Orientation Selection and Microstructural Evolution in Directionally Solidified Tb0.3Dy0.7Fe1.95

Tb0.3Dy0.7Fe1.95 alloy was directionally solidified by using a modified Bridgman technique at a wide range of growth rates of 5 to 100 cm/h. The directionally grown samples exhibited plane front solidification morphology up to a growth rate of 90 cm/h. Typical island banding feature was observed closer to the chilled end, which eventually gave rise to irregular peritectic coupled growth (PCG). The PCG gained prominence with an increase in the growth rate. The texture study revealed formation of strong aOE (c) 311 > texture in a lower growth rate regime, aOE (c) 110 > and ``rotated aOE (c) 110 > aEuroe in an intermediate growth regime, and aOE (c) 112 > in a higher growth rate regime. In-depth analysis of the atomic configuration of a solid-liquid interface revealed that the growth texture is influenced by the kinetics of atomic attachment to the solid-liquid interface, which is intimately related to a planar packing fraction and an atomic stacking sequence of the interfacial plane. The mechanism proposed in this article is novel and will be useful in addressing the orientation selection mechanism of topologically closed packed intermetallic systems. The samples grown at a higher growth rate exhibit larger magnetostriction (lambda) and d lambda/dH owing to the absence of pro-peritectic (Tb,Dy)Fe-3 and formation of aOE (c) 112 > texture, which lies closer to the easy magnetization direction (EMD).

Prototype Selection on Large and Streaming Data

Since streaming data keeps coming continuously as an ordered sequence, massive amounts of data is created. A big challenge in handling data streams is the limitation of time and space. Prototype selection on streaming data requires the prototypes to be updated in an incremental manner as new data comes in. We propose an incremental algorithm for prototype selection. This algorithm can also be used to handle very large datasets. Results have been presented on a number of large datasets and our method is compared to an existing algorithm for streaming data. Our algorithm saves time and the prototypes selected gives good classification accuracy.

Direct Link-Aware Relay Selection for Average Interference-Constrained Underlay Cognitive Radio

Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio network. We present a novel and optimal relay selection (RS) rule that minimizes the symbol error probability (SEP) of an average interference-constrained underlay secondary system that uses amplify-and-forward relays. A key point that the rule highlights for the first time is that, for the average interference constraint, the signal-to-interference-plus-noise-ratio (SINR) of the direct source-to-destination (SI)) link affects the choice of the optimal relay. Furthermore, as the SINR increases, the odds that no relay transmits increase. We also propose a simpler, more practical, and near-optimal variant of the optimal rule that requires just one bit of feedback about the state of the SD link to the relays. Compared to the SD-unaware ad hoc RS rules proposed in the literature, the proposed rules markedly reduce the SEP by up to two orders of magnitude.

Nitrogen-assisted electroless assembling of 3D nanodendrites consisting of Pd and N-doped carbon nanoparticles as bifunctional catalysts

We report a facile synthesis of three-dimensional (3D) nanodendrites of Pd nanoparticles (NPs) and nitrogen-doped carbon NPs (N-CNPs) by electroless deposition of Pd2+ ions. N-CNPs being an electron-enriched material act as a reducing agent. Moreover, the availability of a variety of nitrogen species in N-CNPs promotes the open arm structure as well as stabilizes the oriented 3D assembly of primary Pd NPs. The dendrites exhibit superior catalytic activity for methanol (0.5 M) oxidation in alkaline media (1 M NaOH) which is ascribed to the large electrochemical active surface area and the enhanced mass activity with repeated use. Further mass activity improvement has been realized after acid-treatment of dendrites which is attributed to the increment in the -OH group. The dendrites show higher mass activity (J(f) similar to 653 A g(-1)) in comparison with a commercial Pt-carbon/Pd-carbon (Pt-C/Pd-C) catalyst (J(f) similar to 46 and 163 A g(-1), respectively), better operational stability, superior CO tolerance with I-f/I-b (similar to 3.7) over a commercial Pt-C/Pd-C catalyst (I-f/I-b similar to 1.6 and 1.75, respectively) and may serve as a promising alternative to commercial Pt-C catalysts for anode application in alkaline fuel cells. To ensure the adaptability of our 3D-nanodendrites for other catalytic activities, we studied 4-nitrophenol reduction at room temperature. The 3D-nanodendrites show excellent catalytic activity toward 4-nitrophenol reduction, as well.