185 resultados para Annaberg (Germany : Landkreis). K. Realgymnasium


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The otoliths (N = 12) of freshwater invasive species tilapia (Tilapia mossambicus) collected from two water bodies located at Kolkata and Bangalore, India, were analyzed for stable isotopes (delta 18O, delta 14C) and major and trace elements in order to assess the suitability of using otoliths as a tracer of aquatic environmental changes. The stable isotope analysis was done using the dual inlet system of a Finnigan-MAT 253 isotope ratio mass spectrometer (Thermo-Fisher, Bremen, Germany). Concentrations of major and trace elements were determined using a Thermo X-Series II quadrupole mass spectrometer. The stable isotope composition in tilapia otolith samples from Bangalore and Kolkata water bodies are quite good agreeing with that of the respective lake/pond and rain water. Elemental composition revealed in a pattern of Ca > Fe > Na > Sr > K > Ba > Cr > Mg > As > Mn > Zn > Co > Cu > Cd > Pb. The otoliths from Kolkata pond water are more enriched in Ba, Zn, Pb, Mn, Se, Cu, Zn, Cd, and Ni whereas Cr and As were found to be higher in otolith samples from Bangalore lake. The enrichment factor (EF) values of Cr were higher for both the sampling location in comparison with other metals, although all the studied metals exhibited EF values >1. The PCA shows clustering of metals in the otolith which are related either with the metabolic and physiological attributes or waterborne source. The study demonstrated the potential of stable isotope techniques to distinguish otolith specimens from varied climatic zone, while elemental composition recorded the quality of water at both the locations. The role of climate driving the quality of water can be understood by detailed and continuous monitoring of otolith specimens in the future. Future method allows reconstruction of climate and water quality from old specimens from field exposures or museum collection.

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We report on the first dielectric investigation of high-k yttrium copper titanate thin films, which were demonstrated to be very promising for nanoelectronics applications. The dielectric constant of these films is found to vary from 100 down to 24 (at 100 kHz) as a function of deposition conditions, namely oxygen pressure and film thickness. The physical origin of such variation was investigated in the framework of universal dielectric response and Cole-Cole relations and by means of voltage dependence studies of the dielectric constant. Surface-related effects and charge hopping polarization processes, strictly dependent on the film microstructure, are suggested to be mainly responsible for the observed dielectric response. In particular, the bulky behaviour of thick films deposited at lower oxygen pressure evolves towards a more complex and electrically heterogeneous structure when either the thickness decreases down to 50 nm or the films are grown under high oxygen pressure.

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We report on the first dielectric investigation of high-k yttrium copper titanate thin films, which were demonstrated to be very promising for nanoelectronics applications. The dielectric constant of these films is found to vary from 100 down to 24 (at 100 kHz) as a function of deposition conditions, namely oxygen pressure and film thickness. The physical origin of such variation was investigated in the framework of universal dielectric response and Cole-Cole relations and by means of voltage dependence studies of the dielectric constant. Surface-related effects and charge hopping polarization processes, strictly dependent on the film microstructure, are suggested to be mainly responsible for the observed dielectric response. In particular, the bulky behaviour of thick films deposited at lower oxygen pressure evolves towards a more complex and electrically heterogeneous structure when either the thickness decreases down to 50 nm or the films are grown under high oxygen pressure.

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We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

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In this letter, we submit our comment on the following recently published papers by Kalidas Das: (1) ``Influence of chemical reaction and viscous dissipation on MHD mixed convection flow,'' Journal of Mechanical Science and Technology 28 (5) (2014) 1881-1885; and (2) ``Cu-water nanofluid flow and heat transfer over a shrinking sheet,'' Journal of Mechanical Science and Technology 28 (12) (2014) 5089-5094. The authors attempt to present the similarity solutions in both papers. We comment that the similarity transformations considered in Refs. 1, 2] are incorrect. Thus, the results presented by Kalidas Das lead to invalid conclusions.