4 resultados para Outcomes virtual case manager

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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OBIETTIVI: Valutazione del rischio di trasmissione verticale e delle conseguenze dell’infezione congenita da cytomegalovirus (CMV) in caso di infezione non primaria versus l’outcome delle gravidanze complicate da infezione primaria. MATERIALI E METODI: Studio retrospettivo di coorte di gravide con infezione recente da CMV diagnosticata c/o il nostro centro negli anni 2000-2013. Le pazienti sono state suddivise in 2 gruppi in base al risultato delle indagini sierologiche (avidità IgG e immunoblot): il primo con profilo sierologico compatibile con infezione non primaria e l'altro compatibile con infezione primaria da CMV. Sono stati confrontati il rischio di trasmissione e di infezione congenita sintomatica nei due gruppi. RISULTATI: Il follow-up è risultato disponibile in 1122 casi di cui 182 con infezione materna non-primaria e 940 con infezione primaria materna. L’infezione congenita è stata diagnosticata in 7 (3.86%) feti/neonati nei casi di infezione non primaria e in 217 (23%) feti/neonati nei casi di infezione primaria (p<0.001). Tra gli infetti, erano sintomatici 43 (19,8%) e 3 (42,8%) rispettivamente nell’infezione primaria e non primaria. COMMENTO: La preesistente immunità materna offre una protezione contro la trasmissione intrauterina nell’infezione da CMV ma non protegge dalla malattia congenita sintomatica.

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Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.

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Broad consensus has been reached within the Education and Cognitive Psychology research communities on the need to center the learning process on experimentation and concrete application of knowledge, rather than on a bare transfer of notions. Several advantages arise from this educational approach, ranging from the reinforce of students learning, to the increased opportunity for a student to gain greater insight into the studied topics, up to the possibility for learners to acquire practical skills and long-lasting proficiency. This is especially true in Engineering education, where integrating conceptual knowledge and practical skills assumes a strategic importance. In this scenario, learners are called to play a primary role. They are actively involved in the construction of their own knowledge, instead of passively receiving it. As a result, traditional, teacher-centered learning environments should be replaced by novel learner-centered solutions. Information and Communication Technologies enable the development of innovative solutions that provide suitable answers to the need for the availability of experimentation supports in educational context. Virtual Laboratories, Adaptive Web-Based Educational Systems and Computer-Supported Collaborative Learning environments can significantly foster different learner-centered instructional strategies, offering the opportunity to enhance personalization, individualization and cooperation. More specifically, they allow students to explore different kinds of materials, to access and compare several information sources, to face real or realistic problems and to work on authentic and multi-facet case studies. In addition, they encourage cooperation among peers and provide support through coached and scaffolded activities aimed at fostering reflection and meta-cognitive reasoning. This dissertation will guide readers within this research field, presenting both the theoretical and applicative results of a research aimed at designing an open, flexible, learner-centered virtual lab for supporting students in learning Information Security.

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La città medievale di Leopoli-Cencelle (fondata da Papa Leone IV nell‘854 d.C. non lontano da Civitavecchia) è stata oggetto di studio e di periodiche campagne di scavo a partire dal 1994. Le stratigrafie investigate con metodi tradizionali, hanno portato alla luce le numerose trasformazioni che la città ha subìto nel corso della sua esistenza in vita. Case, torri, botteghe e strati di vissuto, sono stati interpretati sin dall’inizio dello scavo basandosi sulla documentazione tradizionale e bi-dimensionale, legata al dato cartaceo e al disegno. Il presente lavoro intende re-interpretare i dati di scavo con l’ausilio delle tecnologie digitali. Per il progetto sono stati utilizzati un laser scanner, tecniche di Computer Vision e modellazione 3D. I tre metodi sono stati combinati in modo da poter visualizzare tridimensionalmente gli edifici abitativi scavati, con la possibilità di sovrapporre semplici modelli 3D che permettano di formulare ipotesi differenti sulla forma e sull’uso degli spazi. Modellare spazio e tempo offrendo varie possibilità di scelta, permette di combinare i dati reali tridimensionali, acquisiti con un laser scanner, con semplici modelli filologici in 3D e offre l’opportunità di valutare diverse possibili interpretazioni delle caratteristiche dell’edificio in base agli spazi, ai materiali, alle tecniche costruttive. Lo scopo del progetto è andare oltre la Realtà Virtuale, con la possibilità di analizzare i resti e di re-interpretare la funzione di un edificio, sia in fase di scavo che a scavo concluso. Dal punto di vista della ricerca, la possibilità di visualizzare le ipotesi sul campo favorisce una comprensione più profonda del contesto archeologico. Un secondo obiettivo è la comunicazione a un pubblico di “non-archeologi”. Si vuole offrire a normali visitatori la possibilità di comprendere e sperimentare il processo interpretativo, fornendo loro qualcosa in più rispetto a una sola ipotesi definitiva.