Mortalidad por cáncer bucomaxilofacial según nivel socio económico en la Región Metropolitana período 2002-2014

Tesis (Cirujano Dentista)Objetivo: Describir las tasas de mortalidad de cáncer orofaringeo comunal según IDH. Región Metropolitana, Santiago de Chile, 2002-2014. Material y Método: Estudio ecológico descriptivo. La población fueron los casos de 45 a más años. Se calcularon tasas de mortalidad cruda y ajustada por año y periodo. Se ajustó por método directo para comparar entre comunas y controlar el efecto de la edad, sexo e IDH. Resultados: La tasa ajustada para el periodo fue 3,98 muertes por 100.000 habitantes (5,93 hombres vs 2,3 mujeres). Según IDH, la tasa ajustada fue 15,6% mayor en el grupo de comunas con IDH alto y 13,8% más en el grupo de comunas con IDH medio respecto al grupo de IDH alto. Conclusión: La mortalidad por cáncer bucofaríngeo, entre los años 2002 y 2014, en las diferentes comunas de la Región Metropolitana presentaron una estrecha relación con los indicadores socioeconómicos.Objective: To describe, by commune, the mortality rates of oropharyngeal cancer according to HDI (Human Development Index). Metropolitan Region, Santiago, Chile, 2002-2014. Material and Method: The cases were the 45 years old and more age population., the crude and adjusted mortality rates have been calculating per years and periods. It has been adjusted by direct method to compare among communes and to control the age effect, sex and HDI. Results: The adjusted rate for the period was 3.98 deaths for each 100,000 peoples (5.93 men vs 2.3 women). According to the HDI, the adjusted rate was 15.6% greater in high HDI communes group and 13.8% upper in the medium HDI communes group than in high HDI group. Conclusion: Mortality for oropharyngeal cancer between 2002 and 2014 in the different communes of the Metropolitan Region showed a close relationship with socioeconomic indicators

Exploiting sensor data to increase compliance with ecological momentary assessments

LAUREA MAGISTRALELa salute mentale nelle università è un problema serio. Gli Ecological Momentary Assessment (EMA) sono una famiglia di strumenti che si sono rivelati molto efficaci per la sua valutazione. Purtroppo però di solito sono percepiti come un peso da parte degli utenti e perciò il tasso di conformità è molto basso. In questo lavoro proponiamo un algoritmo di Machine Learning che sfrutta i dati raccolti dagli smartphone per selezionare il miglior EMA da mostrare all’utente per aumentare la sua conformità. Viene formulato un modello matematico per la valutazione della Quantità di Informazione contenuta nei diversi EMA. Successivamente, utilizziamo una variante dell’algoritmo “Multi-Armed Bandit” per selezionare il miglior EMA da visualizzare a seconda del contesto rilevato. Tramite una sperimentazione con 8 partecipanti scopriamo come a diversi contesti corrispondano diversi EMA ottimali. Infine, durante un colloquio individuale con i partecipanti alla fine dello studio riscontriamo quanto sia importante per l’utente avere un formato di EMA che apprezzi e la stretta dipendenza tra la sua disponibilità nel rispondere e il contesto in cui si trova.Monitoring Mental health in student population is a very important task. Ecological Momentary Assessments (EMAs) is a method based on questions prompted on a smartphone to capture the subjective state of an individual in their natural context. Unfortunately, EMAs are perceived as very burdening by the users, and therefore the compliance rate is often low. We propose a machine learning algorithm to exploit sensor data from smartphone to select the optimal format EMA format to prompt such that it maximizes users’ compliance and, consequently, the information get by the researcher. A framework to evaluate the “Quantity of Information” is formulated and used to determine the informativeness of a set of EMAs. Then, a “Multi-Armed Bandit” algorithm variant is employed to select the best EMA according to the sensed context. A small scale field study (8 participants) is carried out, to discover how to different contexts often correspond different optimal EMAs. An individual interview with each participant reveals the importance of the employment of a format of EMA the users appreciate, and the dependence between the context in which they are and their availability to answer different format of EMAs

Multimodal conversational interfaces : design, modelling, applications

DOTTORATOUn agente conversazionale è un software che imita la conversazione umana. Questi agenti stanno riscuotendo sempre più successo e sono adottati in un’ampia gamma di settori, come l’istruzione, l’assistenza agli utenti, la salute mentale e la domotica. Negli ultimi anni, l’interazione con gli agenti conversazionali è stata integrata con altre modalità di interazione per aumentare le capacità del sistema, creando nuovi paradigmi di interazione multimodale. Tuttavia, nonostante sia ampiamente sfruttata, questa integrazione è ancora limitata da un punto di vista metodologico. Questa tesi studia la progettazione, la modellazione e lo sviluppo di agenti conversazionali multimodali. Il lavoro inizia ad esplorare questo dominio partendo dalla progettazione di GeCoAgent e DSBot, due agenti conversazionali a supporto del processo di data science. GeCoAgent è una piattaforma conversazionale multimodale che consente a biologi e clinici di definire pipeline di analisi dei dati genomici attraverso il dialogo con il sistema. La piattaforma lo traduce automaticamente in codice, lo esegue e restituisce all’utente i risultati. Il processo di progettazione di GeCoAgent ha portato anche a modellare il processo di analisi terziaria bioinformatica sotto forma di un’ontologia che può essere utilizzata come riferimento per elicitare i requisiti delle applicazioni interattive. DSBot evolve questo concetto fornendo uno strumento che traduce le domande di ricerca degli utenti, espresse in linguaggio naturale, in pipeline eseguibili. Il sistema sfrutta le metodologie autoML per selezionare l’algoritmo migliore e ottimizzare la scelta dei parametri in modo automatico. Gli utenti sono coinvolti nel processo attraverso la conversazione quando devono essere prese decisioni relative al significato dei dati. Inoltre, abbiamo ri- lasciato uno dei due moduli di DSBot come framework open-source per la risoluzione di problemi conversazionali multimodali. Dopo aver valutato le potenzialità delle interfacce conversazionali multimodali, ci siamo resi conto che la loro progettazione è un dominio largamente inesplorato. Per questo motivo, abbiamo analizzato la letteratura per elicitare una serie di principi da seguire durante il processo di progettazione e abbiamo formalizzato un quadro concettuale per descrivere i possibili gradi di integrazione tra agenti conversazionali e interfacce che sfruttano altre modalità. Successivamente, integriamo i risultati della letteratura tramite l’analisi dell’impatto della multimodalità sull’esperienza conversazionale da una prospettiva linguistica. Osserviamo le performance linguistiche degli utenti in uno studio comparativo con più di 200 partecipanti per valutare come l’introduzione di elementi grafici influisca sull’esperienza conversazionale. Su questi risultati, fondiamo la formulazione di un modello concettuale a supporto del processo di progettazione di interfacce conversazionali multimodali. Il modello sfrutta diagrammi gerarchici, ispirati al formalismo BPMN, per modellare l’interazione conversazionale e separare la descrizione del compito da come viene reificato nelle varie modalità. Nell’ultima parte della tesi, descriviamo Albot Einstein, un caso di studio di un agente conversazionale pedagogico multimodale per insegnare il pH ai bambini. Inoltre, per validare le capacità descrittive del modello, testiamo l’efficacia della piattaforma in uno studio comparativo con 28 bambini, ottenendo risultati paragonabili a quelli ottenuti con un’applicazione web interattiva “tradizionale”. Abbiamo progettato e sviluppato uno strumento di authoring grafico che consente di trasformare le informazioni espresse in una notazione derivata da quella del modello in un’istanza di backend dell’applicazione. Una valutazione empirica con 15 sviluppatori mostra come tale interfaccia possa supportare lo sviluppo di interfacce conversazionali multimodali. Infine, discutiamo come il lavoro presentato possa essere inquadrato in un unico frame- work che copre l’intero processo di progettazione e implementazione di un agente conversazionale multimodale.A conversational agent is a software that mimics human conversation. They are becoming increasingly successful and adopted in a wide range of domains, such as education, user assistance, mental health, and home automation. In recent years, the interaction with conversational agents has been blended with other interaction modalities to increase the system’s capabilities, creating new multimodal paradigms for interaction. However, this integration is still limited from a methodological perspective despite being broadly exploited. This Ph.D. research investigates the design, modeling, and development of multimodal conversational agents. This work starts exploring this domain from the design of GeCoAgent and DSBot, two conversational agents to support the data science process. GeCoAgent is a multimodal conversational platform to enable biologists and clinicians to define data analysis pipelines on genomic data through dialogue. The platform automatically translates it into code, executes it, and returns the user the results. GeCoAgent’s design process also led to modeling the bioinformatics tertiary analysis process in the form of an ontology that can be used as a reference to elicit the requirements for interactive applications. DSBot evolves this concept by providing a tool that translates users’ research questions, expressed in natural language, into executable pipelines. The system exploits autoML methodologies to select the best algorithm and optimize the parameter selection automatically. Users are involved in the process through the conversation when decisions related to the meaning of the data must be taken. In addition, we release one of the two modules of DSBot as an open-source framework for multimodal conversational troubleshooting. Having assessed the potentialities of multimodal conversational interfaces, we realize that their design is a largely unexplored field. For this reason, we survey the literature to elicit a set of principles to follow during the design process, and we formalize a conceptual frame- work to describe the possible degrees of integration of conversational agents and other interfaces. Then, we complement the finding in the literature by analyzing the impact of multimodality on the conversational experience from a linguistic perspective. We observe users’ linguistic performances in a comparative study with more than 120 participants to assess how the introduction of graphical elements affects the conversational experience. We use these findings to ground the formulation of a conceptual model to support the design process of multimodal conversational interfaces. The model exploits hierarchical schemes, inspired by BPMN formalism, to model conversational interaction and separate the task’s description from how it is reified on the various modalities. In the last part of the thesis, we describe Albot Einstein, a case study of a multimodal pedagogical conversational agent to teach pH to children. In addition, to validate the descriptive capabilities of the model, we test the platform’s efficacy in a comparative study with 28 children, obtaining results comparable to the ones achieved through a ‘‘traditional” interactive web application. We design and develop a graphical authoring tool that enables that transform expressed in a notation derived from one of the model into an instance of the application backend. An empirical evaluation with 15 developers shows how such an interface can support developing multimodal conversational interfaces. Finally, we discuss how the work presented can be framed in a single framework that covers a multimodal conversational agent’s whole design and implementation process.DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIAComputer Science and Engineering35MIRANDOLA, RAFFAELAPIRODDI, LUIG

History of polio vaccination in Italy

Polio, as a social disease, was first noted in Italy after the First World War (1915-18), with a consistent upward trend in the number of reported cases (Table 1, Figure 1). This situation has led to important research being undertaken in several National Hygiene Departments, in particular those located in Milan (Giovanardi, Monaci, Bergamini), Genoa (Petrilli, Agnese, Crovari), Palermo (D’Alessandro, Dardanoni), and Padua (Vendramini, Majori, Gasparini). Studies such as these, have examined the epidemiological and virological character of the illness in order to determine modalities for disease prevention. These studies demonstrated that all three poliovirus serotypes were circulating in Italy, with a higher prevalence (as a cause of paralytic disease) of poliovirus type 1 (about 80%), followed by type 3 (about 15%) and then type 2 (about 10 %). The presence of healthy carriers of the virus was very common in children (2-3%).The evidence of neutralizing antibodies in patients of different age groups confirmed that poliovirus infection was widespread. About 90% of the population over 14 years of age had antibodies against all three serotypes.

Invasive diseases: new vaccines and vaccination strategies

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Influenza (AH1N1v) Pandemic 2009: an update

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The intradermal vaccination: past experiences and current perspectives

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Delivering Green Persuasion Strategies with a Conversational Agent: a Pilot Study

Climate change is undeniable. The drastic consequences it may have on our lives make a collective effort crucial. Our research explores how Conversational Agents (CAs) can persuade people into environmentally sustainable behaviors, particularly in domestic spaces where these technologies are becoming increasingly popular. In this research work, we conducted an empirical evaluation (N=29) exploring the effectiveness and stance towards the adoption of different persuasive strategies compared to a CA delivering messages referring to just one persuasion strategy. Furthermore, this contribution reports on a custom dialogue manager's implementation, designed to enable the execution of the experiment. Although study results suggested no significant difference in persuasion effectiveness and usability of the conversational agents, participants reported a significant difference in the perceptions of parasocial interactions and dialogue with the CA, preferring the one delivering multiple persuasive strategies

Multicriteria Decision Analysis and Conversational Agents for children with autism

Conversational agents has emerged as a new means of communication and social skills training for children with autism spectrum disorders (ASD), encouraging academia, industry, and therapeutic centres to investigate it further. This paper aims to develop a methodological framework based on Multicriteria Decision Analysis (MCDA) to identify the best , i.e. the most effective, conversational agent for this target group. To our knowledge, it is the first time the MCDA is applied to this specific domain. Our contribution is twofold: i) our method is an extension of traditional MCDA and we exemplify how to apply it to decision making process related to CA for person with autism: a methodological result that would be adopted for a broader range of technologies for person with impairments similar to ASD; ii) our results, based on the above mentioned method, suggest that Embodied Conversational Agent is most appropriate conversational technology to interact with children with ASD

Delivering Green Persuasion Strategies with a Conversational Agent: a Pilot Study

Climate change is undeniable. The drastic consequences it may have on our lives make a collective effort crucial. Our research explores how Conversational Agents (CAs) can persuade people into environmentally sustainable behaviors, particularly in domestic spaces where these technologies are becoming increasingly popular. In this research work, we conducted an empirical evaluation (N=29) exploring the effectiveness and stance towards the adoption of different persuasive strategies compared to a CA delivering messages referring to just one persuasion strategy. Furthermore, this contribution reports on a custom dialogue manager\u27s implementation, designed to enable the execution of the experiment. Although study results suggested no significant difference in persuasion effectiveness and usability of the conversational agents, participants reported a significant difference in the perceptions of parasocial interactions and dialogue with the CA, preferring the one delivering multiple persuasive strategies