865 resultados para Privacy Based Access Control
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OBJECTIVE Use of diuretics has been associated with an increased risk of gout. Data on different types of diuretics are scarce. We undertook this study to investigate the association between use of loop diuretics, thiazide or thiazide-like diuretics, and potassium-sparing agents and the risk of developing incident gout. METHODS We conducted a retrospective population-based case-control analysis using the General Practice Research Database established in the UK. We identified case patients who were diagnosed as having incident gout between 1990 and 2010. One control patient was matched to each case patient for age, sex, general practice, calendar time, and years of active history in the database. We used conditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs), and we adjusted for potential confounders. RESULTS We identified 91,530 incident cases of gout and the same number of matched controls. Compared to past use of diuretics from each respective drug class, adjusted ORs for current use of loop diuretics, thiazide diuretics, thiazide-like diuretics, and potassium-sparing diuretics were 2.64 (95% CI 2.47-2.83), 1.70 (95% CI 1.62-1.79), 2.30 (95% CI 1.95-2.70), and 1.06 (95% CI 0.91-1.23), respectively. Combined use of loop diuretics and thiazide diuretics was associated with the highest relative risk estimates of gout (adjusted OR 4.65 [95% CI 3.51-6.16]). Current use of calcium channel blockers or losartan slightly attenuated the risk of gout in patients who took diuretics. CONCLUSION Use of loop diuretics, thiazide diuretics, and thiazide-like diuretics was associated with an increased risk of incident gout, although use of potassium-sparing agents was not.
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OBJECTIVE The aim of this study was to explore the risk of incident gout in patients with type 2 diabetes mellitus (T2DM) in association with diabetes duration, diabetes severity and antidiabetic drug treatment. METHODS We conducted a case-control study in patients with T2DM using the UK-based Clinical Practice Research Datalink (CPRD). We identified case patients aged ≥18 years with an incident diagnosis of gout between 1990 and 2012. We matched to each case patient one gout-free control patient. We used conditional logistic regression analysis to calculate adjusted ORs (adj. ORs) with 95% CIs and adjusted our analyses for important potential confounders. RESULTS The study encompassed 7536 T2DM cases with a first-time diagnosis of gout. Compared to a diabetes duration <1 year, prolonged diabetes duration (1-3, 3-6, 7-9 and ≥10 years) was associated with decreased adj. ORs of 0.91 (95% CI 0.79 to 1.04), 0.76 (95% CI 0.67 to 0.86), 0.70 (95% CI 0.61 to 0.86), and 0.58 (95% CI 0.51 to 0.66), respectively. Compared to a reference A1C level of <7%, the risk estimates of increasing A1C levels (7.0-7.9, 8.0-8.9 and ≥9%) steadily decreased with adj. ORs of 0.79 (95% CI 0.72 to 0.86), 0.63 (95% CI 0.55 to 0.72), and 0.46 (95% CI 0.40 to 0.53), respectively. Neither use of insulin, metformin, nor sulfonylureas was associated with an altered risk of incident gout. CONCLUSIONS Increased A1C levels, but not use of antidiabetic drugs, was associated with a decreased risk of incident gout among patients with T2DM.
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OBJECTIVE This study aims to assess the odds of developing incident gout in association with the use of postmenopausal estrogen-progestogen therapy, according to type, timing, duration, and route of administration of estrogen-progestogen therapy. METHODS We conducted a retrospective population-based case-control analysis using the United Kingdom-based Clinical Practice Research Datalink. We identified women (aged 45 y or older) who had a first-time diagnosis of gout recorded between 1990 and 2010. We matched one female control with each case on age, general practice, calendar time, and years of active history in the database. We used multivariate conditional logistic regression to calculate odds ratios (ORs) with 95% CIs (adjusted for confounders). RESULTS The adjusted OR for gout with current use of oral formulations of opposed estrogens (estrogen-progestogen) was 0.69 (95% CI, 0.56-0.86) compared with never use. Current use was associated with a decreased OR for gout in women without renal failure (adjusted OR, 0.71; 95% CI, 0.57-0.87) and hypertension (adjusted OR, 0.62; 95% CI, 0.44-0.87) compared with never use. Tibolone was associated with a decreased OR for gout (adjusted OR, 0.77; 95% CI, 0.63-0.95) compared with never use. Estrogens alone did not alter the OR for gout. CONCLUSIONS Current use of oral opposed estrogens, but not unopposed estrogens, is associated with a decreased OR for incident gout in women without renal failure and is more pronounced in women with hypertension. Use of tibolone is associated with a decreased OR for incident gout. The decreased OR for gout may be related to the progestogen component rather than the estrogen component.
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Background. It is important to understand the association between diet and risk of pancreatic cancer in order to better understand the etiology of pancreatic cancer.^ Objectives. Describe the dietary patterns of cases of adenocarcinoma of the pancreas and non-cancer controls and evaluate the odds of having a healthy eating pattern among cases and non-cancer controls.^ Design and Methods. An ongoing hospital-based case-control study was conducted in Houston, Texas from 2000-2008 with 678 pancreatic adenocarcinoma cases and 724 controls. Participants completed a food frequency questionnaire and a risk factor questionnaire. Dietary patterns were derived by principal component analysis and associations between dietary patterns and pancreatic cancer risk were assessed using unconditional logistic regression.^ Results. Two dietary patterns were derived: fruit-vegetable and high fat-meat. There were no statistically significant associations between the fruit-vegetable pattern and pancreatic cancer. An inverse association was seen between the high fat-meat pattern and pancreatic cancer risk when comparing those in the upper intake quintile to those scoring in the lowest quintile after adjusting for demographic and risk factor variables (OR=0.67, p=0.03). In sex-stratified analysis adjusted for demographic and risk factor variables, females scoring in the upper intake quintile of the fruit-vegetable pattern had a 49% lower risk of pancreatic cancer compared to females scoring in the lowest quintile (OR=0.51, p=0.03). An inverse relationship was also seen for the high fat-meat pattern when comparing females in the upper intake quintile to females in the lowest quintile (OR=0.50, p=0.03). In males, neither dietary pattern was significantly associated with pancreatic cancer.^ Conclusions. The current findings for the fruit-vegetable pattern are similar to those of previous studies and support the hypothesis that there is an inverse association between a “healthy” diet (comprised of fruits, vegetables, and whole grains) and risk of having pancreatic cancer (in females only). However, the inverse relationship with the high fat-meat pattern and risk of pancreatic cancer is contrary to other results. Further research on dietary patters and pancreatic cancer risk may lead to better understanding of the etiologic cause of pancreatic cancer.^
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Objective: The objective of this study is to investigate the association between processed and unprocessed red meat consumption and prostate cancer (PCa) stage in a homogenous Mexican-American population. Methods: This population-based case-control study had a total of 582 participants (287 cases with histologically confirmed adenocarcinoma of the prostate gland and 295 age and ethnicity-matched controls) that were all residing in the Southeast region of Texas from 1998 to 2006. All questionnaire information was collected using a validated data collection instrument. Statistical Analysis: Descriptive analyses included Student's t-test and Pearson's Chi-square tests. Odds ratios and 95% confidence intervals were calculated to quantify the association between nutritional factors and PCa stage. A multivariable model was used for unconditional logistic regression. Results: After adjusting for relevant covariates, those who consume high amounts of processed red meat have a non-significant increased odds of being diagnosed with localized PCa (OR = 1.60 95% CI: 0.85 - 3.03) and total PCa (OR = 1.43 95% CI: 0.81 - 2.52) but not for advanced PCa (OR = 0.91 95% CI: 1.37 - 2.23). Interestingly, high consumption of carbohydrates shows a significant reduction in the odds of being diagnosed with total PCa and advanced PCa (OR = 0.43 95% CI: 0.24 - 0.77; OR = 0.27 95% CI: 0.10 - 0.71, respectively). However, consuming high amounts of energy from protein and fat was shown to increase the odds of being diagnosed with advanced PCa (OR = 4.62 95% CI: 1.69 - 12.59; OR = 2.61 95% CI: 1.04 - 6.58, respectively). Conclusion: Mexican-Americans who consume high amounts of energy from protein and fat had increased odds of being diagnosed with advanced PCa, while high amounts of carbohydrates reduced the odds of being diagnosed with total and advanced PCa.^
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El objetivo principal de esta Tesis es extender la utilización del “Soft- Computing” para el control de vehículos sin piloto utilizando visión. Este trabajo va más allá de los típicos sistemas de control utilizados en entornos altamente controlados, demonstrando la fuerza y versatilidad de la lógica difusa (Fuzzy Logic) para controlar vehículos aéreos y terrestres en un abanico de applicaciones diferentes. Para esta Tesis se ha realizado un gran número de pruebas reales en las cuales los controladores difusos han manejado una plataforma visual “pan-and-tilt”, un helicoptero, un coche comercial y hasta dos tipos de quadrirotores. El uso del método de optimización “Cross-Entropy” ha sido utilizado para mejorar el comportamiento de algunos de los controladores borrosos. Todos los controladores difusos presentados en ésta Tesis han sido implementados utilizando un código desarrollado por el candidato para tal efecto, llamado MOFS (Miguel Olivares’ Fuzzy Software). Diferentes algoritmos visuales han sido utilizados para adquirir la informaci´on visual del entorno, “Cmashift”, descomposición de la homografía y detección de marcas de realidad aumentada, entre otros. Dicha información visual ha sido utilizada como entrada de los controladores difusos para comandar los vehículos en las diferentes applicaciones autonomas. El volante de un vehículo comercial ha sido controlado para realizar pruebas de conducción autónoma en condiciones de tráfico similares a las de una ciudad. El sistema ha llegado a completar con éxito pruebas de más de 6 km sin ninguna interacción humana, mediante el seguimiento de una línea pintada en el suelo. El limitado campo visual del sistema no ha sido impedimento para alcanzar velocidades de hasta 48 km/h y ser guiado autonomamente en curvas de radio reducido. Objetos estáticos y móviles han sido seguidos desde un helicoptero no tripulado, mediante el control de una plataforma visual “pan-and-tilt”. ´Éste mismo helicoptero ha sido controlado completamente para su aterrizaje autonomo, mediante el control del movimiento lateral (roll), horizontal (pitch) y de altitud. El seguimiento de objetos volantes ha sido resulto mediante el control horizontal (pitch) y de orientación (heading) de un quadrirotor. Para tareas de evitación de obstáculos se ha implementado un controlador difuso para el manejo de la orientación (heading) de un quadrirotor. En el campo de la optimización de controladores se ha aportado al estado del arte una extensión del uso del método “Cross-Entropy”. Está Tesis presenta una novedosa implementación de dicho método para la optimización de las ganancias, la posición y medida de los conjuntos de las funciones de pertenecia y el peso de las reglas para mejorar el comportamiento de un controlador difuso. Dichos procesos de optimización se han realizado utilizando “ROS” y “Matlab Simulink” para obtener mejores resultados para la evitación de colisiones con vehículos aéreos no tripulados. Ésta Tesis demuestra que los controladores implementados con lógica difusa son altamente capaces de controlador sistemas sin tener en cuenta el modelo del vehículo a controlador en entornos altamente perturbables con un sensor de bajo coste como es una cámara. El ruido presentes causado por los cambios de iluminación en la adquisición de imágenes y la alta incertidumbre en la detección visual han sido manejados satisfactoriamente por ésta técnica de de “Soft-Computing” para distintas aplicaciones tanto con vehículos aéreos como terrestres.
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Sensor networks are increasingly becoming one of the main sources of Big Data on the Web. However, the observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse these data for other purposes than those for which they were originally set up. In this thesis we address these challenges, considering how we can transform streaming raw data to rich ontology-based information that is accessible through continuous queries for streaming data. Our main contribution is an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. We introduce novel query rewriting and data translation techniques that rely on mapping definitions relating streaming data models to ontological concepts. Specific contributions include: • The syntax and semantics of the SPARQLStream query language for ontologybased data access, and a query rewriting approach for transforming SPARQLStream queries into streaming algebra expressions. • The design of an ontology-based streaming data access engine that can internally reuse an existing data stream engine, complex event processor or sensor middleware, using R2RML mappings for defining relationships between streaming data models and ontology concepts. Concerning the sensor metadata of such streaming data sources, we have investigated how we can use raw measurements to characterize streaming data, producing enriched data descriptions in terms of ontological models. Our specific contributions are: • A representation of sensor data time series that captures gradient information that is useful to characterize types of sensor data. • A method for classifying sensor data time series and determining the type of data, using data mining techniques, and a method for extracting semantic sensor metadata features from the time series.
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This paper presents the design and implementation of an intelligent control system based on local neurofuzzy models of the milling process relayed through an Ehternet-based application. Its purpose is to control the spindle torque of a milling process by using an internal model control paradigm to modify the feed rate in real time. The stabilization of cutting cutting torque is especially necessary in milling processes such as high-spedd roughing of steel moulds and dies tha present minor geometric uncertainties. Thus, maintenance of the curring torque increaes the material removal rate and reduces the risk of damage due to excessive spindle vibration, a very sensitive and expensive component in all high-speed milling machines. Torque control is therefore an interesting challenge from an industrial point of view.
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Ubiquitous computing (one person, many computers) is the third era in the history of computing. It follows the mainframe era (many people, one computer) and the PC era (one person, one computer). Ubiquitous computing empowers people to communicate with services by interacting with their surroundings. Most of these so called smart environments contain sensors sensing users’ actions and try to predict the users’ intentions and necessities based on sensor data. The main drawback of this approach is that the system might perform unexpected or unwanted actions, making the user feel out of control. In this master thesis we propose a different procedure based on Interactive Spaces: instead of predicting users’ intentions based on sensor data, the system reacts to users’ explicit predefined actions. To that end, we present REACHeS, a server platform which enables communication among services, resources and users located in the same environment. With REACHeS, a user controls services and resources by interacting with everyday life objects and using a mobile phone as a mediator between himself/herself, the system and the environment. REACHeS’ interfaces with a user are built upon NFC (Near Field Communication) technology. NFC tags are attached to objects in the environment. A tag stores commands that are sent to services when a user touches the tag with his/her NFC enabled device. The prototypes and usability tests presented in this thesis show the great potential of NFC to build such user interfaces.
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This paper presents a vision based autonomous landing control approach for unmanned aerial vehicles (UAV). The 3D position of an unmanned helicopter is estimated based on the homographies estimated of a known landmark. The translation and altitude estimation of the helicopter against the helipad position are the only information that is used to control the longitudinal, lateral and descend speeds of the vehicle. The control system approach consists in three Fuzzy controllers to manage the speeds of each 3D axis of the aircraft s coordinate system. The 3D position estimation was proven rst, comparing it with the GPS + IMU data with very good results. The robust of the vision algorithm against occlusions was also tested. The excellent behavior of the Fuzzy control approach using the 3D position estimation based in homographies was proved in an outdoors test using a real unmanned helicopter.
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Objective: To determine the relation between depression, anxiety, and use of antidepressants and the onset of ischaemic heart disease.
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Objective: To determine the relative risk of hip fracture associated with postmenopausal hormone replacement therapy including the effect of duration and recency of treatment, the addition of progestins, route of administration, and dose.