987 resultados para Mark and recapture method


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A new mild method has been devised for generating o-(naphtho)quinone methides via fluoride-induced desilylation of silyl derivatives of o-hydroxybenzyl(or 1-naphthylmethyl) nitrate. The reactive o-(naphtho)quinone methide intermediates were trapped by C, O, N and S nucleophiles and underwent “inverse electron-demand” hetero Diels- Alder reaction with dienophiles to give stable adducts. The method has useful potential application in natural product synthesis and drug research

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This article presents a reinterpretation of James Harrington's writings. It takes issue with J. G. A. Pocock's reading, which treats him as importing into England a Machiavellian ‘language of political thought’. This reading is the basis of Pocock's stress on the republicanism of eighteenth-century opposition values. Harrington's writings were in fact a most implausible channel for such ideas. His outlook owed much to Stoicism. Unlike the Florentine, he admired the contemplative life; was sympathetic to commerce; and was relaxed about the threat of ‘corruption’ (a concept that he did not understand). These views can be associated with his apparent aims: the preservation of a national church with a salaried but politically impotent clergy; and the restoration of the royalist gentry to a leading role in English politics. Pocock's hypothesis is shown to be conditioned by his method; its weaknesses reflect some difficulties inherent in the notion of ‘languages of thought’.

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The objective of this study was to test a device developed to improve the functionality, accuracy and precision of the original technique for sweating rate measurements proposed by Schleger and Turner [Schleger AV, Turner HG (1965) Aust J Agric Res 16:92-106]. A device was built for this purpose and tested against the original Schleger and Turner technique. Testing was performed by measuring sweating rates in an experiment involving six Mertolenga heifers subjected to four different thermal levels in a climatic chamber. The device exhibited no functional problems and the results obtained with its use were more consistent than with the Schleger and Turner technique. There was no difference in the reproducibility of the two techniques (same accuracy), but measurements performed with the new device had lower repeatability, corresponding to lower variability and, consequently, to higher precision. When utilizing this device, there is no need for physical contact between the operator and the animal to maintain the filter paper discs in position. This has important advantages: the animals stay quieter, and several animals can be evaluated simultaneously. This is a major advantage because it allows more measurements to be taken in a given period of time, increasing the precision of the observations and diminishing the error associated with temporal hiatus (e.g., the solar angle during field studies). The new device has higher functional versatility when taking measurements in large-scale studies (many animals) under field conditions. The results obtained in this study suggest that the technique using the device presented here could represent an advantageous alternative to the original technique described by Schleger and Turner.

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A simple, fast, accurate, and sensitive spectrophotometric method was developed to determine zinc(II). This method is based on the reaction of Zn(II) with di-2-pyridyl ketone benzoylhydrazone (DPKBH), at pH=5.5 and 50% (v/v) ethanol. Beers law was obeyed in the range 0.020-1.82 mu g mL(-1) with a molar apsorptivity of 3.64 x 10(4) L mol(-1) cm(-1), and a detection limit (3) of 2.29 mu g L-1. The action of some interfering ions was verified and the developed method applied to pharmaceutical and biological samples. The results were then compared with those obtained by using a flame atomic absorption technique.

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Nanowires represent a new class of ZnO morphologies with many exiting new properties and applications. The research in the synthesis and characterization of ZnO nanowires has received enormous attention in recent years. However, most synthesis methods using vapor deposition process can only produce small amount of sample, mass production has not been achieved yet. Large-quantity production of ZnO nanowires needs to be realized for large-scale property and application studies. One of the promising approaches to the large scale synthesis is a ball-milling and annealing method. This paper first introduces several common synthesis methods of ZnO nanowires and then summarizes the one dimensional nanomaterials produced by the ball milling and annealing method. Finally, some preliminary results of ZnO nanowire synthesis are presented.

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A boron nitride (BN) nanostructure, conical BN nanorod, has been synthesized in a large quantity on Si substrates for the first time via the ball-milling and annealing method. Nitridation of milled boron carbide (B4C) powders was performed in nitrogen gas at 1300°C on the surface of the substrates to form the BN nanorods. The highly crystallized nanorods consist of conical BN basal layers stacked along the nanorod axis. Ball milling of the B4C powders can significantly enhance the nitridation of the powders and thus facilitate the formation of nanorods during the annealing process.

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ZnO powder was mechanically milled in a ball mill. This procedure was found to greatly increase its evaporation ability. The anomalous evaporation behaviour was caused by the disordered structure of the milled material and was not related to the increase in its surface area after milling. ZnO nanowires were synthesized by evaporation of this milled precursor. Nanowires with smooth and rough surfaces were present in the sample; the latter morphology was dominant. A green emission band centred at 510 nm was dominant in the cathodoluminescence spectrum of the nanowires.

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The validity of the priority vector used in the analytic hierarchy process (AHP) relies on two factors: the selection of a numerical scale and the selection of a prioritization method. The traditional AHP selects only one numerical scale (e.g., the Saaty scale) and one prioritization method (e.g., the eigenvector method) for each particular problem. For this traditional selection approach, there is disagreement on which numerical scale and prioritization method is better in deriving a priority vector. In fact, the best numerical scale and the best prioritization method both rely on the content of the pairwise comparison data provided by the AHP decision makers. By defining a set of concepts regarding the scale function and the linguistic pairwise comparison matrices (LPCMs) of the priority vector and by using LPCMs to unify the format of the input and output of AHP, this paper extends the AHP prioritization process under the 2-tuple fuzzy linguistic model. Based on the extended AHP prioritization process, we present two performance measure criteria to evaluate the effect of the numerical scales and prioritization methods. We also use the performance measure criteria to develop a 2-tuple fuzzy linguistic multicriteria approach to select the best numerical scales and the best prioritization methods for different LPCMs. In this paper, we call this type of selection the individual selection of the numerical scale and prioritization method. We also compare this individual selection with traditional selection by using both random and real data and show better results with individual selection.

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Optical inspection techniques have been widely used in industry as they are non-destructive. Since defect patterns are rooted from the manufacturing processes in semiconductor industry, efficient and effective defect detection and pattern recognition algorithms are in great demand to find out closely related causes. Modifying the manufacturing processes can eliminate defects, and thus to improve the yield. Defect patterns such as rings, semicircles, scratches, and clusters are the most common defects in the semiconductor industry. Conventional methods cannot identify two scale-variant or shift-variant or rotation-variant defect patterns, which in fact belong to the same failure causes. To address these problems, a new approach is proposed in this paper to detect these defect patterns in noisy images. First, a novel scheme is developed to simulate datasets of these 4 patterns for classifiers' training and testing. Second, for real optical images, a series of image processing operations have been applied in the detection stage of our method. In the identification stage, defects are resized and then identified by the trained support vector machine. Adaptive resonance theory network 1 is also implemented for comparisons. Classification results of both simulated data and real noisy raw data show the effectiveness of our method.