852 resultados para 080109 Pattern Recognition and Data Mining


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SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

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W5.43(194), a conserved tryptophan residue among G-protein coupled receptors (GPCRs) and cannabinoid receptors (CB), was examined in the present report for its significance in CB2 receptor ligand binding and adenylyl cyclase (AC) activity. Computer modeling postulates that this site in CB2 may be involved in the affinity of WIN55212-2 and SR144528 through aromatic contacts. In the present study, we reported that a CB2 receptor mutant, W5.43(194)Y, which had a tyrosine (Y) substitution for tryptophan (W), retained the binding affinity for CB agonist CP55940, but reduced binding affinity for CB2 agonist WIN55212-2 and inverse agonist SR144528 by 8-fold and 5-fold, respectively; the CB2 W5.43(194)F and W5.43(194)A mutations significantly affect the binding activities of CP55940, WIN55212-2 and SR144528. Furthermore, we found that agonist-mediated inhibition of the forskolin-induced cAMP production was dramatically diminished in the CB2 mutant W5.43(194)Y, whereas W5.43(194)F and W5.43(194)A mutants resulted in complete elimination of downstream signaling, suggesting that W5.43(194) was essential for the full activation of CB2. These results indicate that both aromatic interaction and hydrogen bonding are involved in ligand binding for the residue W5.43(194), and the mutations of this tryptophan site may affect the conformation of the ligand binding pocket and therefore control the active conformation of the wild type CB2 receptor. W5.43(194)Y/F/A mutations also displayed noticeable enhancement of the constitutive activation probably attributed to the receptor conformational changes resulted from the mutations.

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Hepatitis C virus (HCV) clearance has been associated with reduced viral evolution in targeted cytotoxic T-lymphocyte (CTL) epitopes, suggesting that HCV clearers may mount CTL responses with a superior ability to recognize epitope variants and prevent viral immune escape. Here, 40 HCV-infected subjects were tested with 406 10-mer peptides covering the vast majority of the sequence diversity spanning a 197-residue region of the NS3 protein. HCV clearers mounted significantly broader CTL responses of higher functional avidity and with wider variant cross-recognition capacity than nonclearers. These observations have important implications for vaccine approaches that may need to induce high-avidity responses in vivo.

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The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model's ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality's residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained.

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Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

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Central Eastern Europe, the research area this paper is concerned with, is a region characterized by a high diversity of languages and cultures. It is, at the same time, an area where political, cultural and social conflicts have emerged over time, nowadays especially in border zones, where people of different ethnic, cultural or linguistic background live. In this context, it is important for us researchers to get balanced interview data, and consequently we very often have to conduct interviews in several different languages and within changing cultural contexts. In order to avoid "communication problems" or even conflictual (interview) situations, which might damage the outcome of the research, we are thus challenged to find appropriate communication strategies for any of these situations. This is especially difficult when we are confronted with language or culture-specific terminology or taboo expressions that carry political meaning(s). Once the interview data is collected and it comes to translating and analysing it, we face further challenges and new questions arise. First of all, we have to decide what a good translation strategy would be. Many words and phrases that exist in one language do not have an exact equivalent in another. Therefore we have to find a solution for translating these expressions and concepts in a way that their meanings do not get "lost by translation". In this paper I discuss and provide insights to these challenges by presenting and discussing numerous examples from the region in question. Specifically, I focus on the deconstruction of the meaning of geographical names and politically loaded expressions in order to show the sensitivities of language, the difficulties of research in multilingual settings and with multilingual data as well as the strategies or "ways out" of certain dilemmas.

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