Optimal MSE solution for a decision feedback equalizer

Due to the inherent feedback in a decision feedback equalizer (DFE) the minimum mean square error (MMSE) or Wiener solution is not known exactly. The main difficulty in such analysis is due to the propagation of the decision errors, which occur because of the feedback. Thus in literature, these errors are neglected while designing and/or analyzing the DFEs. Then a closed form expression is obtained for Wiener solution and we refer this as ideal DFE (IDFE). DFE has also been designed using an iterative and computationally efficient alternative called least mean square (LMS) algorithm. However, again due to the feedback involved, the analysis of an LMS-DFE is not known so far. In this paper we theoretically analyze a DFE taking into account the decision errors. We study its performance at steady state. We then study an LMS-DFE and show the proximity of LMS-DFE attractors to that of the optimal DFE Wiener filter (obtained after considering the decision errors) at high signal to noise ratios (SNR). Further, via simulations we demonstrate that, even at moderate SNRs, an LMS-DFE is close to the MSE optimal DFE. Finally, we compare the LMS DFE attractors with IDFE via simulations. We show that an LMS equalizer outperforms the IDFE. In fact, the performance improvement is very significant even at high SNRs (up to 33%), where an IDFE is believed to be closer to the optimal one. Towards the end, we briefly discuss the tracking properties of the LMS-DFE.

Bipolar Poisson Solution for Independent Double-Gate MOSFET

We propose a new set of input voltage equations (IVEs) for independent double-gate MOSFET by solving the governing bipolar Poisson equation (PE) rigorously. The proposed IVEs, which involve the Legendre's incomplete elliptic integral of the first kind and Jacobian elliptic functions and are valid from accumulation to inversion regimes, are shown to have good agreement with the numerical solution of the same PE for all bias conditions.

Physics-Based Solution for Electrical Resistance of Graphene Under Self-Heating Effect

In this brief, we present a physics-based solution for the temperature-dependent electrical resistance of a suspended metallic single-layer graphene (SLG) sheet under Joule self-heating. The effect of in-plane and flexural phonons on the electron scattering rates for a doped SLG layer has been considered, which particularly demonstrates the variation of the electrical resistance with increasing temperature at different current levels using the solution of the self-heating equation. The present solution agrees well with the available experimental data done with back-gate electrostatic method over a wide range of temperatures.

IceCube: efficient targeted mining in data cubes

We address the problem of mining targeted association rules over multidimensional market-basket data. Here, each transaction has, in addition to the set of purchased items, ancillary dimension attributes associated with it. Based on these dimensions, transactions can be visualized as distributed over cells of an n-dimensional cube. In this framework, a targeted association rule is of the form {X -> Y} R, where R is a convex region in the cube and X. Y is a traditional association rule within region R. We first describe the TOARM algorithm, based on classical techniques, for identifying targeted association rules. Then, we discuss the concepts of bottom-up aggregation and cubing, leading to the CellUnion technique. This approach is further extended, using notions of cube-count interleaving and credit-based pruning, to derive the IceCube algorithm. Our experiments demonstrate that IceCube consistently provides the best execution time performance, especially for large and complex data cubes.

Algorithm for mining outliers in categorical data through ranking

The rapid growth in the field of data mining has lead to the development of various methods for outlier detection. Though detection of outliers has been well explored in the context of numerical data, dealing with categorical data is still evolving. In this paper, we propose a two-phase algorithm for detecting outliers in categorical data based on a novel definition of outliers. In the first phase, this algorithm explores a clustering of the given data, followed by the ranking phase for determining the set of most likely outliers. The proposed algorithm is expected to perform better as it can identify different types of outliers, employing two independent ranking schemes based on the attribute value frequencies and the inherent clustering structure in the given data. Unlike some existing methods, the computational complexity of this algorithm is not affected by the number of outliers to be detected. The efficacy of this algorithm is demonstrated through experiments on various public domain categorical data sets.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Chemical unfolding of chicken villin headpiece in aqueous dimethyl sulfoxide solution: cosolvent concentration dependence, pathway, and microscopic mechanism

Unfolding of a protein often proceeds through partial unfolded intermediate states (PUIS). PUIS have been detected in several experimental and simulation studies. However, complete analyses of transitions between different PUIS and the unfolding trajectory are sparse. To understand such dynamical processes, we study chemical unfolding of a small protein, chicken villin head piece (HP-36), in aqueous dimethyl sulfoxide (DMSO) solution. We carry out molecular dynamics simulations at various solution compositions under ambient conditions. In each concentration, the initial step of unfolding involves separation of two adjacent native contacts, between phenyl alanine residues (11-18 and 7-18). This first step induces, under appropriate conditions, subsequent separation among other hydrophobic contacts, signifying a high degree of cooperativity in the unfolding process. The observed sequence of structural changes in HP-36 on increasing DMSO concentration and the observed sequence of PUIS, are in approximate agreement with earlier simulation results (in pure water) and experimental observations on unfolding of HP-36. Peculiar to water-DMSO mixture, an intervening structural transformation (around 15% of DMSO) in the binary mixture solvent retards the progression of unfolding as composition is increased. This is reflected in a remarkable nonmonotonic composition dependence of RMSD, radius of gyration and the fraction of native contacts. At 30% mole fraction of DMSO, we find the extended randomly coiled structure of the unfolded protein. The molecular mechanism of DMSO induced unfolding process is attributed to the initial preferential solvation of the hydrophobic side chain atoms through the methyl groups of DMSO, followed by the hydrogen bonding of the oxygen atom of DMSO to the exposed backbone NH groups of HP-36.

Development of uniformly grown ZnO NPs films using single precursor solution by pulsed spray pyrolysis technique

In this article, we have reported the controlled synthesis of uniformly grown zinc oxide nanoparticles (ZnO NPs) films by a simple, low-cost, and scalable pulsed spray pyrolysis technique. From the surface analysis it is noticed that the as-deposited films have uniformly dispersed NPs-like morphology. The structural studies reveal that these NPs films have highly crystalline hexagonal crystal structure, which are preferentially orientated along the (001) planes. The size of the NPs varied between 5 and 100 nm, and exhibited good stoichiometric chemical composition. Raman spectroscopic analysis reveals that these ZnO NPs films have pure single phase and hexagonal crystal structure. These unique nanostructured films exhibited a low electrical resistivity (5 Omega cm) and high light transmittance (90 %) in visible region.

Synthesis of nanosized Ce0.85M0.1Ru0.05O2-delta (M = Si, Fe) solid solution exhibiting high CO oxidation and water gas shift activity

Nanosized Ce0.85M0.1Ru0.05O2-delta (M = Si, Fe) has been synthesized using a low temperature sonication method and characterized using XRD, TEM, XPS and H-2-TPR. The potential application of both the solid solutions has been explored as exhaust catalysts by performing CO oxidation. The addition of Si- and Fe-in Ce0.95Ru0.05O2-delta greatly enhanced the reducibility of Ce0.85M0.1Ru0.05O2-delta (M = Si, Fe), as indicated by the H-2-TPR study. The oxygen storage capacity has been used to correlate surface oxygen reactivity to the CO oxidation activity. Both the compounds reversibly release lattice oxygen and exhibit excellent CO oxidation activity with 99% conversion below 200 degrees C. A bifunctional reaction mechanism involving CO oxidation by the extraction of lattice oxygen and rejuvenation of oxide vacancy with gas feed O-2 has been used to correlate experimental data. The performance of both the solid solutions has also been investigated for energy application by performing the water gas shift reaction. The present catalysts are highly active and selective towards the hydrogen production and a lack of methanation activity is an important finding of present study.

Interdiffusion and solid solution strengthening in Ni-Co-Pt and Ni-Co-Fe ternary systems

Diffusion couple experiments are conducted in Co-Ni-Pt system at 1200 degrees C and in Co-Ni-Fe system at 1150 degrees C, by coupling binary alloys with the third element. Uphill diffusion is observed for both Co and Ni in Pt rich corner of the Co-Ni-Pt system, whereas in the Co-Ni-Fe system, it is observed for Co. Main and cross interdiffusion coefficients are calculated at the composition of intersection of two independent diffusion profiles. In both the systems, the main interdiffusion coefficients are positive over the whole composition range and the cross interdiffusion coefficients show both positive and negative values at different regions. Hardness measured by performing the nanoindentations on diffusion couples of both the systems shows the higher values at intermediate compositions.

Solution nuclear magnetic resonance structure of the GATase subunit and structural Basis of the interaction between GATase and ATPPase subunits in a two-subunit-type GMPS from methanocaldococcus jannaschii

The solution structure of the monomeric glutamine amidotransferase (GATase) subunit of the Methanocaldococcus janaschii (Mj) guanosine monophosphate synthetase (GMPS) has been determined using high-resolution nuclear magnetic resonance methods. Gel filtration chromatography and N-15 backbone relaxation studies have shown that the Mj GATase subunit is present in solution as a 21 kDa (188-residue) monomer. The ensemble of 20 lowest-energy structures showed root-mean-square deviations of 0.35 +/- 0.06 angstrom for backbone atoms and 0.8 +/- 0.06 angstrom for all heavy atoms. Furthermore, 99.4% of the backbone dihedral angles are present in the allowed region of the Ramachandran map, indicating the stereochemical quality of the structure. The core of the tertiary structure of the GATase is composed of a seven-stranded mixed beta-sheet that is fenced by five alpha-helices. The Mj GATase is similar in structure to the Pyrococcus horikoshi (Ph) GATase subunit. Nuclear magnetic resonance (NMR) chemical shift perturbations and changes in line width were monitored to identify residues on GATase that were responsible for interaction with magnesium and the ATPPase subunit, respectively. These interaction studies showed that a common surface exists for the metal ion binding as well as for the protein-protein interaction. The dissociation constant for the GATase-Mg2+ interaction has been found to be similar to 1 mM, which implies that interaction is very weak and falls in the fast chemical exchange regime. The GATase-ATPPase interaction, on the other hand, falls in the intermediate chemical exchange regime on the NMR time scale. The implication of this interaction in terms of the regulation of the GATase activity of holo GMPS is discussed.

Mining large-scale response networks reveals `topmost activities' in Mycobacterium tuberculosis infection

Mycobacterium tuberculosis owes its high pathogenic potential to its ability to evade host immune responses and thrive inside the macrophage. The outcome of infection is largely determined by the cellular response comprising a multitude of molecular events. The complexity and inter-relatedness in the processes makes it essential to adopt systems approaches to study them. In this work, we construct a comprehensive network of infection-related processes in a human macrophage comprising 1888 proteins and 14,016 interactions. We then compute response networks based on available gene expression profiles corresponding to states of health, disease and drug treatment. We use a novel formulation for mining response networks that has led to identifying highest activities in the cell. Highest activity paths provide mechanistic insights into pathogenesis and response to treatment. The approach used here serves as a generic framework for mining dynamic changes in genome-scale protein interaction networks.

Fast Eigen solution for homogeneous quadratic minimization with at most three constraints

We propose an eigenvalue based technique to solve the Homogeneous Quadratic Constrained Quadratic Programming problem (HQCQP) with at most three constraints which arise in many signal processing problems. Semi-Definite Relaxation (SDR) is the only known approach and is computationally intensive. We study the performance of the proposed fast eigen approach through simulations in the context of MIMO relays and show that the solution converges to the solution obtained using the SDR approach with significant reduction in complexity.

Solution of Time Dependent Joule Heat Equation for a Graphene Sheet Under Thomson Effect

We address a physics-based solution of joule heating phenomenon in a single-layer graphene (SLG) sheet under the presence of Thomson effect. We demonstrate that the temperature in an isotopically pure (containing only C-12) SLG sheet attains its saturation level quicker than when doped with its isotopes (C-13). From the solution of the joule heating equation, we find that the thermal time constant of the SLG sheet is in the order of tenths of a nanosecond for SLG dimensions of a few micrometers. These results have been formulated using the electron interactions with the inplane and flexural phonons to demonstrate a field-dependent Landauer transmission coefficient. We further develop an analytical model of the SLG specific heat using the quadratic (out of plane) phonon band structure over the room temperature. Additionally, we show that a cooling effect in the SLG sheet can be substantially enhanced with the addition of C-13. The methodologies as discussed in this paper can be put forward to analyze the graphene heat spreader theory.

Steric and Electronic Interactions Controlling the cis/trans Isomer Equilibrium at X-Pro Tertiary Amide Motifs in Solution

A systematic understanding of the noncovalent interactions that influence the structures of the cis conformers and the equilibrium between the cis and the trans conformers, of the X-Pro tertiary amide motifs, is presented based on analyses of H-1-, C-13-NMR and FTIR absorption spectra of two sets of homologous peptides, X-Pro-Aib-OMe and X-Pro-NH-Me (where X is acetyl, propionyl, isobutyryl and pivaloyl), in solvents of varying polarities. First, this work shows that the cis conformers of any X-Pro tertiary amide motif, including Piv-Pro, are accessible in the new motifs X-Pro-Aib-OMe, in solution. These conformers are uniquely observable by FTIR spectroscopy at ambient temperatures and by NMR spectroscopy from temperatures as high as 273 K. This is made possible by the persistent presence of n(i-1i)* interactions at Aib, which also influence the disappearance of steric effects at these cis X-Pro rotamers. Second, contrary to conventional understanding, the energy contribution of steric effects to the cis/trans equilibrium at the X-Pro motifs is found to be nonvariant (0.54 +/- 0.02 kcal/mol) with increase in steric bulk on the X group. Third, the current studies provide direct evidence for the weak intramolecular interactions namely the n(i-1i)*, the N-Pro center dot center dot center dot Hi+1 (C(5)a), and the C-7 hydrogen bond that operate and influence the structures, stabilities, and dynamics between different conformational states of X-Pro tertiary amide motifs. NMR and IR spectral data suggest that the cis conformers of X-Pro motifs are ensembles of short-lived rotamers about the C-X-N-Pro bond. (c) 2013 Wiley Periodicals, Inc. Biopolymers 101: 66-77, 2014.