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[pt] A popularização da Internet das Coisas (IoT) abriu uma série de oportuni-dades para a geração de novas aplicações que não eram possíveis anteriormente. No cenário atual de IoT existem marketplaces que vendem soluções completas para os clientes com objetos inteligentes, gateways para a transmissão dos dados e provedores que analisam estes por uma taxa de assinatura. Partimos da visão de que no futuro deverá ocorrer uma uberização de IoT, onde cada pessoa poderá oferecer dados de sensores e acesso a atuadores para outra e que eles estarão categorizados com base no QoS dos objetos que os fornecem, similarmente como são classificadas commodities hoje. Além disso, haverá plataformas multilaterais onde essas informações poderão ser negociadas em combinação com provedores de conectividade, para transmitir os dados, e de análise. Uma plataforma que fornece esse serviço deve garantir que o fluxo de dados (e do estado) de objetos seja contínuo, sem expor para o cliente algum problema de conectividade entre eles e os provedores. Ou seja, ela deve ter mecanismos para detectá-los e rapidamente selecionar novos provedores, isso dentro de um cenário de intensa troca de dados. Este trabalho apresenta como contribuições um mecanismo de detecção contínuo de problemas de conectividade que utiliza o paradigma Publish-Subscribe para o envio de mensagens de identificação de problemas e uma solução arquitetural de uma plataforma baseada em conceitos de marketplaces para IoT, que inclui os serviços de comoditização dos provedores de serviço e o matchmaking para selecionar uma combinação destes para prestar serviços para o cliente. Um estudo de caso no domínio de marketplaces é conduzido, com a análise dos serviços da plataforma em vários cenários de testes e a avaliação do mecanismo de detecção de problemas de conectividade, com a simulação de diferentes falhas na conexão. / [en] The popularization of the Internet of Things (IoT) opened up a series of opportunities for the generation of new applications that were not previously possible. In the current scenario of IoT there are marketplaces that sell complete solutions for users with smart objects, gateways for data transmission and providers that analyze these for a subscription fee. We start from the view that in the future an uberization of IoT should occur, where each person can offer sensor data and access to actuators to another and that they will be categorized based on the QoS of the objects that provide them, similarly as commodities are classified today. In addition, there will be multilateral platforms where this information can be negotiated in combination with connectivity providers, to transmit data, and analytics. A platform that provides this service must ensure that the data (and state) flow of objects is continuous, without exposing to the user any connectivity problems between them and the providers. That is, it must have mechanisms to detect problems and quickly select new providers, all this in a scenario of intense data exchange. This work presents as contributions a continuous connectivity problem detection mechanism that uses a Publish-Subscribe paradigm to send problem identification messages and an architectural solution of a platform based on marketplaces concepts for IoT, which includes the commoditization of service providers and a matchmaking service to select a combination of these to provide services to the customer. A case study in the domain of marketplaces is conducted, with the analysis of the services of the platform with several tests scenarios and the evaluation of the mechanism of detection of connectivity problems, with the simulation of different connection failures.

Master of Arts / Modern Languages / Earl K. Brown / Considerable research exists on subjunctive versus indicative mood patterns of use by both native and L2 speakers of Spanish. Though intermediate level textbooks expose L2 learners to the various tenses of the subjunctive mood, literature has shown that students still struggle with its implementation in their discourse, and various reasons are offered. Little has been done to analyze the prescribed uses that textbooks offer to students regarding mood selection and how these prescribed uses may differ from what Spanish speakers do in real life. The paper first offers a brief explanation of L2 learners’ mood selection in Spanish, followed by a description of Spanish moods and the realis/irrealis dichotomy that is often placed at the center of Spanish mood selection in the literature. Following this, the study offers an analysis of six intermediate level Spanish textbooks’ prescribed uses of two past subjunctive tenses (present perfect and imperfect), as prior research has shown an overlap in the functions of their indicative counterparts. The textbook analysis is then compared to a corpus composed of messages sent on the social media platform Twitter, containing one of six emotive phrases as main clauses, with three in present, three in preterit. The results show that Spanish-speaking users of Twitter employ the prescribed subjunctive mood more often when the verb in the main clause is expressed in the preterit instead of the present, though no such tendency is discussed in the textbooks. The results also reveal an overlap in the functions of the past tense subjunctive moods. The present perfect subjunctive (i.e. haya trabajado ‘has worked’) is used in the subordinate clause nearly 40% of the time with emotive verbal main clauses expressed in the preterit, where the imperfect subjunctive would normally be expected according to prescriptive norms. This pattern of use is not discussed in any of the analyzed textbooks. A discussion of the limitations of the study, implications for textbook writers and further research then follow.

Este trabalho tem como objetivo desenvolver um método de análise de risco qualitativo que propicie um nível de segurança contra incêndio adequado ao risco esperado em uma edificação hospitalar de grande porte, visto que o estrito atendimento às exigências de códigos e regulamentações prescritivas podem não garantir um adequado nível de segurança contra incêndio. O método baseou-se na metodologia de análise de risco qualitativa e em técnicas de gestão de risco corporativo. O trabalho resultou no Método de Avaliação de Risco Incêndio Hospitalar (MARIH). O MARIH foi idealizado com o intuito de demonstrar que, a partir da identificação e da análise dos principais riscos de incêndio em edifícios hospitalares, é possível tomar medidas adequadas para minimizar tais riscos, ainda na fase de projeto, e implementar medidas de controle (tratamento), tornando a edificação mais segura em relação à ocorrência de incêndios, sem necessariamente onerar sua construção. O método MARIH foi concebido para atuar como uma ferramenta para o desenvolvimento do projeto, com vistas a elevar o nível de segurança contra incêndio nas edificações hospitalares. Além disso, pretende-se, com o uso dessa ferramenta, demonstrar aos projetistas e empreendedores a importância da inserção adequada e da integração da segurança contra incêndio no processo de projeto de edificações de grande porte e complexas. / In view of the fact that requirements of prescriptive codes are not always enough to guarantee fire safety to hospital buildings, this study proposes and develops a qualitative method of risk analysis aiming to provide an adequate level of fire safety for such a type of building. The method named Fire Risk Assessment Method for Hospital Buildings (Método de Avaliação de Risco Incêndio Hospitalar - MARIH) is based on qualitative risk analysis methodology and on corporate risk management techniques. The method was developed in order to prove that, by the identification and the analysis of the main fire risks in hospitals, countermeasures may be taken to reduce such risks, still during the design process, without increasing construction costs. The MARIH method is proposed as a design tool so as to improve the fire safety level in hospital buildings, emphasizing how important fire safety is along the design process as well.

Introdução: Novas condutas terapêuticas e de prevenção frente à obesidade tornam-se objetos de estudo, entre elas a abordagem Health at Every Size® (HAES®). A abordagem HAES® aponta para o prazer em comer como crucial para a promoção de saúde e sustentabilidade no tratamento. A condenação cultural do prazer em paralelo à negligência do prazer no tratamento da obesidade forma um cenário de crítica, em que a mulher obesa é alvo de múltiplas desvantagens, entre elas a culpabilização do comer. Assumimos, para este estudo, a importância de aprofundar-se nas relações entre novas perspectivas no cuidado à mulher obesa e o estímulo ao prazer em comer. Objetivos: Investigar as percepções de mulheres na condição de obesidade acerca do prazer em comer antes e após uma intervenção interdisciplinar, não prescritiva e pautada na abordagem do HAES®. Métodos: Estudo qualitativo a partir de um ensaio clínico randomizado controlado com seguimento de sete meses nos anos de 2015 e 2016. Incluiu 97 mulheres na condição de obesidade de 25 a 50 anos de idade, com índice de massa corporal entre 30 e 39,9Kg/m², sendo alocadas em dois grupos: Intervenção e Controle. Ao final do estudo, 39 mulheres concluíram no grupo Intervenção (62,90 por cento ) e 19 concluíram no Controle (54,28 por cento ). Para os dois grupos, as atividades tiveram como linha condutora a abordagem do HAES®. O grupo Intervenção trouxe uma proposta original, com oferta de atividade física 3 vezes na semana, acompanhamento nutricional individual e oferta de discussões no formato de cinco oficinas filosóficas. O grupo Controle baseou-se ao modelo tradicional de aplicação da abordagem HAES®, com palestras expositivas bimestrais. A construção dos dados ocorreu a partir de grupos focais. Para análise das transcrições dos grupos, foi realizado o método de Análise de Conteúdo, sendo construídos temas pela técnica de Cutting e Sorting, os quais fundamentaram a argumentação teórica neste estudo. Resultados: Vinte e três temas sobre as percepções do prazer em comer das mulheres estudadas foram construídos. Após a intervenção, foram construídos de maneira significativa para o grupo Intervenção temas sobre maior autocontrole e reflexão sobre os próprios desejos; sensação de empoderamento para escolher o que e quando comer; aumento do prazer em comer acompanhada; aumento do prazer em comer comidas feitas por si própria; aumento dos discursos sobre comer sem culpa; diminuição da sensação de não sentir prazer e ainda diminuição do comer por emoções como ansiedade. Conclusão: A nova intervenção proposta promoveu efeitos positivos na relação das mulheres com o prazer em comer, evidenciando a desculpabilização do prazer em comer e melhora de outros aspectos da prática alimentar, como a comensalidade. Percebemos que este efeito se deu sobretudo a partir do estímulo a um processo reflexivo sobre corpo, comida e saúde, ficando claro que o prazer em comer sem culpa é um desfecho necessário quando falamos da saúde da mulher obesa / Introduction: New therapies and prevention practices directed to obesity become objects of study. The Health at Every Size® (HAES®) approach is one of them. The HAES® approach indicate the pleasure in eating as crucial for health promotion and sustainability of treatments. The cultural condemnation of pleasure and its disregard in the treatment of obesity created a critic scenario in which the obese woman is target of multiple disadvantages, such as blame for eating. We assume, for this study, the importance to deepen the relationship between new approaches to the care of obese woman and the encouragement of pleasure of eating. Objectives: To investigate obese women perceptions about the pleasure of eating, before and after an interdisciplinary, non-prescriptive and based on HAES® approach intervention. Methods: Qualitative study branch of a randomized controlled clinical trial, conducted over seven months in 2015 and 2016. It included 97 obese women, with 25 to 50 years old, with a body mass index between 30 and 39, 9 kg/m². The women were randomized to two groups: intervention and control. At the end, 39 women concluded in the Intervention Group (62.90 per cent ) and 19 in Control Group (54.28 per cent ). The two groups received activities based on HAES® approach. The Intervention Group, however, brought an original proposal, with physical activity 3 times a week, individual nutritional counseling and philosophical discussions in form of workshops. The Control Group received traditional model of HAES® approach application, with bimonthly expository lectures. The data construction occurred from Focus Groups. Analysis of the Focus Groups transcripts was conducted with Analysis of Content method, in which themes were built of Cutting and Sorting technique, and were used to theoretical arguments that substantiated this study. Results: Twenty-three themes about the perceptions of pleasure in eating of the studied women were built. After the intervention, more significantly for the Intervention Group, themes manifested greater self-control on the own desires; increased hunger and satiety response; sense of empowerment to choose what and when to eat; increase of the pleasure in eating accompanied; increase of the pleasure in eating food made by herself; increase of speeches about \"eat without guilt\"; decreased perception of not feeling pleasure and even decreased eating by emotions such as anxiety. Conclusion: The new proposed intervention promoted positive effects on women\'s relationship with pleasure in eating, showing decrease of guilt on pleasure in eating and improvements of other aspects of the eating practices, such as commensality. We realize that this effect occurred mainly due to stimulus to a reflection about body, food and health, becoming clear that the pleasure in eating without guilt is a necessary outcome when we talk about obese woman health

Este trabalho tem como objetivo desenvolver um método de análise de risco qualitativo que propicie um nível de segurança contra incêndio adequado ao risco esperado em uma edificação hospitalar de grande porte, visto que o estrito atendimento às exigências de códigos e regulamentações prescritivas podem não garantir um adequado nível de segurança contra incêndio. O método baseou-se na metodologia de análise de risco qualitativa e em técnicas de gestão de risco corporativo. O trabalho resultou no Método de Avaliação de Risco Incêndio Hospitalar (MARIH). O MARIH foi idealizado com o intuito de demonstrar que, a partir da identificação e da análise dos principais riscos de incêndio em edifícios hospitalares, é possível tomar medidas adequadas para minimizar tais riscos, ainda na fase de projeto, e implementar medidas de controle (tratamento), tornando a edificação mais segura em relação à ocorrência de incêndios, sem necessariamente onerar sua construção. O método MARIH foi concebido para atuar como uma ferramenta para o desenvolvimento do projeto, com vistas a elevar o nível de segurança contra incêndio nas edificações hospitalares. Além disso, pretende-se, com o uso dessa ferramenta, demonstrar aos projetistas e empreendedores a importância da inserção adequada e da integração da segurança contra incêndio no processo de projeto de edificações de grande porte e complexas. / In view of the fact that requirements of prescriptive codes are not always enough to guarantee fire safety to hospital buildings, this study proposes and develops a qualitative method of risk analysis aiming to provide an adequate level of fire safety for such a type of building. The method named Fire Risk Assessment Method for Hospital Buildings (Método de Avaliação de Risco Incêndio Hospitalar - MARIH) is based on qualitative risk analysis methodology and on corporate risk management techniques. The method was developed in order to prove that, by the identification and the analysis of the main fire risks in hospitals, countermeasures may be taken to reduce such risks, still during the design process, without increasing construction costs. The MARIH method is proposed as a design tool so as to improve the fire safety level in hospital buildings, emphasizing how important fire safety is along the design process as well.

Background: Johnson and Dillon (2011) provided a model-based comparison of current generic hearing aid prescriptive methods for adults with hearing loss based on the attributes of speech intelligibility, loudness, and bandwidth. Purpose: This study compared the National Acoustic Laboratories-Non-linear 2 (NAL-NL2) and Cambridge Method for Loudness Equalization 2-High-Frequency (CAM2) prescriptive methods using adult participants with less high-frequency hearing loss than Johnson and Dillon (2011). Of study interest was quantification of prescribed audibility, speech intelligibility, and loudness. The preferences of participants for either NAL-NL2 or CAM2 and preferred deviations from prescribed settings are also reported. Research Design: Using a single-blind, counter-balanced, randomized design, preference judgments for the prescriptive methods with regard to sound quality of speech and music stimuli were obtained. Preferred gain adjustments from the prescription within the 4-10 kHz frequency range were also obtained from each participant. Speech intelligibility and loudness model calculations were completed on the prescribed and adjusted amplification. Study Sample: Fourteen male Veterans, whose average age was 65 yr and whose hearing sensitivity averaged normal to borderline normal through 1000 Hz sloping to a moderately severe sensorineural loss, served as participants. Data Collection and Analysis: Following a brief listening time (∼10 min), typical of an initial fitting visit, the participants made paired comparison of sound quality between the NAL-NL2 and CAM2 prescriptive settings. Participants were also asked to modify each prescription in the range of 4-10 kHz using an overall gain control and make subsequent comparisons of sound quality preference between prescriptive and adjusted settings. Participant preferences were examined with respect to quantitative analysis of loudness modeling, speech intelligibility modeling, and measured high-frequency bandwidth audibility. Results: Consistent with the lack of difference in predicted speech intelligibility between the two prescriptions, sound quality preferences on the basis of clarity were split across participants while some participants did not have a discernable preference. Considering sound quality judgments of pleasantness, the majority of participants preferred the sound quality of the NAL-NL2 (8 of 14) prescription instead of the CAM2 prescription (2 of 14). Four of the 14 participants showed no preference on the basis of pleasantness for either prescription. Individual subject preferences were supported by loudness modeling that indicated NAL-NL2 was the softer of the two prescriptions and CAM2 was the louder. CAM2 did provide more audibility to the higher frequencies (5-8 kHz) than NAL-NL2. Participants turned the 4-10 kHz gain recommendation of CAM2 lower, on average, by a significant amount of 4 dB when making adjustments while no significant adjustment was made to the initial NAL-NL2 recommendation. Conclusions: NAL-NL2 prescribed gains were more often preferred at the initial fitting by the majority of participating veterans. For those patients with preference for a louder fitting than NAL-NL2, CAM2 is a good alternative. When the participant adjustment from the prescription between 4 and 10 kHz exceeded 4 dB from either NAL-NL2 (2 of 14) or CAM2 (11 of 14), the participants demonstrated a later preference for that adjustment 69% of the time. These findings are viewed as limited evidence that some individuals may have a preference for high-frequency gain that differs from the starting prescription.

With the popularity of model-driven methodologies and the abundance of modelling languages, a major question for a modeller is: Which language is suitable for modelling a system under study? To answer this question, one not only needs to know the range of relevant languages for modelling the system under study, but also needs to be able to compare these languages. In this dissertation, I consider these challenges from a semantic point of view for a diverse range of behavioural modelling languages that I refer to as the family of Big-Step Modelling Languages (BSMLs). There is a plethora of BSMLs, including statecharts, its variants, SCR, un-clocked variants of synchronous languages (e.g., Esterel and Argos), and reactive modules. BSMLs are often used to model systems that continuously interact with their environments. In a BSML model, the reaction of the model to an environmental input is a big step, which consists of a sequence of small steps, each of which can be the concurrent execution of a set of transitions. To provide a systematic method to understand and compare the semantics of BSMLs, this dissertation introduces the big-step semantic deconstruction framework that deconstructs the semantic design space of BSMLs into eight high-level, independent semantic aspects together with the enumeration of the common semantic options of each semantic aspect. The dissertation also presents a comparative analysis of the semantic options of each semantic aspect to assist one to choose one semantic option over another. A key idea in the big-step semantic deconstruction is that the high-level semantic aspects in the deconstruction recognize a big step as a whole, rather than only considering its constituent transitions operationally. A novelty of the big-step semantic deconstruction is that it lends itself to a systematic semantic formalization of most of the languages in the deconstruction. The dissertation presents a parametric, formal semantic definition method whose parameters correspond to the semantic aspects of the deconstruction, and thus it produces prescriptive semantics: The manifestation of a semantic option in the semantics of a BSML can be clearly identified. The way transitions are ordered to form a big step in a BSML is a source of semantic complexity: A modeller needs to be aware of the possible orders of the execution of transitions when constructing and analyzing a model. The dissertation introduces three semantic quality attributes that each exempts a modeller from considering an aspect of ordering in big steps. The ranges of BSMLs that support each of these semantic quality attributes are formally specified. These specifications indicate that achieving a semantic quality attribute in a BSML is a cross-cutting concern over the choices of its different semantic options. The semantic quality attributes together with the semantic analysis of individual semantic options can be used in tandem to assist a modeller or a semanticist to compare two BSMLs or to create a new, desired BSML from scratch. Through the big-step semantic deconstruction, I have discovered that some of the semantic aspects of BSMLs can be uniformly described as forms of synchronization. The dissertation presents a general synchronization framework for behavioural modelling languages. This framework is based on a notion of synchronization between transitions of complementary roles. It is parameterized by the number of interactions a transition can take part in, i.e., one vs. many, and the arity of the interaction mechanisms, i.e., exclusive vs. shared, which are considered for the complementary roles to result in 16 synchronization types. To enhance BSMLs with the capability to use the synchronization types, a synchronizer syntax is introduced for BSMLs, resulting in the family of Synchronizing Big-Step Modelling Languages (SBSMLs). Using the expressiveness of SBSMLs, the dissertation describes how underlying the semantics of many modelling constructs, such as multi-source, multi-destination transitions, various composition operators, and workflow patterns, there is a notion of synchronization that can be systematically modelled in SBSMLs.

Neuroeconomics is an interdisciplinary research program with the goal of building a biological model of decision making in economic environments. Neuroeconomists ask, how does the embodied brain enable the mind (or groups of minds) to make economic decisions? By combining techniques from cognitive neuroscience and experimental economics we can now watch neural activity in real time, observe how this activity depends on the economic environment, and test hypotheses about how the emergent mind makes economic decisions. Neuroeconomics allows us to better understand both the wide range of heterogeneity in human behavior, and the role of institutions as ordered extensions of our minds. The brain is the most amazing complex organ in known universe.The brain is a organ with most amazingly magic infinite potential. Neuroplasticity: Transforming the Mind by Changing the Brain.Neuroplasticity refers to structural and functional changes in the brain that are brought about by training and experience. The brain is the organ that is designed to change in response to experience.The decision theories can be categorized into three paradigms:the normative,descriptive and prescriptive theories.The decision processing have four steps:accumulation of sensory evidence,integration of sensory signals with reward expectation and prior knowledge,comparision of current reward expectation with that in prior experience,and the selection of behavioral response.

With the popularity of model-driven methodologies and the abundance of modelling languages, a major question for a modeller is: Which language is suitable for modelling a system under study? To answer this question, one not only needs to know the range of relevant languages for modelling the system under study, but also needs to be able to compare these languages. In this dissertation, I consider these challenges from a semantic point of view for a diverse range of behavioural modelling languages that I refer to as the family of Big-Step Modelling Languages (BSMLs). There is a plethora of BSMLs, including statecharts, its variants, SCR, un-clocked variants of synchronous languages (e.g., Esterel and Argos), and reactive modules. BSMLs are often used to model systems that continuously interact with their environments. In a BSML model, the reaction of the model to an environmental input is a big step, which consists of a sequence of small steps, each of which can be the concurrent execution of a set of transitions. To provide a systematic method to understand and compare the semantics of BSMLs, this dissertation introduces the big-step semantic deconstruction framework that deconstructs the semantic design space of BSMLs into eight high-level, independent semantic aspects together with the enumeration of the common semantic options of each semantic aspect. The dissertation also presents a comparative analysis of the semantic options of each semantic aspect to assist one to choose one semantic option over another. A key idea in the big-step semantic deconstruction is that the high-level semantic aspects in the deconstruction recognize a big step as a whole, rather than only considering its constituent transitions operationally. A novelty of the big-step semantic deconstruction is that it lends itself to a systematic semantic formalization of most of the languages in the deconstruction. The dissertation presents a parametric, formal semantic definition method whose parameters correspond to the semantic aspects of the deconstruction, and thus it produces prescriptive semantics: The manifestation of a semantic option in the semantics of a BSML can be clearly identified. The way transitions are ordered to form a big step in a BSML is a source of semantic complexity: A modeller needs to be aware of the possible orders of the execution of transitions when constructing and analyzing a model. The dissertation introduces three semantic quality attributes that each exempts a modeller from considering an aspect of ordering in big steps. The ranges of BSMLs that support each of these semantic quality attributes are formally specified. These specifications indicate that achieving a semantic quality attribute in a BSML is a cross-cutting concern over the choices of its different semantic options. The semantic quality attributes together with the semantic analysis of individual semantic options can be used in tandem to assist a modeller or a semanticist to compare two BSMLs or to create a new, desired BSML from scratch. Through the big-step semantic deconstruction, I have discovered that some of the semantic aspects of BSMLs can be uniformly described as forms of synchronization. The dissertation presents a general synchronization framework for behavioural modelling languages. This framework is based on a notion of synchronization between transitions of complementary roles. It is parameterized by the number of interactions a transition can take part in, i.e., one vs. many, and the arity of the interaction mechanisms, i.e., exclusive vs. shared, which are considered for the complementary roles to result in 16 synchronization types. To enhance BSMLs with the capability to use the synchronization types, a synchronizer syntax is introduced for BSMLs, resulting in the family of Synchronizing Big-Step Modelling Languages (SBSMLs). Using the expressiveness of SBSMLs, the dissertation describes how underlying the semantics of many modelling constructs, such as multi-source, multi-destination transitions, various composition operators, and workflow patterns, there is a notion of synchronization that can be systematically modelled in SBSMLs.