Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

A new pentameric structure of rotavirus NSP4 revealed by molecular replacement

The region spanning residues 95-146 of the rotavirus nonstructural protein NSP4 from the asymptomatic human strain ST3 has been purified and crystallized and diffraction data have been collected to a resolution of 2.6 angstrom. Several attempts to solve the structure by the molecular-replacement method using the available tetrameric structures of this domain were unsuccessful despite a sequence identity of 73% to the already known structures. A more systematic approach with a dimer as the search model led to an unexpected pentameric structure using the program Phaser. The various steps involved in arriving at this molecular-replacement solution, which unravelled a case of subtle variation between different oligomeric states unknown at the time of solving the structure, are presented in this paper.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

Durable Transition-Metal-Carbide-Supported Pt-Ru Anodes for Direct Methanol Fuel Cells

Molybdenum carbide (MoC) and tungsten carbide (WC) are synthesized by direct carbonization method. PtRu catalysts supported on MoC, WC, and Vulcan XC-72R are prepared, and characterized by X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy in conjunction with electrochemistry. Electrochemical activities for the catalysts towards methanol electro-oxidation are studied by cyclic voltammetry. All the electro-catalysts are subjected to accelerated durability test (ADT). The electrochemical activity of carbide-supported electro-catalysts towards methanol electro-oxidation is found to be higher than carbon-supported catalysts before and after ADT. The study suggests that PtRu/MoC and PtRu/WC catalysts are more durable than PtRu/C. Direct methanol fuel cells (DMFCs) with PtRu/MoC and PtRu/WC anodes also exhibit higher performance than the DMFC with PtRu/C anode.

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.

Seed dispersal in changing landscapes

A growing understanding of the ecology of seed dispersal has so far had little influence on conservation practice, while the needs of conservation practice have had little influence on seed dispersal research. Yet seed dispersal interacts decisively with the major drivers of biodiversity change in the 21st century: habitat fragmentation, overharvesting, biological invasions, and climate change. We synthesize current knowledge of the effects these drivers have on seed dispersal to identify research gaps and to show how this information can be used to improve conservation management. The drivers, either individually, or in combination, have changed the quantity, species composition, and spatial pattern of dispersed seeds in the majority of ecosystems worldwide, with inevitable consequences for species survival in a rapidly changing world. The natural history of seed dispersal is now well-understood in a range of landscapes worldwide. Only a few generalizations that have emerged are directly applicable to conservation management, however, because they are frequently confounded by site-specific and species-specific variation. Potentially synergistic interactions between disturbances are likely to exacerbate the negative impacts, but these are rarely investigated. We recommend that the conservation status of functionally unique dispersers be revised and that the conservation target for key seed dispersers should be a population size that maintains their ecological function, rather than merely the minimum viable population. Based on our analysis of conservation needs, seed dispersal research should be carried out at larger spatial scales in heterogenous landscapes, examining the simultaneous impacts of multiple drivers on community-wide seed dispersal networks. (C) 2011 Elsevier Ltd. All rights reserved.

Distinct mechanisms of DNA repair in mycobacteria and their implications in attenuation of the pathogen growth

About a third of the human population is estimated to be infected with Mycobacterium tuberculosis. Emergence of drug resistant strains and the protracted treatment strategies have compelled the scientific community to identify newer drug targets, and to develop newer vaccines. In the host macrophages, the bacterium survives within an environment rich in reactive nitrogen and oxygen species capable of damaging its genome. Therefore, for its successful persistence in the host, the pathogen must need robust DNA repair mechanisms. Analysis of M. tuberculosis genome sequence revealed that it lacks mismatch repair pathway suggesting a greater role for other DNA repair pathways such as the nucleotide excision repair, and base excision repair pathways. In this article, we summarize the outcome of research involving these two repair pathways in mycobacteria focusing primarily on our own efforts. Our findings, using Mycobacterium smegmatis model, suggest that deficiency of various DNA repair functions in single or in combinations severely compromises their DNA repair capacity and attenuates their growth under conditions typically encountered in macrophages. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Rural electrification: Optimising the choice between decentralised renewable energy sources and grid extension

The study presents an analysis aimed at choosing between off-grid solar photovoltaic, biomass gasifier based power generation and conventional grid extension for remote village electrification. The model provides a relation between renewable energy systems and the economical distance limit (EDL) from the existing grid point, based on life cycle cost (LCC) analysis, where the LCC of energy for renewable energy systems and grid extension will match. The LCC of energy feed to the village is arrived at by considering grid availability and operating hours of the renewable energy systems. The EDL for the biomass gasifier system of 25 kW capacities is 10.5 km with 6 h of daily operation and grid availability. However, the EDL for a similar 25 kW capacity photovoltaic system is 35 km for the same number of hours of operation and grid availability. The analysis shows that for villages having low load demand situated far away from the existing grid line, biomass gasification based systems are more cost competitive than photovoltaic systems or even compared to grid extension. (C) 2012 Elsevier Inc. All rights reserved.

Severe diffraction anisotropy, rotational pseudosymmetry and twinning complicate the refinement of a pentameric coiled-coil structure of NSP4 of rotavirus

The crystal structure of the region spanning residues 95-146 of the rotavirus nonstructural protein NSP4 from the asymptomatic human strain ST3 was determined at a resolution of 2.5 angstrom. Severe diffraction anisotropy, rotational pseudo-symmetry and twinning complicated the refinement of this structure. A systematic explanation confirming the crystal pathologies and describing how the structure was successfully refined is given in this report.

Optimization of thermoacoustic primemover using response surface methodology

Thermoacoustic engines are energy conversion devices that convert thermal energy from a high-temperature heat source into useful work in the form of acoustic power while diverting waste heat into a cold sink; it can be used as a drive for cryocoolers and refrigerators. Though the devices are simple to fabricate, it is very challenging to design an optimized thermoacoustic primemover with better performance. The study presented here aims to optimize the thermoacoustic primemover using response surface methodology. The influence of stack position and its length, resonator length, plate thickness, and plate spacing on pressure amplitude and frequency in a thermoacoustic primemover is investigated in this study. For the desired frequency of 207 Hz, the optimized value of the above parameters suggested by the response surface methodology has been conducted experimentally, and simulations are also performed using DeltaEC. The experimental and simulation results showed similar output performance.

A broad pore size distribution mesoporous SnO2 as anode for lithium-ion batteries

We demonstrate here that mesoporous tin dioxide (abbreviated M-SnO2) with a broad pore size distribution can be a prospective anode in lithium-ion batteries. M-SnO2 with pore size ranging between 2 and 7.5 nm was synthesized using a hydrothermal procedure involving two different surfactants of slightly different sizes, and characterized. The irreversible capacity loss that occurs during the first discharge and charge cycle is 890 mAh g(-1), which is smaller than the 1,010-mAh g(-1) loss recorded for mesoporous SnO2 (abbreviated S-SnO2) synthesized using a single surfactant. After 50 cycles, the discharge capacity of M-SnO2 (504 mAh g(-1)) is higher than that of S-SnO2 (401 mAh g(-1)) and solid nanoparticles of SnO2 (abbreviated nano-SnO2 < 4 mAh g(-1)) and nano-SnO2. Transmission electron microscopy revealed higher disorder in the pore arrangement in M-SnO2. This, in turn imparts lower stiffness to M-SnO2 (elastic modulus, E (R) a parts per thousand aEuro parts per thousand 14.5 GPa) vis-a-vis S-SnO2 (E (R) a parts per thousand aEuro parts per thousand 20.5 GPa), as obtained using the nanoindentation technique. Thus, the superior battery performance of M-SnO2 is attributed to its intrinsic material mechanical property. The fluidity of the internal microstructure of M-SnO2 resulted in a lower degree of aggregation of Sn particles compared to S-SnO2 and nano-SnO2 structural stabilization and long-term cyclability.