Entropy Constrained Exemplar-based Image Inpainting

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

Luffa acutangula agglutinin: Primary structure determination and identification of a tryptophan residue involved in its carbohydrate-binding activity using mass spectrometry

A lectin from phloem exudates of Luffa acutangula (ridge gourd) was purified on chitin affinity chromatography and characterized for its amino acid sequence and to study the role of tryptophan in its activity. The purified lectin was subjected to various proteolytic digestions, and the resulting peptides were analyzed by liquid chromatography coupled electrospray ionization ion trap mass spectrometer. The peptide precursor ions were fragmented by collision-induced dissociation or electron transfer dissociation experiments, and a manual interpretation of MS/MS was performed to deduce amino acid sequence. This gave rise to almost complete sequence coverage of the lectin which showed high-sequence similarity with deduced sequences of phloem lectins present in the database. Chemical modification of lysine, tyrosine, histidine, arginine, aspartic acid, and glutamic acid residues did not inhibit the hemagglutinating activity. However, the modification of tryptophan residues using N-bromosuccinimide showed the loss of hemagglutinating activity. Additionally, the mapping of tryptophan residues was performed to determine the extent and number of residues modified, which revealed that six residues per molecule were oxidized suggesting their accessibility. The retention of the lectin activity was seen when the modifications were performed in the presence of chitooligosaccharides due to protection of a tryptophan residue (W-102) in the protein. These studies taken together have led to the identification of a particular tryptophan residue (W-102) in the activity of the lectin. (c) 2015 IUBMB Life, 67(12):943-953, 2015

Comparison of Convective and Radiative Heating Modes on the Thermophysical Changes of a Cerium Nitrate Droplet

In this paper, we try to establish the equivalence or similarity in the thermal and physiochemical changes in precursor droplets (cerium nitrate) in convective and radiative fields. The radiative field is created through careful heating of the droplet using a monochromatic light source (CO2 laser). The equivalence is also established for different modes of convection like droplet injected into a high-speed flow and droplet experiencing a convective flow due to acoustic streaming (levitated) only. The thermophysical changes are studied in an aqueous cerium nitrate droplet, and the dissociation of cerium nitrate to ceria is modeled using modified Kramers' reaction rate formulation. It is observed that vaporization, species accumulation, and chemical characteristics obtained in a convectively heated droplet are retained in a radiatively heated droplet by careful adjustment of the laser intensity. The timescales and ceria yield match reasonably well for both the cases. It is also noted that similar conclusions are drawn in both levitated droplet and a nonlevitated droplet.

Fuzzy Approach to Rank Global Climate Models

Eleven coupled model intercomparison project 3 based global climate models are evaluated for the case study of Upper Malaprabha catchment, India for precipitation rate. Correlation coefficient, normalised root mean square deviation, and skill score are considered as performance indicators for evaluation in fuzzy environment and assumed to have equal impact on the global climate models. Fuzzy technique for order preference by similarity to an ideal solution is used to rank global climate models. Top three positions are occupied by MIROC3, GFDL2.1 and GISS with relative closeness of 0.7867, 0.7070, and 0.7068. IPSL-CM4, NCAR-PCMI occupied the tenth and eleventh positions with relative closeness of 0.4959 and 0.4562.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

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.

Comments on ``Influence of chemical reaction and viscous dissipation on MHD mixed convection flow'' by K. Das JMST 28 (5) (2014) 1881 similar to 1885] and ``Cu-water nanofluid flow and heat transfer over a shrinking sheet'' by K. Das JMST 28 (12) 5089 similar to 5094]

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.

Structural analysis of dihydrofolate reductases enables rationalization of antifolate binding affinities and suggests repurposing possibilities

Antifolates are competitive inhibitors of dihydrofolate reductase ( DHFR), a conserved enzyme that is central to metabolism and widely targeted in pathogenic diseases, cancer and autoimmune disorders. Although most clinically used antifolates are known to be target specific, some display a fair degree of cross-reactivity with DHFRs from other species. A method that enables identification of determinants of affinity and specificity in target DHFRs from different species and provides guidelines for the design of antifolates is currently lacking. To address this, we first captured the potential druggable space of a DHFR in a substructure called the `supersite' and classified supersites of DHFRs from 56 species into 16 `site-types' based on pairwise structural similarity. Analysis of supersites across these site-types revealed that DHFRs exhibit varying extents of dissimilarity at structurally equivalent positions in and around the binding site. We were able to explain the pattern of affinities towards chemically diverse antifolates exhibited by DHFRs of different site-types based on these structural differences. We then generated an antifolate-DHFR network by mapping known high-affinity antifolates to their respective supersites and used this to identify antifolates that can be repurposed based on similarity between supersites or antifolates. Thus, we identified 177 human-specific and 458 pathogen-specific antifolates, a large number of which are supported by available experimental data. Thus, in the light of the clinical importance of DHFR, we present a novel approach to identifying differences in the druggable space of DHFRs that can be utilized for rational design of antifolates.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.