990 resultados para destructive crowd


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This paper describes a non-destructive "peak parking" protocol in order to assess the axial heterogeneity of an in situ modified monolithic column for high performance liquid chromatography; a "gradient stationary phase" was designed whereby the ligand density decreases along the length of the rod in the "forward flow" configuration. The results of multi-location peak parking demonstrated a consistent increase in peak variance from the 1 cm position of the column to the 9 cm location. This increase in band broadening supported the theory of a decreasing ligand density along the length of this gradient column. This is consistent with efficiency measurements performed in both the forward and reverse flow directions, with an improved efficiency (15% increase in N m-1) in the reverse direction. These results are consistent with theoretical investigations into stationary phase gradients.

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Several people are looking at sample prints in this photograph of the Lithographic Technical Forum. In the background the booth for the Lithographic Technical Foundation, Inc. can be seen. Black and white photograph.

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Introduction. Leaf area is often related to plant growth, development, physiology and yield. Many non-destructive models have been proposed for leaf area estimation of several plant genotypes, demonstrating that leaf length, leaf width and leaf area are closely correlated. Thus, the objective of our study was to develop a reliable model for leaf area estimation from linear measurements of leaf dimensions for citrus genotypes. Materials and methods. Leaves of citrus genotypes were harvested, and their dimensions (length, width and area) were measured. Values of leaf area were regressed against length, width, the square of length, the square of width and the product (length x width). The most accurate equations, either linear or second-order polynomial, were regressed again with a new data set; then the most reliable equation was defined. Results and discussion. The first analysis showed that the variables length, width and the square of length gave better results in second-order polynomial equations, while the linear equations were more suitable and accurate when the width and the product (length x width) were used. When these equations were regressed with the new data set, the coefficient of determination (R(2)) and the agreement index 'd' were higher for the one that used the variable product (length x width), while the Mean Absolute Percentage Error was lower. Conclusion. The product of the simple leaf dimensions (length x width) can provide a reliable and simple non-destructive model for leaf area estimation across citrus genotypes.

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Objetivou-se com o presente trabalho, estabelecer a relação entre os pigmentos fotossintéticos extraídos em DMSO e as leituras obtidas no clorofilômetro portátil ClorofiLOG® 1030, gerando modelos matemáticos capazes de predizer os teores de clorofila e de carotenóides em folhas de mamoneira. O trabalho foi conduzido na Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Algodão, situada em Campina Grande, Estado da Paraíba, em outubro de 2010. Para a análise indireta, foi utilizado um equipamento portátil, sendo realizada a leitura em discos foliares com diferentes tonalidades de verde, sendo feita, nesses mesmos discos, a determinação da clorofila pelo método clássico. Para a extração da clorofila, utilizaram-se 5 mL de dimetilsulfóxido (DMSO), a qual foi mantida em banho-maria a 70ºC, por 30 minutos, e retirou-se 3 mL da alíquota para leitura em espectrofotômetro nos comprimentos de onda de 470, 646 e 663 nm. Os dados foram submetidos à análise da variância e regressão polinomial. A leitura obtida no clorofilômetro portátil foi a variável dependente, e os pigmentos fotossintéticos determinados pelo método clássico foi a variável independente. Os resultados indicaram que o clorofilômetro portátil ClorofiLOG® 1030, associado a modelos matemáticos, permitiu estimar a concentração dos pigmentos fotossintéticos, exceto a clorofila b, com alta precisão, com economia de tempo e com reagentes normalmente utilizados nos procedimentos convencionais.

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This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

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DNA-based studies have been one of the major interests in conservation biology of endangered species and in population genetics. As species and population genetic assessment requires a source of biological material, the sampling strategy can be overcome by non-destructive procedures for DNA isolation. An improved method for obtaining DNA from fish fins and scales with the use of an extraction buffer containing urea and further DNA purification with phenol-chloroform is described. The methodology combines the benefits of a non-destructive DNA sampling and its high efficiency. In addition, comparisons with other methodologies for isolating DNA from fish demonstrated that the present procedure also becomes a very attractive alternative to obtain large amounts of high-quality DNA for use in different molecular analyses. The DNA samples, isolated from different fish species, have been successfully used on random amplified polymorphic DNA (RAPD) experiments, as well as on amplification of specific ribosomal and mitochondrial DNA sequences. The present DNA extraction procedure represents an alternative for population approaches and genetic studies on rare or endangered taxa.

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Ethanol can compromise the body mineral composition and affect bone, and when associated to hypogonadism is considered an important risk factor for osteoporosis in man. The aim of this study was to investigate the effect of androgen deficient and chronic ethanol consuming on mineral contents by biochemistry and non-destructive techniques. Wistar rat (n=54) were divided in orchiectomy (ORQ) or SHAM-operated and subdivided by diet. They were daily fed with a Lieber DeCarli diet model for 8 weeks long. The controls groups were free-diet and pair-fed. Ca and P were analyzed by biochemistry test in the blood and by nX-ray fluorescence and FT-Raman on the femur area. Serum analysis revealed hypocalcaemia and hypeiphosphataemia in ethanol groups more than pair-fed and free-diet. In similarity, spectroscopy indicated a decrease in bone Ca content in ORQ groups, mainly for ethanol groups. Phosphorus content and Ca/P molar ratio, otherwise, doesn't diverge in all 6 groups. Ethanol consumption impaired Ca and P homeostasis in ORQ rat more than SHAM. The relationships among ethanol consume and androgen deficit support the hypothesis that ethanol affects the mineral-regulating hormones and may mediate some effects on bone. These findings demonstrate that ethanol seemed to interfere with the normal compensatory response to these Ca and P levels and is more significant M androgen deficiency rats.

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This paper considers the role of automatic estimation of crowd density and its importance for the automatic monitoring of areas where crowds are expected to be present. A new technique is proposed which is able to estimate densities ranging from very low to very high concentration of people, which is a difficult problem because in a crowd only parts of people's body appear. The new technique is based on the differences of texture patterns of the images of crowds. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. The image pixels are classified in different texture classes and statistics of such classes are used to estimate the number of people. The texture classification and the estimation of people density are carried out by means of self organising neural networks. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented. (C) 1998 Elsevier B.V. Ltd. All rights reserved.

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The goal of this work is to assess the efficacy of texture measures for estimating levels of crowd densities ill images. This estimation is crucial for the problem of crowd monitoring. and control. The assessment is carried out oil a set of nearly 300 real images captured from Liverpool Street Train Station. London, UK using texture measures extracted from the images through the following four different methods: gray level dependence matrices, straight lille segments. Fourier analysis. and fractal dimensions. The estimations of dowel densities are given in terms of the classification of the input images ill five classes of densities (very low, low. moderate. high and very high). Three types of classifiers are used: neural (implemented according to the Kohonen model). Bayesian. and an approach based on fitting functions. The results obtained by these three classifiers. using the four texture measures. allowed the conclusion that, for the problem of crowd density estimation. texture analysis is very effective.