853 resultados para Detection and representation


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Passive person detection and localization is an emerging area in UWB localization systems, whereby people are not required to carry any UWB ranging device. Based on experimental data, we propose a novel method to detect static persons in the absence of template waveforms, and to compute distances to these persons. Our method makes very little assumptions on the environment and can achieve ranging performances on the order of 50 cm, using off-the-shelf UWB devices. © 2013 IEEE.

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An endocrine disruptor (ED) is an exogenous compound that interferes with the body's endocrine system. Exposure to EDs may result in adverse health effects such as infertility and cancer. EDs are composed of a vast group of chemicals including compounds of natural origin such as phytoestrogens or mycotoxins and a wide range of man-made chemicals such as pesticides. Synthetic compounds may find their way into the food chain where a number of them can biomagnify. Additionally, processing activities and food contact materials may add further to the already existing pool of food contaminants. Thus, our diet is considered to be one of the main exposure routes to EDs. Some precautionary legislation has already been introduced to control production and/or application of some persistent organic pollutants with ED characteristics. However, newly emerging EDs with bioaccumulative properties have recently been reported to appear at lower tiers of the food chain but have not been monitored at the grander scale. Milk and dairy products are a major component of our diet, thus it is important to monitor them for EDs. However, most methods developed to date are devoted to one group of compounds at a time. The UHPLC-MS/MS method described here has been validated according to EC decision 2002/657/EC and allows simultaneous extraction, detection, quantitation and confirmation of 19 EDs in milk. The method calibration range is between 0.50 and 20.0 μg kg with coefficients of determination above 0.99 for all analytes. Precision varied from 4.7% to 23.4% in repeatability and reproducibility studies. Established CCα and CCβ values (0.11-0.67 μg kg) facilitate fast, reliable, quantitative and confirmatory analysis of sub μg kg levels of a range of EDs in milk.

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In this short paper, we present an integrated approach to detecting and mitigating cyber-attacks to modern interconnected industrial control systems. One of the primary goals of this approach is that it is cost effective, and thus whenever possible it builds on open-source security technologies and open standards, which are complemented with novel security solutions that address the specific challenges of securing critical infrastructures.

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Purpose: There is an urgent need to develop diagnostic tests to improve the detection of pathogens causing life-threatening infection (sepsis). SeptiFast is a CE-marked multi-pathogen real-time PCR system capable of detecting DNA sequences of bacteria and fungi present in blood samples within a few hours. We report here a systematic review and meta-analysis of diagnostic accuracy studies of SeptiFast in the setting of suspected sepsis.

Methods: A comprehensive search strategy was developed to identify studies that compared SeptiFast with blood culture in suspected sepsis. Methodological quality was assessed using QUADAS. Heterogeneity of studies was investigated using a coupled forest plot of sensitivity and specificity and a scatter plot in receiver operator characteristic space. Bivariate model method was used to estimate summary sensitivity and specificity.

Results: From 41 phase III diagnostic accuracy studies, summary sensitivity and specificity for SeptiFast compared with blood culture were 0.68 (95 % CI 0.63–0.73) and 0.86 (95 % CI 0.84–0.89) respectively. Study quality was judged to be variable with important deficiencies overall in design and reporting that could impact on derived diagnostic accuracy metrics.

Conclusions: SeptiFast appears to have higher specificity than sensitivity, but deficiencies in study quality are likely to render this body of work unreliable. Based on the evidence presented here, it remains difficult to make firm recommendations about the likely clinical utility of SeptiFast in the setting of suspected sepsis.

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Threat prevention with limited security resources is a challenging problem. An optimal strategy is to eectively predict attackers' targets (or goals) based on current available information, and use such predictions to prevent (or disrupt) their planned attacks. In this paper, we propose a game-theoretic framework to address this challenge which encompasses the following three elements. First, we design a method to analyze an attacker's types in order to determine the most plausible type of an attacker. Second, we propose an approach to predict possible targets of an attack and the course of actions that the attackers may take even when the attackers' types are ambiguous. Third, a game-theoretic based strategy is developed to determine the best protection actions for defenders (security resources).

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The cysteine cathepsins are a family of closely related thiol proteases, normally found in the endosomal and lysosomal compartments of cells. A growing body of evidence has clearly linked the dysregulated activity of these proteases with many diseases and pathological conditions, offering therapeutic, prognostic and diagnostic potential. However, these proteases are synthesised as inactive precursors and once activated, are controlled by factors such as pH and presence of endogenous inhibitors, meaning that overall protein and activity levels do not necessarily correlate. In order to fully appreciate the role and potential of these proteases, tools are required that can detect and quantify overall cathepsin activity. Two main strategies have evolved; synthetic substrates and protease-labelling with affinity-binding probes (or activity-based probes). This review examines recent innovations in these approaches as the field moves towards developing tools that could ultimately be used in patients for diagnostic or prognostic applications.

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Residual recipient haematopoietic cells may coexist with donor haemopoietic tissue following BMT. This is known as mixed chimaerism. The incidence of mixed chimaerism varies with the sensitivity of the detection system used; DNA based methodologies are the most sensitive. The influence of mixed chimaerism on leukaemia relapse and graft rejection is unclear. The lineages in which mixed chimaerism occurs may affect outcome.

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Current methods for measuring deoxyribonucleoside triphosphates (dNTPs) employ reagent and labor-intensive assays utilizing radioisotopes in DNA polymerase-based assays and/or chromatography-based approaches. We have developed a rapid and sensitive 96-well fluorescence-based assay to quantify cellular dNTPs utilizing a standard real-time PCR thermocycler. This assay relies on the principle that incorporation of a limiting dNTP is required for primer-extension and Taq polymerase-mediated 5-3' exonuclease hydrolysis of a dual-quenched fluorophore-labeled probe resulting in fluorescence. The concentration of limiting dNTP is directly proportional to the fluorescence generated. The assay demonstrated excellent linearity (R(2) > 0.99) and can be modified to detect between ∼0.5 and 100 pmol of dNTP. The limits of detection (LOD) and quantification (LOQ) for all dNTPs were defined as <0.77 and <1.3 pmol, respectively. The intra-assay and inter-assay variation coefficients were determined to be <4.6% and <10%, respectively with an accuracy of 100 ± 15% for all dNTPs. The assay quantified intracellular dNTPs with similar results obtained from a validated LC-MS/MS approach and successfully measured quantitative differences in dNTP pools in human cancer cells treated with inhibitors of thymidylate metabolism. This assay has important application in research that investigates the influence of pathological conditions or pharmacological agents on dNTP biosynthesis and regulation.

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This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

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Explores the relation between gender and the encounter of Jews with various conditions of Modernity. She makes clear that the study of the process of Jewish assimilation in contemporary times must include women and gender in its framework.

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Explores the relation between gender and the encounter of Jews with various conditions of Modernity. She makes clear that the study of the process of Jewish assimilation in contemporary times must include women and gender in its framework.

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Thesis (Ph.D.)--University of Washington, 2016-03

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Explores the relation between gender and the encounter of Jews with various conditions of Modernity. She makes clear that the study of the process of Jewish assimilation in contemporary times must include women and gender in its framework.

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Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.