Linear programming approach for state estimation incorporating phasor measurements

This paper presents methodologies for incorporating phasor measurements into conventional state estimator. The angle measurements obtained from Phasor Measurement Units are handled as angle difference measurements rather than incorporating the angle measurements directly. Handling in such a manner overcomes the problems arising due to the choice of reference bus. Current measurements obtained from Phasor Measurement Units are treated as equivalent pseudo-voltage measurements at the neighboring buses. Two solution approaches namely normal equations approach and linear programming approach are presented to show how the Phasor Measurement Unit measurements can be handled. Comparative evaluation of both the approaches is also presented. Test results on IEEE 14 bus system are presented to validate both the approaches.

Linear Coding Schemes for the Distributed Computation of Subspaces

Let X-1,..., X-m be a set of m statistically dependent sources over the common alphabet F-q, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation setting in which the receiver is interested in the lossless computation of the elements of an s-dimensional subspace W spanned by the elements of the row vector X-1,..., X-m]Gamma in which the (m x s) matrix Gamma has rank s. A sequence of three increasingly refined approaches is presented, all based on linear encoders. The first approach uses a common matrix to encode all the sources and a Korner-Marton like receiver to directly compute W. The second improves upon the first by showing that it is often more efficient to compute a carefully chosen superspace U of W. The superspace is identified by showing that the joint distribution of the {X-i} induces a unique decomposition of the set of all linear combinations of the {X-i}, into a chain of subspaces identified by a normalized measure of entropy. This subspace chain also suggests a third approach, one that employs nested codes. For any joint distribution of the {X-i} and any W, the sum-rate of the nested code approach is no larger than that under the Slepian-Wolf (SW) approach. Under the SW approach, W is computed by first recovering each of the {X-i}. For a large class of joint distributions and subspaces W, the nested code approach is shown to improve upon SW. Additionally, a class of source distributions and subspaces are identified, for which the nested-code approach is sum-rate optimal.

Sonic hedgehog-Dependent Induction of MicroRNA 31 and MicroRNA 150 Regulates Mycobacterium bovis BCG-Driven Toll-Like Receptor 2 Signaling

Hedgehog (HH) signaling is a significant regulator of cell fate decisions during embryogenesis, development, and perpetuation of various disease conditions. Testing whether pathogen-specific HH signaling promotes unique innate recognition of intracellular bacteria, we demonstrate that among diverse Gram-positive or Gram-negative microbes, Mycobacterium bovis BCG, a vaccine strain, elicits a robust activation of Sonic HH (SHH) signaling in macrophages. Interestingly, sustained tumor necrosis factor alpha (TNF-alpha) secretion by macrophages was essential for robust SHH activation, as TNF-alpha(-/-) macrophages exhibited compromised ability to activate SHH signaling. Neutralization of TNF-alpha or blockade of TNF-alpha receptor signaling significantly reduced the infection-induced SHH signaling activation both in vitro and in vivo. Intriguingly, activated SHH signaling downregulated M. bovis BCG-mediated Toll-like receptor 2 (TLR2) signaling events to regulate a battery of genes associated with divergent functions of M1/M2 macrophages. Genome-wide expression profiling as well as conventional gain-of-function or loss-of-function analysis showed that SHH signaling-responsive microRNA 31 (miR-31) and miR-150 target MyD88, an adaptor protein of TLR2 signaling, thus leading to suppression of TLR2 responses. SHH signaling signatures could be detected in vivo in tuberculosis patients and M. bovis BCG-challenged mice. Collectively, these investigations identify SHH signaling to be what we believe is one of the significant regulators of host-pathogen interactions.

Structure, molecular dynamics, and stress in a linear polymer

We present a study correlating uniaxial stress in a polymer with its underlying structure when it is strained. The uniaxial stress is significantly influenced by the mean-square bond length and mean bond angle. In contrast, the size and shape of the polymer, typically represented by the end-to-end length, mass ratio, and radius of gyration, contribute negligibly. Among externally set control variables, density and polymer chain length play a critical role in influencing the anisotropic uniaxial stress. Short chain polymers more or less behave like rigid molecules. Temperature and rate of loading, in the range considered, have a very mild effect on the uniaxial stress.

A nine-level inverter topology for medium-voltage induction motor drive with open-end stator winding

A new scheme for nine-level voltage space-vector generation for medium-voltage induction motor (IM) drives with open-end stator winding is presented in this paper. The proposed nine-level power converter topology consists of two conventional three-phase two-level voltage source inverters powered by isolated dc sources and six floating-capacitor-connected H-bridges. The H-bridge capacitor voltages are effectively maintained at the required asymmetrical levels by employing a space vector modulation (SVPWM) based control strategy. An interesting feature of this topology is its ability to function in five-or three-level mode, in the entire modulation range, at full-power rating, in the event of any failure in the H-bridges. This feature significantly improves the reliability of the proposed drive system. Each leg of the three-phase two-level inverters used in this topology switches only for a half cycle of the reference voltage waveform. Hence, the effective switching frequency is reduced by half, resulting in switching loss reduction in high-voltage devices. The transient as well as the steady-state performance of the proposed nine-level inverter-fed IM drive system is experimentally verified in the entire modulation range including the overmodulation region.

A study on the usefulness of Support Vector Machines for the realtime computational simulation of soft biological organs

Realistic and realtime computational simulation of soft biological organs (e.g., liver, kidney) is necessary when one tries to build a quality surgical simulator that can simulate surgical procedures involving these organs. Since the realistic simulation of these soft biological organs should account for both nonlinear material behavior and large deformation, achieving realistic simulations in realtime using continuum mechanics based numerical techniques necessitates the use of a supercomputer or a high end computer cluster which are costly. Hence there is a need to employ soft computing techniques like Support Vector Machines (SVMs) which can do function approximation, and hence could achieve physically realistic simulations in realtime by making use of just a desktop computer. Present work tries to simulate a pig liver in realtime. Liver is assumed to be homogeneous, isotropic, and hyperelastic. Hyperelastic material constants are taken from the literature. An SVM is employed to achieve realistic simulations in realtime, using just a desktop computer. The code for the SVM is obtained from [1]. The SVM is trained using the dataset generated by performing hyperelastic analyses on the liver geometry, using the commercial finite element software package ANSYS. The methodology followed in the present work closely follows the one followed in [2] except that [2] uses Artificial Neural Networks (ANNs) while the present work uses SVMs to achieve realistic simulations in realtime. Results indicate the speed and accuracy that is obtained by employing the SVM for the targeted realistic and realtime simulation of the liver.

Antibody-mediated catalysis: Induction and therapeutic relevance

Abzymes are immunoglobulins endowed with enzymatic activities. The catalytic activity of an abzyme resides in the variable domain of the antibody, which is constituted by the close spatial arrangement of amino acid residues involved in catalysis. The origin of abzymes is conferred by the innate diversity of the immunoglobulin gene repertoire. Under deregulated immune conditions, as in autoimmune diseases, the generation of abzymes to self-antigens could be deleterious. Technical advancement in the ability to generate monoclonal antibodies has been exploited in the generation of abzymes with defined specificities and activities. Therapeutic applications of abzymes are being investigated with the generation of monoclonal abzymes against several pathogenesis-associated antigens. Here, we review the different contexts in which abzymes are generated, and we discuss the relevance of monoclonal abzymes for the treatment of human diseases.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Intravenous immunoglobulin expands regulatory T cells via induction of cyclooxygenase-2-dependent prostaglandin E2 in human dendritic cells

CD4(+)CD25(+)FoxP3(+) regulatory T cells (Tregs) play a critical role in the maintenance of immune tolerance. Intravenous immunoglobulin (IVIg), a therapeutic preparation of normal pooled human IgG, expands Tregs in various experimental models and in patients. However, the cellular and molecular mechanisms by which IVIg expands Tregs are relatively unknown. As Treg expansion in the periphery requires signaling by antigen-presenting cells such as dendritic cells (DCs) and IVIg has been demonstrated to modulate DC functions, we hypothesized that IVIg induces distinct signaling events in DCs that subsequently mediate Treg expansion. We demonstrate that IVIg expands Tregs via induction of cyclooxygenase (COX)-2-dependent prostaglandin E2 (PGE(2)) in human DCs. However, costimulatory molecules of DCs such as programmed death ligands, OX40 ligand, and inducible T-cell costimulator ligands were not implicated. Inhibition of PGE(2) synthesis by COX-2 inhibitors prevented IVIg-mediated Treg expansion in vitro and significantly diminished IVIg-mediated Treg expansion in vivo and protection from disease in experimental autoimmune encephalomyelitis model. IVIg-mediated COX-2 expression, PGE(2) production, and Treg expansion were mediated in part via interaction of IVIg and F(ab('))(2) fragments of IVIg with DC-specific intercellular adhesion molecule-3-grabbing nonintegrin. Our results thus uncover novel cellular and molecular mechanism by which IVIg expands Tregs.

Application of the random eigenvalue problem in forced response analysis of a linear stochastic structure

The random eigenvalue problem arises in frequency and mode shape determination for a linear system with uncertainties in structural properties. Among several methods of characterizing this random eigenvalue problem, one computationally fast method that gives good accuracy is a weak formulation using polynomial chaos expansion (PCE). In this method, the eigenvalues and eigenvectors are expanded in PCE, and the residual is minimized by a Galerkin projection. The goals of the current work are (i) to implement this PCE-characterized random eigenvalue problem in the dynamic response calculation under random loading and (ii) to explore the computational advantages and challenges. In the proposed method, the response quantities are also expressed in PCE followed by a Galerkin projection. A numerical comparison with a perturbation method and the Monte Carlo simulation shows that when the loading has a random amplitude but deterministic frequency content, the proposed method gives more accurate results than a first-order perturbation method and a comparable accuracy as the Monte Carlo simulation in a lower computational time. However, as the frequency content of the loading becomes random, or for general random process loadings, the method loses its accuracy and computational efficiency. Issues in implementation, limitations, and further challenges are also addressed.

Linear and nonlinear optical properties of expanded porphyrins: a DMRG study

We study absorption spectra and two photon absorption coefficient of expanded porphyrins (EPs) by the density matrix renormalization group (DMRG) technique. We employ the Pariser-Parr-Pople (PPP) Hamiltonian which includes long-range electron-electron interactions. We find that, in the 4n+2 EPs, there are two prominent low-lying one-photon excitations, while in 4n EPs, there is only one such excitation. We also find that 4n+2 EPs have large two-photon absorption cross sections compared to 4n EPs. The charge density rearrangement in the one-photon excited state is mostly at the pyrrole nitrogen site and at the meso carbon sites. In the two-photon states, the charge density rearrangement occurs mostly at the aza-ring sites. In the one-photon state, the C-C bond length in aza rings shows a tendency to become uniform. In the two-photon state, the bond distortions are on C-N bonds of the pyrrole ring and the adjoining C-C bonds which connect the pyrrole ring to the aza or meso carbon sites.

Induction of Supramolecular Chirality in the Self-Assemblies of Lipophilic Pyrimidine Derivatives by Choice of the Amino Acid-Based Chiral Spacer

A new family of supramolecular organogelators, based on chiral amino acid derivatives of 2,4,6-trichloro-pyrimidine-5-carbaldehyde, has been synthesized. L-alanine was incorporated as a spacer between the pyrimidine core and long hydrocarbon tails to compare the effect of chirality and hydrogen bonding to that of the achiral analogue. The role of aromatic moiety on the chiral spacer was also investigated by introducing L-phenyl alanine moieties. The presence of intermolecular hydrogen-bonding leading to the chiral self-assembly was probed by concentration-dependent FTIR and UV/Vis spectroscopies, in addition to circular dichroism (CD) studies. Temperature and concentration-dependent CD spectroscopy ascribed to the formation of -sheet-type H-bonded networks. The morphology and the arrangements of the molecules in the freeze-dried gels were examined by scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and X-ray diffraction (XRD) techniques. Calculation of the length of each molecular system by energy minimization in its extended conformation and comparison with the small-angle XRD pattern reveals that this class of gelator molecules adopts a lamellar organization. Polarized optical microscopy (POM) and differential scanning calorimetry (DSC) indicate that the solid state phase behavior of these molecules is totally dependent on the choice of their amino acid spacers. Structure-induced aggregation properties based on the H-bonding motifs and the packing of the molecule in three dimensions leading to gelation was elucidated by rheological studies. However, viscoelasticity was shown to depend only marginally on the H-bonding interactions; rather it depends on the packing of the gelators to a greater extent.

A nearly constant switching frequency current hysteresis controller with generalized parabolic boundaries using 12-sided polygonal voltage space vectors for IM drives

In this paper, a current hysteresis controller with parabolic boundaries for a 12-sided polygonal voltage space vector inverter fed induction motor (IM) drive is proposed. Parabolic boundaries with generalized vector selection logic, valid for all sectors and rotational direction, is used in the proposed controller. The current error space phasor boundary is obtained by first studying the drive scheme with space vector based PWM (SVPWM) controller. Four parabolas are used to approximate this current error space phasor boundary. The system is then run with space phasor based hysteresis PWM controller by limiting the current error space vector (CESV) within the parabolic boundary. The proposed controller has simple controller implementation, nearly constant switching frequency, extended modulation range and fast dynamic response with smooth transition to the over modulation region.