997 resultados para Material intensity


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Introduction: Detection of the ALK rearrangement in a solid tumor gives these patients the option of crizotinib as an oral form of anticancer treatment. The current test of choice is fluorescence in situ hybridization (FISH), but various cheaper and more convenient immunohistochemical (IHC) assays have been proposed as alternatives. 
Methods: Fifteen FISH-positive cases from patients, seven with data on crizotinib therapy and clinical response, were evaluated for the presence of ALK protein using three different commercially available antibodies: D5F3, using the proprietary automated system (Ventana), ALK1 (Dako), and 5A4 (Abcam). A further 14 FISH-negative and three uncertain (<15% rearrangement detected) cases were also retrieved. Of the total 32 specimens, 17 were excisions and 15 were computed tomography-guided biopsies or cytological specimens. All three antibodies were applied to all cases. Antibodies were semiquantitatively scored on intensity, and the proportion of malignant cells stained was documented. Cutoffs were set by receiver operating curve analysis for positivity to optimize correct classification. 
Results: All three IHC assays were 100% specific but sensitivity did vary: D5F3 86%, ALK 79%, 5A4 71%. Intensity was the most discriminating measure overall, with a combination of proportion and intensity not improving the test. No FISH-negative IHC-positive cases were seen. Two FISH-positive cases were negative with all three IHC assays. One of these had been treated with crizotinib and had failed to show clinical response. The other harbored a second driving mutation in the EGFR gene.
Conclusions: IHC with all three antibodies is especially highly specific (100%) although variably sensitive (71%-86%), specifically in cases with scanty material. D5F3 assay was most sensitive in these latter cases. Occasional cases are IHC-positive but FISH-negative, suggesting either inaccuracy of one assay or occasional tumors with ALK rearrangement that do not express high levels of ALK protein.

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A purified commercial double-walled carbon nanotube (DWCNT) sample was investigated by transmission electron microscopy (TEM), thermogravimetry (TG), and Raman spectroscopy. Moreover, the heat capacity of the DWCNT sample was determined by temperature-modulated differential scanning calorimetry in the range of temperature between -50 and 290 °C. The main thermo-oxidation characterized by TG occurred at 474 °C with the loss of 90 wt% of the sample. Thermo-oxidation of the sample was also investigated by high-resolution TG, which indicated that a fraction rich in carbon nanotube represents more than 80 wt% of the material. Other carbonaceous fractions rich in amorphous coating and graphitic particles were identified by the deconvolution procedure applied to the derivative of TG curve. Complementary structural data were provided by TEM and Raman studies. The information obtained allows the optimization of composites based on this nanomaterial with reliable characteristics.

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A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.

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The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

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Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.