Gli accordi tra pubblica amministrazione e privati.

Lo scopo di questa tesi è quello di descrivere come l'introduzione della consensualità vada ad incidere nell'azione amministrativa e nei tradizionali rapporti tra potere pubblico e privati. Il lavoro è suddiviso in quattro capitoli. Nel primo capitolo ho trattato l'evoluzione delle teorie più significative sulla possibilità dell'introduzione del principio di consensualità nell'azione amministrativa; partendo da una concezione di pubblica ammistrazione monolitica e autoritaria, propria della concezione ottocentesca dello Stato di diritto, fino ad arrivare alla commissione Nigro e alla legge 7 agosto 1990, n.214, che con l'art. 11 ha introdotto la figura degli accordi tra pubblica amministrazione e privati. Nel secondo capitolo ho trattato l'inquadramento sistematico degli accordi ex art. 11, anche alla luce dell'importante legge 11 febbraio 2005, n. 15. Ho inoltre analizzato le varie teorie sulla natura giuridica degli accordi amministrativi, comprendendo in questa analisi le altanelanti pronunce giurisprudenziali, fino alla nota sentenza n. 204 del 6 luglio 2004 della Corte Costituzionale, che ha consacrato la concezione pubblicistica degli accordi amministrativi. Il terzo capitolo è dedicato al regime giuridico degli accordi partendo da quattro tipi di fonti: le regole individuate direttamente dall’art. 11; la disciplina contenuta nelle leggi settoriali; i principi del Codice civile in materia di obbligazioni e contratti; le clausole dell’accordo definibili dalle parti nello scambio negoziale. Ho poi analizzato i casi di patologia dell'accordo e quale disciplina si applica ai singoli casi per porvi rimedio, tenendo conto della giurisdizione esclusiva del giudice amministrativo. Ho dedicato il quarto capitolo alle fattispecie di accordi tipizzate dal legislatore, concentrandomi particolarmente sulle convenzioni urbanistiche. Ho poi analizzato le concessioni di diritti pubblici e la figura del project financing

Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging

Cluster of microcalcifications can be an early sign of breast cancer. In this paper we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work we used 283 mammograms to train and validate our model, obtaining an accuracy of 98.22% in the detection of preliminary suspect regions and of 97.47% in the segmentation task. Our results show how deep learning could be an effective tool to effectively support radiologists during mammograms examination.Comment: 13 pages, 7 figure

An automatic deep learning approach for coronary artery calcium segmentation

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications

OS DESASTRES AMBIENTAIS E OS REFUGIADOS AMBIENTAIS: parâmetros para um desenvolvimento humano sustentável

O objetivo deste artigo é compreender o fenômeno dos refugiados ambientais consequência dos desastres ambientais como um problema de justiça. O aumento desse contingente clama pela busca de soluções sustentáveis, especialmente quando esses dramas são inevitáveis. Os movimentos migratórios forçados, nestes casos, estão relacionados com a falta de estrutura social de acolhida interna e a ausência de vontade política para a sua solução. Quando obrigados a migrar para outros países enfrentam diversas formas de exclusão e sofrimento. Esta abordagem tem como base a compreensão de sustentabilidade ambiental com técnicas de pesquisa bibliográfica e fontes secundárias. Afirma-se a necessidade de um modelo de desenvolvimento humano sustentável para a construção de soluções equitativas

A Conway–Maxwell–Poisson (CMP) model to address data dispersion on positron emission tomography

Positron emission tomography (PET) in medicine exploits the properties of positron-emitting unstable nuclei. The pairs of γ- rays emitted after annihilation are revealed by coincidence detectors and stored as projections in a sinogram. It is well known that radioactive decay follows a Poisson distribution; however, deviation from Poisson statistics occurs on PET projection data prior to reconstruction due to physical effects, measurement errors, correction of deadtime, scatter, and random coincidences. A model that describes the statistical behavior of measured and corrected PET data can aid in understanding the statistical nature of the data: it is a prerequisite to develop efficient reconstruction and processing methods and to reduce noise. The deviation from Poisson statistics in PET data could be described by the Conway-Maxwell-Poisson (CMP) distribution model, which is characterized by the centring parameter λ and the dispersion parameter ν, the latter quantifying the deviation from a Poisson distribution model. In particular, the parameter ν allows quantifying over-dispersion (ν<1) or under-dispersion (ν>1) of data. A simple and efficient method for λ and ν parameters estimation is introduced and assessed using Monte Carlo simulation for a wide range of activity values. The application of the method to simulated and experimental PET phantom data demonstrated that the CMP distribution parameters could detect deviation from the Poisson distribution both in raw and corrected PET data. It may be usefully implemented in image reconstruction algorithms and quantitative PET data analysis, especially in low counting emission data, as in dynamic PET data, where the method demonstrated the best accuracy

Bacteriological conversion in twenty urinary tuberculosis patients treated with ofloxacin, rifampin and isoniazid: a 10-year follow-up study

Twenty patients withuri nary tuberculosis were treated withofloxac in (200 mg/day, 6 months), rifampin (600 mg/day, 3 months) and isoniazid (300 mg/day, 3 months) between 1989 and 1990. All patients were new cases, diagnosed by observation and/or isolation of Mycobacterium tuberculosis in one of the three morning urine samples. Bacteriological culture conversion (negativization) was assessed as a clinical guide of efficacy, comparing it, as the only parameter, against a control group (150 patients) withurina ry tuberculosis who received conventional therapy. Bacteriological follow-up studies were performed in bothgroups monthly for 6 months, then again 6 months later and then every year for 10 years after completion of treatment. In the 20 patients, the initial culture was positive with over 100 colonies per culture (>50%); the smear was positive in 45% of the patients (most were 2+). All strains were susceptible to rifampin, isoniazid and ofloxacin. Two patients discontinued treatment. Beginning withth e first monthof treatment, the bacteriological conversion was 100%, 89.5% and 100% in the remaining controls. In the control group, which received conventional treatment, the conversion was: 90%, 87%, 93% and 100% in the remaining controls. Treatment withofloxacin resulted in a bacteriological conversion similar to that following conventional treatment (p>0.05, Fisher’s exact test). After 10 years of patient follow-up, we conclude that ofloxacin, in combination withrifampin and isoniazid (bothfor 3 months only is effective against M. tuberculosis, providing satisfactory bacteriological and clinical efficacy

4-Dimensional Velocity Mapping Cardiac Magnetic Resonance of Extracardiac Bypass for Aortic Coarctation Repair

Abstract This report describes a case of a young lady who, following extracardiac bypass between ascending and descending aorta for severe aortic coarctation, underwent 4-dimensional flow cardiac magnetic resonance, a technique that, by 3-dimensional flow assessment over time (4-dimensional), allows not only quantification of flows but also wall shear stress. In this case, increased wall shear stress was observed in the conduit's acute angle (kinking) as well as at the distal anastomosis level. The authors postulate that increased wall shear stress could help identify and risk stratify adult congenital heart disease who could develop vascular complications in the future. ( Level of Difficulty: Intermediate.

Locus Coeruleus Magnetic Resonance Imaging in Neurological Diseases

Locus coeruleus (LC) is the main noradrenergic nucleus of the brain, and its degeneration is considered to be key in the pathogenesis of neurodegenerative diseases. In the last 15 years,MRI has been used to assess LC in vivo, both in healthy subjects and in patients suffering from neurological disorders. In this review, we summarize the main findings of LC-MRI studies, interpreting them in light of preclinical and histopathological data, and discussing its potential role as diagnostic and experimental tool