985 resultados para 030101 Analytical Spectrometry


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Cardiovascular diseases are nowadays the first cause of mortality worldwide, causing around the 30% of global deaths each year. The risk of suffering from cardiovascular illnesses is strongly related to some factors such as hypertension, high cholesterol levels, diabetes, obesity The combination of these different risk factors is known as metabolic syndrome and it is considered a pandemic due to the high prevalence worldwide. The pathology of the disorders implies a combined cardiovascular therapy with drugs which have different targets and mechanisms of action, to regulate each factor separately. The simultaneous analysis of these drugs turns interesting but it is a complex task since the determination of multiple substances with different physicochemical properties and physiological behavior is always a challenge for the analytical chemist. The complexity of the biological matrices and the difference in the expected concentrations of some analytes require the development of extremely sensitive and selective determination methods. The aim of this work is to fill the gap existing in this field of the drug analysis, developing analytical methods capable of quantifying the different drugs prescribed in combined cardiovascular therapy simultaneously. Liquid chromatography andem mass spectrometry (LCMS/MS) has been the technique of choice throughout the main part of this work, due to the high sensitivity and selectivity requirements.

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In this paper, common criterions about residual strength evaluation at home and abroad are generalized and seven methods are acquired, namely ASME-B31G, DM, Wes-2805-97, CVDA-84, Burdekin, Irwin and J integral methods. BP neural network are Combined with Genetic Algorithm (GA) named by modified BP-GA methods to successfully predict residual strength and critical pressure of injecting water, corrosion pipelines. Examples are shown that calculation results of every kind of method have great difference and calculating values of Wes-2805-97 criterion, ASME-B31G criterion, CVDA-84 criterion and Irwin fracture mechanics model are conservative and higher than, those of J integral methods while calculating values of Burdiken model and DM fracture mechanics model are dangerous and less than those of J integral methods and calculating values of modified BP-GA methods are close and moderate to those of J integral methods. Therefore modified BP-GA methods and J integral methods are considered better methods to calculate residual strength and critical pressure of injecting water corrosion pipelines

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This document describes the analytical methods used to quantify core organic chemicals in tissue and sediment collected as part of NOAA’s National Status and Trends Program (NS&T) for the years 2000-2006. Organic contaminat analytical methods used during the early years of the program are described in NOAA Technical Memoranda NOS ORCA 71 and 130 (Lauenstein and Cantillo, 1993; Lauenstein and Cantillo, 1998) for the years 1984-1992 and 1993-1996, respectively. These reports are available from our website (http://www.ccma.nos.gov) The methods detailed in this document were utilized by the Mussel Watch Project and Bioeffects Project, which are both part of the NS&T program. The Mussel Watch Project has been monitoring contaminants in bivalves and sediments since 1986 and is the longest active national contaminant monitoring program operating in U.S. costal waters. Approximately 280 Mussel Watch sites are sampled on a biennial and decadal timescale for bivalve tissue and sediment respectively. Similarly, the Bioeffects Assessment Project began in 1986 to characterize estuaries and near coastal environs. Using the sediment quality triad approach that measures; (1) levels of contaminants in sediments, (2) incidence and severity of toxicity, and (3) benthic macrofaunal conmmunities, the Bioeffects Project describes the spatial extent of sediment toxicity. Contaminant assessment is a core function of both projects. These methods, while discussed here in the context of sediment and bivalve tissue, were also used with other matricies including: fish fillet, fish liver, nepheloid layer, and suspended particulate matter. The methods described herein are for the core organic contaminants monitored in the NS&T Program and include polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), butyltins, and organochlorines that have been analyzed consistently over the past 15-20 years. Organic contaminants such as dioxins, perfluoro compounds and polybrominated biphenyl ethers (PBDEs) were analyzed periodically in special studies of the NS&T Program and will be described in another document. All of the analytical techniques described in this document were used by B&B Laboratories, Inc, an affiliate of TDI-Brook International, Inc. in College Station, Texas under contract to NOAA. The NS&T Program uses a performance-based system approach to obtain the best possible data quality and comparability, and requires laboratories to demonstrate precision, accuracy, and sensitivity to ensure results-based performance goals and measures. (PDF contains 75 pages)

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The Taylor series expansion method is used to analytically calculate the Eulerian and Lagrangian time correlations in turbulent shear flows. The short-time behaviors of those correlation functions can be obtained from the series expansions. Especially, the propagation velocity and sweeping velocity in the elliptic model of space-time correlation are analytically calculated and further simplified using the sweeping hypothesis and straining hypothesis. These two characteristic velocities mainly determine the space-time correlations.

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Polycyclic aromatic hydrocarbons, butyltins, polychlorinated biphenyls, DDT and metabolites, other chlorinated pesticides, trace and major elements, and a number of measures of contaminant effects are quantified in bivalves and sediments collected as part of the NOAA National Status and Trends (NS&T) Program. This document contains descriptions of some of the sampling and analytical protocols used by NS&T contract laboratories from 1993 through 1996. (PDF contains 257 pages)

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One of the major concerns in an Intelligent Transportation System (ITS) scenario, such as that which may be found on a long-distance train service, is the provision of efficient communication services, satisfying users' expectations, and fulfilling even highly demanding application requirements, such as safety-oriented services. In an ITS scenario, it is common to have a significant amount of onboard devices that comprise a cluster of nodes (a mobile network) that demand connectivity to the outside networks. This demand has to be satisfied without service disruption. Consequently, the mobility of the mobile network has to be managed. Due to the nature of mobile networks, efficient and lightweight protocols are desired in the ITS context to ensure adequate service performance. However, the security is also a key factor in this scenario. Since the management of the mobility is essential for providing communications, the protocol for managing this mobility has to be protected. Furthermore, there are safety-oriented services in this scenario, so user application data should also be protected. Nevertheless, providing security is expensive in terms of efficiency. Based on this considerations, we have developed a solution for managing the network mobility for ITS scenarios: the NeMHIP protocol. This approach provides a secure management of network mobility in an efficient manner. In this article, we present this protocol and the strategy developed to maintain its security and efficiency in satisfactory levels. We also present the developed analytical models to analyze quantitatively the efficiency of the protocol. More specifically, we have developed models for assessing it in terms of signaling cost, which demonstrates that NeMHIP generates up to 73.47% less signaling compared to other relevant approaches. Therefore, the results obtained demonstrate that NeMHIP is the most efficient and secure solution for providing communications in mobile network scenarios such as in an ITS context.