Generalized survival in step fluctuations

The properties of the generalized survival probability, that is, the probability of not crossing an arbitrary location R during relaxation, have been investigated experimentally (via scanning tunneling microscope observations) and numerically. The results confirm that the generalized survival probability decays exponentially with a time constant tau(s)(R). The distance dependence of the time constant is shown to be tau(s)(R)=tau(s0)exp[-R/w(T)], where w(2)(T) is the material-dependent mean-squared width of the step fluctuations. The result reveals the dependence on the physical parameters of the system inherent in the prior prediction of the time constant scaling with R/L-alpha, with L the system size and alpha the roughness exponent. The survival behavior is also analyzed using a contrasting concept, the generalized inside survival S-in(t,R), which involves fluctuations to an arbitrary location R further from the average. Numerical simulations of the inside survival probability also show an exponential time dependence, and the extracted time constant empirically shows (R/w)(lambda) behavior, with lambda varying over 0.6 to 0.8 as the sampling conditions are changed. The experimental data show similar behavior, and can be well fit with lambda=1.0 for T=300 K, and 0.5

Intent Based Clustering of Search Engine Query Log

The keyword based search technique suffers from the problem of synonymic and polysemic queries. Current approaches address only theproblem of synonymic queries in which different queries might have the same information requirement. But the problem of polysemic queries,i.e., same query having different intentions, still remains unaddressed. In this paper, we propose the notion of intent clusters, the members of which will have the same intention. We develop a clustering algorithm that uses the user session information in query logs in addition to query URL entries to identify cluster of queries having the same intention. The proposed approach has been studied through case examples from the actual log data from AOL, and the clustering algorithm is shown to be successful in discerning the user intentions.

Discovering user preferences by using time entries in click-through data to improve search engine results

The search engine log files have been used to gather direct user feedback on the relevancy of the documents presented in the results page. Typically the relative position of the clicks gathered from the log files is used a proxy for the direct user feedback. In this paper we identify reasons for the incompleteness of the relative position of clicks for deciphering the user preferences. Hence, we propose the use of time spent by the user in reading through the document as indicative of user preference for a document with respect to a query. Also, we identify the issues involved in using the time measure and propose means to address them.

Locant: A nature inspired location service for ad hoc networks

An efficient location service is a prerequisite to any robust, effective and precise location information aided Mobile Ad Hoc Network (MANET) routing protocol. Locant, presented in this paper is a nature inspired location service which derives inspiration from the insect colony framework, and it is designed to work with a host of location information aided MANET routing protocols. Using an extensive set of simulation experiments, we have compared the performance of Locant with RLS, SLS and DLS, and found that it has comparable or better performance compared to the above three location services on most metrics and has the least overhead in terms of number of bytes transmitted per location query answered.

Temperature- and pressure-dependent study of Cl-35 NQR frequency and spin lattice relaxation time in 2,3-dichloroanisole

The temperature and pressure dependence of Cl-35 NQR frequency and spin lattice relaxation time (T-1) were investigated in 2,3-dichloroanisole. Two NQR signals were observed throughout the temperature and pressure range studied. T-1 were measured in the temperature range from 77 to 300 K and from atmospheric pressure to 5 kbar. Relaxation was found to be due to the torsional motion of the molecule and also reorientation f motion of the CH3 group. T-1 versus temperature data were analyzed on the basis of Woessner and Gutowsky model, and the activation energy for the reorientation of the CH3 group was estimated. The temperature dependence of the average torsional lifetimes of the molecules and the transition probabilities were also obtained. NQR frequency shows a nonlinear behavior with pressure, indicating both dynamic and static effects of pressure. The pressure coefficients were observed to be positive for both the lines. A thermodynamic analysis of the data was carried out to determine the constant volume temperature coefficients of the NQR frequency. The variation of spin lattice time with pressure was very small, showing that the relaxation is mainly due to the torsional motions of the molecules. Copyright (C) 2010 John Wiley & Sons, Ltd.

A multi-station satellite radio beacon study of ionospheric variations during total solar eclipses

Faraday rotation data obtained at Delhi, Kurukshetra, Hyderabad, Bangalore, Waltair, Nagpur and Calcutta during the total solar eclipse of 16 February 1980 and at Delhi during the total solar eclipse of 31 July 1981 have been analysed to detect the gravity waves generated by a total solar eclipse as hypothesized by Chimonas and Hines (1970, J. geophys. Res. 75, 875). It has been found that gravity waves can be generated by a total solar eclipse but their detection at ionospheric heights is critically dependent on the location of the observing station in relation to the eclipse path geometry. The distance of the observing station from the eclipse path should be more than 500 km in order to detect such gravity waves.

Direction dependence in supernova data: constraining isotropy

We revise and extend the extreme value statistic, introduced in Gupta et al., to study direction dependence in the high-redshift supernova data, arising either from departures, from the cosmological principle or due to direction-dependent statistical systematics in the data. We introduce a likelihood function that analytically marginalizes over the,Hubble constant and use it to extend our previous statistic. We also introduce a new statistic that is sensitive to direction dependence arising from living off-centre inside a large void as well as from previously mentioned reasons for anisotropy. We show that for large data sets, this statistic has a limiting form that can be computed analytically. We apply our statistics to the gold data sets from Riess et al., as in our previous work. Our revision and extension of the previous statistic show that the effect of marginalizing over the Hubble constant instead of using its best-fitting value on our results is only marginal. However, correction of errors in our previous work reduces the level of non-Gaussianity in the 2004 gold data that were found in our earlier work. The revised results for the 2007 gold data show that the data are consistent with isotropy and Gaussianity. Our second statistic confirms these results.

Size-Dependent Tuning of Mn2+ d Emission in Mn2+-Doped CdS Nanocrystals: Bulk vs Surface

We show that the characteristic Mn2+ d emission color from Mn2+-doped CdS nanocrystals can be tuned over as much as 40 nm, in contrast to what should be expected from such a nearly localized d-d transition. This is achieved surprisingly by a fine-tuning of the host particle diameter from 1.9 to 2.6 nm, thereby changing the overall emission color from red to yellow. Systematic experiments in conjunction with state-of-the-art ab initio calculations with full geometry optimization establish that Mn2+ ions residing at surface/subsurface regions have a distorted tetrahedral coordination resulting in a larger ligand field splitting. Consequently, these near-surface Mn2+ species exhibit a lower Mn2+ d emission energy, compared to those residing at the core of the nanocrystal with an undisturbed tetrahedral coordination. The origin of the tunability of the observed Mn2+ emission is the variation of emission contributions arising from Mn2+ doped at the core, subsurface, and surface of the host. Our findings provide a unique and easy method to identify the location of an emitting Mn2+ ion in the nanocrystal, which would be otherwise very difficult to decipher.

Temperature-dependent chirped coherent phonon dynamics in Bi2Te3 using high-intensity femtosecond laser pulses

Degenerate pump-probe reflectivity experiments have been performed on a single crystal of bismuth telluride (Bi2Te3) as a function of sample temperature (3 K to 296 K) and pump intensity using similar to 50 femtosecond laser pulses with central photon energy of 1.57 eV. The time-resolved reflectivity data show two coherently generated totally symmetric A(1g) modes at 1.85 THz and 3.6 THz at 296 K which blue-shift to 1.9 THz and 4.02 THz, respectively, at 3 K. At high photoexcited carrier density of similar to 1.7 x 10(21) cm(-3), the phonon mode at 4.02 THz is two orders of magnitude higher positively chirped (i.e the phonon time period decreases with increasing delay time between the pump and the probe pulses) than the lower-frequency mode at 1.9 THz. The chirp parameter, beta is shown to be inversely varying with temperature. The time evolution of these modes is studied using continuous-wavelet transform of the time-resolved reflectivity data. Copyright (C) EPLA, 2010

Hydrogen-bond-directed self-assembly of D-(+)-dibenzoyltartaric acid and 4-aminopyridine: optical nonlinearities and stoichiometry-dependent novel structural features

Attempts to prepare hydrogen-bond-directed nonlinear optical materials from a 1:1 molar mixture Of D-(+)-dibenzoyltartaric acid (DBT, I) and 4-aminopyridine (4-AP, II) resulted in two salts of different stoichiometry. One of them crystallizes in an unusual 1.5:1 (acid:base) monohydrate salt form III while the other one crystallizes as 1:1 (acid:base) salt IV. Crystal structures of both of the salts were determined from single-crystal X-ray diffraction data. The salt III crystallizes in a monoclinic space group C2 with a = 30.339(l), b = 7.881(2), c = 14.355(1) angstrom, beta = 97.48(1)degrees, V = 3403.1(9) angstrom3, Z = 4, R(w) = 0.058, R(w)= 0.058. The salt IV also crystallizes in a monoclinic space group P2(1) with a = 7.500(1), b = 14.968(2), c = 10.370(1) angstrom, beta = 102.67(1)degrees, V = 1135.9(2) angstrom3, Z = 2, R = 0.043, R(w) = 0.043. Interestingly, two DBT molecules with distinctly different conformation are present in the same crystal lattice of salt III. Extensive hydrogen-bonding interactions are found in both of the salts, and both of them show SHG intensity 1.4-1.6 times that of urea.

Calcium/Calmodulin Dependent Protein Kinase II Bound to NMDA Receptor 2B Subunit Exhibits Increased ATP Affinity and Attenuated Dephosphorylation

Calcium/calmodulin dependent protein kinase II (CaMKII) is implicated to play a key role in learning and memory. NR2B subunit of N-methyl-D-aspartate receptor (NMDAR) is a high affinity binding partner of CaMKII at the postsynaptic membrane. NR2B binds to the T-site of CaMKII and modulates its catalysis. By direct measurement using isothermal titration calorimetry (ITC), we show that NR2B binding causes about 11 fold increase in the affinity of CaMKII for ATP gamma S, an analogue of ATP. ITC data is also consistent with an ordered binding mechanism for CaMKII with ATP binding the catalytic site first followed by peptide substrate. We also show that dephosphorylation of phospho-Thr(286)-alpha-CaMKII is attenuated when NR2B is bound to CaMKII. This favors the persistence of Thr(286) autophosphorylated state of CaMKII in a CaMKII/phosphatase conjugate system in vitro. Overall our data indicate that the NR2B- bound state of CaMKII attains unique biochemical properties which could help in the efficient functioning of the proposed molecular switch supporting synaptic memory.

Bounds on the Lifetime of Wireless Sensor Networks Employing Multiple Data Sinks

Employing multiple base stations is an attractive approach to enhance the lifetime of wireless sensor networks. In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple base stations are employed, and obtain optimum locations of the base stations (BSs) that maximize these lifetime bounds. For the case of two BSs, we jointly optimize the BS locations by maximizing the lifetime bound using a genetic algorithm based optimization. Joint optimization for more number of BSs is complex. Hence, for the case of three BSs, we optimize the third BS location using the previously obtained optimum locations of the first two BSs. We also provide simulation results that validate the lifetime bounds and the optimum locations of the BSs.

Lazy structure sharing for query optimization

We study lazy structure sharing as a tool for optimizing equivalence testing on complex data types, We investigate a number of strategies for implementing lazy structure sharing and provide upper and lower bounds on their performance (how quickly they effect ideal configurations of our data structure). In most cases when the strategies are applied to a restricted case of the problem, the bounds provide nontrivial improvements over the naive linear-time equivalence-testing strategy that employs no optimization. Only one strategy, however, which employs path compression, seems promising for the most general case of the problem.

Vibration Signature Analysis Using Artificial Neural Networks

Damage detection by measuring and analyzing vibration signals in a machine component is an established procedure in mechanical and aerospace engineering. This paper presents vibration signature analysis of steel bridge structures in a nonconventional way using artificial neural networks (ANN). Multilayer perceptrons have been adopted using the back-propagation algorithm for network training. The training patterns in terms of vibration signature are generated analytically for a moving load traveling on a trussed bridge structure at a constant speed to simulate the inspection vehicle. Using the finite-element technique, the moving forces are converted into stationary time-dependent force functions in order to generate vibration signals in the structure and the same is used to train the network. The performance of the trained networks is examined for their capability to detect damage from unknown signatures taken independently at one, three, and five nodes. It has been observed that the prediction using the trained network with single-node signature measurement at a suitability chosen location is even better than that of three-node and five-node measurement data.