Thermodynamics of ideal gas in doubly special relativity

We study thermodynamics of an ideal gas in doubly special relativity. A new type of special functions (which we call ``incomplete modified Bessel functions'') emerge. We obtain a series solution for the partition function and derive thermodynamic quantities. We observe that doubly special relativity thermodynamics is nonperturbative in the special relativity and massless limits. A stiffer equation of state is found.

Analysis for the Reflected Waves Transmitted on to the Channel by Tall Grounded Objects Using a Special Case

During lightning strike to a tall grounded object (TGO), reflected current waves from TGO are transmitted on to the channel. With regard to these transmitted waves, there seems to be some uncertainties like: 1) will they get reflected at the main wavefront; and 2) if so, what would be their final status. This study makes an attempt to address these issues considering a special case of strike to a TGO involving equal channel core and TGO radii. A macroscopic physical model for the lightning return stroke is adopted for the intended work. Analysis showed that the waves transmitted on to the channel merges with the main wavefront without any sign of reflection. Investigation revealed that: 1) the nonlinear spatio-temporal resistance profile of the channel at the wavefront is mainly responsible for the same; and 2) the distributed source provides additional support. The earlier findings are not limited to the special case of TGO considered. In spite of considering equal TGO and channel core radii, salient features of the model predicted remote electromagnetic fields agree well with the measured data reported in literature.

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background: The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better. Results: Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions. Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family. Conclusions: CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.

Super Resolution Using a Single Image Dictionary

To perform super resolution of low resolution images, state-of-the-art methods are based on learning a pair of lowresolution and high-resolution dictionaries from multiple images. These trained dictionaries are used to replace patches in lowresolution image with appropriate matching patches from the high-resolution dictionary. In this paper we propose using a single common image as dictionary, in conjunction with approximate nearest neighbour fields (ANNF) to perform super resolution (SR). By using a common source image, we are able to bypass the learning phase and also able to reduce the dictionary from a collection of hundreds of images to a single image. By adapting recent developments in ANNF computation, to suit super-resolution, we are able to perform much faster and accurate SR than existing techniques. To establish this claim, we compare the proposed algorithm against various state-of-the-art algorithms, and show that we are able to achieve b etter and faster reconstruction without any training.

Efficient Dictionary for Salted Password Analysis

User authentication is essential for accessing computing resources, network resources, email accounts, online portals etc. To authenticate a user, system stores user credentials (user id and password pair) in system. It has been an interested field problem to discover user password from a system and similarly protecting them against any such possible attack. In this work we show that passwords are still vulnerable to hash chain based and efficient dictionary attacks. Human generated passwords use some identifiable patterns. We have analysed a sample of 19 million passwords, of different lengths, available online and studied the distribution of the symbols in the password strings. We show that the distribution of symbols in user passwords is affected by the native language of the user. From symbol distributions we can build smart and efficient dictionaries, which are smaller in size and their coverage of plausible passwords from Key-space is large. These smart dictionaries make dictionary based attacks practical.

Synthesis, X-ray structure and in vitro cytotoxicity studies of Cu(I/II) complexes of thiosemicarbazone: special emphasis on their interactions with DNA

4-(p-X-phenyl)thiosemicarbazone of napthaldehyde {where X = Cl (HL1) and X = Br (HL2)}, thiosemicarbazone of quinoline-2-carbaldehyde (HL3) and 4-(p-fluorophenyl) thiosemicarbazone of salicylaldehyde (H2L4) and their copper(I) {Cu(HL1)(PPh3)(2)Br]center dot CH3CN (1) and Cu(HL2)(PPh3)(2)Cl]center dot DMSO (2)} and copper(II) {((Cu2L2Cl)-Cl-3)(2)(mu-Cl)(2)]center dot 2H(2)O (3) and Cu(L-4)(Py)] (4)} complexes are reported herein. The synthesized ligands and their copper complexes were successfully characterized by elemental analysis, cyclic voltammetry, NMR, ESI-MS, IR and UV-Vis spectroscopy. Molecular structures of all the Cu(I) and Cu(II) complexes have been determined by X-ray crystallography. All the complexes (1-4) were tested for their ability to exhibit DNA-binding and - cleavage activity. The complexes effectively interact with CT-DNA possibly by groove binding mode, with binding constants ranging from 10(4) to 10(5) M-1. Among the complexes, 3 shows the highest chemical (60%) as well as photo-induced (80%) DNA cleavage activity against pUC19 DNA. Finally, the in vitro antiproliferative activity of all the complexes was assayed against the HeLa cell line. Some of the complexes have proved to be as active as the clinical referred drugs, and the greater potency of 3 may be correlated with its aqueous solubility and the presence of the quinonoidal group in the thiosemicarbazone ligand coordinated to the metal.