Triarylborane conjugated dicyanovinyl chromophores: intriguing optical properties and colorimetric anion discrimination

Three new triarylborane conjugated dicyanovinyl chromophores (Mes(2)B-pi-donor-DCV); donor: N-methyldiphenylamine (1) and triphenylamine (2 and 3 with two BMes(2) substitutions]) of type A-D-A (acceptor-donor- acceptor) are reported. Compounds 1-3 exhibit intense charge transfer (CT) absorption bands in the visible region. These absorption peaks are combination CT bands of the amine donor to both the BMes(2) and DCV units. This inference was supported by theoretical studies. Compound 1 shows weak fluorescence compared to 2 and 3. The discrimination of fluoride and cyanide ions is essential in the case of triarylborane (TAB) based anion sensors as a similar response is given towards both the anions. Anion binding studies of 1, 2 and 3 showed that fluoride ions bind selectively to the boron centre and block the corresponding CT transition (donor to BMes(2)) leaving the other CT transition to be red shifted. On the other hand, cyanide ions bind with both the receptor sites and stop both the CT transition processes and hence a different colorimetric response was noted. The binding of F-/CN- induces colour changes in the visible region of the electronic spectra of 2 and 3, which allows for the naked-eye detection of F- and CN- ions. The anion binding mechanisms are established using NMR titration experiments.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.

Mechano-fluorochromic Pt-II Luminogen and Its Cysteine Recognition

A new triphenylamine-based organometallic Pt-II luminogen (1) and its analogous organic compound (2) are reported. The molecules are decorated with aldehyde functionality to improve their photophysical properties by utilising donor-acceptor interactions. The single crystal X-ray structure analysis of PtII analogue 1 revealed that the neighbouring molecules were loosely organised by weak intermolecular C-H center dot center dot center dot pi interactions. Because of the twisted nature of the triphenylamine backbone the compounds showed aggregation-induced emission enhancement in THF/water mixture. Due to their loose crystal packing, upon application of external stimuli these luminogens exhibited mechano-fluorochromic behaviour. The crystalline forms of the compounds displayed a more superior emission efficiency than the grinded samples. Moreover, the compounds showed crystallization-induced emission enhancement (CIEE) and exhibited chemodosimetric response towards cysteine under physiological condition.

Hidden role of anion exchange reactions in nucleation of colloidal nanocrystals

We investigate the processes involved in the nucleation of colloidal lead selenide nanoparticles. Our studies show that an unusual pathway - an anion exchange reaction, causes the nucleation of lead selenide nanocrystals. In this process, one quantum dot is transformed into another due to a substitution of its constituent anions. The existence of this pathway was never anticipated perhaps due to its unusually rapid kinetics. The nucleation and growth kinetics of colloidal lead selenide quantum dots are found to fit well to a two-step process. The rate constant associated with the anion exchange process is found to be four orders of magnitude greater than that of the nanocrystal growth. The complete consumption of the initial oxide nanoparticle thus provides a sharp, temporally well-defined nucleation event.

New insight into the architecture of oxy-anion pocket in unliganded conformation of GAT domains: A MD-simulation study

Human Guanine Monophosphate Synthetase (hGMPS) converts XMP to GMP, and acts as a bifunctional enzyme with N-terminal ``glutaminase'' (GAT) and C-terminal ``synthetase'' domain. The enzyme is identified as a potential target for anticancer and immunosuppressive therapies. GAT domain of enzyme plays central role in metabolism, and contains conserved catalytic residues Cys104, His190, and Glu192. MD simulation studies on GAT domain suggest that position of oxyanion in unliganded conformation is occupied by one conserved water molecule (W1), which also stabilizes that pocket. This position is occupied by a negatively charged atom of the substrate or ligand in ligand bound crystal structures. In fact, MD simulation study of Ser75 to Val indicates that W1 conserved water molecule is stabilized by Ser75, while Thr152, and His190 also act as anchor residues to maintain appropriate architecture of oxyanion pocket through water mediated H-bond interactions. Possibly, four conserved water molecules stabilize oxyanion hole in unliganded state, but they vacate these positions when the enzyme (hGMPS)-substrate complex is formed. Thus this study not only reveals functionally important role of conserved water molecules in GAT domain, but also highlights essential role of other non-catalytic residues such as Ser75 and Thr152 in this enzymatic domain. The results from this computational study could be of interest to experimental community and provide a testable hypothesis for experimental validation. Conserved sites of water molecules near and at oxyanion hole highlight structural importance of water molecules and suggest a rethink of the conventional definition of chemical geometry of inhibitor binding site.

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.