385 research outputs found

    ISBDD model for classification of hyperspectral remote sensing imagery

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    The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels). However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD) model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and the Push-broom Hyperspectral Imager (PHI) are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively

    Bacterial growth, detachment and cell size control on polyethylene terephthalate surfaces.

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    In medicine and food industry, bacterial colonisation on surfaces is a common cause of infections and severe illnesses. However, the detailed quantitative information about the dynamics and the mechanisms involved in bacterial proliferation on solid substrates is still lacking. In this study we investigated the adhesion and detachment, the individual growth and colonisation, and the cell size control of Escherichia coli (E. coli) MG1655 on polyethylene terephthalate (PET) surfaces. The results show that the bacterial growth curve on PET exhibits the distinct lag and log phases, but the generation time is more than twice longer than in bulk medium. Single cells in the lag phase are more likely to detach than clustered ones in the log phase; clustered bacteria in micro-colonies have stronger adhesive bonds with surfaces and their neighbours with the progressing colonisation. We show that the cell size is under the density-dependent pathway control: when the adherent cells are at low density, the culture medium is responsible for coordinating cell division and cell size; when the clustered cells are at high population density, we demonstrate that the effect of quorum sensing causes the cell size decrease as the cell density on surfaces increases.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/srep1515

    PI parameter tuning of converters for sub-synchronous interactions existing in grid-connected DFIG wind turbines

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    Durability Environmental Regionalization for Concrete Structures

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    Environment is the external factor that affects the durability of concrete structures. Buildings in different regions with different climates will respond to durability deterioration in different ways. For macroenvironmental regionalization, the dominant factor analysis method of the climatic zonation was applied into the environmental regionalization in this paper. Based on the environmental characteristics in China and the effect of environmental factor on the durability of concrete structure, the proper regionalization indexes are chosen, and the environmental regionalization is made. For microenvironmental regionalization, fuzzy set and rough set theories were used in date mining on discrete measured data, and the weight determination of various factors affecting durability was transformed into evaluation of the significance of attributes among rough sets. The method of durability environmental regionalization is established by analyzing the degree of influence that various factors have on the durability of concrete structures. The result of durability environmental regionalization for concrete structures in Shenzhen city shows that the proposed approach is reasonable

    The Longest Common Exemplar Subsequence Problem

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    In this paper, we propose to find order conserved subsequences of genomes by finding longest common exemplar subsequences of the genomes. The longest common exemplar subsequence problem is given by two genomes, asks to find a common exemplar subsequence of them, such that the exemplar subsequence length is maximized. We focus on genomes whose genes of the same gene family are in at most s spans. We propose a dynamic programming algorithm with time complexity O(s4 s mn) to find a longest common exemplar subsequence of two genomes with one genome admitting s span genes of the same gene family, where m, n stand for the gene numbers of those two given genomes. Our algorithm can be extended to find longest common exemplar subsequences of more than one genomes

    Ultrafast Spin-To-Charge Conversion at the Surface of Topological Insulator Thin Films

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    Strong spin-orbit coupling, resulting in the formation of spin-momentum-locked surface states, endows topological insulators with superior spin-to-charge conversion characteristics, though the dynamics that govern it have remained elusive. Here, we present an all-optical method that enables unprecedented tracking of the ultrafast dynamics of spin-to-charge conversion in a prototypical topological insulator Bi2_2Se3_3/ferromagnetic Co heterostructure, down to the sub-picosecond timescale. Compared to pure Bi2_2Se3_3 or Co, we observe a giant terahertz emission in the heterostructure than originates from spin-to-charge conversion, in which the topological surface states play a crucial role. We identify a 0.12-picosecond timescale that sets a technological speed limit of spin-to-charge conversion processes in topological insulators. In addition, we show that the spin-to-charge conversion efficiency is temperature independent in Bi2_2Se3_3 as expected from the nature of the surface states, paving the way for designing next-generation high-speed opto-spintronic devices based on topological insulators at room temperature.Comment: 19 pages, 4 figure

    Anisodamine combined with lidocaine improves healing of myocardial ischemia reperfusion injury in rats via PI3K/Akt signaling pathway

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    Purpose: To study the effects of anisodamine (Ad) combined with lidocaine (Ldc) on myocardial ischemia-reperfusion injury (MIRI) in rats, and its correlation with PI3K/AKT signaling pathway.Methods: A total of 70 healthy rats were randomly divided into S group, M group, Ad group, Ldc group, Ad + Ldc group, Ad + Ldc + LY group, and LY group. The cardiac hemodynamic indices in each group were determined, and the area of myocardial infarction measured. Serum biochemical indices were also determined. Furthermore, the protein expressions of p-Akt, T-Akt, Bcl-2, and Bax in myocardial cells were determined by Western blotting.Results: Compared with those in M group, Ad group, Ldc group, Ad + Ldc + LY group, and LY group, cardiac hemodynamic indices significantly improved, while the area of myocardial infarction was significantly reduced (p < 0.01). Furthermore, serum malondialdehyde (MDA) concentration but the activities of CK, CK-MB, TNF-α, and IL-6 declined, while the activities of superoxide dismutase (SOD), CAT and GSH-Px rose in Ad + Ldc group (p < 0.01). In Ad + Ldc group, p-Akt, T-Akt, and Bcl-2 increased, while Bax significantly decreased. Through comparison LY294002 significantly inhibited the protective effect of Ad combined with Ldc against MIRI in rats (p < 0.01).Conclusion: Anisodamine combination with lidocaine has a protective effect against MIRI in rats via PI3K/Akt signaling pathway, thus indicating that it is a potential therapeutic strategy for the management of myocardial ischemia-reperfusion

    Morphometric characterisation of landform from DEMs

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    We describe a method of morphometric characterisation of landform from DEMs. The method is implemented by first classifying every location into morphometric classes based on the mathematical shape of a locally fitted quadratic surface and its positional relationship with the analysis window. Single-scale fuzzy terrain indices of peakness, pitness, passness, ridgeness, and valleyness are then calculated based on the distance of the analysis location from the ideal cases. These can then be combined into multi-scale terrain indices to summarise terrain information across different operational scales. The algorithm has four characteristics: (1) the ideal cases of different geomorphometric features are simply and clearly defined; (2) the output is spatially continuous to reflect the inherent fuzziness of geomorphometric features; (3) the output is easily combined into a multi-scale index across a range of operational scales; and (4) the standard general morphometric parameters are quantified as the first and second order derivatives of the quadratic surface. An additional benefit of the quadratic surface is the derivation of the R2 goodness of fit statistic, which allows an assessment of both the reliability of the results and the complexity of the terrain. An application of the method using a test DEM indicates that the single- and multi-scale terrain indices perform well when characterising the different geomorphometric features
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