Growth and characterization of single crystal cored fibers of organic nonlinear optical materials

The recent development of several organic materials with large nonlinear susceptibilities, high damage threshold and low melting points encouraged researchers to employ these materials in fiber form to efficiently couple diode laser pumps and obtain enhanced second harmonic generation (SHG). In this paper we report the growth of single crystal cored fibers of 4-nitro-4'-methylbenzylidene aniline, ethoxy methoxy chalcone and (-)2-((alpha) -methylbenzylamino)-5- nitropyridine by inverted Bridgman-Stockbarger technique. The fibers were grown in glass capillaries with varying internal diameters and lengths and were characterized using x-ray and polarizing microscope techniques. The propagation loss at 632.8 nm and 1300 nm were measured and SHG was studied using 1064 nm pump.

Crystal and molecular structure of Boc-Phe-Val-OMe; comparison of the peptide conformation with its dehydro analogue

The crystal structure of the peptide Boc-Phe-Val-OMe determined by X-ray diffraction methods is reported in this paper. The crystals grown from aqueous methanol are orthorhombic, space group P2(1)2(1)2(1), a = 11.843(2), b = 21.493(4), c = 26.676(4)Angstrom and V = 6790 Angstrom(3). Data were collected on a CAD4 diffractometer using MoK2 radiation (lambda = 0.7107 Angstrom) up to Bragg angle theta = 26 degrees. The structure was solved by direct methods and refined by a least-squares procedure to an R value of 6.8% for 3288 observed reflections. There are three crystallographically independent peptide molecules in the asymmetric unit. All the three molecules exhibit extended conformation. The sidechain of the Val(2) residue shows two different conformations. The conformation of the peptide Boc-Phe-Val-OMe is compared with the conformation of Ac-Delta Phe-Val-OH. It is observed that while Boc-Phe-Val-OMe exhibits an extended conformation, Ac-Delta Phe-Val-OH shows a folded conformation. The results of this comparison highlight the conformation constraining property of the Delta Phe residue. Interestingly, even though Boc-Phe-Val-OMe and Ac-Delta Phe-Val-OH are conformationally different, they exhibit similar packing patterns in the solid state. (C) Munksgaard 1995.

Primary structure of a cytotoxin-like basic protein from Naja naja naja (Indian Cobra) venom

The complete amino acid sequence of a cytotoxin-like basic protein (CLBP) from the venom of Naja naja naja (Indian Cobra) was determined by manual degradation using a 4-dimethylaminoazobenzene-4'-isothiocyanate double-coupling method. Peptide fragments obtained by chemical cleavage with cyanogen bromide and enzymic cleavages with trypsin and Staphylococcus aureus proteases for sequence analysis were purified by reversed-phase chromatography. The total number of amino acid residues was 61, with leucine as the C-terminal residue. (C) Munksgaard 1995.

Resonant microwave power absorption in slabs

Resonant microwave power absorption is examined for slabs exposed to TEM waves from both faces and for a slab placed on a reflecting support. Using the electric field distribution in the slab, the average power is obtained by integrating the spatially distributed power across the sample length. Due to constructive interference of the standing waves within the sample, the average power rises to a local maximum during a resonance. Irrespective of the material, resonances occur at integral values of L/lambda(s) when the slab is exposed to radiation from both faces and at L/lambda(s) = 0.5n-0.25 when placed on a reflecting support.

Artifact-free reconstruction from off-axis digital holograms through nonlinear filtering

We present experimental investigation of a new reconstruction method for off-axis digital holographic microscopy (DHM). This method effectively suppresses the object auto-correlation, commonly called the zero-order term, from holographic measurements, thereby suppressing the artifacts generated by the intensities of the two beams employed for interference from complex wavefield reconstruction. The algorithm is based on non-linear filtering, and can be applied to standard DHM setups, with realistic recording conditions. We study the applicability of the technique under different experimental configurations, such as topographic images of microscopic specimens or speckle holograms.

Robust Formulations for Handling Uncertainty in Kernel Matrices

We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it reduces to a convex program. The problem of uncertainty in kernel matrix is motivated from the real world problem of classifying proteins when the structures are provided with some uncertainty. The formulation derived here naturally incorporates such uncertainty in a principled manner leading to significant improvements over the state of the art. 1.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

Two Dimensional Principal Component Analysis for Online Tamil Character Recognition

This paper presents a new application of two dimensional Principal Component Analysis (2DPCA) to the problem of online character recognition in Tamil Script. A novel set of features employing polynomial fits and quartiles in combination with conventional features are derived for each sample point of the Tamil character obtained after smoothing and resampling. These are stacked to form a matrix, using which a covariance matrix is constructed. A subset of the eigenvectors of the covariance matrix is employed to get the features in the reduced sub space. Each character is modeled as a separate subspace and a modified form of the Mahalanobis distance is derived to classify a given test character. Results indicate that the recognition accuracy using the 2DPCA scheme shows an approximate 3% improvement over the conventional PCA technique.

GMM basedbayesian approach to speech enhancement in signal/transform domain

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator.The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

Analysis of Serpentine folded-waveguide slow-wave structures by elliptical conformal transformation

Analysis of the serpentine folded-waveguide slow-wave structure was carried out using elliptical conformal transformation, for the dispersion and interaction impedance characteristics of the structure. The results obtained from the present analysis were compared with those from 3D electromagnetic simulation using MAFIA.