Physicochemical studies on the gelation of hen's egg yolk: Delipidation of yolk plasma by treatment with phospholipase-C and extraction with solvents

A method for the delipidation of egg yolk plasma using phospholipase-C, n-heptane, and 1-butanol has been described. An aggregating protein fraction and a soluble protein fraction were separated by the action of phospholipase-C. The aggregating protein fraction freed of most of the lipids by treatment with n-heptane and 1-butanol was shown to be the apolipoproteins of yolk plasma, whereas the soluble proteins were identified as the livetins. Carbohydrate and the N-terminal amino acid analysis of these protein fractions are reported. A comparison of these protein fractions with the corresponding fractions obtained by formic acid delipidation of yolk plasma has been made. The gelation of yolk plasma by the action of phospholipase-C has been interpreted as an aggregation of lipoproteins caused by ionic interactions. The role of lecithin in maintaining the structural integrity of lipoproteins has been discussed.

Text localization and extraction from complex gray images

We propose two texture-based approaches, one involving Gabor filters and the other employing log-polar wavelets, for separating text from non-text elements in a document image. Both the proposed algorithms compute local energy at some information-rich points, which are marked by Harris' corner detector. The advantage of this approach is that the algorithm calculates the local energy at selected points and not throughout the image, thus saving a lot of computational time. The algorithm has been tested on a large set of scanned text pages and the results have been seen to be better than the results from the existing algorithms. Among the proposed schemes, the Gabor filter based scheme marginally outperforms the wavelet based scheme.

3D shape extraction of human face in presence of facial hair: A profilometric approach

The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

Reversible cation/anion extraction from K2La2Ti3O10: Formation of new layered titanates, KLa2Ti3O9.5 and La2Ti3O9

A new soft-chemical transformation of layered perovskite oxides is described wherein K2O is sequentially extracted from the Ruddlesden-Popper (R-P) phase, K2La2Ti3O10 (I), yielding novel anion-deficient KLa2Ti3O9.5 (II) and La2Ti3O9 (III). The transformation occurs in topochemical reactions of the R-P phase I with PPh4Br and PBu4Br (Ph = phenyl; Bu = n-butyl). The mechanism involves the elimination of KBr accompanied by decomposition of PR4+ (R = phenyl or n-butyl) that extracts oxygen from the titanate. Analysis of the organic products of decomposition reveals formation of Ph3PO, Ph3P, and Ph-Ph for R = phenyl, and Bu3PO, Bu3P along with butane, butene, and octane for R = butyl. The inorganic oxides II and III crystallize in tetragonal structures (II: P4/mmm, a = 3.8335(1) angstrom, c = 14.334(1) angstrom; III: /4/ mmm, a = 3.8565(2) angstrom, c = 24.645(2) angstrom) that are related to the parent R-P phase. II is isotypic with the Dion-Jacobson phase, RbSr2Nb3O10, while III is a unique layered oxide consisting of charge-neutral La2Ti3O9 anion-deficient perovskite sheets stacked one over the other without interlayer cations. Interestingly, both II and III convert back to the parent R-P phase in a reaction with KNO3. While transformations of the R-P phases to other related layered/three-dimensional perovskite oxides in ion-exchange/metathesis/dehydration/reduction reactions are known, the simultaneous and reversible extraction of both cations and anions in the conversions K2La2Ti3O10 reversible arrow KLa2Ti3O9.5 reversible arrow La2Ti3O9 is reported here for the first time.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Enantiodiscrimination and extraction of short and long range homo- and hetero-nuclear residual dipolar couplings by a spin selective correlation experiment

A two dimensional correlation experiment for the measurement of short and long range homo- and hetero- nuclear residual dipolar couplings (RDCs) from the broad and featureless proton NMR spectra including C-13 satellites is proposed. The method employs a single natural abundant C-13 spin as a spy nucleus to probe all the coupled protons and permits the determination of RDCs of negligible strengths. The technique has been demonstrated for the study of organic chiral molecules aligned in chiral liquid crystal, where additional challenge is to unravel the overlapped spectrum of enantiomers. The significant advantage of the method is demonstrated in better chiral discrimination using homonuclear RDCs as additional parameters. (C) 2010 Elsevier B.V. All rights reserved.

Formant extraction from linear-prediction phase spectra

Extraction of formant information from linear-prediction phase spectra is proposed. It is shown that the derivative of phase spectrum gives reliable formant information. Since the phase spectra for several resonators in cascade are additive, the resonance peaks are additive in the derivative of the phase spectrum unlike in the magnitude spectrum and hence the problem of identifying merged peaks is very easily solved by this method. Application of the method is illustrated through examples of linear-prediction spectra obtained for simulated models and for actural speech segments.

Power extraction studies in a gasdynamic laser

A generalized two‐dimensional flow‐radiation coupled model to extract power from a gasdynamic laser is proposed. The model is used for the study of power extraction from a 9.4‐μm CO2 downstream‐mixing gasdynamic laser, where a cold CO2+H2 stream is mixed with a vibrationally excited N2 stream at the nozzle exits. This model is developed by coupling radiation with the two‐dimensional, unsteady, laminar and viscous flow modeling needed for such systems. The analysis showed that the steady‐state value of 9.4‐μm intensity as high as 5×107 W/m2 can be obtained from the system studied. The role of H2 relaxant in the power extraction process has also been investigated.

Epoch extraction from linear prediction residual for identification of closed glottis interval

In voiced speech analysis epochal information is useful in accurate estimation of pitch periods and the frequency response of the vocal tract system. Ideally, linear prediction (LP) residual should give impulses at epochs. However, there are often ambiguities in the direct use of LP residual since samples of either polarity occur around epochs. Further, since the digital inverse filter does not compensate the phase response of the vocal tract system exactly, there is an uncertainty in the estimated epoch position. In this paper we present an interpretation of LP residual by considering the effect of the following factors: 1) the shape of glottal pulses, 2) inaccurate estimation of formants and bandwidths, 3) phase angles of formants at the instants of excitation, and 4) zeros in the vocal tract system. A method for the unambiguous identification of epochs from LP residual is then presented. The accuracy of the method is tested by comparing the results with the epochs obtained from the estimated glottal pulse shapes for several vowel segments. The method is used to identify the closed glottis interval for the estimation of the true frequency response of the vocal tract system.

Relation-Aware Isosurface Extraction in Multifield Data

We introduce a variation density function that profiles the relationship between multiple scalar fields over isosurfaces of a given scalar field. This profile serves as a valuable tool for multifield data exploration because it provides the user with cues to identify interesting isovalues of scalar fields. Existing isosurface-based techniques for scalar data exploration like Reeb graphs, contour spectra, isosurface statistics, etc., study a scalar field in isolation. We argue that the identification of interesting isovalues in a multifield data set should necessarily be based on the interaction between the different fields. We demonstrate the effectiveness of our approach by applying it to explore data from a wide variety of applications.

Growth and extraction of flux free YBCO crystals

An improved flux draining technique for the extraction of grown YBCO crystals from its solvent is reported. This simple and efficient technique facilitates in-situ flux separation in the isothermal region of the furnace. Consequently, the crystals are spared from thermal shock and subsequent damage. Flux-free surfaces of these crystals were studied by optical microscopy. Transmission X-ray topographs of the crystals reveal the dislocations present in them as well as the stresses developed as a result of ferroelastic phase transition occurring during cooling.

Mining Land Cover Information Using Multilayer Perceptron and Decision Tree from MODIS Data

Land cover (LC) changes play a major role in global as well as at regional scale patterns of the climate and biogeochemistry of the Earth system. LC information presents critical insights in understanding of Earth surface phenomena, particularly useful when obtained synoptically from remote sensing data. However, for developing countries and those with large geographical extent, regular LC mapping is prohibitive with data from commercial sensors (high cost factor) of limited spatial coverage (low temporal resolution and band swath). In this context, free MODIS data with good spectro-temporal resolution meet the purpose. LC mapping from these data has continuously evolved with advances in classification algorithms. This paper presents a comparative study of two robust data mining techniques, the multilayer perceptron (MLP) and decision tree (DT) on different products of MODIS data corresponding to Kolar district, Karnataka, India. The MODIS classified images when compared at three different spatial scales (at district level, taluk level and pixel level) shows that MLP based classification on minimum noise fraction components on MODIS 36 bands provide the most accurate LC mapping with 86% accuracy, while DT on MODIS 36 bands principal components leads to less accurate classification (69%).

Optimal feature extraction for bilingual OCR

Feature extraction in bilingual OCR is handicapped by the increase in the number of classes or characters to be handled. This is evident in the case of Indian languages whose alphabet set is large. It is expected that the complexity of the feature extraction process increases with the number of classes. Though the determination of the best set of features that could be used cannot be ascertained through any quantitative measures, the characteristics of the scripts can help decide on the feature extraction procedure. This paper describes a hierarchical feature extraction scheme for recognition of printed bilingual (Tamil and Roman) text. The scheme divides the combined alphabet set of both the scripts into subsets by the extraction of certain spatial and structural features. Three features viz geometric moments, DCT based features and Wavelet transform based features are extracted from the grouped symbols and a linear transformation is performed on them for the purpose of efficient representation in the feature space. The transformation is obtained by the maximization of certain criterion functions. Three techniques : Principal component analysis, maximization of Fisher's ratio and maximization of divergence measure have been employed to estimate the transformation matrix. It has been observed that the proposed hierarchical scheme allows for easier handling of the alphabets and there is an appreciable rise in the recognition accuracy as a result of the transformations.

Tree structure for efficient data mining using rough sets

In data mining, an important goal is to generate an abstraction of the data. Such an abstraction helps in reducing the space and search time requirements of the overall decision making process. Further, it is important that the abstraction is generated from the data with a small number of disk scans. We propose a novel data structure, pattern count tree (PC-tree), that can be built by scanning the database only once. PC-tree is a minimal size complete representation of the data and it can be used to represent dynamic databases with the help of knowledge that is either static or changing. We show that further compactness can be achieved by constructing the PC-tree on segmented patterns. We exploit the flexibility offered by rough sets to realize a rough PC-tree and use it for efficient and effective rough classification. To be consistent with the sizes of the branches of the PC-tree, we use upper and lower approximations of feature sets in a manner different from the conventional rough set theory. We conducted experiments using the proposed classification scheme on a large-scale hand-written digit data set. We use the experimental results to establish the efficacy of the proposed approach. (C) 2002 Elsevier Science B.V. All rights reserved.