999 resultados para gram matrix
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We provide a new proof of Volberg's Theorem characterizing thin interpolating sequences as those for which the Gram matrix associated to the normalized reproducing kernels is a compact perturbation of the identity. In the same paper, Volberg characterized sequences for which the Gram matrix is a compact perturbation of a unitary as well as those for which the Gram matrix is a Schatten-2 class perturbation of a unitary operator. We extend this characterization from 2 to p, where 2 <= p <= infinity.
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This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.
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Alguns Bastonetes Gram-negativos não fermentadores (BGNNF) costumam ser considerados clinicamente pouco significantes e a sua implicação em infecções é subestimada. Devido à similaridade fenotípica, mudanças taxonômicas, baixa reatividade bioquímica e limitações nos bancos de dados em sistemas comerciais, a identificação de BGNNF é frequentemente equivocada, culminando com a denominação de diferentes micro-organismos apenas como BGNNF, por falta de melhor diferenciação. O objetivo desse estudo foi avaliar, por métodos fenotípico convencional, proteômico e molecular, a identificação de BGNNF incomuns isolados em hemoculturas de pacientes atendidos em um hospital universitário no Rio de Janeiro. Foram selecionadas 78 amostras isoladas de hemoculturas caracterizadas no laboratório clinico como BGNNF para a identificação por sequenciamento dos genes 16S RNA e recA, por um conjunto amplo de testes fenotípicos manuais e por MALDI-TOF MS. Os micro-organismos predominantes na amostragem foram genotipados pela técnica de eletroforese em gel de campo pulsado (PFGE). Pelo sequenciamento do gene 16S rRNA, a maioria das amostras (n=31; 40%) foi incluída no gênero Burkholderia, seguido de Pseudomonas stutzeri (10%) e Delftia acidovorans (4%). Os demais isolados foram agrupados em 27 diferentes espécies. O sequencimento do gene recA identificou a maioria das espécies de Burkholderia como Burkholderia contaminans (n=19; 24%). Os testes fenotípicos incluíram as 31 amostras apenas no CBc e para as outras 47 amostras, a concordância com o sequenciamento do gene 16S rRNA em nível de espécie foi de 64% (n=30) e apenas em gênero a concordância foi de 17% (n=8). A análise comparativa geral da identificação por MALDI-TOF MS com o sequenciamento do gene16S rRNA mostrou que 42% (n=33) das 78 amostras foram concordantes em nível de espécie e 45% (n=35) apenas em gênero. Excluindo as amostras do CBc, houve um aumento da concordância em nível de espécie para 60%. As discordâncias parecem ser devido às diferenças nos perfis proteicos das amostras em relação às amostras-referência do banco de dados do equipamento e podem ser aprimorados com a atualização de perfis no sistema. A análise do polimorfismo genético de B. contaminans mostrou a ausência de um clone disseminado causando surto, além da provável origem ambiental das infecções. Os setores de nefrologia e hemodiálise contribuíram com maior número de pacientes com amostras positivas (5 pacientes e 9 amostras). Os grupos clonais BcoD e BcoE foram encontrados em pacientes assistidos no mesmo setor com diferença de quatro meses (BcoD, nefrologia) e 1,5 ano (BcoE, hemodilálise), entre as culturas, respectivamente. As discordâncias entre as técnicas ocorreram principalmente devido a dificuldade de identificação das espécies do CBc. Os BGNNF incomuns são de difícil caracterização independente da metodologia usada e nenhum método por si só foi capaz de identificar todas as amostras.
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A novel in situ core@shell structure consisting of nanoparticles of Ag (Ag Nps) and AgI in agarose matrix (Ag@ AgI/agarose) has been synthesized as a hybrid, in order to have an efficient antibacterial agent for repetitive usage with no toxicity. The synthesized core@shell structure is very well characterized by XRD, UV-visible, photoluminescence, and TEM. A detailed antibacterial studies including repetitive cycles are carried out on Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus) bacteria in saline water, both in dark and on exposure to visible light. The hybrid could be recycled for the antibacterial activity and is nontoxic toward human cervical cancer cells (HeLa cells). The water insoluble Ag@AgI in agarose matrix forms a good coating on quartz, having good mechanical strength. EPR and TEM studies are carried out on the Ag@AgI/agarose and the bacteria, respectively, to elucidate a possible mechanism for killing of the bacteria.
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Carbapenemases should be accurately and rapidly detected, given their possible epidemiological spread and their impact on treatment options. Here, we developed a simple, easy and rapid matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)-based assay to detect carbapenemases and compared this innovative test with four other diagnostic approaches on 47 clinical isolates. Tandem mass spectrometry (MS-MS) was also used to determine accurately the amount of antibiotic present in the supernatant after 1 h of incubation and both MALDI-TOF and MS-MS approaches exhibited a 100% sensitivity and a 100% specificity. By comparison, molecular genetic techniques (Check-MDR Carba PCR and Check-MDR CT103 microarray) showed a 90.5% sensitivity and a 100% specificity, as two strains of Aeromonas were not detected because their chromosomal carbapenemase is not targeted by probes used in both kits. Altogether, this innovative MALDI-TOF-based approach that uses a stable 10-μg disk of ertapenem was highly efficient in detecting carbapenemase, with a sensitivity higher than that of PCR and microarray.
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This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Enterococcus faecium has emerged as an important cause of nosocomial infections over the last two decades. We recently demonstrated collagen type I (CI) as a common adherence target for some E. faecium isolates and a significant correlation was found to exist between acm-mediated CI adherence and clinical origin. Here, we evaluated 60 diverse E. faecium isolates for their adherence to up to 15 immobilized host extracellular matrix and serum components. Adherence phenotypes were most commonly observed to fibronectin (Fn) (20% of the 60 isolates), fibrinogen (17%) and laminin (Ln) (13%), while only one or two of the isolates adhered to collagen type V (CV), transferrin or lactoferrin and none to the other host components tested. Adherence to Fn and Ln was almost exclusively restricted to clinical isolates, especially the endocarditis-enriched nosocomial genogroup clonal complex 17 (CC17). Thus, the ability to adhere to Fn and Ln, in addition to CI, may have contributed to the emergence and adaptation of E. faecium, in particular CC17, as a nosocomial pathogen.
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Existe um problema de representação em processamento de linguagem natural, pois uma vez que o modelo tradicional de bag-of-words representa os documentos e as palavras em uma unica matriz, esta tende a ser completamente esparsa. Para lidar com este problema, surgiram alguns métodos que são capazes de representar as palavras utilizando uma representação distribuída, em um espaço de dimensão menor e mais compacto, inclusive tendo a propriedade de relacionar palavras de forma semântica. Este trabalho tem como objetivo utilizar um conjunto de documentos obtido através do projeto Media Cloud Brasil para aplicar o modelo skip-gram em busca de explorar relações e encontrar padrões que facilitem na compreensão do conteúdo.
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Ameliorated strategies were put forward to improve the model predictive control in reducing the wind induced vibration of spatial latticed structures. The dynamic matrix control (DMC) predictive method was used and the reference trajectory which is called the decaying functions was suggested for the analysis of spatial latticed structure (SLS) under wind loads. The wind-induced vibration control model of SLS with improved DMC model predictive control was illustrated, then the different feedback strategies were investigated and a typical SLS was taken as example to investigate the reduction of wind-induced vibration. In addition, the robustness and reliability of DMC strategy were discussed by varying the model configurations.
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The ideas for this CRC research project are based directly on Sidwell, Kennedy and Chan (2002). That research examined a number of case studies to identify the characteristics of successful projects. The findings were used to construct a matrix of best practice project delivery strategies. The purpose of this literature review is to test the decision matrix against established theory and best practice in the subject of construction project management.
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The Co-operative Research Centre for Construction Innovation (CRC-CI) is funding a project known as Value Alignment Process for Project Delivery. The project consists of a study of best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best procurement approach for a specific project or group of projects. These resources will be focused on promoting the principles that underlie best practice project delivery rather than simply identifying an off-the-shelf procurement system. This project builds on earlier work by Sidwell, Kennedy and Chan (2002), on re-engineering the construction delivery process, which developed a procurement framework in the form of a Decision Matrix
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The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.