Growth and characterization of single crystal cored fibers of organic nonlinear optical materials

The recent development of several organic materials with large nonlinear susceptibilities, high damage threshold and low melting points encouraged researchers to employ these materials in fiber form to efficiently couple diode laser pumps and obtain enhanced second harmonic generation (SHG). In this paper we report the growth of single crystal cored fibers of 4-nitro-4'-methylbenzylidene aniline, ethoxy methoxy chalcone and (-)2-((alpha) -methylbenzylamino)-5- nitropyridine by inverted Bridgman-Stockbarger technique. The fibers were grown in glass capillaries with varying internal diameters and lengths and were characterized using x-ray and polarizing microscope techniques. The propagation loss at 632.8 nm and 1300 nm were measured and SHG was studied using 1064 nm pump.

Performance of a mixed flow pump with varying tip clearance .2.

Measurements in a mixed flow pump of non-dimensional specific speed k = 1.89[N-S = 100 r/min (metric)] are analysed to give loss distribution and local hydraulic efficiencies at different flowrates and values of tip clearance. Fairly close agreement is obtained between the relative flow angles leaving the blading as predicted by simple deviation and slip models and derived from the measurements. The head developed is broken up into two parts: that contributed by Coriolis action and that associated with blade circulation. It is suggested that lift coefficients based on blade circulation are of limited value in selecting blade profiles. The variation of pump efficiency with tip clearance is greater than that reported for centrifugal pumps.

Solid Oxide-Ion Electrolytes

Solid oxide-ion electrolytes find application in oxygen sensors, oxygen pumps and in high-temperature electrolyser-fuel-cell hybrid systems. All the solid electrolytes known so Qr, however, exhibit: tow oxide-ion conductivities below 973 K. Therefore, there is a need for fast oxide-ion conductors operative at temperatures around 673 K, Recently, efforts have been directed towards developing such materials. This article summarizes various type of oxide-ton electrolytes reported in literature and outlines a strategy for the identificatiom/synthesis of improved materials.

Enhanced lithium-ion transport in PEG-based composite polymer electrolyte with Mn0.03Zn0.97Al2O4 nanoparticles

The ion conduction and thermal properties of composite solid polymer electrolyte (SPE) comprising Poly(ethylene) Glycol (PEG, mol wt. 2000), lithium perchlorate (LiClO4) and insulating Mn0.03Zn0.97Al2O4 nanoparticle fillers were studied by complex impedance analysis and DSC techniques. The average size of the nanoparticles was determined by powder X-ray diffraction (XRD) using Scherrer's equation and was found to be similar to 8 nm. The same was also determined by TEM imaging and found to be similar to 12 nm. The glass transition temperature T, as measured by differential scanning calorimeter (DSC), showed a minimum at 5 mol% of narroparticles. Fractional crystallinity was determined using DSC. NMR was used to deter-mine crystallinity of a pure PEG sample, which was then used as the standard. Fractional crystallinity X. was the lowest for 5 mol% and beyond. The ionic conductivity of the composite polymer electrolyte containing 5 mol% Mn0.03Zn0.97Al2O4 nanoparticles was found to be 1.82 x 10(-5) S/cm, while for the pristine one, it was 7.27 x 10(-7) S/cm at room temperature. As a function of nanoparticle content, conductivity was observed to go through two maxima, one at around 5 mol% and another shallower one at around 12 mol%. The temperature dependence of conductivity could be divided into two regions, one consistent with Arrhenius behaviour and the other with VTF. We conclude that the enhancement of ionic conductivity on the addition of Mn0.03Zn0.97Al2O4 nanoparticles is a result of reduction in both the T, and the crystallinity. (C) 2002 Elsevier Science B.V. All rights reserved.

A self-supported 40W direct methanol fuel cell system

A self-supported 40W Direct Methanol Fuel Cell (DMFC) system has been developed and performance tested. The auxiliaries in the DMFC system comprise a methanol sensor, a liquid-level indicator, and fuel and air pumps that consume a total power of about 5W. The system has a 15-cell DMFC stack with active electrode-area of 45 cm(2). The self-supported DMFC system addresses issues related to water recovery from the cathode exhaust, and maintains a constant methanol-feed concentration with thermal management in the system. Pure methanol and water from cathode exhaust are pumped to the methanol-mixing tank where the liquid level is monitored and controlled with the help of a liquid-level indicator. During the operation, methanol concentration in the feed solution at the stack outlet is monitored using a methanol sensor, and pure methanol is added to restore the desired methanol concentration in the feed tank by adding the product water from the cathode exhaust. The feed-rate requirements of fuel and oxidant are designed for the stack capacity of 40W. The self-supported DMFC system is ideally suited for various defense and civil applications and, in particular, for charging the storage batteries.

The physics of active membranes

We review recent work on the physical properties of model fluid membranes in nonequilibrium situations resembling those encountered in the living cell and contrast their properties with those of the more familiar membranes at thermal equilibrium. We survey models for the effect of (i) active pumps and (ii) active fission–fusion processes encountered in intracellular trafficking on the stability and fluctuations of fluid membranes. Our purpose is twofold: to highlight the exciting nonequilibrium phenomena that arise in biological systems, and to show how some crucial features of living systems, namely dissipative energy uptake and directed motion, can fruitfully be incorporated into physical models of biological interest.

Stream-Close: Fast mining of Closed Frequent Itemsets in high speed data streams

With the emergence of large-volume and high-speed streaming data, the recent techniques for stream mining of CFIpsilas (closed frequent itemsets) will become inefficient. When concept drift occurs at a slow rate in high speed data streams, the rate of change of information across different sliding windows will be negligible. So, the user wonpsilat be devoid of change in information if we slide window by multiple transactions at a time. Therefore, we propose a novel approach for mining CFIpsilas cumulatively by making sliding width(ges1) over high speed data streams. However, it is nontrivial to mine CFIpsilas cumulatively over stream, because such growth may lead to the generation of exponential number of candidates for closure checking. In this study, we develop an efficient algorithm, stream-close, for mining CFIpsilas over stream by exploring some interesting properties. Our performance study reveals that stream-close achieves good scalability and has promising results.

Physical chemistry of the reduction of calcium oxide with aluminium in vacuum

The physical chemistry of "aluminothermic" reduction of calcium oxide in vacuum is analyzed. Basic thermodynamic data required for the analysis have been generated by a variety of experiments. These include activity measurements in liquid AI-Ca alloys and determination of the Gibbs energies of formation of calcium aluminates. These data have been correlated with phase relations in the Ca-AI-0 system at 1373 K. The various stages of reduction, the end products and the corresponding equilibrium partial pressures of calcium have been established from thermodynamic considerations. In principle, the recovery of calcium can be improved by reducing the pressure in the reactor. However,, the cost of a high vacuum system and the enhanced time for reduction needed to achieve higher yields makes such a practice uneconomic. Aluminum contamination of calcium also increases at low pressures. The best compromise is to carry the reduction up to the stage where 3CaO-Al,O, is formed as the product. This corresponds to an equilibrium calcium partial pressure of 31.3 Pa at 1373 K and 91.6 Pa at 1460 K. Calcium can be extracted at this pressure using mechanical pumps in approximately 8 to 15 hr, depending on the size and the fill ratio of the retort and porosity of the charge briquettes.

Biosorption of heavy metal ions from aqueous and cyanide solutions using fungal biomass

A waste fungal biomass containing killed cells of Aspergillus niger was efficiently used in the removal of toxic metal ions such as nickel, calcium, iron and chromium from aqueous solutions. The role of different parameters such as initial metal ion concentration, solution pH and biomass concentration on biosorption capacity was established. The maximum metal uptake was found to be dependent on solution pH and increased with biomass loading upto 10g/L. The adsorption densities for various metal ions could be arranged as Ca>Cr (III)>Ni>Fe>Cr (VI). The effect of the presence of various metal ions in binary, ternary and quaternary combinations on biosorption was also assessed. Ni uptake was significantly affected, while that of Cr (VI) the least, in the presence of other metal ions. Uptake of base metals from an industrial cyanide effluent was studied using different species of fungi such as Aspergillus niger, Aspergillus terreus and Penicillium funiculosum and yeast such as Saccharomyces cerevisiae which were isolated from a gold mine. Traces of gold present in the cyanide effluent could be efficiently recovered. Among the four base metal contaminants present in the cyanide effluent, zinc was found to be most efficiently biosorbed, followed by iron, copper and lead. The role of both living and dead biomass on biosorption was distinguished and probable mechanisms illustrated.

Development of experimental setup for study of adsorption characteristics of porous materials down to 4.2 K

The knowledge of adsorption characteristics of activated carbon (porous material) in the temperature range from 5 to 20 K is essential when used in cryosorption pumps for nuclear fusion applications. However, such experimental data are very scarce in the literature, especially below 77 K. So, an experimental system is designed and fabricated to measure the adsorption characteristics of porous materials under variable cryogenic temperatures (from 5 K to 100 K). This is based on the commercially available micropore-analyser coupled to a closed helium cycle two-stage Gifford McMahon (GM) Cryocooler, which allows the sample to be cooled to 4.2 K. The sample port is coupled to the Cryocooler through a heat switch, which isolates this port from the cold head of the Cryocooler. By this, the sample temperature can now be varied without affecting the Cryocooler. The setup enables adsorption studies in the pressure range from atmospheric down to 10(-4) Pa. The paper describes the details of the experimental setup and presents the results of adsorption studies at 77 K for activated carbon with nitrogen as adsorbate. The system integration is now completed to enable adsorption studies at 4.2 K.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Studies of cryocooler based cryosorption pump with activated carbon panels operating at 11K

Cryosorption pump is the only solution for pumping helium and hydrogen in fusion reactors. It is chosen because it offers highest pumping speed as well as the only suitable pump for the harsh environments in a tokamak. Towards the development of such cryosorption pumps, the optimal choice of the right activated carbon panels is essential. In order to characterize the performance of the panels with indigenously developed activated carbon, a cryocooler based cryosorption pump with scaled down sizes of panels is experimented. The results are compared with the commercial cryopanel used in a CTI cryosorption (model: Cryotorr 7) pump. The cryopanel is mounted on the cold head of the second stage GM cryocooler which cools the cryopanel down to 11K with first stage reaching about similar to 50K. With no heat load, cryopump gives the ultimate vacuum of 2.1E-7 mbar. The pumping speed of different gases such as nitrogen, argon, hydrogen, helium are tested both on indigenous and commercial cryopanel. These studies serve as a bench mark towards the development of better cryopanels to be cooled by liquid helium for use with tokamak.

Influence of operational and geometrical parameters on the performance of twin thermoacoustic prime mover

Thermoacoustics is the interaction between heat and sound, which are useful in designing heat engines and heat pumps. Research in the field of thermoacoustics focuses on the demand to improve the performance which is achieved by altering operational, geometrical and fluid parameters. The present study deals with improving the performance of twin thermoacoustic prime mover, which has gained the significant importance in the recent years for the production of high amplitude sound waves. The performance of twin thermoacoustic prime mover is evaluated in terms of onset temperature difference, resonance frequency and pressure amplitude of the acoustic waves by varying the resonator length and charge pressures of fluid medium nitrogen. DeltaEC, the free simulation software developed by LANL, USA is employed in the present study to simulate the performance of twin thermoacoustic prime mover. Experimental and simulated results are compared and the deviation is found to be within 10%.

Discovering Math APIs by Mining Unit Tests

In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).