Subclinical hypothyroidism and the risk of coronary heart disease and mortality.

CONTEXT: Data regarding the association between subclinical hypothyroidism and cardiovascular disease outcomes are conflicting among large prospective cohort studies. This might reflect differences in participants' age, sex, thyroid-stimulating hormone (TSH) levels, or preexisting cardiovascular disease. OBJECTIVE: To assess the risks of coronary heart disease (CHD) and total mortality for adults with subclinical hypothyroidism. DATA SOURCES AND STUDY SELECTION: The databases of MEDLINE and EMBASE (1950 to May 31, 2010) were searched without language restrictions for prospective cohort studies with baseline thyroid function and subsequent CHD events, CHD mortality, and total mortality. The reference lists of retrieved articles also were searched. DATA EXTRACTION: Individual data on 55,287 participants with 542,494 person-years of follow-up between 1972 and 2007 were supplied from 11 prospective cohorts in the United States, Europe, Australia, Brazil, and Japan. The risk of CHD events was examined in 25,977 participants from 7 cohorts with available data. Euthyroidism was defined as a TSH level of 0.50 to 4.49 mIU/L. Subclinical hypothyroidism was defined as a TSH level of 4.5 to 19.9 mIU/L with normal thyroxine concentrations. RESULTS: Among 55,287 adults, 3450 had subclinical hypothyroidism (6.2%) and 51,837 had euthyroidism. During follow-up, 9664 participants died (2168 of CHD), and 4470 participants had CHD events (among 7 studies). The risk of CHD events and CHD mortality increased with higher TSH concentrations. In age- and sex-adjusted analyses, the hazard ratio (HR) for CHD events was 1.00 (95% confidence interval [CI], 0.86-1.18) for a TSH level of 4.5 to 6.9 mIU/L (20.3 vs 20.3/1000 person-years for participants with euthyroidism), 1.17 (95% CI, 0.96-1.43) for a TSH level of 7.0 to 9.9 mIU/L (23.8/1000 person-years), and 1.89 (95% CI, 1.28-2.80) for a TSH level of 10 to 19.9 mIU/L (n = 70 events/235; 38.4/1000 person-years; P <.001 for trend). The corresponding HRs for CHD mortality were 1.09 (95% CI, 0.91-1.30; 5.3 vs 4.9/1000 person-years for participants with euthyroidism), 1.42 (95% CI, 1.03-1.95; 6.9/1000 person-years), and 1.58 (95% CI, 1.10-2.27, n = 28 deaths/333; 7.7/1000 person-years; P = .005 for trend). Total mortality was not increased among participants with subclinical hypothyroidism. Results were similar after further adjustment for traditional cardiovascular risk factors. Risks did not significantly differ by age, sex, or preexisting cardiovascular disease. CONCLUSIONS: Subclinical hypothyroidism is associated with an increased risk of CHD events and CHD mortality in those with higher TSH levels, particularly in those with a TSH concentration of 10 mIU/L or greater.

Kontekstitietoinen personalisointi mobiiliympäristössä

Tässä työssä selvitetään mitä mobiiliympäristössä käytettävillä kontekstitietoisilla sovelluksilla tarkoitetaan, miksi niitä tarvitaan ja mitä niiden avulla voidaan saavuttaa. Käyttäjäkeskeisen palvelun tavoitteena on mukautua käyttäjän kontekstiin, sekä hänen tarpeisiin ja tavoitteisiin ilman käyttäjältä vaadittavaa jatkuvaa vuorovaikutusta. Kontekstitietoisen sovelluksen suunnittelussa ja toteutuksessa tulee kiinnittää huomiota muun muassa kontekstitiedon keräämiseen, tallentamiseen ja tiedon eheyden säilyttämiseen. Sovelluksen suunnittelun tärkein haaste on toteuttaa hyvä logiikka, joka osaa päätellä kontekstitiedoista mitä toimintoja sen tulisi suorittaa. Mobiilipalveluiden personalisoinnissa on tärkeää ottaa huomioon käyttäjän, laitteen ja palvelun väliset vuorovaikutussuhteet. Nämä vuorovaikutussuhteet määrittelevät miten tiettyä mobiilipalvelua tulisi personalisoida jotta palvelu pystyy täyttämään käyttäjän sille asettamat vaatimukset.

Assessment of purchasing maturity in spare parts supply chain

To describe the change of purchasing moving from administrative to strategic function academics have put forward maturity models which help practitioners to compare their purchasing activities to industry top performers and best practices. However, none of the models aim to distinguish the purchasing maturity from the after-sales point of view, even though after-sales activities are acknowledged as a relevant source of revenue, profit and competitive advantage in most manufacturing firms. The maturity of purchasing and supply management practices have a large impact to the overall performance of the spare parts supply chain and ultimately to the value creation and relationship building for the end customer. The research was done as a case study for a European after-sales organization which is part of a globally operating industrial firm specialized in heavy machinery. The study mapped the current state of the purchasing practices in the case organization and also distinguished the relevant areas for future development. The study was based on the purchasing maturity model developed by Schiele (2007) and investigated also how applicable is the maturity model in the spare parts supply chain context. Data for the assessment was gathered using five expert interviews inside the case organization and other parties involved in the company’s spare parts supply chain. Inventory management dimension was added to the original maturity model in order to better capture the important areas in a spare parts supply chain. The added five questions were deduced from the spare parts management literature and verified as relevant areas by the case organization’s personnel. Results indicate that largest need for development in the case organization are: better collaboration between sourcing and operative procurement functions, use of installed base information in the spare parts management, training plan development for new buyers, assessment of aligned KPI’s between the supply chain parties and better defining the role of after-sales sourcing. The purchasing maturity model used in this research worked well in H&R Leading, Controlling and Inventory Management dimensions. The assessment was more difficult to conduct in the Supplier related processes, Process integration and Organizational structure –dimensions, mainly because the assessment in these sections would for some parts require more company-wide assessment. Results indicate also that the purchasing maturity model developed by Schiele (2007) captures the relevant areas in the spare parts supply as well.

Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

As dimensões da sustentabilidade nas relações de poder: O Comércio Justo no setor alimentício brasileiro

A presente pesquisa tem por objetivo descrever e explicar como as dimensões econômica, social e ambiental interferem nas relações de poder setor alimentício brasileiro certificado Comércio Justo. A tese defendida é de que as dimensões da sustentabilidade – econômica, social e ambiental – interferem nas relações de poder entre organizações, tendo abrangência de impacto distintas. A base teórica de análise das relações de poder envolveu a conjunção entre as teorias de dependência de recursos, racionalidade limitada, custos de transação e a relação entre justiça e poder. O estudo demonstra como ocorrem interferências das dimensões elencadas, sendo a análise realizada a partir de: 1. conflitos ao longo da inserção d o Comércio Justo no Brasil; 2. estruturação das redes e parcerias; 4. uso de discursos; 5. papel de tecnologias e recursos; 6. preço; 7. entendimentos sobre justiça. O estudo é de cunho qualitativo, assumindo o caráter descritivo e interpretativo. A coleta de dados foi realizada por intermédio de: 1. pesquisa bibliográfica; 2. investigação documental e na internet – notadamente com auxílio da ferramenta alertas do google; 3. entrevistas; 4. pesquisa de campo. A amostra foi composta por dezenove representantes de organizações, inseridas no contexto dos produtores de alimentos certificados. A coleta teve o corte longitudinal. Realizou- se a análise discursiva, do conteúdo das entrevistas. A análise de dados resultou de leituras e triangulações diversas entre objetivos da pesquisa, referencial teórico e resultados da pesquisa. Como resultado do estudo, concluiu-se que há parcialidade nas relações, sendo afetadas predominantemente por interferências da dimensão econômica. A dependência em recursos proporciona relações assimétricas. Tecnologias e conhecimentos, por intermédio da dimensão social, servem de instrumentos para: 1. minorar as diferenças entre os atores; 2. proporcionar um diferencial efetivo, que não apoiado exclusivamente na certificação. A configuração de organizações, parcerias e redes é passível de redução de assimetrias, quando compreendidas necessidades de pessoas, conhecimentos específicos e, portanto, da relevância da dimensão social. A variável ambiental é relevante, sobretudo em termos de recursos e processos produtivos. Porém, o impacto da dimensão ambiental gera interferências superiores, quando há: 1. a conscientização sobre sua relevância; 2. demandas sociais e de mercado por adaptações em processos. Logo, interferências do meio ambiente nas relações de poder são originárias, principalmente, daquelas de caráter social e econômico. Conclui-se, portanto, que há validade na tese da existência de distinção no impacto e interferências das dimensões da sustentabilidade, nas relações de poder entre organizações.

A gestão de mudanças na perícia criminal federal: a implementação dos indicadores de complexidade

Este pesquisa, inserida no campo de estudo sobre mudanças organizacionais, buscou investigar como é realizada a gestão de mudanças na Criminalística da Polícia Federal. Para isso, partiu-se de um referencial teórico para a estruturação de categorias de análise essenciais para o estudo do tema, agrupadas em três dimensões: conteúdo da mudança, processo de implementação da mudança e contexto em que ocorreu a mudança. Dessa forma, essa pesquisa de caráter qualitativo avaliou o processo de gestão de mudança ocorrido por meio da implementação de indicadores de complexidade na Criminalística da Polícia Federal, à luz do modelo proposto por John P. Kotter para a implementação eficaz de mudanças nas organizações, considerando sua interação com as circunstâncias contextais prevalecentes. Para a coleta de dados foram utilizadas entrevistas semiestruturadas com os componentes do corpo gerencial e diretor da Criminalística, responsáveis pela condução do processo de implementação da mudança. A análise de documentos institucionais e a observação direta complementaram a coleta dos dados. Os resultados apontaram para uma significante concorrência dos fatores relacionados às três dimensões estudadas que impediu o alcance dos objetivos esperados com a mudança, destacando-se: a) aspecto negativo relacionado à própria natureza da mudança, que se enquadra no campo de avaliação de desempenho, questão polêmica que levanta muitas discussões; b) contexto organizacional desfavorável, por estar inserida em uma organização policial, com forte cultura disciplinar e punitiva; c) processo de gestão de mudança mal conduzido, de acordo com modelo teórico para a implementação eficaz de mudanças nas organizações proposto por Kotter (1995, 1997).

Contribuições e dificuldades da abordagem de questões sociocientíficas na prática de professores de ciências

Neste artigo, apresentamos os resultados de uma pesquisa sobre as contribuições e as dificuldades da abordagem de questões sociocientíficas na prática de professores de ciências em serviço. Na pesquisa realizada, de caráter qualitativo com corte crítico, a realidade é entendida como uma construção social subjetiva e intersubjetiva, marcada por um contexto histórico. A constituição dos dados foi feita no decorrer de uma disciplina sobre ensino de ciências a partir de questões sociocientíficas, desenvolvida em um curso de mestrado em ensino de química, e teve a participação de 31 professores de ciências em serviço. No intuito de garantir a validade de fidedignidade da pesquisa, foi utilizada mais de uma fonte de dados. Assim, os dados foram constituídos por meio de vários instrumentos, tais como: questionário inicial de caracterização dos participantes da pesquisa, gravações de entrevistas focais e trabalhos apresentados pelos professores sobre a abordagem de questões sociocientíficas (QSCs) em sala de aula. As análises alcançadas indicam que a abordagem de questões sociocientíficas possui um potencial considerável para a prática do professor em termos da tomada de decisão e do desenvolvimento de pensamento crítico dos alunos. O trabalho com questões sociocientíficas também exige planejamento do ensino e ações bem sustentadas, assim como a participação ativa do professor. Finalmente, são caracterizadas as dificuldades do trabalho realizado em termos pedagógicos, formativos e curriculares.

A Teoria das inteligências múltiplas no ensino e aprendizagem de língua inglesa na escola pública

Pós-graduação em Estudos Linguísticos - IBILCE

Avaliação do impacto do reservatório de Três Irmãos sobre a superfície potenciométrica do aquífero livre na cidade de Pereira Barreto (SP): uma abordagem numérica e geoestatística

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Acesso ao ensino superior: a expectativa do aluno surdo do ensino médio

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

SEMIPARAMETRIC METHODS IN THE ESTIMATION OF TAIL PROBABILITIES AND EXTREME QUANTILES

In quantitative risk analysis, the problem of estimating small threshold exceedance probabilities and extreme quantiles arise ubiquitously in bio-surveillance, economics, natural disaster insurance actuary, quality control schemes, etc. A useful way to make an assessment of extreme events is to estimate the probabilities of exceeding large threshold values and extreme quantiles judged by interested authorities. Such information regarding extremes serves as essential guidance to interested authorities in decision making processes. However, in such a context, data are usually skewed in nature, and the rarity of exceedance of large threshold implies large fluctuations in the distribution's upper tail, precisely where the accuracy is desired mostly. Extreme Value Theory (EVT) is a branch of statistics that characterizes the behavior of upper or lower tails of probability distributions. However, existing methods in EVT for the estimation of small threshold exceedance probabilities and extreme quantiles often lead to poor predictive performance in cases where the underlying sample is not large enough or does not contain values in the distribution's tail. In this dissertation, we shall be concerned with an out of sample semiparametric (SP) method for the estimation of small threshold probabilities and extreme quantiles. The proposed SP method for interval estimation calls for the fusion or integration of a given data sample with external computer generated independent samples. Since more data are used, real as well as artificial, under certain conditions the method produces relatively short yet reliable confidence intervals for small exceedance probabilities and extreme quantiles.

User interaction monitoring and analysis framework

An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

A pro-active and dynamic prediction assistance using BaranC framework

Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic; it is dynamic both in responding to the current context, and also in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.