Investigations on micro-blast wave assisted metal foil forming for biomedical applications

The deformation dynamics of metal foils (<0.25 mm thick) subjected to micro-blast wave are presented in this paper. The energy of micro-blast wave emanating from the open end of a polymer tube is used to deliver micro-particles for bio-medical applications. In these experiments metal foils are used to transfer the energy of the micro-blast wave to the micro-particles. Using cubic root scaling law the over pressure of the blast wave at the open end of the polymer tube is estimated and using this peak plate over pressure is estimated. The finite element analysis is used to estimate the velocity profile of the deforming metal foils. The finite element analysis results are compared with experimental results for the maximum deformation and deformed shape. Based on the deformation velocity, metal foil to be used for experiments is selected. Among the materials investigated 0.1 mm thick brass foil has the maximum velocity of 205 m/s and is used in the experiments. It is found from finite element analysis that the particles deposited within a radius of 0.5 mm will leave the foil with nearly equal velocity (error < 5%). The spray cone angle which is the angle of deviation of the path of particles from the axis of the polymer tube is also estimated and found to be less than 7 degrees up to a radius of 0.75 mm. Illustrative experiments are carried out to deliver micro particles (0.7 mu m diameter tungsten) into plant tissues. Particle penetration depth up to 460 mu m was achieved in ground tissue of potato tuber. (C) 2012 Elsevier Ltd. All rights reserved.

Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments

Facet-based sentiment analysis involves discovering the latent facets, sentiments and their associations. Traditional facet-based sentiment analysis algorithms typically perform the various tasks in sequence, and fail to take advantage of the mutual reinforcement of the tasks. Additionally,inferring sentiment levels typically requires domain knowledge or human intervention. In this paper, we propose aseries of probabilistic models that jointly discover latent facets and sentiment topics, and also order the sentiment topics with respect to a multi-point scale, in a language and domain independent manner. This is achieved by simultaneously capturing both short-range syntactic structure and long range semantic dependencies between the sentiment and facet words. The models further incorporate coherence in reviews, where reviewers dwell on one facet or sentiment level before moving on, for more accurate facet and sentiment discovery. For reviews which are supplemented with ratings, our models automatically order the latent sentiment topics, without requiring seed-words or domain-knowledge. To the best of our knowledge, our work is the first attempt to combine the notions of syntactic and semantic dependencies in the domain of review mining. Further, the concept of facet and sentiment coherence has not been explored earlier either. Extensive experimental results on real world review data show that the proposed models outperform various state of the art baselines for facet-based sentiment analysis.

Microwave Spectroscopic and Atoms in Molecules Theoretical Investigations on the ArPropargyl Alcohol Complex: ArHO, Ar, and ArC Interactions

The structure of the Arpropargyl alcohol (ArPA) complex is determined from the rotational spectra of the parent complex and its two deuterated isotopologues, namely ArPA-D(OD) and ArPA-D(CD). The spectra confirm a geometry in which PA exists in the gauche form with Ar located in between OH and CCH groups. All a, b and c types of transitions show small splitting due to some large-amplitude motion dominated by COH torsion, as in the monomer. Splittings in a- and b-type transitions are of the order of a few kilohertz, whereas splitting in the c-type transitions is relatively larger (0.92.6 MHz) and decreases in the order ArPA>ArPA-D(CD)>ArPA-D(OD). The assignments are well supported by ab initio calculations. Atoms in molecules (AIM) and electrostatic potential calculations are used to explore the nature of the interactions in this complex. AIM calculations not only reveal the expected OHAr and Ar interactions in the Argauche-PA complex, but also novel CAr (of CH2OH group) and OHAr interactions in the Artrans-PA complex. Similar interactions are also present in the Armethanol complex.

Comprehensive investigations on DNa center dot center dot center dot A (D = H/F) complexes show why `sodium bonding' is not commonly observed

A comprehensive study of D-Na center dot center dot center dot A (D = H/F) complexes has been done using advanced ab initio and atoms in molecule (AIM) theoretical analyses. The correlation between electron density at bond critical point and binding energy gives a distinguishing feature for hydrogen bonding, different from the `electrostatic complexes' formed by LiD and NaD. Moreover, the LiD/NaD dimers have both linear and anti-parallel minima, as expected for electrostatic dipole-dipole interactions. The HF dimer has a quasi-linear minimum and the anti-parallel structure is a saddle point. Clearly, characterizing hydrogen bonding as `nothing but electrostatic interaction between two dipoles' is grossly in error.

Investigations on high enthalpy shock wave exposed graphitic carbon nanoparticles

The impact of high enthalpy shock wave on graphitic carbon nanoparticle (GCNP) films has been investigated and discussed in view of space and chemical engineering applications. The GCNP films were developed by using spray method and exposed to high enthalpy shock wave under an inert atmosphere. Upon shock wave treatment, two typical amendments such as weight loss in the deposited material and growth of second order nanostructures (SONS) have been observed. While increasing test gas pressure, the loss of material and density of SONs are gradually increased. Most of the shock wave induced SONS are highly crystalline and belong to the cubic diamond structure. Upon shock treatment as well as with increase of test gas pressure, a considerable improvement in the quality of GCNP films has been observed. Further, ablation of GCNPs exclusively on the top surface of the coatings and formation of hierarchical NPs (diamond NPs on GCNPs) has been observed.

Combining indentation and diffusion couple techniques for combinatorial discovery of high temperature shape memory alloys

We demonstrate the possibility of accelerated identification of potential compositions for high-temperature shape memory alloys (SMAs) through a combinatorial material synthesis and analysis approach, wherein we employ the combination of diffusion couple and indentation techniques. The former was utilized to generate smooth and compositionally graded inter-diffusion zones (IDZs) in the Ni-Ti-Pd ternary alloy system of varying IDZ thickness, depending on the annealing time at high temperature. The IDZs thus produced were then impressed with an indenter with a spherical tip so as to inscribe a predetermined indentation strain. Subsequent annealing of the indented samples at various elevated temperatures, T-a, ranging between 150 and 550 degrees C allows for partial to full relaxation of the strain imposed due to the shape memory effect. If T-a is above the austenite finish temperature, A(f), the relaxation will be complete. By measuring the depth recovery, which serves as a proxy for the shape recovery characteristic of the SMA, a three-dimensional map in the recovery temperature composition space is constructed. A comparison of the published Af data for different compositions with the Ta data shows good agreement when the depth recovery is between 70% and 80%, indicating that the methodology proposed in this paper can be utilized for the identification of promising compositions. Advantages and further possibilities of this methodology are discussed.

Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

Investigations of Ramachandran disallowed conformations in protein domain families

In peptide and protein structures, occurrence of (phi,psi.) angles in the disallowed region of the Ramachandran map almost always suggests local regions of error or poor accuracy. However, very rarely genuine disallowed conformations occur as noted in the current study in proteins of known structure available at ultra-high resolution (<= 1.2 (A) over circle). In the current work, extent of conservation of genuine disallowed conformations in homologous proteins of known structures has been analyzed. From a dataset of 124 protein domain families, with structure of at least one constituent member in each family available at a resolution of 1.2 (A) over circle or better, we have analyzed the conservation of 221 disallowed conformations. It is observed that the disallowed conformation is only moderately conservedin protein domain families. In the gross dataset no particular residue type adopting disallowed conformation elicit high conservation of residue type though there are alignment positions in the dataset with complete conservation of both the residue type and the disallowed conformation. Conserved disallowed conformation in protein domain families play biologically significant role in roughly 50% of the cases. The residues with the disallowed conformation or its flanking residues are often located within or around the functional site of the protein. (C) 2013 Elsevier B.V. All rights reserved.

Charge and color breaking constraints in MSSM after the Higgs discovery at LHC

We revisit the constraints on the parameter space of the Minimal Supersymmetric Standard Model (MSSM), from charge and color breaking minima in the light of information on the Higgs from the LHC so far. We study the behavior of the scalar potential keeping two light sfermion fields along with the Higgs in the pMSSM framework and analyze the stability of the vacuum. We find that for lightest stops a parts per thousand(2) 1 TeV and small mu a parts per thousand(2) 500 GeV, the absolute stability of the potential can be attained only for . The bounds become stronger for larger values of the mu parameter. Note that this is approximately the value of Xt which maximizes the Higgs mass. Our bounds on the low scale MSSM parameters are more stringent than those reported earlier in literature. We reanalyze the stau sector as well, keeping both staus. We study the connections between the observed Higgs rates and vacuum (meta)stability. We show how a precision study of the ratio of signal strengths, (mu (gamma gamma) /mu (ZZ) ) can shed further light.

Structural Investigations on the Compositional Anomalies in Lanthanum Zirconate System Synthesized by Coprecipitation Method

The study set out to investigate the compositional inconsistency in lanthanum zirconate system revealed the presence of nonstoichiometry in lanthanum zirconate powders when synthesized by coprecipitation route. X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) investigations confirmed the depletion of La3+ ions in the system. Analysis using Vegard's law showed the La/Zr mole ratio in the sample to be around 0.45. An extra step of ultrasonication, introduced during the washing stage followed by the coprecipitation reaction, ensured the formation of stoichiometric La2Zr2O7. Noteworthy is also the difference between crystal sizes in the samples prepared by with and without ultrasonication step. This difference has been explained in light of the formation of individual nuclei and their scope of growth within the precipitate core. The differential scanning calorimetry (DSC) analyses revealed that optimum pH for the synthesis of La2Zr2O7 is about 11. The ultrasonication step was pivotal in assuring consistency in mixing and composition for the lanthanum zirconate powders.

ESD Investigations of Multiwalled Carbon Nanotubes

Electrostatic discharge (ESD) investigations on the multiwalled carbon nanotubes (MWCNTs) are performed for the first time. A novel ESD failure mechanism of subsequent shell burning has been discovered. By using nanosecond pulse measurements, a new insight into metal-to-carbon nanotube (CNT) contact behavior could be achieved. Clear signature of two very different conduction mechanisms and related failure types at high current injection has been found. By determining the time to failure, an Arrhenius-like relation was extracted, which was explained by the oxidation of CNT shells. Finally, an extraordinary ESD failure current density of MWCNT of 1.2 x 10(9) A/cm(2) could be shown.

Suramin is a potent and selective inhibitor of Mycobacterium tuberculosis RecA protein and the SOS response: RecA as a potential target for antibacterial drug discovery

In eubacteria, RecA is essential for recombinational DNA repair and for stalled replication forks to resume DNA synthesis. Recent work has implicated a role for RecA in the development of antibiotic resistance in pathogenic bacteria. Consequently, our goal is to identify and characterize small-molecule inhibitors that target RecA both in vitro and in vivo. We employed ATPase, DNA strand exchange and LexA cleavage assays to elucidate the inhibitory effects of suramin on Mycobacterium tuberculosis RecA. To gain insights into the mechanism of suramin action, we directly visualized the structure of RecA nucleoprotein filaments by atomic force microscopy. To determine the specificity of suramin action in vivo, we investigated its effect on the SOS response by pull-down and western blot assays as well as for its antibacterial activity. We show that suramin is a potent inhibitor of DNA strand exchange and ATPase activities of bacterial RecA proteins with IC50 values in the low micromolar range. Additional evidence shows that suramin inhibits RecA-catalysed proteolytic cleavage of the LexA repressor. The mechanism underlying such inhibitory actions of suramin involves its ability to disassemble RecA-single-stranded DNA filaments. Notably, suramin abolished ciprofloxacin-induced recA gene expression and the SOS response and augmented the bactericidal action of ciprofloxacin. Our findings suggest a strategy to chemically disrupt the vital processes controlled by RecA and hence the promise of small molecules for use against drug-susceptible as well as drug-resistant strains of M. tuberculosis for better infection control and the development of new therapies.

Drug Discovery Research in India: Current State and Future Prospects

Indian civilization developed a strong system of traditional medicine and was one of the first nations to develop a synthetic drug. In the postindependence era, Indian pharmaceutical industry developed a strong base for production of generic drugs. Challenges for the future are to give its traditional medicine a strong scientific base and develop research and clinical capability to consistently produce new drugs based on advances in modem biological sciences.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

In-cylinder investigations and analysis of a SI gas engine fuelled with H-2 and CO rich syngas fuel: Sensitivity analysis of combustion descriptors for engine diagnostics and control

The sensitivity of combustion phasing and combustion descriptors to ignition timing, load and mixture quality on fuelling a multi-cylinder natural gas engine with bio-derived H-2 and CO rich syngas is addressed. While the descriptors for conventional fuels are well established and are in use for closed loop engine control, presence of H-2 in syngas potentially alters the mixture properties and hence combustion phasing, necessitating the current study. The ability of the descriptors to predict abnormal combustion, hitherto missing in the literature, is also addressed. Results from experiments using multi-cylinder engines and numerical studies using zero dimensional Wiebe function based simulation models are reported. For syngas with 20% H-2 and CO and 2% CH4 (producer gas), an ignition retard of 5 +/- 1 degrees was required compared to natural gas ignition timing to achieve peak load of 72.8 kWe. It is found that, for syngas, whose flammability limits are 0.42-1.93, the optimal engine operation was at an equivalence ratio of 1.12. The same methodology is extended to a two cylinder engine towards addressing the influence of syngas composition, especially H-2 fraction (varying from 13% to 37%), on the combustion phasing. The study confirms the utility of pressure trace derived combustion descriptors, except for the pressure trace first derivative, in describing the MBT operating condition of the engine when fuelled with an alternative fuel. Both experiments and analysis suggest most of the combustion descriptors to be independent of the engine load and mixture quality. A near linear relationship with ignition angle is observed. The general trend(s) of the combustion descriptors for syngas fuelled operation are similar to those of conventional fuels; the differences in sensitivity of the descriptors for syngas fuelled engine operation requires re-calibration of control logic for MBT conditions. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.