28 research outputs found

    Synthesis, structural and morphological property of BaSnO3 nanopowder prepared by solid state ceramic method.

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    BaSnO3 is a cubic perovskite-type oxide that behaves as an n-type semiconductor with a wide band gap of 3.4 eV and remains stable at temperatures up to 1000{deg}C. It has wide applications such as thermally stable capacitors, humidity sensors, gas sensors, etc. Barium stannate has also been used in optical applications, in capacitors and ceramic boundary layers, and as a promising material to produce gas phase sensors for the detection of carbon monoxide and carbon dioxide. BaSnO3 powder was prepared by solid state ceramic method. X-ray diffraction pattern of the prepared sample presents all the characteristic peaks of cubic phase of BaSnO3 (JCPDScard no: 15 -0780). The lattice constant for the compound was calculated and found to be 4.101A0 which is in agreement with the reported value (4.112A0). The average size of the crystallites estimated by Debye Scherrer's formula was found to be 49 nm shows the nanostructured nature. The Raman bands observed ~ 139, 833 and 1122 cm-1 can be assigned on the basis of the fundamental vibrations of SnO6 octahedron which has Oh symmetry, in the distorted perovskite structure. The SEM image shows a porous surface morphology with grains of cuboidal structure with well-defined grain boundaries. UV-Visible spectra shows BaSnO3powder exhibit high reflectance in the 400-700 nm range

    Vegetation type is an important predictor of the arctic summer land surface energy budget

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    Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

    Vegetation type is an important predictor of the arctic summer land surface energy budget

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    Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

    India’s Trade in Drugs and Pharmaceuticals: Emerging Trends, Opportunities and Challenges

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    It was argued in the context economic reforms in pharmaceuticals sector, particularly in the context of changing patent regime, that growth in exports would be restricted, imports would get a fillip and balance of trade would be adversely affected. The paper looks into the recent experience in exports and imports of drugs and pharmaceutical products. It is found that there is a tremendous growth in the exports. The focus of exports has shifted from intermediates and bulk drugs to formulations. The expiry of patents on drugs worth billions of dollars in the near future, would provide a big opportunity for Indian generic producers. However, the expansion of formulation exports is increasingly facing challenges from various corners-increasing application of non tariff barriers by importing countries, authorised Indian generics being targeted by global anti-counterfeit drive and competition from China. Import of formulations did not increase as has been anticipated. Paper also finds that there is a negative and growing trade balance, owing to the import of intermediates and bulk drugs. The industry is now increasingly adopting the strategy of importing intermediates and bulk drugs and processing them into formulations. The removal of ratio parameter linking the production of intermediates and bulk drugs to the production of formulations has eliminated compulsions on the indigenous production of intermediates and bulk drugs.pharmaceutical sector, trade, India, intelluctual property, generic

    Studies on in-situ deposition of lead zirconate titanate (PZT) by electrolytic and electrophoretic methods

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    Level Identification of Brain MR Images using Histogram of a LBP variant

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    Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper, we compare Histogram based Features of LBP (HF/LBP), against Histogram based Features of MOD-LBP (HF/MOD-LBP) in retrieving similar axial brain images. We show that replacing local histogram with a local distance transform based similarity metric further improves the performance of MOD-LBP based image retrievalCochin University of Science and Technology2012 IEEE International Conference on Computational Intelligence and Computing Researc

    Content Based Image Retrieval of Brain MR Images across Different Classes

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    Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users’ feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrievedCochin University of Science and TechnologyInternational Journal of Electrical, Robotics, Electronics and Communications Engineering Vol:7 No:8, 201
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