Automatically Generating Interfaces for Personalized Interaction with Digital Libraries

We present an approach to automatically generate interfaces supporting personalized interaction with digital libraries; these interfaces augment the user-DL dialog by empowering the user to (optionally) supply out-of-turn information during an interaction, flatten or restructure the dialog, and inquire about dialog options. Interfaces generated using this approach for CITIDEL are described

Strongly correlated superconductivity in Rh<SUB>17</SUB>S<SUB>15</SUB>

In this work, we show the highly correlated nature of the superconductor Rh17S15 via transport, magnetization and heat capacity measurements. In particular, we will discuss resistivity, susceptibility, heat-capacity and upper critical field studies on a polycrystalline Rh17S15 sample which exhibits superconductivity below 5.4 K. Detailed studies suggest that the superconductivity in this compound arises from strongly correlated charge carriers presumably due to the high density of states of Rh d-bands at the Fermi level. Moreover, the Hall coefficient shows a sign change and increases at low temperature before the sample becomes a superconductor below 5.4 K

Vortex phase diagram in weakly pinned Rh<SUB>17</SUB>S<SUB>15</SUB>

A vortex phase diagram of the strongly correlated superconductor Rh17S15 has been constructed via exploration of the anomalous variations in critical current density extracted from ac and dc magnetization measurements. The isofield in-phase ac susceptiblity data reveal the presence of multiple steps at different fields. The dc magnetisation hysteresis loops show the presence of a very broad fishtail commencing deep inside the mixed state and lasting upto Hc2. We have also analysed the scan rate dependence of the hysteresis width in the vibrating sample magnetometer data with a view to distinguish between the different possible order-disorder transformations in the flux line lattice

Use of antibacterial nanoparticles in Endodontics

Several root canal irrigants and medicaments are available to combat endodontic pathogens. However, evidence of complete elimination of these pathogens by the use of these solutions is not recorded in the literature. The possible development of resistant bacterial species is one of the problems related to the efficacy of the currently available irrigants and medicaments. In addition, the complex anatomy of the root canal system allows endodontic pathogens to be hidden in areas inaccessible to the action of the irrigating preparations. This is further enhanced by the protective layer that is formed by the remnants of pulp tissue, dentin powder and dead cells which inhibit the antibacterial activity of the root canal irrigants and medicaments. Antimicrobial nanoparticles show promising effect against resistant pathogens in pharmaceutical science as a result of their unique physio-chemical properties. Unlike traditionally used antimicrobial agents, these nanoparticles destroy bacterial cells through multiple mechanisms. The concept of using nanoparticles in endodontics as a new treatment modality was developed recently and their antibacterial efficacy against endodontic pathogens was evaluated by several researchers in many in vitro studies. This article reviews some of the currently available literature on laboratory studies that evaluated the efficacy of nanoparticles against endodontic pathogens

Using Hierarchical Data Mining to Characterize Performance of Wireless System Configurations

This paper presents a statistical framework for assessing wireless systems performance using hierarchical data mining techniques. We consider WCDMA (wideband code division multiple access) systems with two-branch STTD (space time transmit diversity) and 1/2 rate convolutional coding (forward error correction codes). Monte Carlo simulation estimates the bit error probability (BEP) of the system across a wide range of signal-to-noise ratios (SNRs). A performance database of simulation runs is collected over a targeted space of system configurations. This database is then mined to obtain regions of the configuration space that exhibit acceptable average performance. The shape of the mined regions illustrates the joint influence of configuration parameters on system performance. The role of data mining in this application is to provide explainable and statistically valid design conclusions. The research issue is to define statistically meaningful aggregation of data in a manner that permits efficient and effective data mining algorithms. We achieve a good compromise between these goals and help establish the applicability of data mining for characterizing wireless systems performance

BSML: A Binding Schema Markup Language for Data Interchange in Problem Solving Environments (PSEs)

We describe a binding schema markup language (BSML) for describing data interchange between scientific codes. Such a facility is an important constituent of scientific problem solving environments (PSEs). BSML is designed to integrate with a PSE or application composition system that views model specification and execution as a problem of managing semistructured data. The data interchange problem is addressed by three techniques for processing semistructured data: validation, binding, and conversion. We present BSML and describe its application to a PSE for wireless communications system design