Effect of choice of basis functions in neural network for capturing unknown function for dynamic inversion control

The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.

The relationship between classification of multi-domain proteins using an alignment-free approach and their functions: a case study with immunoglobulins

Establishing functional relationships between multi-domain protein sequences is a non-trivial task. Traditionally, delineating functional assignment and relationships of proteins requires domain assignments as a prerequisite. This process is sensitive to alignment quality and domain definitions. In multi-domain proteins due to multiple reasons, the quality of alignments is poor. We report the correspondence between the classification of proteins represented as full-length gene products and their functions. Our approach differs fundamentally from traditional methods in not performing the classification at the level of domains. Our method is based on an alignment free local matching scores (LMS) computation at the amino-acid sequence level followed by hierarchical clustering. As there are no gold standards for full-length protein sequence classification, we resorted to Gene Ontology and domain-architecture based similarity measures to assess our classification. The final clusters obtained using LMS show high functional and domain architectural similarities. Comparison of the current method with alignment based approaches at both domain and full-length protein showed superiority of the LMS scores. Using this method we have recreated objective relationships among different protein kinase sub-families and also classified immunoglobulin containing proteins where sub-family definitions do not exist currently. This method can be applied to any set of protein sequences and hence will be instrumental in analysis of large numbers of full-length protein sequences.

End point estimates for Radon transform of radial functions on non-Euclidean spaces

We prove end point estimate for Radon transform of radial functions on affine Grasamannian and real hyperbolic space. We also discuss analogs of these results on the sphere.

The Ginibre Ensemble and Gaussian Analytic Functions

We show that as n changes, the characteristic polynomial of the n x n random matrix with i.i.d. complex Gaussian entries can be described recursively through a process analogous to Polya's urn scheme. As a result, we get a random analytic function in the limit, which is given by a mixture of Gaussian analytic functions. This suggests another reason why the zeros of Gaussian analytic functions and the Ginibre ensemble exhibit similar local repulsion, but different global behavior. Our approach gives new explicit formulas for the limiting analytic function.

Analytical test functions for free vibration analysis of rotating non-homogeneous Timoshenko beams

In this paper, the governing equations for free vibration of a non-homogeneous rotating Timoshenko beam, having uniform cross-section, is studied using an inverse problem approach, for both cantilever and pinned-free boundary conditions. The bending displacement and the rotation due to bending are assumed to be simple polynomials which satisfy all four boundary conditions. It is found that for certain polynomial variations of the material mass density, elastic modulus and shear modulus, along the length of the beam, the assumed polynomials serve as simple closed form solutions to the coupled second order governing differential equations with variable coefficients. It is found that there are an infinite number of analytical polynomial functions possible for material mass density, shear modulus and elastic modulus distributions, which share the same frequency and mode shape for a particular mode. The derived results are intended to serve as benchmark solutions for testing approximate or numerical methods used for the vibration analysis of rotating non-homogeneous Timoshenko beams.

The HORMA domain: an evolutionarily conserved domain discovered in chromatin-associated proteins, has unanticipated diverse functions

The HORMA domain (for Hop1p, Rev7p and MAD2) was discovered in three chromatin-associated proteins in the budding yeast Saccharomyces cerevisiae. This domain has also been found in proteins with similar functions in organisms including plants, animals and nematodes. The HORMA domain containing proteins are thought to function as adaptors for meiotic checkpoint protein signaling and in the regulation of meiotic recombination. Surprisingly, new work has disclosed completely unanticipated and diverse functions for the HORMA domain containing proteins. A. M. Villeneuve and colleagues (Schvarzstein et al., 2013) show that meiosis-specific HORMA domain containing proteins plays a vital role in preventing centriole disengagement during Caenorhabditis elegans spermatocyte meiosis. Another recent study reveals that S. cerevisiae Atg13 HORMA domain acts as a phosphorylation-dependent conformational switch in the cellular autophagic process. (C) 2014 Elsevier B.V. All rights reserved.

Magmas functions as a ROS regulator and provides cytoprotection against oxidative stress-mediated damages

Redox imbalance generates multiple cellular damages leading to oxidative stress-mediated pathological conditions such as neurodegenerative diseases and cancer progression. Therefore, maintenance of reactive oxygen species (ROS) homeostasis is most important that involves well-defined antioxidant machinery. In the present study, we have identified for the first time a component of mammalian protein translocation machinery Magmas to perform a critical ROS regulatory function. Magmas overexpression has been reported in highly metabolically active tissues and cancer cells that are prone to oxidative damage. We found that Magmas regulates cellular ROS levels by controlling its production as well as scavenging. Magmas promotes cellular tolerance toward oxidative stress by enhancing antioxidant enzyme activity, thus preventing induction of apoptosis and damage to cellular components. Magmas enhances the activity of electron transport chain (ETC) complexes, causing reduced ROS production. Our results suggest that J-like domain of Magmas is essential for maintenance of redox balance. The function of Magmas as a ROS sensor was found to be independent of its role in protein import. The unique ROS modulatory role of Magmas is highlighted by its ability to increase cell tolerance to oxidative stress even in yeast model organism. The cytoprotective capability of Magmas against oxidative damage makes it an important candidate for future investigation in therapeutics of oxidative stress-related diseases.

Improved quasiparticle wave functions and mean field for G(0)W(0) calculations: Initialization with the COHSEX operator

The GW approximation to the electron self-energy has become a standard method for ab initio calculation of excited-state properties of condensed-matter systems. In many calculations, the G W self-energy operator, E, is taken to be diagonal in the density functional theory (DFT) Kohn-Sham basis within the G0 W0 scheme. However, there are known situations in which this diagonal Go Wo approximation starting from DFT is inadequate. We present two schemes to resolve such problems. The first, which we called sc-COHSEX-PG W, involves construction of an improved mean field using the static limit of GW, known as COHSEX (Coulomb hole and screened exchange), which is significantly simpler to treat than GW W. In this scheme, frequency-dependent self energy E(N), is constructed and taken to be diagonal in the COHSEX orbitals after the system is solved self-consistently within this formalism. The second method is called off diagonal-COHSEX G W (od-COHSEX-PG W). In this method, one does not self-consistently change the mean-field starting point but diagonalizes the COHSEX Hamiltonian within the Kohn-Sham basis to obtain quasiparticle wave functions and uses the resulting orbitals to construct the G W E in the diagonal form. We apply both methods to a molecular system, silane, and to two bulk systems, Si and Ge under pressure. For silane, both methods give good quasiparticle wave functions and energies. Both methods give good band gaps for bulk silicon and maintain good agreement with experiment. Further, the sc-COHSEX-PGW method solves the qualitatively incorrect DFT mean-field starting point (having a band overlap) in bulk Ge under pressure.

Attractive holographic c-functions

Using the attractor mechanism for extremal solutions in N = 2 gauged supergravity, we construct a c-function that interpolates between the central charges of theories at ultraviolet and infrared conformal fixed points corresponding to anti-de Sitter geometries. The c-function we obtain is couched purely in terms of bulk quantities and connects two different dimensional CFTs at the stable conformal fixed points under the RG flow.

Solving Dynamic Constraint Single Objective Functions using a Nature Inspired Technique

We present in this paper a new algorithm based on Particle Swarm Optimization (PSO) for solving Dynamic Single Objective Constrained Optimization (DCOP) problems. We have modified several different parameters of the original particle swarm optimization algorithm by introducing new types of particles for local search and to detect changes in the search space. The algorithm is tested with a known benchmark set and compare with the results with other contemporary works. We demonstrate the convergence properties by using convergence graphs and also the illustrate the changes in the current benchmark problems for more realistic correspondence to practical real world problems.

Lower bounds for testing triangle-freeness in Boolean functions

Given a Boolean function , we say a triple (x, y, x + y) is a triangle in f if . A triangle-free function contains no triangle. If f differs from every triangle-free function on at least points, then f is said to be -far from triangle-free. In this work, we analyze the query complexity of testers that, with constant probability, distinguish triangle-free functions from those -far from triangle-free. Let the canonical tester for triangle-freeness denotes the algorithm that repeatedly picks x and y uniformly and independently at random from , queries f(x), f(y) and f(x + y), and checks whether f(x) = f(y) = f(x + y) = 1. Green showed that the canonical tester rejects functions -far from triangle-free with constant probability if its query complexity is a tower of 2's whose height is polynomial in . Fox later improved the height of the tower in Green's upper bound to . A trivial lower bound of on the query complexity is immediate. In this paper, we give the first non-trivial lower bound for the number of queries needed. We show that, for every small enough , there exists an integer such that for all there exists a function depending on all n variables which is -far from being triangle-free and requires queries for the canonical tester. We also show that the query complexity of any general (possibly adaptive) one-sided tester for triangle-freeness is at least square root of the query complexity of the corresponding canonical tester. Consequently, this means that any one-sided tester for triangle-freeness must make at least queries.

Typical and atypical domain combinations in human protein kinases: functions, disease causing mutations and conservation in other primates

Ser/Thr and Tyr protein kinases orchestrate many signalling pathways and hence loss in this balance leads to many disease phenotypes. Due to their high abundance, diversity and importance, efforts have been made in the past to classify kinases and annotate their functions at both gross and fine levels. These kinases are conventionally classified into subfamilies based on the sequences of catalytic domains. Usually the domain architecture of a full-length kinase is consistent with the subfamily classification made based on the sequence of kinase domain. Important contributions of modular domains to the overall function of the kinase are well known. Recently occurrence of two kinds of outlier kinases-''Hybrid'' and ``Rogue'' has been reported. These show considerable deviations in their domain architectures from the typical domain architecture known for the classical kinase subfamilies. This article provides an overview of the different subfamilies of human kinases and the role of non-kinase domains in functions and diseases. Importantly this article provides analysis of hybrid and rogue kinases encoded in the human genome and highlights their conservation in closely related primate species. These kinases are examples of elegant rewiring to bring about subtle functional differences compared to canonical variants.

Novel Functions of (p)ppGpp and Cyclic di-GMP in Mycobacterial Physiology Revealed by Phenotype Microarray Analysis of Wild-Type and Isogenic Strains of Mycobacterium smegmatis

The bacterial second messengers (p)ppGpp and bis-(3'-5')-cyclic dimeric GMP (c-di-GMP) regulate important functions, such as transcription, virulence, biofilm formation, and quorum sensing. In mycobacteria, they regulate long-term survival during starvation, pathogenicity, and dormancy. Recently, a Pseudomonas aeruginosa strain lacking (p) ppGpp was shown to be sensitive to multiple classes of antibiotics and defective in biofilm formation. We were interested to find out whether Mycobacterium smegmatis strains lacking the gene for either (p)ppGpp synthesis (Delta rel(Msm)) or c-di-GMP synthesis (Delta dcpA) would display similar phenotypes. We used phenotype microarray technology to compare the growth of the wild-type and the knockout strains in the presence of several antibiotics. Surprisingly, the Delta rel(Msm) and Delta dcpA strains showed enhanced survival in the presence of many antibiotics, but they were defective in biofilm formation. These strains also displayed altered surface properties, like impaired sliding motility, rough colony morphology, and increased aggregation in liquid cultures. Biofilm formation and surface properties are associated with the presence of glycopeptidolipids (GPLs) in the cell walls of M. smegmatis. Thin-layer chromatography analysis of various cell wall fractions revealed that the levels of GPLs and polar lipids were reduced in the knockout strains. As a result, the cell walls of the knockout strains were significantly more hydrophobic than those of the wild type and the complemented strains. We hypothesize that reduced levels of GPLs and polar lipids may contribute to the antibiotic resistance shown by the knockout strains. Altogether, our data suggest that (p)ppGpp and c-di-GMP may be involved in the metabolism of glycopeptidolipids and polar lipids in M. smegmatis.

Mode coupling theory analysis of electrolyte solutions: Time dependent diffusion, intermediate scattering function, and ion solvation dynamics

A self-consistent mode coupling theory (MCT) with microscopic inputs of equilibrium pair correlation functions is developed to analyze electrolyte dynamics. We apply the theory to calculate concentration dependence of (i) time dependent ion diffusion, (ii) intermediate scattering function of the constituent ions, and (iii) ion solvation dynamics in electrolyte solution. Brownian dynamics with implicit water molecules and molecular dynamics method with explicit water are used to check the theoretical predictions. The time dependence of ionic self-diffusion coefficient and the corresponding intermediate scattering function evaluated from our MCT approach show quantitative agreement with early experimental and present Brownian dynamic simulation results. With increasing concentration, the dispersion of electrolyte friction is found to occur at increasingly higher frequency, due to the faster relaxation of the ion atmosphere. The wave number dependence of intermediate scattering function, F(k, t), exhibits markedly different relaxation dynamics at different length scales. At small wave numbers, we find the emergence of a step-like relaxation, indicating the presence of both fast and slow time scales in the system. Such behavior allows an intriguing analogy with temperature dependent relaxation dynamics of supercooled liquids. We find that solvation dynamics of a tagged ion exhibits a power law decay at long times-the decay can also be fitted to a stretched exponential form. The emergence of the power law in solvation dynamics has been tested by carrying out long Brownian dynamics simulations with varying ionic concentrations. The solvation time correlation and ion-ion intermediate scattering function indeed exhibit highly interesting, non-trivial dynamical behavior at intermediate to longer times that require further experimental and theoretical studies. (c) 2015 AIP Publishing LLC.

A faster algorithm for testing polynomial representability of functions over finite integer rings

Given a function from Z(n) to itself one can determine its polynomial representability by using Kempner function. In this paper we present an alternative characterization of polynomial functions over Z(n) by constructing a generating set for the Z(n)-module of polynomial functions. This characterization results in an algorithm that is faster on average in deciding polynomial representability. We also extend the characterization to functions in several variables. (C) 2015 Elsevier B.V. All rights reserved.