Solution properties of methyl methacrylate–acrylonitrile copolymers

Characterization of methyl methacrylate-acrylonitrile copolymers is done through viscosity, swelling, and differential refractometric studies. Viscosities of the copolymers and homopolymers were determined at 30, 40, and 50°C. The activation parameters of viscous flow, voluminosity, and shape factor were also calculated. The average shape factor was observed to be 2.5 ± 0.005 for all copolymer systems. Viscosity molecular weights were calculated, and from intramolecular expansion factor (α), it was observed that copolymers are less flexible than are homopolymers. dn/dc values obtained from differential refractometry are in good agreement with those calculated theoretically. © 1993 John Wiley & Sons, Inc.     

An ensemble-based incremental learning approach to data fusion.

This paper introduces Learn++, an ensemble of classifiers based algorithm originally developed for incremental learning, and now adapted for information/data fusion applications. Recognizing the conceptual similarity between incremental learning and data fusion, Learn++ follows an alternative approach to data fusion, i.e., sequentially generating an ensemble of classifiers that specifically seek the most discriminating information from each data set. It was observed that Learn++ based data fusion consistently outperforms a similarly configured ensemble classifier trained on any of the individual data sources across several applications. Furthermore, even if the classifiers trained on individual data sources are fine tuned for the given problem, Learn++ can still achieve a statistically significant improvement by combining them, if the additional data sets carry complementary information. The algorithm can also identify-albeit indirectly-those data sets that do not carry such additional information. Finally, it was shown that the algorithm can consecutively learn both the supplementary novel information coming from additional data of the same source, and the complementary information coming from new data sources without requiring access to any of the previously seen data.     

Effect of low-density filler on mechanical properties of syntactic foams of cyanate ester

Syntactic foam composites of cyanate ester with varying volume fractions of resin and glass microballoon were processed and evaluated for tensile, flexural and compressive properties. The effect of nature and volume fraction of microballoon on the mechanical properties was studied. The mechanical properties showed a gradual decrease in strength with increase in volume fraction of microballoon. The specific strength values also manifested a similar order. A similar behaviour was observed for syntactic foams with microballoons of varying true density. The properties increased proportional to the strength of the microballoon in resin-rich systems implying a strong microballoon-resin interface, corroborated by Scanning Electron Microscopy studies. The compressive modulus showed a decreasing trend with enhanced microballoon loading.     

An improved algorithm for connectivity analysis of distribution networks

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks.     

Improved field emission from multiwall carbon nanotubes with nano-size defects produced by ultra-low energy ion bombardment

Multiwalled carbon nanotubes were irradiated with ultra-low energy (few eV) nitrogen and hydrogen ions using a microwave discharge. These ultra-low energy plasma-ions remain confined to the nanotube walls, transferring their maximum energy to the carbon atoms, and produce extraordinary structural changes to the carbon nanotube pillars as well as within the carbon nanotubes. Conical shaped emitters and nanotube structures with nano-defects are produced that exhibit remarkable field emission with ultra-low turn-on electric field (∼0.16 V/μm) and a >300-fold increase in the maximum emission current density compared to non-irradiated nanotubes. Doping of nitrogen is also identified due to such irradiation processes.     

Correlation between structural properties and gas sensing characteristics of SnO2 based gas sensors

Undoped polycrystalline tin oxide sintered in the temperature range 500–1000 °C has been comprehensively characterized with respect to its response to CO, methane and H₂. Results obtained at an operating temperature of 300 °C show that increasing the sintering temperature leads to a gradual increase in CO sensitivity which reaches a maximum after sintering at 800 °C.     

Development of a PCR assay for the detection of nifH and nifD genes in indigenous photosynthetic bacteria

Molybdenum (Mo) nitrogenases consist of two components: dinitrogenase reductase (encoded by nifH) and the dinitrogenase or MoFe protein (encoded by nifDK). Nitrogenase enzyme of photosynthetic bacteria is responsible for hydrogen production. Therefore, primers were designed for the nitrogenase gene only. In this study, two primers (ND and NH) were designed after comparative genomic analysis of nifH and nifD gene sequences from public databases. The designed primers were used for the amplification of nifH and nifD genes to detect nitrogenase genes in photosynthetic bacteria. Initial detection was done using a monoplex Polymerase Chain Reactions (PCRs) followed by optimization of the PCR protocols. Subsequently, a duplex PCR was designed for amplification and detection of nifH and nifD genes in indigenous photosynthetic bacteria. Evaluation of the duplex PCR on six samples isolated from Palm Oil Mill Effluent (POME) showed that only four isolates contained both the nifH and nifD genes, indicating that these isolates were potential hydrogen-producing bacteria. PCR detection provides a rapid and efficient pre-identification of potential photosynthetic bacterial hydrogen producers.