A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Ribosome-RNA interaction: a potential target for developing antiviral against hepatitis C virus

Hepatitis C virus (HCV), a member of Flaviviridae, encoding a positive-sense single-stranded RNA translates by cap-independent mechanism using the internal ribosome entry site (IRES) present in the 5' UTR of the virus. The IRES has complex stem loop structures and is capable of recruiting the 40S ribosomal subunit in a factor-independent fashion. As the IRES sequence is highly conserved throughout the HCV genotypes and the translation is the first obligatory step of the HCV life cycle, the IRE'S-mediated translation, or more specifically, the ribosome HCV RNA interaction is an attractive target to design effective antivirals. This article will focus on the mechanism of the HCV IRES translation and the various ways in which the interaction of ribosome and IRES has been targeted.

The Nature of Bond Critical Points in Dinuclear Copper(I) Complexes

Closed-shell contacts between two copper(I) ions are expected to be repulsive. However, such contacts are quite frequent and are well documented. Crystallographic characterization of such contacts in unsupported and bridged multinuclear copper(I) complexes has repeatedly invited debates on the existence of cuprophilicity. Recent developments in the application of Baders theory of atoms-in-molecules (AIM) to systems in which weak hydrogen bonds are involved suggests that the copper(I)copper(I) contacts would benefit from a similar analysis. Thus the nature of electron-density distributions in copper(I) dimers that are unsupported, and those that are bridged, have been examined. A comparison of complexes that are dimers of symmetrical monomers and those that are dimers of two copper(I) monomers with different coordination spheres has also been made. AIM analysis shows that a bond critical point (BCP) between two Cu atoms is present in most cases. The nature of the BCP in terms of the electron density, ?, and its Laplacian is quite similar to the nature of critical points observed in hydrogen bonds in the same systems. The ? is inversely correlated to Cu?Cu distance. It is higher in asymmetrical systems than what is observed in corresponding symmetrical systems. By examining the ratio of the local electron potential-energy density (Vc) to the kinetic energy density (Gc), |Vc|/Gc at the critical point suggests that these interactions are not perfectly ionic but have some shared nature. Thus an analysis of critical points by using AIM theory points to the presence of an attractive metallophilic interaction similar to other well-documented weak interactions like hydrogen bonding.

Recent Developments in the Chemistry and Biology of G-Quadruplexes with Reference to the DNA Groove Binders

DNA is the chemotherapeutic target for treating diseases of genetic origin. Besides well-known double-helical structures (A, B, Z, parallel stranded-DNA etc.), DNA is capable of forming several multi-stranded structures (triplex, tetraplex, i-motif etc.) which have unique biological significance. The G-rich 3'-ends of chromosomes, called telomeres, are synthesized by telomerase, a ribonucleoprotein, and over-expression of telomerase is associated with cancer. The activity of telomerase is suppressed if the G-rich region is folded into the four stranded structures, called G-quadruplexes (G4-DNAs) using small synthetic ligands. Thus design and synthesis of new G4-DNA ligands is an attractive strategy to combat cancer. G4-DNA forming sequences are also prevalent in other genomic regions of biological significance including promoter regions of several oncogenes. Effective gene regulation may be achieved by inducing a G4-DNA structure within the G-rich promoter sequences. To date, several G4-DNA stabilizing ligands are known. DNA groove binders interact with the duplex B-DNA through the grooves (major and minor groove) in a sequence-specific manner. Some of the groove binders are known to stabilize the G4-DNA. However, this is a relatively under explored field of research. In this review, we focus on the recent advances in the understanding of the G4-DNA structures, particularly made from the human telomeric DNA stretches. We summarize the results of various investigations of the interaction of various organic ligands with the G4-DNA while highlighting the importance of groove binder-G4-DNA interactions.

First principles calculations of H-storage in sorption materials

A review of various contributions of first principles calculations in the area of hydrogen storage, particularly for the carbon-based sorption materials, is presented. Carbon-based sorption materials are considered as promising hydrogen storage media due to their light weight and large surface area. Depending upon the hybridization state of carbon, these materials can bind the hydrogen via various mechanisms, including physisorption, Kubas and chemical bonding. While attractive binding energy range of Kubas bonding has led to design of several promising storage systems, in reality the experiments remain very few due to materials design challenges that are yet to be overcome. Finally, we will discuss the spillover process, which deals with the catalytic chemisorption of hydrogen, and arguably is the most promising approach for reversibly storing hydrogen under ambient conditions.

Colossal nonsaturating linear magnetoresistance in two-dimensional electron systems at a GaAs/(Al,Ga)As heterointerface

Engineering devices with a large electrical response to magnetic field is of fundamental importance for a range of applications such as magnetic field sensing and magnetic read heads. We show that a colossal nonsaturating linear magnetoresistance (NLMR) arises in two-dimensional electron systems hosted in a GaAs/AlGaAs heterostructure in the strongly insulating regime. When operated at high source-drain bias, the magnetoresistance of our devices increases almost linearly with magnetic field, reaching nearly 10 000% at 8 T, thus surpassing many known nonmagnetic materials that exhibit giant NLMR. The temperature dependence and mobility analysis indicate that the NLMR has a purely classical origin, driven by nanoscale inhomogeneities. A large NLMR combined with small device dimensions makes these systems an attractive candidate for on-chip magnetic field sensing.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

Fast image reconstruction for fluorescence microscopy

Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

Confined fluids in a Janus pore: influence of surface asymmetry on structure and solvation forces

Density distribution, fluid structure and solvation forces for fluids confined in Janus slit-shaped pores are investigated using grand canonical Monte Carlo simulations. By varying the degree of asymmetry between the two smooth surfaces that make up the slit pores, a wide variety of adsorption situations are observed. The presence of one moderately attractive surface in the asymmetric pore is sufficient to disrupt the formation of frozen phases observed in the symmetric case. In the extreme case of asymmetry in which one wall is repulsive, the pore fluid can consist of a frozen contact layer at the attractive surface for smaller surface separations (H) or a frozen contact layer with liquid-like and gas-like regions as the pore width is increased. The superposition approximation, wherein the solvation pressure and number density in the asymmetric pores can be obtained from the results on symmetric pores, is found to be accurate for H > 4 sigma(ff), where sigma(ff) is the Lennard-Jones fluid diameter and within 10% accuracy for smaller surface separations. Our study has implications in controlling stick slip and overcoming static friction `stiction' in micro and nanofluidic devices.

Frequency domain turbo equalization for MIMO-CPSC systems with large delay spreads

In this paper, we consider low-complexity turbo equalization for multiple-input multiple-output (MIMO) cyclic prefixed single carrier (CPSC) systems in MIMO inter-symbol interference (ISI) channels characterized by large delay spreads. A low-complexity graph based equalization is carried out in the frequency domain. Because of the reduction in correlation among the noise samples that happens for large frame sizes and delay spreads in frequency domain processing, improved performance compared to time domain processing is shown to be achieved. This improved performance is attractive for equalization in severely delay spread ISI channels like ultrawideband channels and underwater acoustic channels.

Unraveling siRNA unzipping kinetics with graphene

Using all atom molecular dynamics simulations, we report spontaneous unzipping and strong binding of small interfering RNA (siRNA) on graphene. Our dispersion corrected density functional theory based calculations suggest that nucleosides of RNA have stronger attractive interactions with graphene as compared to DNA residues. These stronger interactions force the double stranded siRNA to spontaneously unzip and bind to the graphene surface. Unzipping always nucleates at one end of the siRNA and propagates to the other end after few base-pairs get unzipped. While both the ends get unzipped, the middle part remains in double stranded form because of torsional constraint. Unzipping probability distributions fitted to single exponential function give unzipping time (tau) of the order of few nanoseconds which decrease exponentially with temperature. From the temperature variation of unzipping time we estimate the energy barrier to unzipping. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4742189]

Stabilization and Structural Alteration of the G-Quadruplex DNA Made from the Human Telomeric Repeat Mediated by Troger's Base Based Novel Benzimidazole Derivatives

Ligand-induced stabilization of the G-quadruplex DNA structure derived from the single-stranded 3'-overhang of the telomeric DNA is an attractive strategy for the inhibition of the telomerase activity. The agents that can induce/stabilize a DNA sequence into a G-quadruplex structure are therefore potential anticancer drugs. Herein we present the first report of the interactions of two novel bisbenzimidazoles (TBBz1 and TBBz2) based on Troger's base skeleton with the G-quadruplex DNA (G4DNA). These Troger's base molecules stabilize the G4DNA derived from a human telomeric sequence. Evidence of their strong interaction with the G4DNA has been obtained from CD spectroscopy, thermal denaturation, and UV-vis titration studies. These ligands also possess significantly higher affinity toward the G4DNA over the duplex DNA. The above results obtained are in excellent agreement with the biological activity, measured in vitro using a modified TRAP assay. Furthermore, the ligands are selectively more cytotoxic toward the cancerous cells than the corresponding noncancerous cells. Computational studies suggested that the adaptive scaffold might allow these ligands to occupy not only the G-quartet planes but also the grooves of the G4DNA.

Urea-based constructs readily amplify and attenuate nonlinear optical activity in response to H-bonding and anion recognition

Urea-based molecular constructs are shown for the first time to be nonlinear optically (NLO) active in solution. We demonstrate self-assembly triggered large amplification and specific anion recognition driven attenuation of the NLO activity. This orthogonal modulation along with an excellent nonlinearity-transparency trade-off makes them attractive NLO probes for studies related to weak self-assembly and anion transportation by second harmonic microscopy.

Spatial Modulation and Space Shift Keying in Single Carrier Communication

Spatial modulation (SM) and space shift keying (SSK) are relatively new modulation techniques which are attractive in multi-antenna communications. Single carrier (SC) systems can avoid the peak-to-average power ratio (PAPR) problem encountered in multicarrier systems. In this paper, we study SM and SSK signaling in cyclic-prefixed SC (CPSC) systems on MIMO-ISI channels. We present a diversity analysis of MIMO-CPSC systems under SSK and SM signaling. Our analysis shows that the diversity order achieved by (n(t), n(r)) SSK scheme and (n(t), n(r), Theta(M)) SM scheme in MIMO-CPSC systems under maximum-likelihood (ML) detection is n(r), where n(t), n(r) denote the number of transmit and receive antennas and Theta(M) denotes the modulation alphabet of size M. Bit error rate (BER) simulation results validate this predicted diversity order. Simulation results also show that MIMO-CPSC with SM and SSK achieves much better performance than MIMO-OFDM with SM and SSK.

Graphene transistors for CMOS applications: opportunities and challenges

In the last decade, there has been a tremendous interest in Graphene transistors. The greatest advantage for CMOS nanoelectronics applications is the fact that Graphene is compatible with planar CMOS technology and potentially offers excellent short channel properties. Because of the zero bandgap, it will not be possible to turn off the MOSFET efficiently and hence the typical on current to off current ratio (Ion/Ioff) has been less than 10. Several techniques have been proposed to open the bandgap in Graphene. It has been demonstrated, both theoretically and experimentally, that Graphene Nanoribbons (GNR) show a bandgap which is inversely proportional to their width. GNRs with about 20 nm width have bandgaps in the range of 100meV. But it is very difficult to obtain GNRs with well defined edges. An alternate technique to open the band gap is to use bilayer Graphene (BLG), with an asymmetric bias applied in the direction perpendicular to their plane. Another important CMOS metric, the subthreshold slope is also limited by the inability to turn off the transistor. However, these devices could be attractive for RF CMOS applications. But even for analog and RF applications the non-saturating behavior of the drain current can be an issue. Although some studies have reported current saturation, the mechanisms are still not very clear. In this talk we present some of our recent findings, based on simulations and experiments, and propose possible solutions to obtain high on current to off current ratio. A detailed study on high field transport in grapheme transistors, relevant for analog and RF applications will also be presented.