neurodegenerative process. In this context, the search for quantitative biomarkers capable of identifying parkinsonian patients in the prodromal phases of the disease, of correctly distinguishing them from atypical parkinsonisms and of predicting clinical evolution and response to therapy represent the main goal of most current clinical research studies. Our aim was to review the recent literature and describe the current knowledge about the contribution given by machine learning applications to research and clinical management of parkinsonian syndromes

Dc superconducting quantum interference device amplifier for gravitational wave detectors with a true noise temperature of 16 μK

We report on the noise characterization of a two-stage dc superconducting quantum interference device (SQUID) amplifier developed for resonant gravitational wave detectors. The back action noise is estimated by coupling the SQUID to an electrical resonator at 1.6 kHz with Q=1.1×106. From measurements of back action and additive SQUID noise, performed in the temperature range 1.5–4.2 K, an upper limit is set on the noise temperature Tn of the device at the resonator frequency. The best value obtained at 1.5 K is Tn⩽16 μK and corresponds to 200 resonator quanta. The thermal component of the noise temperature is found in reasonable agreement with the predicted value

Haemodynamic Crosstalk Between Carotid Arteries and Implications for Wall Shear Stress Measurements

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Mesoporous bioactive glass as a multifunctional system for bone regeneration and controlled drug release

Purpose: Coupling the potential for bone regeneration and the ability for in situ controlled drug release in a single device is a challenging field of research in bone tissue engineering; in an attempt to pursue this aim, mesoporous bioactive glass (MBG) membranes belonging to the SiO2-P2O5-CaO ternary system were produced and characterized. Methods: The glass was synthesized via a sol-gel route coupled with an evaporation-induced self-assembly process by using a non-ionic block co-polymer as a mesostructure former. MBG structure and morphology, as well as mesopores size and shape, were investigated by x-ray diffraction, transmission electron microscopy, and N2 adsorption-desorption measurements. In vitro bioactivity was investigated by soaking MBG membranes in simulated body fluid (SBF) for different time frames. Ibuprofen was encapsulated into MBG pores and drug release kinetics in SBF were assessed. Biological tests by using SAOS-2 cells were performed to assess the material cytocompatibility. Results: The material revealed significant ability to induce hydroxyapatite formation on its surface (bioactivity). Drug release kinetics in SBF are very similar to those obtained for mesoporous silica having mesopore size comparable to that of the prepared MBG (∼5 nm). No evidence of cell viability depression was detected during in vitro culture, which demonstrates the good biological compatibility of the material. Conclusions: The easiness of tailoring and shaping, the highly bioactive and biocompatible behavior, and the drug uptake/release ability of the prepared materials may suggest their use as "smart" multifunctional grafts for bone reconstructive surgery