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A novel route has been developed to synthesize sub-micron Zinc Selenide semiconductor particles through elemental solvothermal process. Transparent polyvinyl alcohol matrix was chosen as host material for embedding these ZnSe particles in order to stop agglomeration of the particles as well as to facilitate optical characterization. Structural and morphological characterizations were carried out through high resolution electron microscopy and UV-vis spectroscopy. In order to understand light scattering phenomena of these particles, they were investigated by a custom made set up which uses a He-Ne laser of wavelength 632.8nm and an array of Silicon photodetectors. An attempt was made to experimentally determine the most significant element of the Mueller scattering matrix. Novel computational technique, involving single scattering for spherical particles using T-matrix theory was applied. The analysis of the experimental data was done by the method of comparison with theoretically generated data. The theoretical prediction was found to agree well qualitatively with the experimental data. Our results validitate that within an acceptable margin of error of the experimental results, the combination of experimental setup and associated computational method is an efficient and reliable in-situ system for size quantification of sub-micron semiconductor particles in the laboratory.

Wide-scale information embedding is a prerequisite to enhance the performance as well as the reliability of decision-making algorithms for viable implementation. Feature fusion technology significantly helps to incorporate such information to provide promising algorithm performance. In this Letter, a fusion-based model with the aid of discriminant correlation analysis to classify electroencephalogram signals is proposed. Sets of multiple feature matrices are generated from signals in both time and wavelet domains for study-specific classes, which are further decomposed to derive a set of sub-multi-view features followed by optimisation to extract statistical features. Features are concatenated using feature fusion technique to derive low order discriminant features. Besides, the analysis of variance was also performed to validate the analysis. The statistically significant features are evaluated for the effective model performance. Experimental results manifest that the proposed feature fusion based algorithm is superior to many state-of-the-art methods and thus promote real-time implementation.

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A 64-year male came for treatment of a lesion on his eyelid. Approximately 10 years earlier, he had developed a small blackish mass on his right lower eyelid, which was gradually increasing in size along the infra-orbital crease. It is associated with blackish discharge. Laboratory tests were normal; medical history and family history were unremarkable. Incisional biopsy shows strings of stratified squamous epithelium, proliferative basal cells, and scattered melanin pigmentation. The tumor was completely excised, and the defect is reconstructed with modified island pedicle advancement cheek flap and sent for HPE examination. It is a powerful technique for reconstruction with minimal complication.