Il processo migratorio come determinante della salute mentale: l'esperienza del Centro di Consultazione Socio-Culturale nel Distretto di Pianura Est, AUSL di Bologna.

La ricerca in oggetto ha analizzato le relazioni tra migrazione e salute mentale nel Distretto di Pianura Est dell'AUSL di Bologna. Attraverso un dispositivo d’indagine multi-disciplinare basato sui quadri teorici dell'Antropologia Medica Critica, della Salute Pubblica e della Psichiatria, la ricerca si è inserita nell’ampio contesto di sperimentazione di un innovativo modello di assistenza per pazienti migranti, denominato Centro di Consultazione Socio- Culturale. L'architettura dello studio si rifà a un modello di Ricerca-Azione Partecipata e Multi-Situata fondato su un approccio analitico e auto-riflessivo, il quale ha consentito di problematizzare, oltre alle azioni e alle traiettorie dei vari soggetti che operano nel campo della ricerca, anche le categorie oggetto della ricerca stessa. L'analisi, profondamente radicata nel dato empirico, è stata condotta a partire dall'esperienza degli attori sociali coinvolti. Le esperienze, le informazioni e le rappresentazioni reciproche sono state co-costruite in forma partecipativa attraverso l'uso combinato di metodologie quali-quantitative proprie sia delle discipline sanitarie sia di quelle sociali. Come materiali della ricerca sono stati utilizzati: dati primari e secondari prodotti dalle istituzioni e dalle organizzazioni del territorio stesso; informazioni provenienti dall'osservazione partecipante; colloqui con informatori-chiave; interviste semi-strutturate con decisori politici, amministratori, organizzazioni del territorio, operatori dei servizi, cittadini e pazienti. La ricerca ha dimostrato la validità delle prospettive teoriche utilizzate e delle strategie di lavoro proposte. Il modello di lavoro multi-disciplinare e multi-metodologico si è rivelato produttivo nell'indagare congiuntamente le prospettive degli attori coinvolti insieme alle loro traiettorie, alle reciproche interconnessioni e alle relazioni tra processi locali e globali. L’analisi auto-riflessiva ha consentito di analizzare le attività del Centro di Consultazione evidenziandone vantaggi e limiti. Infine, la collaborazione tra Salute Pubblica e Antropologia Medica Critica ha dimostrato una grande potenzialità e produttività sia sul versante della ricerca scientifica sia su quello dell'assistenza sanitaria.

Formalizing languages for service oriented computing

Service Oriented Computing is a new programming paradigm for addressing distributed system design issues. Services are autonomous computational entities which can be dynamically discovered and composed in order to form more complex systems able to achieve different kinds of task. E-government, e-business and e-science are some examples of the IT areas where Service Oriented Computing will be exploited in the next years. At present, the most credited Service Oriented Computing technology is that of Web Services, whose specifications are enriched day by day by industrial consortia without following a precise and rigorous approach. This PhD thesis aims, on the one hand, at modelling Service Oriented Computing in a formal way in order to precisely define the main concepts it is based upon and, on the other hand, at defining a new approach, called bipolar approach, for addressing system design issues by synergically exploiting choreography and orchestration languages related by means of a mathematical relation called conformance. Choreography allows us to describe systems of services from a global view point whereas orchestration supplies a means for addressing such an issue from a local perspective. In this work we present SOCK, a process algebra based language inspired by the Web Service orchestration language WS-BPEL which catches the essentials of Service Oriented Computing. From the definition of SOCK we will able to define a general model for dealing with Service Oriented Computing where services and systems of services are related to the design of finite state automata and process algebra concurrent systems, respectively. Furthermore, we introduce a formal language for dealing with choreography. Such a language is equipped with a formal semantics and it forms, together with a subset of the SOCK calculus, the bipolar framework. Finally, we present JOLIE which is a Java implentation of a subset of the SOCK calculus and it is part of the bipolar framework we intend to promote.

Knowledge Flows and Networks: the Interplay between Local and Global Linkages within Bangalore IT Cluster

This doctoral work gains deeper insight into the dynamics of knowledge flows within and across clusters, unfolding their features, directions and strategic implications. Alliances, networks and personnel mobility are acknowledged as the three main channels of inter-firm knowledge flows, thus offering three heterogeneous measures to analyze the phenomenon. The interplay between the three channels and the richness of available research methods, has allowed for the elaboration of three different papers and perspectives. The common empirical setting is the IT cluster in Bangalore, for its distinguished features as a high-tech cluster and for its steady yearly two-digit growth around the service-based business model. The first paper deploys both a firm-level and a tie-level analysis, exploring the cases of 4 domestic companies and of 2 MNCs active the cluster, according to a cluster-based perspective. The distinction between business-domain knowledge and technical knowledge emerges from the qualitative evidence, further confirmed by quantitative analyses at tie-level. At firm-level, the specialization degree seems to be influencing the kind of knowledge shared, while at tie-level both the frequency of interaction and the governance mode prove to determine differences in the distribution of knowledge flows. The second paper zooms out and considers the inter-firm networks; particularly focusing on the role of cluster boundary, internal and external networks are analyzed, in their size, long-term orientation and exploration degree. The research method is purely qualitative and allows for the observation of the evolving strategic role of internal network: from exploitation-based to exploration-based. Moreover, a causal pattern is emphasized, linking the evolution and features of the external network to the evolution and features of internal network. The final paper addresses the softer and more micro-level side of knowledge flows: personnel mobility. A social capital perspective is here developed, which considers both employees’ acquisition and employees’ loss as building inter-firm ties, thus enhancing company’s overall social capital. Negative binomial regression analyses at dyad-level test the significant impact of cluster affiliation (cluster firms vs non-cluster firms), industry affiliation (IT firms vs non-IT fims) and foreign affiliation (MNCs vs domestic firms) in shaping the uneven distribution of personnel mobility, and thus of knowledge flows, among companies.

Machine learning as a service for high energy physics (MLaaS4HEP): a service for ML-based data analyses

With the CERN LHC program underway, there has been an acceleration of data growth in the High Energy Physics (HEP) field and the usage of Machine Learning (ML) in HEP will be critical during the HL-LHC program when the data that will be produced will reach the exascale. ML techniques have been successfully used in many areas of HEP nevertheless, the development of a ML project and its implementation for production use is a highly time-consuming task and requires specific skills. Complicating this scenario is the fact that HEP data is stored in ROOT data format, which is mostly unknown outside of the HEP community. The work presented in this thesis is focused on the development of a ML as a Service (MLaaS) solution for HEP, aiming to provide a cloud service that allows HEP users to run ML pipelines via HTTP calls. These pipelines are executed by using the MLaaS4HEP framework, which allows reading data, processing data, and training ML models directly using ROOT files of arbitrary size from local or distributed data sources. Such a solution provides HEP users non-expert in ML with a tool that allows them to apply ML techniques in their analyses in a streamlined manner. Over the years the MLaaS4HEP framework has been developed, validated, and tested and new features have been added. A first MLaaS solution has been developed by automatizing the deployment of a platform equipped with the MLaaS4HEP framework. Then, a service with APIs has been developed, so that a user after being authenticated and authorized can submit MLaaS4HEP workflows producing trained ML models ready for the inference phase. A working prototype of this service is currently running on a virtual machine of INFN-Cloud and is compliant to be added to the INFN Cloud portfolio of services.