914 resultados para fractionation and identification


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An approach towards shape description, based on prototype modification and generalized cylinders, has been developed and applied to the object domains pottery and polyhedra: (1) A program describes and identifies pottery from vase outlines entered as lists of points. The descriptions have been modeled after descriptions by archeologists, with the result that identifications made by the program are remarkably consisten with those of the archeologists. It has been possible to quantify their shape descriptors, which are everyday terms in our language applied to many sorts of objects besides pottery, so that the resulting descriptions seem very natural. (2) New parsing strategies for polyhedra overcome some limitations of previous work. A special feature is that the processes of parsing and identification are carried out simultaneously.

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Molecular diagnosis is playing an increasingly important role in the rapid detection and identification of pathogenic organisms in clinical samples. The genetic variation of ribosomal genes in bacteria offers an alternative to culturing for the detection and identification of these organisms. Here 16S rRNA and 16S-23S rRNA spacer region genes were chosen as the amplified targets for single-strand conformation polymorphism (SSCP) and restriction fragment length polymorphism (RFLP) capillary electrophoresis analysis and bacterial identification. The multiple fluorescence based SSCP method for the 16S rRNA gene and the RFLP method for the 16S-23S rRNA spacer region gene were developed and applied to the identification of pathogenic bacteria in clinical samples, in which home-made short-chained linear polyacrylamide (LPA) was used as a sieving matrix; a higher sieving capability and shorter analysis time were achieved than with a commercial sieving matrix because of the simplified template preparation procedure. A set of 270 pathogenic bacteria representing 34 species in 14 genera were analyzed, and a total of 34 unique SSCP patterns representing 34 different pathogenic bacterial species were determined. Based on the use of machine code to represent peak patterns developed in this paper, the identification of bacterial species becomes much easier.

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King, R.D., Garrett, S.M., Coghill, G.M. (2005). On the use of qualitative reasoning to simulate and identify metabolic pathways. Bioinformatics 21(9):2017-2026 RAE2008

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Material discrimination based on conventional or dual energy X-ray computed tomography (CT) imaging can be ambiguous. X-ray diffraction imaging (XDI) can be used to construct diffraction profiles of objects, providing new molecular signature information that can be used to characterize the presence of specific materials. Combining X-ray CT and diffraction imaging can lead to enhanced detection and identification of explosives in luggage screening. In this work we are investigating techniques for joint reconstruction of CT absorption and X-ray diffraction profile images of objects to achieve improved image quality and enhanced material classification. The initial results have been validated via simulation of X-ray absorption and coherent scattering in 2 dimensions.

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How does the brain use eye movements to track objects that move in unpredictable directions and speeds? Saccadic eye movements rapidly foveate peripheral visual or auditory targets and smooth pursuit eye movements keep the fovea pointed toward an attended moving target. Analyses of tracking data in monkeys and humans reveal systematic deviations from predictions of the simplest model of saccade-pursuit interactions, which would use no interactions other than common target selection and recruitment of shared motoneurons. Instead, saccadic and smooth pursuit movements cooperate to cancel errors of gaze position and velocity, and thus to maximize target visibility through time. How are these two systems coordinated to promote visual localization and identification of moving targets? How are saccades calibrated to correctly foveate a target despite its continued motion during the saccade? A neural model proposes answers to such questions. The modeled interactions encompass motion processing areas MT, MST, FPA, DLPN and NRTP; saccade planning and execution areas FEF and SC; the saccadic generator in the brain stem; and the cerebellum. Simulations illustrate the model’s ability to functionally explain and quantitatively simulate anatomical, neurophysiological and behavioral data about SAC-SPEM tracking.

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Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

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Cystic fibrosis (CF) patients may suffer increased morbidity and mortality through colonisation, allergy and invasive infection from fungi. The black yeast, Exophiala dermatitidis (synonym Wangiella dermatitidis) has been found with increasing frequency in sputum specimens of CF patients, with reported isolation rates ranging from 1.1 to 15.7%. At present, no diagnostic PCR exists to aid with the clinical laboratory detection and identification of this organism. A novel species-specific PCR-based assay was developed for the detection of E. dermatitidis, based on employment of rDNA operons and interspacer (ITS) regions between these rDNA operons. Two novel primers, (designated ExdF & ExdR) were designed in silico with the aid of computer-aided alignment software and with the alignment of multiple species of Exophiala, as well as with other commonly described yeasts and filamentous fungi within CF sputum, including Candida. Aspergillus and Scedosporium. An amplicon of approximately 455 by was generated, spanning the partial ITS I region - the complete 5.8S rDNA region - partial ITS2 region, employing ExdF (forward primer [16-mer], 5'-CCG CCT ATT CAG GTC C-3' and ExdR (reverse primer [16-mer], 5'-TCT CTC CCA CTC CCG C-3', was employed and optimised on extracted genomic DNA from a well characterised culture of E. dermatitidis, as well as with high quality genomic DNA template from a further 16 unrelated fungi, including Candida albicans, C. dubliniensis, C. parapsilosis, C. glabrata, Scedosporium apiospermum, Penicillium sp., Aspergillus fumigatus, Aspergillus versicolor, Pichia guilliermondii, Rhodotorula sp., Trichosporon sp., Aureobasidium pullulans, Fusarium sp., Mucor hiemalis, Bionectria ochroleuca, Gibberella pulicaris. Results demonstrated that only DNA from E. dermatitidis gave an amplification product of the expected sire, whilst none of the other fungi were amplifiable. Subsequent employment of this primer pair detected this yeast from mycological cultures from 2/50 (4%) adult CF patients. These two patients were the only patients who were previously shown to have a cultural history of E. dermatitidis from their sputum. E. dermatitidis is a slow-growing fungus, which usually takes up to two weeks to culture in the microbiology laboratory and therefore is slow to detect conventionally, with the risk of bacterial overgrowth from common co-habiting pan- and multiresistant bacterial pathogens from sputum. namely Pseudomonas aeruginosa and Burkholderia cepacia complex organisms, hence this species-specific PCR assay may help detect this organism from CF sputum more specifically and rapidly. Overall, employment of this novel assay nay help in the understanding of the occurrence. aetiology and epidemiology of E. dermatitidis, as an emerging fungal agent in patients with CF. (C) 2008 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

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A rapid liquid chromatographic-tandem mass spectrometric (LC-MS/MS) multi-residue method for the simultaneous quantitation and identification of sixteen synthetic growth promoters and bisphenol A in bovine milk has been developed and validated. Sample preparation was straightforward, efficient and economically advantageous. Milk was extracted with acetonitrile followed by phase separation with NaCl. After centrifugation, the extract was purified by dispersive solid-phase extraction with C18 sorbent material. The compounds were analysed by reversed-phase LC-MS/MS using both positive and negative ionization and operated in multiple reaction monitoring (MRM) mode, acquiring two diagnostic product ions from each of the chosen precursor ions for unambiguous confirmation. Total chromatographic run time was less than 10 min for each sample. The method was validated at a level of 1 mu g L-1. A wide variety of deuterated internal standards were used to improve method performance. The accuracy and precision of the method were satisfactory for all analytes. The confirmative quantitative liquid chromatographic tandem mass spectrometric (LC-MS/MS) method was validated according to Commission Decision 2002/657/EC. The decision limit (CC alpha) and the detection capability (CC beta) were found to be below the chosen validation level of 1 mu g L-1 for all compounds. (C) 2010 Elsevier B.V. All rights reserved.

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Today, the classification systems for myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) already incorporate cytogenetic and molecular genetic aberrations in an attempt to better reflect disease biology. However, in many MDS/AML patients no genetic aberrations have been identified yet, and even within some cytogenetically well-defined subclasses there is considerable clinical heterogeneity. Recent advances in genomics technologies such as gene expression profiling (GEP) provide powerful tools to further characterize myeloid malignancies at the molecular level, with the goal to refine the MDS/AML classification system, incorporating as yet unknown molecular genetic and epigenetic pathomechanisms, which are likely reflected by aberrant gene expression patterns. In this study, we provide a comprehensive review on how GEP has contributed to a refined molecular taxonomy of MDS and AML with regard to diagnosis, prediction of clinical outcome, discovery of novel subclasses and identification of novel therapeutic targets and novel drugs. As many challenges remain ahead, we discuss the pitfalls of this technology and its potential including future integrative studies with other genomics technologies, which will continue to improve our understanding of malignant transformation in myeloid malignancies and thereby contribute to individualized risk-adapted treatment strategies for MDS and AML patients. Leukemia (2011) 25, 909-920; doi:10.1038/leu.2011.48; published online 29 March 2011

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Dynamic mechanical analysis (DMA) is an analytical technique in which an oscillating stress is applied to a sample and the resultant strain measured as functions of both oscillatory frequency and temperature. From this, a comprehensive knowledge of the relationships between the various viscoelastic parameters, e.g. storage and loss moduli, mechanical damping parameter (tan delta), dynamic viscosity, and temperature may be obtained. An introduction to the theory of DMA and pharmaceutical and biomedical examples of the use of this technique are presented in this concise review. In particular, examples are described in which DMA has been employed to quantify the storage and loss moduli of polymers, polymer damping properties, glass transition temperature(s), rate and extent of curing of polymer systems, polymer-polymer compatibility and identification of sol-gel transitions. Furthermore, future applications of the technique for the optimisation of the formulation of pharmaceutical and biomedical systems are discussed. (C) 1999 Elsevier Science B.V. All rights reserved.

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In this study the design and development of two real-time PCR assays for the rapid, sensitive and specific detection of infectious laryngotracheitis virus (ILTV) DNA is described. A Primer-Probe Energy Transfer (PriProET) assay and 5' conjugated Minor Groove Binder (MGB) method are compared and contrasted. Both have been designed to target the thymidine kinase gene of the ILTV genome. Both PriProET and MGB assays are capable of detecting 20 copies of a DNA standard per reaction and are linear from 2 x 10(8) to 2 x 10(2) copies/mu l. Neither PriProET, nor MGB reacted with heterologous herpesviruses, indicating a high specificity of the two methods as novel tools for virus detection and identification. This study demonstrates the suitability of PriProET and 5' conjugated MGB probes as real-time PCR chemistries for the diagnosis of respiratory diseases caused by ILTV. (C) 2011 Elsevier B.V. All rights reserved.

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Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.

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Background: Pregnancy is viewed as a major life event and, while the majority of healthy, low-risk women adapt well to pregnancy, there are those whose levels of stress are heightened by the experience.

Objectives: To determine the level of pregnancy-related stress experienced by a group of healthy, low-risk pregnant women and to relate the level of stress with a number of maternal characteristics.

Design: An observational cross-sectional study.

Setting: A large, urban maternity centre in Northern Ireland.

Participants: Of the 306 pregnant women who were invited to participate, 278 provided informed consent and were administered one self-complete questionnaire. Due to the withdrawal criteria, 15 questionnaires were removed from the analysis, resulting in a final sample of 263 healthy, low-risk pregnant women.

Methods: Levels of stress were measured using a self-report measure designed to assess specific worries and concerns relating to pregnancy. Maternal characteristics collected included age, marital status, social status, parity, obstetric history, perceived health status and 'wantedness' for the pregnancy. Regression analysis was undertaken using an ordinary linear regression model.

Results: The mean prenatal distress score in the sample was 15.1 (SD = 7.4; range 0-46). The regression model showed that women who had had previous pregnancies, with or without complications, had significantly lower mean prenatal distress scores than primiparous women (p < 0.01). Women reporting poorer physical health had higher mean prenatal distress scores than those who reported at least average health, while women aged 16-20 experienced a mean increase in the reported prenatal distress score (p < 0.05) in comparison to the reference group of 36 years and over.

Conclusions: This study brings to light the prevalence of pregnancy-related stress within a sample representative of healthy, low-risk women. Current antenatal care is ill-equipped to identify women suffering from high levels of stress; yet a growing body of research evidence links stress with adverse pregnancy outcomes. This study emphasises that healthy, low-risk women experience a range of pregnancy-related stress and identification of stress levels, either through the use of a simple stress measurement tool or through the associated factors identified within this research study, provides valuable data on maternal well-being. (C) 2010 Elsevier Ltd. All rights reserved.

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The objective of this study was to identify, through a consensus process, the essential practices in primary palliative care. A three-phase study was designed. Phase 1 methods included development of a working group; a literature review; development of a baseline list of practices; and identification of levels of intervention. In Phase 2, physicians, nurses, and nurse aides (n = 425) from 63 countries were asked in three Delphi rounds to rate the baseline practices as essential or nonessential and select the appropriate levels of intervention for each. In Phase 3, representatives of 45 palliative care organizations were asked to select and rank the 10 most important practices resulting from Phase 2. Scores (1-10) were assigned to each, based on the selected level of importance. Results of Phase 1 were a baseline list of 140 practices. Three levels of intervention were identified: Identification/Evaluation; Diagnosis; and Treatment/Solution measures. In Phase 2, the response rates (RR) for the Delphi rounds were 96.5%, 73.6%, and 71.8%, respectively. A consensus point (=80% agreement) was applied, resulting in 62 practices. In Phase 3, RR was 100%. Forty-nine practices were selected and ranked. "Evaluation, Diagnosis and Treatment of Pain" scored the highest (352 points). The working group (WG) arranged the resulting practices in four categories: Physical care needs, Psychological/Emotional/Spiritual care needs, Care Planning and Coordination, and Communication. The IAHPC List of Essential Practices in Palliative care may help define appropriate primary palliative care and improve the quality of care delivered globally. Further studies are needed to evaluate their uptake and impact.

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The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.