Evaluation of the Quality of Drinking Water in Kerala State, India

The quality of tap water from water supplies from 14 districts of Kerala state, India was studied. Parameters like pH, water temperature, total dissolved solids, salinity, nitrates, chloride, hardness, magnesium, calcium, sodium, potassium, fluoride, sulphate, phosphates, and coliform bacteria were enumerated. The results showed that all water samples were contaminated by coliform bacteria. About 20% of the tap water samples from Alappuzha and 15% samples from Palakkad district are above desirable limits prescribed by Bureau of Indian Standards. The contamination of the source water (due to lack of community hygiene) and insufficient treatment are the major cause for the coliform contamination in the state. Water samples from Alappuzha and Palakkad have high ionic and fluoride content which could be attributed to the geology of the region. Water supplied for drinking in rural areas are relatively free of any contamination than the water supplied in urban area by municipalities, which may be attributed higher chances of contamination in urban area due to mismanagement of solid and liquid wastes. The study highlights the need for regular bacteriological enumeration along with water quality in addition to setting up decentralised region specific improved treatment system.

Spin State Selective Excitation of Single Quantum Transitions Using Multiple Quantum Spectroscopy- an Aid to Analyse Complex Proton NMR spectra of Oriented Molecules

NMR spectra of molecules oriented in liquid-crystalline matrix provide information on the structure and orientation of the molecules. Thermotropic liquid crystals used as an orienting media result in the spectra of spins that are generally strongly coupled. The number of allowed transitions increases rapidly with the increase in the number of interacting spins. Furthermore, the number of single quantum transitions required for analysis is highly redundant. In the present study, we have demonstrated that it is possible to separate the subspectra of a homonuclear dipolar coupled spin system on the basis of the spin states of the coupled heteronuclei by multiple quantum (MQ)−single quantum (SQ) correlation experiments. This significantly reduces the number of redundant transitions, thereby simplifying the analysis of the complex spectrum. The methodology has been demonstrated on the doubly 13C labeled acetonitrile aligned in the liquid-crystal matrix and has been applied to analyze the complex spectrum of an oriented six spin system.

Two-timescale Q-learning Algorithms with an Application to Routing in Networks

We propose two variants of the Q-learning algorithm that (both) use two timescales. One of these updates Q-values of all feasible state-action pairs at each instant while the other updates Q-values of states with actions chosen according to the ‘current ’ randomized policy updates. A sketch of convergence of the algorithms is shown. Finally, numerical experiments using the proposed algorithms for routing on different network topologies are presented and performance comparisons with the regular Q-learning algorithm are shown.

Incremental natural-gradient actor-critic algorithms

We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic rein- forcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated by stochastic gradient descent. Methods based on policy gradients in this way are of special interest because of their com- patibility with function approximation methods, which are needed to handle large or infinite state spaces. The use of temporal difference learning in this way is of interest because in many applications it dramatically reduces the variance of the gradient estimates. The use of the natural gradient is of interest because it can produce better conditioned parameterizations and has been shown to further re- duce variance in some cases. Our results extend prior two-timescale convergence results for actor-critic methods by Konda and Tsitsiklis by using temporal differ- ence learning in the actor and by incorporating natural gradients, and they extend prior empirical studies of natural actor-critic methods by Peters, Vijayakumar and Schaal by providing the first convergence proofs and the first fully incremental algorithms.

Steady-State Stability of Current-Mode Active-Clamp ZVS DC-DC Converters

Active-clamp dc-dc converters are pulsewidth-modulated converters having two switches featuring zero-voltage switching at frequencies beyond 100 kHz. Generalized equivalent circuits valid for steady-state and dynamic performance have been proposed for the family of active-clamp converters. The active-clamp converter is analyzed for its dynamic behavior under current control in this paper. The steady-state stability analysis is presented. On account of the lossless damping inherent in the active-clamp converters, it appears that the stability region in the current-controlled active-clamp converters get extended for duty ratios, a little greater than 0.5 unlike in conventional hard-switched converters. The conventional graphical approach fails to assess the stability of current-controlled active-clamp converters, due to the coupling between the filter inductor current and resonant inductor current. An analysis that takes into account the presence of the resonant elements is presented to establish the condition for stability. This method correctly predicts the stability of the current-controlled active-clamp converters. A simple expression for the maximum duty cycle for subharmonic-free operation is obtained. The results are verified experimentally.

An Empirical Study of Synthesis of Multiple State Devices by Engineering Designers

Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. The research work presented here is based on an empirical study of the process of synthesis of multiple state mechanical devices. As a background to the work, the paper explores concepts of what mechanical device, state, single state and multiple state are, and in the context of the above observational studies, attempts to identify the outstanding issues for supporting multiple state synthesis of mechanical devices.

Quantum Algorithms with Fixed Points: The Case of Database Search

The standard quantum search algorithm lacks a feature, enjoyed by many classical algorithms, of having a fixed-point, i.e. a monotonic convergence towards the solution. Here we present two variations of the quantum search algorithm, which get around this limitation. The first replaces selective inversions in the algorithm by selective phase shifts of $\frac{\pi}{3}$. The second controls the selective inversion operations using two ancilla qubits, and irreversible measurement operations on the ancilla qubits drive the starting state towards the target state. Using $q$ oracle queries, these variations reduce the probability of finding a non-target state from $\epsilon$ to $\epsilon^{2q+1}$, which is asymptotically optimal. Similar ideas can lead to robust quantum algorithms, and provide conceptually new schemes for error correction.

Insulating State and Breakdown of Fermi Liquid Description in Molecular-Scale Single-Crystalline Wires of Gold

Electrical transport measurements on ultrathin single-crystalline Au nanowires, synthesized via a wet chemical route, show an unexpected insulating behavior. The linear response electrical resistance exhibits a power-law dependence on temperature. In addition, the variation of current over a wide range of temperature and voltage obeys a universal scaling relation that provides compelling evidence for a non-Fermi liquid behavior. Our results demonstrate that the quantum ground state In ultrathin nanowires of simple metallic systems can be radically different from their bulk counterparts and can be described In terms of a Tomonaga-Luttinger liquid (TLL), in the presence of remarkably strong electron-electron interactions.

Nanostructuration via solid state transformation as a strategy for improving the thermoelectric efficiency of PbTe alloys

The approach taken in this paper in order to modify the scattering features of electrons and phonons and improve the figure of merit (ZT) of thermoelectric PbTe is to alter the microstructure at constant chemistry. A lamellar pattern of PbTe/GeTe at the nano- and microscale was produced in Pb(0.36)Ge(0.64)Te alloy by the diffusional decomposition of a supersaturated solid solution. The mechanism of nanostructuration is most likely a discontinuous spinodal decomposition. A simple model relating the interface velocity to the observed lamellar spacing is proposed. The effects of nanostructuration in Pb(0.36)Ge(0.64)Te alloy on the electrical and thermal conductivity, thermopower and ZT were investigated. It was shown that nanostructuration through the formation of a lamellar pattern of PbTe/GeTe is unlikely to provide a significant improvement due to the occurrence of discontinuous coarsening. However, the present study allows an analysis of possible strategies to improve thermoelectric materials via optimal design of the microstructure and optimized heat treatment. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.