The basis function approach for modeling autocorrelation in ecological data.
Hefley, Trevor J; Broms, Kristin M; Brost, Brian M; Buderman, Frances E; Kay, Shannon L; Scharf, Henry R; Tipton, John R; Williams, Perry J; Hooten, Mevin B
2017-03-01
Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data. © 2016 by the Ecological Society of America.
Directory of Open Access Journals (Sweden)
Yuri B. Tebekin
2011-11-01
Full Text Available The article is devoted to the problem of the quality management for multiphase processes on the basis of the probabilistic approach. Method with continuous response functions is offered from the application of the method of Lagrange multipliers.
Smidstrup, Søren; Stradi, Daniele; Wellendorff, Jess; Khomyakov, Petr A.; Vej-Hansen, Ulrik G.; Lee, Maeng-Eun; Ghosh, Tushar; Jónsson, Elvar; Jónsson, Hannes; Stokbro, Kurt
2017-11-01
We present an efficient implementation of a surface Green's-function method for atomistic modeling of surfaces within the framework of density functional theory using a pseudopotential localized basis set approach. In this method, the system is described as a truly semi-infinite solid with a surface region coupled to an electron reservoir, thereby overcoming several fundamental drawbacks of the traditional slab approach. The versatility of the method is demonstrated with several applications to surface physics and chemistry problems that are inherently difficult to address properly with the slab method, including metal work function calculations, band alignment in thin-film semiconductor heterostructures, surface states in metals and topological insulators, and surfaces in external electrical fields. Results obtained with the surface Green's-function method are compared to experimental measurements and slab calculations to demonstrate the accuracy of the approach.
Yurchenko, Sergei N; Yachmenev, Andrey; Ovsyannikov, Roman I
2017-09-12
We present a general, numerically motivated approach to the construction of symmetry-adapted basis functions for solving ro-vibrational Schrödinger equations. The approach is based on the property of the Hamiltonian operator to commute with the complete set of symmetry operators and, hence, to reflect the symmetry of the system. The symmetry-adapted ro-vibrational basis set is constructed numerically by solving a set of reduced vibrational eigenvalue problems. In order to assign the irreducible representations associated with these eigenfunctions, their symmetry properties are probed on a grid of molecular geometries with the corresponding symmetry operations. The transformation matrices are reconstructed by solving overdetermined systems of linear equations related to the transformation properties of the corresponding wave functions on the grid. Our method is implemented in the variational approach TROVE and has been successfully applied to many problems covering the most important molecular symmetry groups. Several examples are used to illustrate the procedure, which can be easily applied to different types of coordinates, basis sets, and molecular systems.
Yang, Fan; Kusche, Jürgen; Forootan, Ehsan; Rietbroek, Roelof
2017-08-01
We present a state-of-the-art approach of passive-ocean modified radial basis functions (MRBFs) that improves the recovery of time-variable gravity fields from Gravity Recovery and Climate Experiment (GRACE). As is well known, spherical harmonics (SHs), which are commonly used to recover gravity fields, are orthogonal basis functions with global coverage. However, the chosen SH truncation involves a global compromise between data coverage and obtainable resolution, and strong localized signals may not be fully captured. Radial basis functions (RBFs) provide another representation, which has been proposed in earlier works to be better suited to retrieve regional gravity signals. In this paper, we propose a MRBF approach by embedding the known coastal geometries in the RBF parameterization and imposing global mass conservation and equilibrium behavior of the oceans. Our hypothesis is that with this physically justified constraint, the GRACE-derived gravity signals can be more realistically partitioned into the land and ocean contributions along the coastlines. We test this new technique to invert monthly gravity fields from GRACE level-1b observations covering 2005-2010, for which the numerical results indicate that (1) MRBF-based solutions reduce the number of parameters by approximately 10% and allow for more flexible regularization when compared to ordinary RBF solutions and (2) the MRBF-derived mass flux is better confined along coastal areas. The latter is particularly tested in the southern Greenland, and our results indicate that the trend of mass loss from the MRBF solutions is approximately 11% larger than that from the SH solutions and approximately 4%-6% larger than that of RBF solutions.
A data-driven approach to local gravity field modelling using spherical radial basis functions
Klees, R.; Tenzer, R.; Prutkin, I.; Wittwer, T.
2008-01-01
We propose a methodology for local gravity field modelling from gravity data using spherical radial basis functions. The methodology comprises two steps: in step 1, gravity data (gravity anomalies and/or gravity disturbances) are used to estimate the disturbing potential using least-squares
Directory of Open Access Journals (Sweden)
N. Ahmadi
2017-02-01
Full Text Available Abstract In this paper, we present a collocation method based on Gaussian Radial Basis Functions (RBFs for approximating the solution of stochastic fractional differential equations (SFDEs. In this equation the fractional derivative is considered in the Caputo sense. Also we prove the existence and uniqueness of the presented method. Numerical examples confirm the proficiency of the method.
Energy Technology Data Exchange (ETDEWEB)
Rescigno, Thomas N.; Horner, Daniel A.; Yip, Frank L.; McCurdy,C. William
2005-08-29
Gaussian basis functions, routinely employed in molecular electronic structure calculations, can be combined with numerical grid-based functions in a discrete variable representation to provide an efficient method for computing molecular continuum wave functions. This approach, combined with exterior complex scaling, obviates the need for slowly convergent single-center expansions, and allows one to study a variety of electron-molecule collision problems. The method is illustrated by computation of various bound and continuum properties of H2+.
International Nuclear Information System (INIS)
Feng Weiguo; Wang Hongwei; Wu Xiang
1989-12-01
Based on the real space Correlated-Basis-Functions theory and the collective oscillation behaviour of the electron gas with effective Coulomb interaction, the many body wave function is obtained for the quasi-two-dimensional electron system in the semiconductor inversion layer. The pair-correlation function and the correlation energy of the system have been calculated by the integro-differential method in this paper. The comparison with the other previous theoretical results is also made. The new theoretical approach and its numerical results show that the pair-correlation functions are definitely positive and satisfy the normalization condition. (author). 10 refs, 2 figs
DEFF Research Database (Denmark)
Klinting, Emil Lund; Thomsen, Bo; Godtliebsen, Ian Heide
. This results in a decreased number of single point calculations required during the potential construction. Especially the Morse-like fit-basis functions are of interest, when combined with rectilinear hybrid optimized and localized coordinates (HOLCs), which can be generated as orthogonal transformations......The overall shape of a molecular energy surface can be very different for different molecules and different vibrational coordinates. This means that the fit-basis functions used to generate an analytic representation of a potential will be met with different requirements. It is therefore worthwhile...... single point calculations when constructing the molecular potential. We therefore present a uniform framework that can handle general fit-basis functions of any type which are specified on input. This framework is implemented to suit the black-box nature of the ADGA in order to avoid arbitrary choices...
Kayri, Murat
2015-01-01
The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…
Mixtures of truncated basis functions
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2012-01-01
In this paper we propose a framework, called mixtures of truncated basis functions (MoTBFs), for representing general hybrid Bayesian networks. The proposed framework generalizes both the mixture of truncated exponentials (MTEs) framework and the mixture of polynomials (MoPs) framework. Similar...
Functional Basis of Microorganism Classification.
Zhu, Chengsheng; Delmont, Tom O; Vogel, Timothy M; Bromberg, Yana
2015-08-01
Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with
Construction of global Lyapunov functions using radial basis functions
Giesl, Peter
2007-01-01
The basin of attraction of an equilibrium of an ordinary differential equation can be determined using a Lyapunov function. A new method to construct such a Lyapunov function using radial basis functions is presented in this volume intended for researchers and advanced students from both dynamical systems and radial basis functions. Besides an introduction to both areas and a detailed description of the method, it contains error estimates and many examples.
Learning Methods for Radial Basis Functions Networks
Czech Academy of Sciences Publication Activity Database
Neruda, Roman; Kudová, Petra
2005-01-01
Roč. 21, - (2005), s. 1131-1142 ISSN 0167-739X R&D Projects: GA ČR GP201/03/P163; GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : radial basis function networks * hybrid supervised learning * genetic algorithms * benchmarking Subject RIV: BA - General Mathematics Impact factor: 0.555, year: 2005
Fast radial basis functions for engineering applications
Biancolini, Marco Evangelos
2017-01-01
This book presents the first “How To” guide to the use of radial basis functions (RBF). It provides a clear vision of their potential, an overview of ready-for-use computational tools and precise guidelines to implement new engineering applications of RBF. Radial basis functions (RBF) are a mathematical tool mature enough for useful engineering applications. Their mathematical foundation is well established and the tool has proven to be effective in many fields, as the mathematical framework can be adapted in several ways. A candidate application can be faced considering the features of RBF: multidimensional space (including 2D and 3D), numerous radial functions available, global and compact support, interpolation/regression. This great flexibility makes RBF attractive – and their great potential has only been partially discovered. This is because of the difficulty in taking a first step toward RBF as they are not commonly part of engineers’ cultural background, but also due to the numerical complex...
Modular HTGR Safety Basis and Approach
Energy Technology Data Exchange (ETDEWEB)
Thomas Hicks
2011-08-01
The Next Generation Nuclear Plant (NGNP) will be a licensed commercial high temperature gas-cooled reactor (HTGR) capable of producing electricity and/or high temperature process heat for industrial markets supporting a range of end-user applications. The NGNP Project has adopted the 10 CFR 52 Combined License (COL) process, as recommended in the NGNP Licensing Strategy - A Report to Congress, dated August 2008, as the foundation for the NGNP licensing strategy [DOE/NRC 2008]. Nuclear Regulatory Commission (NRC) licensing of the NGNP plant utilizing this process will demonstrate the efficacy for licensing future HTGRs for commercial industrial applications. This information paper is one in a series of submittals that address key generic issues of the priority licensing topics as part of the process for establishing HTGR regulatory requirements. This information paper provides a summary level introduction to HTGR history, public safety objectives, inherent and passive safety features, radionuclide release barriers, functional safety approach, and risk-informed safety approach. The information in this paper is intended to further the understanding of the modular HTGR safety approach with the NRC staff and public stakeholders. The NGNP project does not expect to receive comments on this information paper because other white papers are addressing key generic issues of the priority licensing topics in greater detail.
Optimal Piecewise Linear Basis Functions in Two Dimensions
Energy Technology Data Exchange (ETDEWEB)
Brooks III, E D; Szoke, A
2009-01-26
We use a variational approach to optimize the center point coefficients associated with the piecewise linear basis functions introduced by Stone and Adams [1], for polygonal zones in two Cartesian dimensions. Our strategy provides optimal center point coefficients, as a function of the location of the center point, by minimizing the error induced when the basis function interpolation is used for the solution of the time independent diffusion equation within the polygonal zone. By using optimal center point coefficients, one expects to minimize the errors that occur when these basis functions are used to discretize diffusion equations, or transport equations in optically thick zones (where they approach the solution of the diffusion equation). Our optimal center point coefficients satisfy the requirements placed upon the basis functions for any location of the center point. We also find that the location of the center point can be optimized, but this requires numerical calculations. Curiously, the optimum center point location is independent of the values of the dependent variable on the corners only for quadrilaterals.
Spatial transformations in the parietal cortex using basis functions.
Pouget, A; Sejnowski, T J
1997-03-01
Sensorimotor transformations are nonlinear mappings of sensory inputs to motor responses. We explore here the possibility that the responses of single neurons in the parietal cortex serve as basis functions for these transformations. Basis function decomposition is a general method for approximating nonlinear functions that is computationally efficient and well suited for adaptive modification. In particular, the responses of single parietal neurons can be approximated by the product of a Gaussian function of retinal location and a sigmoid function of eye position, called a gain field. A large set of such functions forms a basis set that can be used to perform an arbitrary motor response through a direct projection. We compare this hypothesis with other approaches that are commonly used to model population codes, such as computational maps and vectorial representations. Neither of these alternatives can fully account for the responses of parietal neurons, and they are computationally less efficient for nonlinear transformations. Basis functions also have the advantage of not depending on any coordinate system or reference frame. As a consequence, the position of an object can be represented in multiple reference frames simultaneously, a property consistent with the behavior of hemineglect patients with lesions in the parietal cortex.
Basis convergence of range-separated density-functional theory.
Franck, Odile; Mussard, Bastien; Luppi, Eleonora; Toulouse, Julien
2015-02-21
Range-separated density-functional theory (DFT) is an alternative approach to Kohn-Sham density-functional theory. The strategy of range-separated density-functional theory consists in separating the Coulomb electron-electron interaction into long-range and short-range components and treating the long-range part by an explicit many-body wave-function method and the short-range part by a density-functional approximation. Among the advantages of using many-body methods for the long-range part of the electron-electron interaction is that they are much less sensitive to the one-electron atomic basis compared to the case of the standard Coulomb interaction. Here, we provide a detailed study of the basis convergence of range-separated density-functional theory. We study the convergence of the partial-wave expansion of the long-range wave function near the electron-electron coalescence. We show that the rate of convergence is exponential with respect to the maximal angular momentum L for the long-range wave function, whereas it is polynomial for the case of the Coulomb interaction. We also study the convergence of the long-range second-order Møller-Plesset correlation energy of four systems (He, Ne, N2, and H2O) with cardinal number X of the Dunning basis sets cc - p(C)V XZ and find that the error in the correlation energy is best fitted by an exponential in X. This leads us to propose a three-point complete-basis-set extrapolation scheme for range-separated density-functional theory based on an exponential formula.
Diffusion Forecasting Model with Basis Functions from QR-Decomposition
Harlim, John; Yang, Haizhao
2017-12-01
The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.
International Nuclear Information System (INIS)
Koo, B. B.; Lee, J. M.; Kim, J. S.; Kim, I. Y.; Kim, S. I.; Lee, J. S.; Lee, D. S.; Kwon, J. S.; Kim, J. J.
2003-01-01
The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated region because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 brains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeled with the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each region is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease
Structural basis for pulmonary functional imaging
International Nuclear Information System (INIS)
Itoh, Harumi; Nakatsu, Masashi; Yoxtheimer, Lorene M.; Uematsu, Hidemasa; Ohno, Yoshiharu; Hatabu, Hiroto
2001-01-01
An understanding of fine normal lung morphology is important for effective pulmonary functional imaging. The lung specimens must be inflated. These include (a) unfixed, inflated lung specimen, (b) formaldehyde fixed lung specimen, (c) fixed, inflated dry lung specimen, and (d) histology specimen. Photography, magnified view, radiograph, computed tomography, and histology of these specimens are demonstrated. From a standpoint of diagnostic imaging, the main normal lung structures consist of airways (bronchi and bronchioles), alveoli, pulmonary vessels, secondary pulmonary lobules, and subpleural pulmonary lymphatic channels. This review summarizes fine radiologic normal lung morphology as an aid to effective pulmonary functional imaging
A Genetic Basis for Functional Hypothalamic Amenorrhea
Caronia, Lisa M.; Martin, Cecilia; Welt, Corrine K.; Sykiotis, Gerasimos P.; Quinton, Richard; Thambundit, Apisadaporn; Avbelj, Magdalena; Dhruvakumar, Sadhana; Plummer, Lacey; Hughes, Virginia A.; Seminara, Stephanie B.; Boepple, Paul A.; Sidis, Yisrael; Crowley, William F.; Martin, Kathryn A.; Hall, Janet E.; Pitteloud, Nelly
2011-01-01
BACKGROUND Functional hypothalamic amenorrhea is a reversible form of gonadotropin-releasing hormone (GnRH) deficiency commonly triggered by stressors such as excessive exercise, nutritional deficits, or psychological distress. Women vary in their susceptibility to inhibition of the reproductive axis by such stressors, but it is unknown whether this variability reflects a genetic predisposition to hypothalamic amenorrhea. We hypothesized that mutations in genes involved in idiopathic hypogonadotropic hypogonadism, a congenital form of GnRH deficiency, are associated with hypothalamic amenorrhea. METHODS We analyzed the coding sequence of genes associated with idiopathic hypogonadotropic hypogonadism in 55 women with hypothalamic amenorrhea and performed in vitro studies of the identified mutations. RESULTS Six heterozygous mutations were identified in 7 of the 55 patients with hypothalamic amenorrhea: two variants in the fibroblast growth factor receptor 1 gene FGFR1 (G260E and R756H), two in the prokineticin receptor 2 gene PROKR2 (R85H and L173R), one in the GnRH receptor gene GNRHR (R262Q), and one in the Kall-mann syndrome 1 sequence gene KAL1 (V371I). No mutations were found in a cohort of 422 controls with normal menstrual cycles. In vitro studies showed that FGFR1 G260E, FGFR1 R756H, and PROKR2 R85H are loss-of-function mutations, as has been previously shown for PROKR2 L173R and GNRHR R262Q. CONCLUSIONS Rare variants in genes associated with idiopathic hypogonadotropic hypogonadism are found in women with hypothalamic amenorrhea, suggesting that these mutations may contribute to the variable susceptibility of women to the functional changes in GnRH secretion that characterize hypothalamic amenorrhea. Our observations provide evidence for the role of rare variants in common multifactorial disease. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT00494169.) PMID:21247312
Wachspress type' rational basis functions over rectangles
Indian Academy of Sciences (India)
The vertices ai of a closed convex rectangle K in R2 are labeled so that ai and aiЗ1 are consecutive for i И 1Y 2Y 3Y 4X For each subset e of R2Y P├. nЕeЖ is the e-restriction of the vector space of bivariate polynomial functions of degree n in each of the two variables. Let di be the straight line passing through the points ai ...
Higher-Order Hierarchical Legendre Basis Functions in Applications
DEFF Research Database (Denmark)
Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter
2007-01-01
degree of orthogonality. The basis functions are well-suited for solution of complex electromagnetic problems involving multiple homogeneous or inhomogeneous dielectric regions, metallic surfaces, layered media, etc. This paper presents real-life complex antenna radiation problems modeled...... with electromagnetic simulation tools based on the higher-order hierarchical Legendre basis functions....
Fast function-on-scalar regression with penalized basis expansions.
Reiss, Philip T; Huang, Lei; Mennes, Maarten
2010-01-01
Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990 s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals for the coefficient functions, simultaneous inference by permutation tests, and model selection, including a novel notion of pointwise model selection. P-OLS and P-GLS are compared in a simulation study. Our methods are illustrated with an analysis of age effects in a functional magnetic resonance imaging data set, as well as a reanalysis of a now-classic Canadian weather data set. An R package implementing the methods is publicly available.
Using piecewise sinusoidal basis functions to blanket multiple wire segments
CSIR Research Space (South Africa)
Lysko, AA
2009-06-01
Full Text Available , Mathematics and Electrical Engineering at the Norwegian University of Science and Technology (NTNU), Norway. It is assumed that the MoM procedure results in the linear algebraic equations Z⋅I=V, where Z is the impedance matrix [1], [4], I is the column... Basis Functions The general idea behind expressing the original basis functions via new MDBFs may be illustrated with Fig. 1a. The weights corresponding to the old basis functions to form a piecewise linear approximation may be easily computed...
Construction ofWachspress type'rational basis functions over ...
Indian Academy of Sciences (India)
In the present paper, we have constructed rational basis functions of 0 class over rectangular elements with wider choice of denominator function. This construction yields additional number of interior nodes. Hence, extra nodal points and the flexibility of denominator function suggest better approximation.
Radial basis function neural networks applied to NASA SSME data
Wheeler, Kevin R.; Dhawan, Atam P.
1993-01-01
This paper presents a brief report on the application of Radial Basis Function Neural Networks (RBFNN) to the prediction of sensor values for fault detection and diagnosis of the Space Shuttle's Main Engines (SSME). The location of the Radial Basis Function (RBF) node centers was determined with a K-means clustering algorithm. A neighborhood operation about these center points was used to determine the variances of the individual processing notes.
Laguerre-Gauss basis functions in observer models
Burgess, Arthur E.
2003-05-01
Observer models based on linear classifiers with basis functions (channels) are useful for evaluation of detection performance with medical images. They allow spatial domain calculations with a covariance matrix of tractable size. The term "channelized Fisher-Hotelling observer" will be used here. It is also called the "channelized Hotelling observer" model. There are an infinite number of basis function (channel ) sets that could be employed. Examples of channel sets that have been used include: difference of Gaussian (DOG) filters, difference of Mesa (DOM) filters and Laguerre-Gauss (LG) basis functions. Another option, sums of LG functions (LGS), will also be presented here. This set has the advantage of having no DC response. The effect of the number of images used to estimate model observer performance will be described, for both filtered 1/f3 noise and GE digital mammogram backgrounds. Finite sample image sets introduce both bias and variance to the estimate. The results presented here agree with previous work on linear classifiers. The LGS basis set gives a small but statistically significant reduction in bias. However, this may not be of much practical benefit. Finally, the effect of varying the number of basis functions included in the set will be addressed. It was found that four LG bases or three LGS bases are adequate.
Point Set Denoising Using Bootstrap-Based Radial Basis Function.
Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad
2016-01-01
This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.
Closed fringe demodulation using phase decomposition by Fourier basis functions.
Kulkarni, Rishikesh; Rastogi, Pramod
2016-06-01
We report a new technique for the demodulation of a closed fringe pattern by representing the phase as a weighted linear combination of a certain number of linearly independent Fourier basis functions in a given row/column at a time. A state space model is developed with the weights of the basis functions as the elements of the state vector. The iterative extended Kalman filter is effectively utilized for the robust estimation of the weights. A coarse estimate of the fringe density based on the fringe frequency map is used to determine the initial row/column to start with and subsequently the optimal number of basis functions. The performance of the proposed method is evaluated with several noisy fringe patterns. Experimental results are also reported to support the practical applicability of the proposed method.
Speech/Nonspeech Detection Using Minimal Walsh Basis Functions
Directory of Open Access Journals (Sweden)
Pwint Moe
2007-01-01
Full Text Available This paper presents a new method to detect speech/nonspeech components of a given noisy signal. Employing the combination of binary Walsh basis functions and an analysis-synthesis scheme, the original noisy speech signal is modified first. From the modified signals, the speech components are distinguished from the nonspeech components by using a simple decision scheme. Minimal number of Walsh basis functions to be applied is determined using singular value decomposition (SVD. The main advantages of the proposed method are low computational complexity, less parameters to be adjusted, and simple implementation. It is observed that the use of Walsh basis functions makes the proposed algorithm efficiently applicable in real-world situations where processing time is crucial. Simulation results indicate that the proposed algorithm achieves high-speech and nonspeech detection rates while maintaining a low error rate for different noisy conditions.
Speech/Nonspeech Detection Using Minimal Walsh Basis Functions
Directory of Open Access Journals (Sweden)
Moe Pwint
2006-10-01
Full Text Available This paper presents a new method to detect speech/nonspeech components of a given noisy signal. Employing the combination of binary Walsh basis functions and an analysis-synthesis scheme, the original noisy speech signal is modified first. From the modified signals, the speech components are distinguished from the nonspeech components by using a simple decision scheme. Minimal number of Walsh basis functions to be applied is determined using singular value decomposition (SVD. The main advantages of the proposed method are low computational complexity, less parameters to be adjusted, and simple implementation. It is observed that the use of Walsh basis functions makes the proposed algorithm efficiently applicable in real-world situations where processing time is crucial. Simulation results indicate that the proposed algorithm achieves high-speech and nonspeech detection rates while maintaining a low error rate for different noisy conditions.
Accurate correlation energies in one-dimensional systems from small system-adapted basis functions
Baker, Thomas E.; Burke, Kieron; White, Steven R.
2018-02-01
We propose a general method for constructing system-dependent basis functions for correlated quantum calculations. Our construction combines features from several traditional approaches: plane waves, localized basis functions, and wavelets. In a one-dimensional mimic of Coulomb systems, it requires only 2-3 basis functions per electron to achieve high accuracy, and reproduces the natural orbitals. We illustrate its effectiveness for molecular energy curves and chains of many one-dimensional atoms. We discuss the promise and challenges for realistic quantum chemical calculations.
New MoM code incorporating multiple domain basis functions
CSIR Research Space (South Africa)
Lysko, AA
2011-08-01
Full Text Available Multiple Domain Basis Functions Albert A. Lysko1 1 Council for Scientific and Industrial Research (CSIR): Meraka Institute, PO Box 395, Pretoria 0001, South Africa, Tel.: +27 12 841 4609, Fax: +27 12 841 4720, Email: alysko@csir.co.za Abstract A...-domain piecewise linear (PWL) or piecewise sinusoidal (PWS) approximation for the current distribution [1]. WIPL-D [4], being an exception, uses higher order polynomial basis functions [2]. Most of the commercial codes are well optimized but are kept general...
Structural basis for functional tetramerization of lentiviral integrase.
Directory of Open Access Journals (Sweden)
Stephen Hare
2009-07-01
Full Text Available Experimental evidence suggests that a tetramer of integrase (IN is the protagonist of the concerted strand transfer reaction, whereby both ends of retroviral DNA are inserted into a host cell chromosome. Herein we present two crystal structures containing the N-terminal and the catalytic core domains of maedi-visna virus IN in complex with the IN binding domain of the common lentiviral integration co-factor LEDGF. The structures reveal that the dimer-of-dimers architecture of the IN tetramer is stabilized by swapping N-terminal domains between the inner pair of monomers poised to execute catalytic function. Comparison of four independent IN tetramers in our crystal structures elucidate the basis for the closure of the highly flexible dimer-dimer interface, allowing us to model how a pair of active sites become situated for concerted integration. Using a range of complementary approaches, we demonstrate that the dimer-dimer interface is essential for HIV-1 IN tetramerization, concerted integration in vitro, and virus infectivity. Our structures moreover highlight adaptable changes at the interfaces of individual IN dimers that allow divergent lentiviruses to utilize a highly-conserved, common integration co-factor.
Learning Mixtures of Truncated Basis Functions from Data
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre; Pérez-Bernabé, Inmaculada
2014-01-01
In this paper we investigate methods for learning hybrid Bayesian networks from data. First we utilize a kernel density estimate of the data in order to translate the data into a mixture of truncated basis functions (MoTBF) representation using a convex optimization technique. When utilizing...
Radial basis function neural network in fault detection of automotive ...
African Journals Online (AJOL)
Radial basis function neural network in fault detection of automotive engines. ... Five faults have been simulated on the MVEM, including three sensor faults, one component fault and one actuator fault. The three sensor faults ... Keywords: Automotive engine, independent RBFNN model, RBF neural network, fault detection
A Hartree–Fock study of the confined helium atom: Local and global basis set approaches
Energy Technology Data Exchange (ETDEWEB)
Young, Toby D., E-mail: tyoung@ippt.pan.pl [Zakład Metod Komputerowych, Instytut Podstawowych Prolemów Techniki Polskiej Akademia Nauk, ul. Pawińskiego 5b, 02-106 Warszawa (Poland); Vargas, Rubicelia [Universidad Autónoma Metropolitana Iztapalapa, División de Ciencias Básicas e Ingenierías, Departamento de Química, San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, D.F. C.P. 09340, México (Mexico); Garza, Jorge, E-mail: jgo@xanum.uam.mx [Universidad Autónoma Metropolitana Iztapalapa, División de Ciencias Básicas e Ingenierías, Departamento de Química, San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, D.F. C.P. 09340, México (Mexico)
2016-02-15
Two different basis set methods are used to calculate atomic energy within Hartree–Fock theory. The first is a local basis set approach using high-order real-space finite elements and the second is a global basis set approach using modified Slater-type orbitals. These two approaches are applied to the confined helium atom and are compared by calculating one- and two-electron contributions to the total energy. As a measure of the quality of the electron density, the cusp condition is analyzed. - Highlights: • Two different basis set methods for atomic Hartree–Fock theory. • Galerkin finite element method and modified Slater-type orbitals. • Confined atom model (helium) under small-to-extreme confinement radii. • Detailed analysis of the electron wave-function and the cusp condition.
A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.
Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F
2017-11-01
The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach
Compactly Supported Basis Functions as Support Vector Kernels for Classification.
Wittek, Peter; Tan, Chew Lim
2011-10-01
Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.
Complexity of Gaussian-Radial-Basis Networks Approximating Smooth Functions
Czech Academy of Sciences Publication Activity Database
Kainen, P.C.; Kůrková, Věra; Sanguineti, M.
2009-01-01
Roč. 25, č. 1 (2009), s. 63-74 ISSN 0885-064X R&D Projects: GA ČR GA201/08/1744 Institutional research plan: CEZ:AV0Z10300504 Keywords : Gaussian-radial-basis-function networks * rates of approximation * model complexity * variation norms * Bessel and Sobolev norms * tractability of approximation Subject RIV: IN - Informatics, Computer Science Impact factor: 1.227, year: 2009
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2014-11-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.
Libcint: An efficient general integral library for Gaussian basis functions.
Sun, Qiming
2015-08-15
An efficient integral library Libcint was designed to automatically implement general integrals for Gaussian-type scalar and spinor basis functions. The library is able to evaluate arbitrary integral expressions on top of p, r and σ operators with one-electron overlap and nuclear attraction, two-electron Coulomb and Gaunt operators for segmented contracted and/or generated contracted basis in Cartesian, spherical or spinor form. Using a symbolic algebra tool, new integrals are derived and translated to C code programmatically. The generated integrals can be used in various types of molecular properties. To demonstrate the capability of the integral library, we computed the analytical gradients and NMR shielding constants at both nonrelativistic and 4-component relativistic Hartree-Fock level in this work. Due to the use of kinetically balanced basis and gauge including atomic orbitals, the relativistic analytical gradients and shielding constants requires the integral library to handle the fifth-order electron repulsion integral derivatives. The generality of the integral library is achieved without losing efficiency. On the modern multi-CPU platform, Libcint can easily reach the overall throughput being many times of the I/O bandwidth. On a 20-core node, we are able to achieve an average output 8.3 GB/s for C60 molecule with cc-pVTZ basis. © 2015 Wiley Periodicals, Inc.
Basis set approach in the constrained interpolation profile method
International Nuclear Information System (INIS)
Utsumi, T.; Koga, J.; Yabe, T.; Ogata, Y.; Matsunaga, E.; Aoki, T.; Sekine, M.
2003-07-01
We propose a simple polynomial basis-set that is easily extendable to any desired higher-order accuracy. This method is based on the Constrained Interpolation Profile (CIP) method and the profile is chosen so that the subgrid scale solution approaches the real solution by the constraints from the spatial derivative of the original equation. Thus the solution even on the subgrid scale becomes consistent with the master equation. By increasing the order of the polynomial, this solution quickly converges. 3rd and 5th order polynomials are tested on the one-dimensional Schroedinger equation and are proved to give solutions a few orders of magnitude higher in accuracy than conventional methods for lower-lying eigenstates. (author)
Integration a functional approach
Bichteler, Klaus
1998-01-01
This book covers Lebesgue integration and its generalizations from Daniell's point of view, modified by the use of seminorms. Integrating functions rather than measuring sets is posited as the main purpose of measure theory. From this point of view Lebesgue's integral can be had as a rather straightforward, even simplistic, extension of Riemann's integral; and its aims, definitions, and procedures can be motivated at an elementary level. The notion of measurability, for example, is suggested by Littlewood's observations rather than being conveyed authoritatively through definitions of (sigma)-algebras and good-cut-conditions, the latter of which are hard to justify and thus appear mysterious, even nettlesome, to the beginner. The approach taken provides the additional benefit of cutting the labor in half. The use of seminorms, ubiquitous in modern analysis, speeds things up even further. The book is intended for the reader who has some experience with proofs, a beginning graduate student for example. It might...
Patankar, S. J.; Jurs, P. C.
2003-02-01
HIV protease inhibitors are being used as frontline therapy in the treatment of HIV patients. Multi-drug-resistant HIV mutant strains are emerging with the initial aggressive multi-drug treatment of HIV patients. This necessitates continued search for novel inhibitors of viral replication. These protease inhibitors may further be useful as pharmacological agents for inhibition of other viral replication. Classification models of HIV Protease inhibitors are developed using a data set of 123 compounds containing several heterocycles. Their inhibitory concentrations expressed as log (IC50) ranged from -1.52 to 2.12 log units. The dataset was divided into active and inactive classes on the basis of their antiviral potency. Initially a two-class problem (active, inactive) is explored using k-nearest neighbor approach. In order to introduce non-linearity in the classifier different approaches were investigated. This led to the goal of a fast, simple, minimum user input, radial basis function neural network (RBFNN) classifier development. Then the same two-class problem was resolved using the (RBFNN) classifier. A genetic algorithm with RBFNN fitness evaluator was used to search for the optimum descriptor subsets. The application of majority rules was also tested for the RBFNN classification. The best six descriptor model found by the new cost function showed predictive ability in the high 80% range for an external prediction set.
Density functional approaches to nuclear dynamics
Nakatsukasa, T.; Ebata, S.; Avogadro, P.; Guo, L.; Inakura, T.; Yoshida, K.
2012-01-01
We present background concepts of the nuclear density functional theory (DFT) and applications of the time-dependent DFT with the Skyrme energy functional for nuclear response functions. Practical methods for numerical applications of the time-dependent Hartree-Fock-Bogoliubov theory (TDHFB) are proposed; finite amplitude method and canonical-basis TDHFB. These approaches are briefly reviewed and some numerical applications are shown to demonstrate their feasibility.
Spectral Methods Using Rational Basis Functions on an Infinite Interval
Boyd, John P.
1987-03-01
By using the map y = L cot( t) where L is a constant, differential equations on the interval yɛ [- ∞, ∞] can be transformed into tɛ [0, π] and solved by an ordinary Fourier series. In this article, earlier work by Grosch and Orszag ( J. Comput. Phys.25, 273 (1977)), Cain, Ferziger, and Reynolds ( J. Comput. Phys.56, 272 (1984)), and Boyd ( J. Comput. Phys.25, 43 (1982); 57, 454 (1985); SIAM J. Numer. Anal. (1987)) is extended in several ways. First, the series of orthogonal rational functions converge on the exterior of bipolar coordinate surfaces in the complex y-plane. Second, Galerkin's method will convert differential equations with polynomial or rational coefficients into banded matrix problems. Third, with orthogonal rational functions it is possible to obtain exponential convergence even for u( y) that asymptote to a constant although this behavior would wreck alternatives such as Hermite or sinc expansions. Fourth, boundary conditions are usually "natural" rather than "essential" in the sense that the singularities of the differential equation will force the numerical solution to have the correct behavior at infinity even if no constraints are imposed on the basis functions. Fifth, mapping a finite interval to an infinite one and then applying the rational Chebyshev functions gives an exponentially convergent method for functions with bounded endpoint singularities. These concepts are illustrated by five numerical examples.
Anacker, Tony; Hill, J Grant; Friedrich, Joachim
2016-04-21
Minimal basis sets, denoted DSBSenv, based on the segmented basis sets of Ahlrichs and co-workers have been developed for use as environmental basis sets for the domain-specific basis set (DSBS) incremental scheme with the aim of decreasing the CPU requirements of the incremental scheme. The use of these minimal basis sets within explicitly correlated (F12) methods has been enabled by the optimization of matching auxiliary basis sets for use in density fitting of two-electron integrals and resolution of the identity. The accuracy of these auxiliary sets has been validated by calculations on a test set containing small- to medium-sized molecules. The errors due to density fitting are about 2-4 orders of magnitude smaller than the basis set incompleteness error of the DSBSenv orbital basis sets. Additional reductions in computational cost have been tested with the reduced DSBSenv basis sets, in which the highest angular momentum functions of the DSBSenv auxiliary basis sets have been removed. The optimized and reduced basis sets are used in the framework of the domain-specific basis set of the incremental scheme to decrease the computation time without significant loss of accuracy. The computation times and accuracy of the previously used environmental basis and that optimized in this work have been validated with a test set of medium- to large-sized systems. The optimized and reduced DSBSenv basis sets decrease the CPU time by about 15.4% and 19.4% compared with the old environmental basis and retain the accuracy in the absolute energy with standard deviations of 0.99 and 1.06 kJ/mol, respectively.
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2011-08-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network
Directory of Open Access Journals (Sweden)
I.N. Korabejnikov
2009-12-01
Full Text Available The problems of regional industrial complex development on the basis of cluster approach are observed in the article. The methodics of estimation of regional industrial complex development is carried out, which enables to study it as the mediation system of specific, territorial and scientific-innovation functioning aspects. The authors' typology of regional industrial clusters is described, where priorities for study are marked. The authors' approach of methodical explanation of industrial clusters priorities forming as the basic elements of regional industrial complex development is represented. Business models of different types functioning clusters are shown.
The Economic Security of Bank: Theoretical Basis and Systemic Approach
Directory of Open Access Journals (Sweden)
Gavlovska Nataliia I.
2017-07-01
Full Text Available The article analyzes the existing approaches to interpreting the category of «economic security of bank». A author’s own definition of the concept of «economic security of bank» has been proposed, which should be understood as condition of protecting the vital interests of bank, achieved by harmonizing relationships with the entities of external influence and optimizing the internal system processes, thus enabling efficient function as well as development by means of an adaptation mechanism. A number of approaches to understanding the substance of the above concept has been allocated and their main characteristics have been provided. The need to study the specifics of interaction of banking institutions with the external environment in the context of interaction between the State agents and market actors has been underlined. Features of formation of the term of «system» have been defined, three main groups of approaches to interpretation of the term have been provided. A author’s own definition of the concept of «economic security system of bank» has been proposed. A concrete definition of principles for building an economic security system of bank has been provided.
Positivity and monotonicity shape preserving using radial basis function
Ahmad, Afida; Ong, Wen Eng; Piah, Abd. Rahni Mt
2017-04-01
The objective of this paper is to investigate whether radial basis functions (RBF) can be used as an alternative to Bezier and Ball splines in preserving positivity and monotonicity of the data. For positivity shape preserving, multiquadric and Gaussian form of RBF are used in the analysis while for monotonicity, multiquadric quasi-interpolation is used. The analysis involved a free shape parameter, ɛ in preserving positivity and monotonicity for real data set. To preserve positivity, the selection of ɛ is based on the positivity constraint, s(x) > 0 and also a proposed upper bound value. The output from several real data sets are presented and the choice of ɛ varies depending on the data set. The interpolants are comparable with existing interpolation schemes using rational cubic Bezier and rational cubic Ball. For monotonicity shape preserving, the behaviour of the interpolants using different ɛ are investigated. From the examples, the resulted curves using multiquadric quasi-interpolation as the basis can only approximate the data.
The Gaussian radial basis function method for plasma kinetic theory
Energy Technology Data Exchange (ETDEWEB)
Hirvijoki, E., E-mail: eero.hirvijoki@chalmers.se [Department of Applied Physics, Chalmers University of Technology, SE-41296 Gothenburg (Sweden); Candy, J.; Belli, E. [General Atomics, PO Box 85608, San Diego, CA 92186-5608 (United States); Embréus, O. [Department of Applied Physics, Chalmers University of Technology, SE-41296 Gothenburg (Sweden)
2015-10-30
Description of a magnetized plasma involves the Vlasov equation supplemented with the non-linear Fokker–Planck collision operator. For non-Maxwellian distributions, the collision operator, however, is difficult to compute. In this Letter, we introduce Gaussian Radial Basis Functions (RBFs) to discretize the velocity space of the entire kinetic system, and give the corresponding analytical expressions for the Vlasov and collision operator. Outlining the general theory, we also highlight the connection to plasma fluid theories, and give 2D and 3D numerical solutions of the non-linear Fokker–Planck equation. Applications are anticipated in both astrophysical and laboratory plasmas. - Highlights: • A radically new method to address the velocity space discretization of the non-linear kinetic equation of plasmas. • Elegant and physically intuitive, flexible and mesh-free. • Demonstration of numerical solution of both 2-D and 3-D non-linear Fokker–Planck relaxation problem.
Control point selection for dimensionality reduction by radial basis function
Directory of Open Access Journals (Sweden)
Kotryna Paulauskienė
2016-02-01
Full Text Available This research deals with dimensionality reduction technique which is based on radial basis function (RBF theory. The technique uses RBF for mapping multidimensional data points into a low-dimensional space by interpolating the previously calculated position of so-called control points. This paper analyses various ways of selection of control points (regularized orthogonal least squares method, random and stratified selections. The experiments have been carried out with 8 real and artificial data sets. Positions of the control points in a low-dimensional space are found by principal component analysis. We demonstrate that random and stratified selections of control points are efficient and acceptable in terms of balance between projection error (stress and time-consumption.DOI: 10.15181/csat.v4i1.1095
Dynamics Model Abstraction Scheme Using Radial Basis Functions
Directory of Open Access Journals (Sweden)
Silvia Tolu
2012-01-01
Full Text Available This paper presents a control model for object manipulation. Properties of objects and environmental conditions influence the motor control and learning. System dynamics depend on an unobserved external context, for example, work load of a robot manipulator. The dynamics of a robot arm change as it manipulates objects with different physical properties, for example, the mass, shape, or mass distribution. We address active sensing strategies to acquire object dynamical models with a radial basis function neural network (RBF. Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. Biped robots do not have high force joint servos and the control system hardly compensates all the inertia variation of the adjacent joints and disturbance torque on dynamic gait control. In order to achieve smoother control and lead to more reliable sensorimotor complexes, we evaluate and compare a sparse velocity-driven versus a dense position-driven control scheme.
Efficient VLSI Architecture for Training Radial Basis Function Networks
Fan, Zhe-Cheng; Hwang, Wen-Jyi
2013-01-01
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networks. The architecture contains the circuits for fuzzy C-means (FCM) and the recursive Least Mean Square (LMS) operations. The FCM circuit is designed for the training of centers in the hidden layer of the RBF network. The recursive LMS circuit is adopted for the training of connecting weights in the output layer. The architecture is implemented by the field programmable gate array (FPGA). It is used as a hardware accelerator in a system on programmable chip (SOPC) for real-time training and classification. Experimental results reveal that the proposed RBF architecture is an effective alternative for applications where fast and efficient RBF training is desired. PMID:23519346
Design Optimization of Centrifugal Pump Using Radial Basis Function Metamodels
Directory of Open Access Journals (Sweden)
Yu Zhang
2014-05-01
Full Text Available Optimization design of centrifugal pump is a typical multiobjective optimization (MOO problem. This paper presents an MOO design of centrifugal pump with five decision variables and three objective functions, and a set of centrifugal pumps with various impeller shroud shapes are studied by CFD numerical simulations. The important performance indexes for centrifugal pump such as head, efficiency, and required net positive suction head (NPSHr are investigated, and the results indicate that the geometry shape of impeller shroud has strong effect on the pump's performance indexes. Based on these, radial basis function (RBF metamodels are constructed to approximate the functional relationship between the shape parameters of impeller shroud and the performance indexes of pump. To achieve the objectives of maximizing head and efficiency and minimizing NPSHr simultaneously, multiobjective evolutionary algorithm based on decomposition (MOEA/D is applied to solve the triobjective optimization problem, and a final design point is selected from the Pareto solution set by means of robust design. Compared with the values of prototype test and CFD simulation, the solution of the final design point exhibits a good consistency.
Defense-in-depth approach against a beyond design basis event
Energy Technology Data Exchange (ETDEWEB)
Hoang, H., E-mail: Hoa.hoang@ge.com [GE Hitachi Nuclear Energy, 1989 Little Orchard St., 95125 San Jose, California (United States)
2013-10-15
The US industry, with the approval of the Nuclear Regulatory Commission, is promoting an approach to add diverse and flexible mitigation strategies, or Flex, that will increase the defense-in-depth capability for the nuclear power plants in the event of beyond design basis event, such as at the Fukushima Dai-ichi station. The objective of Flex is to establish and indefinite coping capability to prevent damage to the fuel in the core and spent fuel pool, and to maintain the containment function by utilizing installed equipment, on-site portable equipment and pre-staged off-site resources. This capability will address both an extended loss of all Ac power and a loss of ultimate heat sink which could arise following a design basis event with additional failures, and conditions from a beyond design basis event. (author)
Neuronal spike sorting based on radial basis function neural networks
Directory of Open Access Journals (Sweden)
Taghavi Kani M
2011-02-01
Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.
CULTUROLOGICAL APPROACH AS METHODOLOGICAL BASIS OF MATHEMATICAL EDUCATION
Directory of Open Access Journals (Sweden)
Ye. A. Perminov
2017-01-01
literacy have the extreme humanitarian importance, since their existence either indirectly or sometimes directly influences quality of life of any person and society in general. The most in-demand, significant and obligatory thematic and methodological components of mathematical education are highlighted: mathematical modeling, discrete mathematics and computing processes. The principle of a cultural conformity and a harmonious combination of the culturological and artfundamentals of mathematical education are emphasized as the basic educational principles, the use of which is capable to improve and raise the level of mathematical culture of the Russian society on a new, higher position.The evidence from this study points towards the idea that effective functioning of the system of mathematical education is impossible without the qualified, well prepared staff who are not only professionals in the subject sphere, but also bearers of high pedagogical culture. Moral and ethical, communicative and individual, and personal components of pedagogical culture of a teacher-mathematician are characterized.Practical significance. The author is convinced that introduction of the proposed concept of mathematical education based on culturological approach to its contents and the organization will help to overcome the disproportions existing today in mathematical education between integration and subject differentiation of a training material, technologization of educational process and preservation of traditional methods of training, fundamentalization of knowledge and competence-based approach to it, etc.Materials of the publication can be useful for future and practising teachers of mathematics and allied sciences, as well as for other categories of the educators engaged in the organization and advance of mathematical education and promotion of mathematical knowledge.
Organization of Business Processes of the Company on the Basis of the Systems Approach Teners
Directory of Open Access Journals (Sweden)
Vaganova Valentina
2016-01-01
Full Text Available The article considers the management specificity on the basis of the systems approach tenets and description of business processes of the industrial enterprises. As the Company is a service-provider, its functional features are taken into consideration when modeling the business processes. The authors highlight challenges the Company faces in performance management because the existing system doesn’t allow to predict the financial results at the stage of formation of orders portfolio, to evaluate adequacy of financial resources to objectives set and to operate cash flows. All these issues are considered in sufficient detail when analyzing a range of problems and are taken as a basis of the project on implementation of the budgeting system based on the process approach.
Meshfree Local Radial Basis Function Collocation Method with Image Nodes
Energy Technology Data Exchange (ETDEWEB)
Baek, Seung Ki; Kim, Minjae [Pukyong National University, Busan (Korea, Republic of)
2017-07-15
We numerically solve two-dimensional heat diffusion problems by using a simple variant of the meshfree local radial-basis function (RBF) collocation method. The main idea is to include an additional set of sample nodes outside the problem domain, similarly to the method of images in electrostatics, to perform collocation on the domain boundaries. We can thereby take into account the temperature profile as well as its gradients specified by boundary conditions at the same time, which holds true even for a node where two or more boundaries meet with different boundary conditions. We argue that the image method is computationally efficient when combined with the local RBF collocation method, whereas the addition of image nodes becomes very costly in case of the global collocation. We apply our modified method to a benchmark test of a boundary value problem, and find that this simple modification reduces the maximum error from the analytic solution significantly. The reduction is small for an initial value problem with simpler boundary conditions. We observe increased numerical instability, which has to be compensated for by a sufficient number of sample nodes and/or more careful parameter choices for time integration.
Wavelets as basis functions in electronic structure calculations
International Nuclear Information System (INIS)
Chauvin, C.
2005-11-01
This thesis is devoted to the definition and the implementation of a multi-resolution method to determine the fundamental state of a system composed of nuclei and electrons. In this work, we are interested in the Density Functional Theory (DFT), which allows to express the Hamiltonian operator with the electronic density only, by a Coulomb potential and a non-linear potential. This operator acts on orbitals, which are solutions of the so-called Kohn-Sham equations. Their resolution needs to express orbitals and density on a set of functions owing both physical and numerical properties, as explained in the second chapter. One can hardly satisfy these two properties simultaneously, that is why we are interested in orthogonal and bi-orthogonal wavelets basis, whose properties of interpolation are presented in the third chapter. We present in the fourth chapter three dimensional solvers for the Coulomb's potential, using not only the preconditioning property of wavelets, but also a multigrid algorithm. Determining this potential allows us to solve the self-consistent Kohn-Sham equations, by an algorithm presented in chapter five. The originality of our method consists in the construction of the stiffness matrix, combining a Galerkin formulation and a collocation scheme. We analyse the approximation properties of this method in case of linear Hamiltonian, such as harmonic oscillator and hydrogen, and present convergence results of the DFT for small electrons. Finally we show how orbital compression reduces considerably the number of coefficients to keep, while preserving a good accuracy of the fundamental energy. (author)
Functional basis of sinus bradycardia in congenital heart block.
Hu, Keli; Qu, Yongxia; Yue, Yuankun; Boutjdir, Mohamed
2004-03-05
Congenital heart block (CHB) is a conduction abnormality characterized by complete atrioventricular (AV) block. CHB affects fetuses and/or newborn of mothers with autoantibodies reactive with ribonucleoproteins 48-kDa SSB/La, 52-kDa SSA/Ro, and 60-kDa SSA/Ro. We recently established animal models of CHB and reported, for the first time, significant sinus bradycardia preceding AV block. This unexpected observation implies that the spectrum of conduction abnormalities extends beyond the AV node to also affect the SA node. To test this hypothesis, we investigated the functional basis of this sinus bradycardia by characterizing the effects of antibodies from mothers with CHB children (positive IgG) on ionic currents that are known to significantly contribute to spontaneous pacing in SA node cells. We recorded L- (I(Ca.L)) and T- (I(Ca.T)) type Ca2+, delayed rectifier K+ (I(K)), hyperpolarization-activated (I(f)) currents, and action potentials (APs) from young rabbit SA node cells. We demonstrated that positive IgG significantly inhibited both I(Ca.T) and I(Ca.L) and induced sinus bradycardia but did not affect I(f) and I(K). Normal IgG from mothers with healthy children did not affect all the currents studied and APs. These results establish that IgG from mothers with CHB children causes substantial inhibition of I(Ca.T) and I(Ca.L), two important pacemaker currents in rabbit SA node cells and point to both I(Ca.T) and I(Ca.L) as major players in the ionic mechanism by which maternal antibodies induce sinus bradycardia in CHB. These novel findings have important clinical significance and suggest that sinus bradycardia may be a potential marker in the detection and prevention of CHB. The full text of this article is available online at http://circres.ahajournals.org
Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions.
Machado, Jeremias B; Campello, Ricardo J G B; Amaral, Wagner Caradori
2013-06-01
An approach to obtain Takagi-Sugeno (TS) fuzzy models of nonlinear dynamic systems using the framework of orthonormal basis functions (OBFs) is presented in this paper. This approach is based on an architecture in which local linear models with ladder-structured generalized OBFs (GOBFs) constitute the fuzzy rule consequents and the outputs of the corresponding GOBF filters are input variables for the rule antecedents. The resulting GOBF-TS model is characterized by having only real-valued parameters that do not depend on any user specification about particular types of functions to be used in the orthonormal basis. The fuzzy rules of the model are initially obtained by means of a well-known technique based on fuzzy clustering and least squares. Those rules are then simplified, and the model parameters (GOBF poles, GOBF expansion coefficients, and fuzzy membership functions) are subsequently adjusted by using a nonlinear optimization algorithm. The exact gradients of an error functional with respect to the parameters to be optimized are computed analytically. Those gradients provide exact search directions for the optimization process, which relies solely on input-output data measured from the system to be modeled. An example is presented to illustrate the performance of this approach in the modeling of a complex nonlinear dynamic system.
Bruni, S.; Llombart Juan, N.; Neto, A.; Gerini, G.; Maci, S.
2004-01-01
A general algorithm for the analysis of microstrip coupled leaky wave slot antennas was discussed. The method was based on the construction of physically appealing entire domain Methods of Moments (MoM) basis function that allowed a consistent reduction of the number of unknowns and of total
Real-space Kerker method for self-consistent calculation using non-orthogonal basis functions
International Nuclear Information System (INIS)
Shiihara, Yoshinori; Kuwazuru, Osamu; Yoshikawa, Nobuhiro
2008-01-01
We have proposed the real-space Kerker method for fast self-consistent-field calculations in real-space approaches using non-orthogonal basis functions. In large-scale systems with many atoms, the Kerker method is a very efficient way to prevent charge sloshing, which induces numerical instability during the self-consistent iterations. We construct the Kerker preconditioning matrix with non-orthogonal basis functions and the preconditioning is performed by solving linear equations. The proposed real-space Kerker method is identical to the method in reciprocal space, with the following two advantages: (i) the method is suitable for massively parallel computation since it does not use the fast Fourier transform. (ii) The preconditioning is performed in an acceptable computational time since time-consuming integration, including the exponential kernel, need not be performed, unlike the method used by Manninen et al (1975 Phys. Rev. B 12 4012)
Energy Technology Data Exchange (ETDEWEB)
Borges, A.; Solomon, G. C. [Department of Chemistry and Nano-Science Center, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen Ø (Denmark)
2016-05-21
Single molecule conductance measurements are often interpreted through computational modeling, but the complexity of these calculations makes it difficult to directly link them to simpler concepts and models. Previous work has attempted to make this connection using maximally localized Wannier functions and symmetry adapted basis sets, but their use can be ambiguous and non-trivial. Starting from a Hamiltonian and overlap matrix written in a hydrogen-like basis set, we demonstrate a simple approach to obtain a new basis set that is chemically more intuitive and allows interpretation in terms of simple concepts and models. By diagonalizing the Hamiltonians corresponding to each atom in the molecule, we obtain a basis set that can be partitioned into pseudo-σ and −π and allows partitioning of the Landuaer-Büttiker transmission as well as create simple Hückel models that reproduce the key features of the full calculation. This method provides a link between complex calculations and simple concepts and models to provide intuition or extract parameters for more complex model systems.
Molecular basis of glyphosate resistance: Different approaches through protein engineering
Pollegioni, Loredano; Schonbrunn, Ernst; Siehl, Daniel
2011-01-01
Glyphosate (N-phosphonomethyl-glycine) is the most-used herbicide in the world: glyphosate-based formulations exhibit broad-spectrum herbicidal activity with minimal human and environmental toxicity. The extraordinary success of this simple small molecule is mainly due to the high specificity of glyphosate towards the plant enzyme enolpyruvylshikimate-3-phosphate synthase in the shikimate pathway leading to biosynthesis of aromatic amino acids. Starting in 1996, transgenic glyphosate-resistant plants were introduced thus allowing the application of the herbicide to the crop (post-emergence) to remove emerged weeds without crop damage. This review focuses on the evolution of mechanisms of resistance to glyphosate as obtained through natural diversity, the gene shuffling approach to molecular evolution, and a rational, structure-based approach to protein engineering. In addition, we offer rationale for the means by which the modifications made have had their intended effect. PMID:21668647
Organisms modeling: The question of radial basis function networks
Directory of Open Access Journals (Sweden)
Muzy Alexandre
2014-01-01
Full Text Available There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evalution of an usual machine learning technique (radial basis funtion(RBF networks in the context of systems and biological reactive organisms.
Shaw, Robert A; Hill, J Grant
2017-04-11
Auxiliary basis sets for use in the resolution of the identity (RI) approximation in explicitly correlated methods are presented for the elements H-Ar. These extend the cc-pVnZ-F12/OptRI (n = D-Q) auxiliary basis sets of Peterson and co-workers by the addition of a small number of s- and p-functions, optimized so as to yield the greatest complementary auxiliary basis set (CABS) singles correction to the Hartree-Fock energy. The new sets, denoted OptRI+, also lead to a reduction in errors due to the RI approximation and hence an improvement in correlation energies. The atomization energies and heats of formation for a test set of small molecules, and spectroscopic constants for 27 diatomics, calculated at the CCSD(T)-F12b level, are shown to have improved error distributions for the new auxiliary basis sets with negligible additional effort. The OptRI+ sets retain all of the desirable properties of the original OptRI, including the production of smooth potential energy surfaces, while maintaining a compact nature.
The Argentine Approach to Radiation Safety: Its Ethical Basis
International Nuclear Information System (INIS)
Gonzalez, A.J.
2011-01-01
The ethical bases of Argentina's radiation safety approach are reviewed. The applied principles are those recommended and established internationally, namely: the principle of justification of decisions that alters the radiation exposure situation; the principle of optimization of protection and safety; the principle of individual protection for restricting possible inequitable outcomes of optimized safety; and the implicit principle of inter generational prudence for protection future generations and the habitat. The principles are compared vis-a-vis the prevalent ethical doctrines: justification vis-a-vis teleology; optimization vis-a-vis utilitarianism; individual protection vis-a-vis de ontology; and, inter generational prudence vis-a-vis aretaicism (or virtuosity). The application of the principles and their ethics in Argentina is analysed. These principles are applied to All exposure to radiation harm; namely, to exposures to actual doses and to exposures to actual risk and potential doses, including those related to the safety of nuclear installations, and they are harmonized and applied in conjunction. It is concluded that building a bridge among all available ethical doctrines and applying it to radiation safety against actual doses and actual risk and potential doses is at the roots of the successful nuclear regulatory experience in Argentina.
A Functional Approach to User Guides
DEFF Research Database (Denmark)
Nielsen, Sandro
2007-01-01
draw the user's attention to the different types of use-situations in which the dictionary can help him. When the dictionary functions have been established and the relevant user group has been profiled, the lexicographers will have an excellent basis on which to select the types of information needed...... on lexicography and lexicographic products is the writing of a really crafted and valuable user guide for instance by giving increased consideration to the user perspective. This involves the identification of the functions of the dictionary in terms of communication-oriented and cognitive functions, which helps...... to fulfil the requirements of users. By applying the functional approach lexicographers are forced to reconsider the scope of the user guide. The user guide has traditionally centred on the structures of entries - and consequently on the word list - but its scope should be widened, so as to include all...
Radial basis function neural network for power system load-flow
International Nuclear Information System (INIS)
Karami, A.; Mohammadi, M.S.
2008-01-01
This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)
Structural Basis for BRCA1 Function in Breast Cancer
National Research Council Canada - National Science Library
Ladias, John A
2005-01-01
The Breast Cancer Susceptibility gene 1 (BRCA1) encodes an 1863-amino acid protein that has important functions in cell cycle checkpoint control and DNA repair and plays a central role in the pathogenesis of breast cancer...
Integrated reclamation: Approaching ecological function?
Ann L. Hild; Nancy L. Shaw; Ginger B. Paige
2009-01-01
Attempts to reclaim arid and semiarid lands have traditionally targeted plant species composition. Much research attention has been directed to seeding rates, species mixes and timing of seeding. However, in order to attain functioning systems, attention to structure and process must compliment existing efforts. We ask how to use a systems approach to enhance...
Mandal, Sudhansu S.; Mukherjee, Sutirtha; Ray, Koushik
2018-03-01
A method for determining the ground state of a planar interacting many-electron system in a magnetic field perpendicular to the plane is described. The ground state wave-function is expressed as a linear combination of a set of basis functions. Given only the flux and the number of electrons describing an incompressible state, we use the combinatorics of partitioning the flux among the electrons to derive the basis wave-functions as linear combinations of Schur polynomials. The procedure ensures that the basis wave-functions form representations of the angular momentum algebra. We exemplify the method by deriving the basis functions for the 5/2 quantum Hall state with a few particles. We find that one of the basis functions is precisely the Moore-Read Pfaffian wave function.
Sociocultural Competence as a Basis for Functional Education: A ...
African Journals Online (AJOL)
This paper examines the relevance of socio-cultural competence in functional education. It highlights the various roles that a good knowledge of the African cultural values can play in enhancing meaningful education of in the present Nigeria educational system. It also examines various aspects of the indigenous Nigerian ...
52 Sociocultural Competence as a Basis for Functional Education: A ...
African Journals Online (AJOL)
User
2010-10-17
Oct 17, 2010 ... Emphasis was on social responsibility, character training, job orientation, political participation, spiritual values and moral values. Similarly the present educational system places emphasis on functional education; education for self-reliance; scientific and technological advancement; improvement of the ...
Studies in the method of correlated basis functions. Pt. 3
International Nuclear Information System (INIS)
Krotscheck, E.; Clark, J.W.
1980-01-01
A variational theory of pairing phenomena is presented for systems like neutron matter and liquid 3 He. The strong short-range correlations among the particles in these systems are incorporated into the trial states describing normal and pair-condensed phases, via a correlation operator F. The resulting theory has the same basic structure as that ordinarily applied for weak two-body interactions; in place of the pairing matrix elements of the bare interaction one finds certain effective pairing matrix elements Psub(kl), and modified single particle energies epsilon (k) appear. Detailed prescriptions are given for the construction of the Psub(kl) and epsilon (k) in terms of off-diagonal and diagonal matrix elements of the Hamiltonian and unit operators in a correlated basis of normal states. An exact criterion for instability of the assumed normal phase with respect to pair condensation is derived for general F. This criterion is investigated numerically for the special case if Jastrow correlations, the required normal-state quantities being evaluated by integral equation techniques which extend the Fermi hypernetted-chain scheme. In neutron matter, an instability with respect to 1 S 0 pairing is found in the low-density region, in concert with the predictions of Yang and Clark. In liquid 3 He, there is some indication of a 3 P 0 pairing instability in the vicinity of the experimental equilibrium density. (orig.)
Directory of Open Access Journals (Sweden)
Yunfeng Wu
2014-01-01
Full Text Available This paper presents a novel adaptive linear and normalized combination (ALNC method that can be used to combine the component radial basis function networks (RBFNs to implement better function approximation and regression tasks. The optimization of the fusion weights is obtained by solving a constrained quadratic programming problem. According to the instantaneous errors generated by the component RBFNs, the ALNC is able to perform the selective ensemble of multiple leaners by adaptively adjusting the fusion weights from one instance to another. The results of the experiments on eight synthetic function approximation and six benchmark regression data sets show that the ALNC method can effectively help the ensemble system achieve a higher accuracy (measured in terms of mean-squared error and the better fidelity (characterized by normalized correlation coefficient of approximation, in relation to the popular simple average, weighted average, and the Bagging methods.
Representation and Metrics Extraction from Feature Basis: An Object Oriented Approach
Directory of Open Access Journals (Sweden)
Fausto Neri da Silva Vanin
2010-10-01
Full Text Available This tutorial presents an object oriented approach to data reading and metrics extraction from feature basis. Structural issues about basis are discussed first, then the Object Oriented Programming (OOP is aplied to modeling the main elements in this context. The model implementation is then discussed using C++ as programing language. To validate the proposed model, we apply on some feature basis from the University of Carolina, Irvine Machine Learning Database.
Understanding the Structural Basis of Adhesion GPCR Functions.
Araç, Demet; Sträter, Norbert; Seiradake, Elena
2016-01-01
Unlike conventional G-protein-coupled receptors (GPCRs), adhesion GPCRs (aGPCRs) have large extracellular regions that are autoproteolytically cleaved from their membrane-embedded seven-pass transmembrane helices. Autoproteolysis occurs within the conserved GPCR-Autoproteolysis INducing (GAIN) domain that is juxtaposed to the transmembrane domain and cleaves the last beta strand of the GAIN domain. The other domains of the extracellular region are variable and specific to each aGPCR and are likely involved in adhering to various ligands. Emerging evidence suggest that extracellular regions may modulate receptor function and that ligand binding to the extracellular regions may induce receptor activation via multiple mechanisms. Here, we summarize current knowledge about the structural understanding for the extracellular regions of aGPCRs and discuss their possible functional roles that emerge from the available structural information.
Structural Basis of Merlin Tumor Suppressor Functions in Neurofibromatosis-2
2014-12-01
Neurofibromatosis-2 PRINCIPAL INVESTIGATOR: Dr. Tina Izard CONTRACTING ORGANIZATION: The Scripps Research Institute Jupiter , FL 33458...Functions in Neurofibromatosis-2 5b. GRANT NUMBER W81XWH-12-1-0451 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Dr. Tina...ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER The Scripps Research Institute 130 Scripps Way, #2C1 Jupiter , FL 33458
Modular High Temperature Gas-Cooled Reactor Safety Basis and Approach
Energy Technology Data Exchange (ETDEWEB)
David Petti; Jim Kinsey; Dave Alberstein
2014-01-01
Various international efforts are underway to assess the safety of advanced nuclear reactor designs. For example, the International Atomic Energy Agency has recently held its first Consultancy Meeting on a new cooperative research program on high temperature gas-cooled reactor (HTGR) safety. Furthermore, the Generation IV International Forum Reactor Safety Working Group has recently developed a methodology, called the Integrated Safety Assessment Methodology, for use in Generation IV advanced reactor technology development, design, and design review. A risk and safety assessment white paper is under development with respect to the Very High Temperature Reactor to pilot the Integrated Safety Assessment Methodology and to demonstrate its validity and feasibility. To support such efforts, this information paper on the modular HTGR safety basis and approach has been prepared. The paper provides a summary level introduction to HTGR history, public safety objectives, inherent and passive safety features, radionuclide release barriers, functional safety approach, and risk-informed safety approach. The information in this paper is intended to further the understanding of the modular HTGR safety approach. The paper gives those involved in the assessment of advanced reactor designs an opportunity to assess an advanced design that has already received extensive review by regulatory authorities and to judge the utility of recently proposed new methods for advanced reactor safety assessment such as the Integrated Safety Assessment Methodology.
Florez, W. F.; Portapila, M.; Hill, A. F.; Power, H.; Orsini, P.; Bustamante, C. A.
2015-03-01
The aim of this paper is to present how to implement a control volume approach improved by Hermite radial basis functions (CV-RBF) for geochemical problems. A multi-step strategy based on Richardson extrapolation is proposed as an alternative to the conventional dual step sequential non-iterative approach (SNIA) for coupling the transport equations with the chemical model. Additionally, this paper illustrates how to use PHREEQC to add geochemical reaction capabilities to CV-RBF transport methods. Several problems with different degrees of complexity were solved including cases of cation exchange, dissolution, dissociation, equilibrium and kinetics at different rates for mineral species. The results show that the solution and strategies presented here are effective and in good agreement with other methods presented in the literature for the same cases.
Ryu, Duchwan
2013-03-01
The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Brown, James; Carrington, Tucker
2016-06-28
In this paper we show that it is possible to use an iterative eigensolver in conjunction with Halverson and Poirier's symmetrized Gaussian (SG) basis [T. Halverson and B. Poirier, J. Chem. Phys. 137, 224101 (2012)] to compute accurate vibrational energy levels of molecules with as many as five atoms. This is done, without storing and manipulating large matrices, by solving a regular eigenvalue problem that makes it possible to exploit direct-product structure. These ideas are combined with a new procedure for selecting which basis functions to use. The SG basis we work with is orders of magnitude smaller than the basis made by using a classical energy criterion. We find significant convergence errors in previous calculations with SG bases. For sum-of-product Hamiltonians, SG bases large enough to compute accurate levels are orders of magnitude larger than even simple pruned bases composed of products of harmonic oscillator functions.
Avian magnetic compass: Its functional properties and physical basis
Directory of Open Access Journals (Sweden)
Roswitha WILTSCHKO, Wolfgang WILTSCHKO
2010-06-01
Full Text Available The avian magnetic compass was analyzed in bird species of three different orders – Passeriforms, Columbiforms and Galliforms – and in three different behavioral contexts, namely migratory orientation, homing and directional conditioning. The respective findings indicate similar functional properties: it is an inclination compass that works only within a functional window around the ambient magnetic field intensity; it tends to be lateralized in favor of the right eye, and it is wavelength-dependent, requiring light from the short-wavelength range of the spectrum. The underlying physical mechanisms have been identified as radical pair processes, spin-chemical reactions in specialized photopigments. The iron-based receptors in the upper beak do not seem to be involved. The existence of the same type of magnetic compass in only very distantly related bird species suggests that it may have been present already in the common ancestors of all modern birds, where it evolved as an all-purpose compass mechanism for orientation within the home range [Current Zoology 56 (3: 265–276, 2010].
International Nuclear Information System (INIS)
Brorsen, Kurt R.; Sirjoosingh, Andrew; Pak, Michael V.; Hammes-Schiffer, Sharon
2015-01-01
The nuclear electronic orbital (NEO) reduced explicitly correlated Hartree-Fock (RXCHF) approach couples select electronic orbitals to the nuclear orbital via Gaussian-type geminal functions. This approach is extended to enable the use of a restricted basis set for the explicitly correlated electronic orbitals and an open-shell treatment for the other electronic orbitals. The working equations are derived and the implementation is discussed for both extensions. The RXCHF method with a restricted basis set is applied to HCN and FHF − and is shown to agree quantitatively with results from RXCHF calculations with a full basis set. The number of many-particle integrals that must be calculated for these two molecules is reduced by over an order of magnitude with essentially no loss in accuracy, and the reduction factor will increase substantially for larger systems. Typically, the computational cost of RXCHF calculations with restricted basis sets will scale in terms of the number of basis functions centered on the quantum nucleus and the covalently bonded neighbor(s). In addition, the RXCHF method with an odd number of electrons that are not explicitly correlated to the nuclear orbital is implemented using a restricted open-shell formalism for these electrons. This method is applied to HCN + , and the nuclear densities are in qualitative agreement with grid-based calculations. Future work will focus on the significance of nonadiabatic effects in molecular systems and the further enhancement of the NEO-RXCHF approach to accurately describe such effects
Brorsen, Kurt R; Sirjoosingh, Andrew; Pak, Michael V; Hammes-Schiffer, Sharon
2015-06-07
The nuclear electronic orbital (NEO) reduced explicitly correlated Hartree-Fock (RXCHF) approach couples select electronic orbitals to the nuclear orbital via Gaussian-type geminal functions. This approach is extended to enable the use of a restricted basis set for the explicitly correlated electronic orbitals and an open-shell treatment for the other electronic orbitals. The working equations are derived and the implementation is discussed for both extensions. The RXCHF method with a restricted basis set is applied to HCN and FHF(-) and is shown to agree quantitatively with results from RXCHF calculations with a full basis set. The number of many-particle integrals that must be calculated for these two molecules is reduced by over an order of magnitude with essentially no loss in accuracy, and the reduction factor will increase substantially for larger systems. Typically, the computational cost of RXCHF calculations with restricted basis sets will scale in terms of the number of basis functions centered on the quantum nucleus and the covalently bonded neighbor(s). In addition, the RXCHF method with an odd number of electrons that are not explicitly correlated to the nuclear orbital is implemented using a restricted open-shell formalism for these electrons. This method is applied to HCN(+), and the nuclear densities are in qualitative agreement with grid-based calculations. Future work will focus on the significance of nonadiabatic effects in molecular systems and the further enhancement of the NEO-RXCHF approach to accurately describe such effects.
Factorization of products of discontinuous functions applied to Fourier-Bessel basis.
Popov, Evgeny; Nevière, Michel; Bonod, Nicolas
2004-01-01
The factorization rules of Li [J. Opt. Soc. Am. A 13, 1870 (1996)] are generalized to a cylindrical geometry requiring the use of a Bessel function basis. A theoretical study confirms the validity of the Laurent rule when a product of two continuous functions or of one continuous and one discontinuous function is factorized. The necessity of applying the so-called inverse rule in factorizing a continuous product of two discontinuous functions in a truncated basis is demonstrated theoretically and numerically.
Explicit appropriate basis function method for numerical solution of stiff systems
International Nuclear Information System (INIS)
Chen, Wenzhen; Xiao, Hongguang; Li, Haofeng; Chen, Ling
2015-01-01
Highlights: • An explicit numerical method called the appropriate basis function method is presented. • The method differs from the power series method for obtaining approximate numerical solutions. • Two cases show the method is fit for linear and nonlinear stiff systems. • The method is very simple and effective for most of differential equation systems. - Abstract: In this paper, an explicit numerical method, called the appropriate basis function method, is presented. The explicit appropriate basis function method differs from the power series method because it employs an appropriate basis function such as the exponential function, or periodic function, other than a polynomial, to obtain approximate numerical solutions. The method is successful and effective for the numerical solution of the first order ordinary differential equations. Two examples are presented to show the ability of the method for dealing with linear and nonlinear systems of differential equations
Hellweg, Arnim; Rappoport, Dmitrij
2015-01-14
We report optimized auxiliary basis sets for use with the Karlsruhe segmented contracted basis sets including moderately diffuse basis functions (Rappoport and Furche, J. Chem. Phys., 2010, 133, 134105) in resolution-of-the-identity (RI) post-self-consistent field (post-SCF) computations for the elements H-Rn (except lanthanides). The errors of the RI approximation using optimized auxiliary basis sets are analyzed on a comprehensive test set of molecules containing the most common oxidation states of each element and do not exceed those of the corresponding unaugmented basis sets. During these studies an unsatisfying performance of the def2-SVP and def2-QZVPP auxiliary basis sets for Barium was found and improved sets are provided. We establish the versatility of the def2-SVPD, def2-TZVPPD, and def2-QZVPPD basis sets for RI-MP2 and RI-CC (coupled-cluster) energy and property calculations. The influence of diffuse basis functions on correlation energy, basis set superposition error, atomic electron affinity, dipole moments, and computational timings is evaluated at different levels of theory using benchmark sets and showcase examples.
Sun, Jie; Yi, Hong-Liang; Tan, He-Ping
2016-02-20
A local radial basis function meshless scheme (LRBFM) is developed to solve polarized radiative transfer in participating media containing randomly oriented axisymmetric particles in which radial basis functions augmented with polynomial basis are employed to construct the trial functions, and the vector radiative-transfer equation based on the discrete-ordinates approach is discretized directly by collocation method. The LRBFM belongs to a class of truly meshless methods that do not need any mesh or any numerical integration scheme. Performances of the LRBFM are verified with analytical solutions and other numerical results reported earlier in the literature via five various test cases. The predicted angular distribution of brightness temperature and Stokes vector by the LRBFM agree very well with the benchmark. It is demonstrated that the LRBFM is accurate to solve vector radiative transfer in participating media with randomly oriented axisymmetric particles.
Directory of Open Access Journals (Sweden)
Jin-Xiu Hu
2014-01-01
Full Text Available A new approach is presented for the numerical evaluation of arbitrary singular domain integrals. In this method, singular domain integrals are transformed into a boundary integral and a radial integral which contains singularities by using the radial integration method. The analytical elimination of singularities condensed in the radial integral formulas can be accomplished by expressing the nonsingular part of the integration kernels as a series of cubic B-spline basis functions of the distance r and using the intrinsic features of the radial integral. In the proposed method, singularities involved in the domain integrals are explicitly transformed to the boundary integrals, so no singularities exist at internal points. A few numerical examples are provided to verify the correctness and robustness of the presented method.
Lam, Dao; Wunsch, Donald
2017-01-01
Ever-increasing size and complexity of data sets create challenges and potential tradeoffs of accuracy and speed in learning algorithms. This paper offers progress on both fronts. It presents a mechanism to train the unsupervised learning features learned from only one layer to improve performance in both speed and accuracy. The features are learned by an unsupervised feature learning (UFL) algorithm. Then, those features are trained by a fast radial basis function (RBF) extreme learning machine (ELM). By exploiting the massive parallel computing attribute of modern graphics processing unit, a customized compute unified device architecture (CUDA) kernel is developed to further speed up the computing of the RBF kernel in the ELM. Results tested on Canadian Institute for Advanced Research and Mixed National Institute of Standards and Technology data sets confirm the UFL RBF ELM achieves high accuracy, and the CUDA implementation is up to 20 times faster than CPU and the naive parallel approach.
Directory of Open Access Journals (Sweden)
Sharma Rakesh
2004-05-01
Full Text Available Abstract Functional magnetic resonance imaging (fMRI is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities.
Liu, Jinkun
2013-01-01
Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...
Functional Basis for Efficient Physical Layer Classical Control in Quantum Processors
Ball, Harrison; Nguyen, Trung; Leong, Philip H. W.; Biercuk, Michael J.
2016-12-01
The rapid progress seen in the development of quantum-coherent devices for information processing has motivated serious consideration of quantum computer architecture and organization. One topic which remains open for investigation and optimization relates to the design of the classical-quantum interface, where control operations on individual qubits are applied according to higher-level algorithms; accommodating competing demands on performance and scalability remains a major outstanding challenge. In this work, we present a resource-efficient, scalable framework for the implementation of embedded physical layer classical controllers for quantum-information systems. Design drivers and key functionalities are introduced, leading to the selection of Walsh functions as an effective functional basis for both programing and controller hardware implementation. This approach leverages the simplicity of real-time Walsh-function generation in classical digital hardware, and the fact that a wide variety of physical layer controls, such as dynamic error suppression, are known to fall within the Walsh family. We experimentally implement a real-time field-programmable-gate-array-based Walsh controller producing Walsh timing signals and Walsh-synthesized analog waveforms appropriate for critical tasks in error-resistant quantum control and noise characterization. These demonstrations represent the first step towards a unified framework for the realization of physical layer controls compatible with large-scale quantum-information processing.
Multiscale finite element methods for high-contrast problems using local spectral basis functions
Efendiev, Yalchin
2011-02-01
In this paper we study multiscale finite element methods (MsFEMs) using spectral multiscale basis functions that are designed for high-contrast problems. Multiscale basis functions are constructed using eigenvectors of a carefully selected local spectral problem. This local spectral problem strongly depends on the choice of initial partition of unity functions. The resulting space enriches the initial multiscale space using eigenvectors of local spectral problem. The eigenvectors corresponding to small, asymptotically vanishing, eigenvalues detect important features of the solutions that are not captured by initial multiscale basis functions. Multiscale basis functions are constructed such that they span these eigenfunctions that correspond to small, asymptotically vanishing, eigenvalues. We present a convergence study that shows that the convergence rate (in energy norm) is proportional to (H/Λ*)1/2, where Λ* is proportional to the minimum of the eigenvalues that the corresponding eigenvectors are not included in the coarse space. Thus, we would like to reach to a larger eigenvalue with a smaller coarse space. This is accomplished with a careful choice of initial multiscale basis functions and the setup of the eigenvalue problems. Numerical results are presented to back-up our theoretical results and to show higher accuracy of MsFEMs with spectral multiscale basis functions. We also present a hierarchical construction of the eigenvectors that provides CPU savings. © 2010.
CSIR Research Space (South Africa)
Bogaers, Alfred EJ
2016-10-01
Full Text Available In this paper we outline the use of radial basis function interpolation (RBF) to transfer information across non-matching and nonconforming interface meshes, with particular focus to partitioned fluid-structure interactions (FSI). In general...
Image Super-Resolution Using Adaptive 2-D Gaussian Basis Function Interpolation
National Research Council Canada - National Science Library
Hunt, Terence
2004-01-01
... characteristics to be more effectively represented. The interpolation is constrained to reproduce the original image mean gray level, and the mean basis function variance is determined using the expected image smoothness for the increased resolution...
Training Radial Basis Function Neural Networks for Classification via Class-Specific Clustering.
Raitoharju, Jenni; Kiranyaz, Serkan; Gabbouj, Moncef
2016-12-01
In training radial basis function neural networks (RBFNNs), the locations of Gaussian neurons are commonly determined by clustering. Training inputs can be clustered on a fully unsupervised manner (input clustering), or some supervision can be introduced, for example, by concatenating the input vectors with weighted output vectors (input-output clustering). In this paper, we propose to apply clustering separately for each class (class-specific clustering). The idea has been used in some previous works, but without evaluating the benefits of the approach. We compare the class-specific, input, and input-output clustering approaches in terms of classification performance and computational efficiency when training RBFNNs. To accomplish this objective, we apply three different clustering algorithms and conduct experiments on 25 benchmark data sets. We show that the class-specific approach significantly reduces the overall complexity of the clustering, and our experimental results demonstrate that it can also lead to a significant gain in the classification performance, especially for the networks with a relatively few Gaussian neurons. Among other applied clustering algorithms, we combine, for the first time, a dynamic evolutionary optimization method, multidimensional particle swarm optimization, and the class-specific clustering to optimize the number of cluster centroids and their locations.
ANALYTICAL SOLUTION OF BASIC SHIP HYDROSTATICS INTEGRALS USING POLYNOMIAL RADIAL BASIS FUNCTIONS
Dario Ban; Josip Bašić
2015-01-01
One of the main tasks of ship's computational geometry is calculation of basic integrals of ship's hydrostatics. In order to enable direct computation of those integrals it is necessary to describe geometry using analytical methods, like description using radial basis functions (RBF) with L1 norm. Moreover, using the composition of cubic and linear Polynomial radial basis functions, it is possible to give analytical solution of general global 2D description of ship geometry with discontinuiti...
D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel
2016-03-01
We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.
Peculiar motions of galaxy clusters: correlation function approach
Iqbal, Naseer; Masood, Tabasum; Hamid, Mubashir; Ahmad, Naveel; Maqbool, Bari
2014-10-01
The correlation function theory on the basis of prescribed boundary conditions provides a deeper understanding in studying the dynamical parameters of galaxy clusters. The approach approximates that the moderate dense systems discussed by a two point correlation function is helpful for describing the dynamical nature of galaxy clusters. The projected theory of two point correlation function for point mass and extended mass structures can be used an alternative tool in measuring the average peculiar motion and temperature profile of galaxy clusters.
Li, Bo; Rui, Xiaoting
2018-01-01
Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.
Using radial basis functions in airborne gravimetry for local geoid improvement
Li, Xiaopeng
2017-10-01
Radial basis functions (RBFs) have been used extensively in satellite geodetic applications. However, to the author's knowledge, their role in processing and modeling airborne gravity data has not yet been fully advocated or extensively investigated in detail. Compared with satellite missions, the airborne data are more suitable for these kinds of localized basis functions especially considering the following facts: (1) Unlike the satellite missions that can provide global or near global data coverage, airborne gravity data are usually geographically limited. (2) It is also band limited in the frequency domain. (3) It is straightforward to formulate the RBF observation equations from an airborne gravimetric system. In this study, a set of band-limited RBF is developed to model and downward continue the airborne gravity data for local geoid improvement. First, EIGEN6c4 coefficients are used to simulate a harmonic field to test the performances of RBF on various sampling, noise, and flight height levels, in order to gain certain guidelines for processing the real data. Here, the RBF method not only successfully recovers the harmonic field but also presents filtering properties due to its particular design in the frequency domain. Next, the software was tested for the GSVS14 (Geoid Slope Validation Survey 2014) area in Iowa as well as for the area around Puerto Rico and the US Virgin Islands by use of the real airborne gravity data from the Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project. By fully utilizing the three-dimensional correlation information among the flight tracks, the RBF can also be used as a data cleaning tool for airborne gravity data adjustment and cleaning. This property is further extended to surface gravity data cleaning, where conventional approaches have various limitations. All the related numerical results clearly show the importance and contribution of the use of the RBF for high- resolution local gravity field
Radial basis function networks applied to DNBR calculation in digital core protection systems
International Nuclear Information System (INIS)
Lee, Gyu-Cheon; Heung Chang, Soon
2003-01-01
The nuclear power plant has to be operated with sufficient margin from the specified DNBR limit for assuring its safety. The digital core protection system calculates on-line real-time DNBR by using a complex subchannel analysis program, and triggers a reliable reactor shutdown if the calculated DNBR approaches the specified limit. However, it takes a relatively long calculation time even for a steady state condition, which may have an adverse effect on the operation flexibility. To overcome the drawback, a new method using a radial basis function network is presented in this paper. Nonparametric training approach is utilized, which shows dramatic reduction of the training time, no tedious heuristic process for optimizing parameters, and no local minima problem during the training. The test results show that the predicted DNBR is within about ±2% deviation from the target DNBR for the fixed axial flux shape case. For the variable axial flux case including severely skewed shapes that appeared during accidents, the deviation is within about ±10%. The suggested method could be the alternative that can calculate DNBR very quickly while guaranteeing the plant safety
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.
Kumudha, P; Venkatesan, R
Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction
Directory of Open Access Journals (Sweden)
P. Kumudha
2016-01-01
Full Text Available Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN and the novel adaptive dimensional biogeography based optimization (ADBBO model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.
High Rayleigh Number 3-D Spherical Mantle Convection with Radial Basis Functions
Flyer, N.; Yuen (3), G. Wright, D.
2009-04-01
In the last quarter of a century many numerical methods, such as finite-differences, finite-volume, their yin-yang variants, finite-elements and pseudo-spectral methods have been used to study the problem of 3-D spherical convection. All have their respective strengths but also serious weaknesses, such as low-order and can involve high algorithmic complexity, as in triangular elements. Spectrally accurate methods do not practically allow for local mesh refinement and often involve cumbersome algebra. We have recently introduced a new grid/mesh-free approach, using radial basis functions ( RBFs) . It has the advantage of being spectrally accurate for arbitrary node layouts in multi-dimensions with extreme algorithmic simplicity, and allows naturally node-refinement. One virtue of the RBF scheme is the ability to use a simple Cartesian geometry while implementing the required boundary conditions for the temperature, velocity and stresses on a spherical surface of both the outer( planetary surface ) and inner shell ( core-mantle boundary ). The velocity and stress components are expressed in terms of the scalar potential approach and the other remaining variable is the perturbed temperature field. We have studied the problem from the weakly nonlinear to a moderately nonlinear regime involving a Rayleigh number, about 1000 times super-critical. Both purely basal and partially internal -heating cases have been considered
Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model
Directory of Open Access Journals (Sweden)
Yazid Edwar
2014-07-01
Full Text Available This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA. The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.
Satisfiability of logic programming based on radial basis function neural networks
International Nuclear Information System (INIS)
Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong
2014-01-01
In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems
Satisfiability of logic programming based on radial basis function neural networks
Energy Technology Data Exchange (ETDEWEB)
Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)
2014-07-10
In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.
Unification of Plasma Fluid and Kinetic Theory via Gaussian Radial Basis Functions
Candy, J. M.
2015-11-01
A fundamental macroscopic description of a magnetized plasma is the Vlasov equation supplemented by the nonlinear inverse-square force Fokker-Planck collision operator [Rosenbluth et al., Phys. Rev. 107, 1957]. The Vlasov part describes advection in a six-dimensional phase space whereas the collision operator contains friction and diffusion coefficients that are weighted velocity-space integrals of the particle distribution function. The Fokker-Planck collision operator is an integro-differential, nonlinear (bilinear) operator. Numerical discretization of the operator, in particular for collisions of unlike species, is extremely challenging. In this work, we describe a new approach to discretize the entire kinetic system based on an expansion in Gaussian Radial Basis functions (RBFs). This approach is particularly well-suited to treat the collision operator because the friction and diffusion coefficients can be analytically calculated. Although the RBF method is known to be a powerful scheme for the interpolation of scattered multidimensional data, Gaussian RBFs also have a deep physical interpretation in statistical mechanics and plasma physics as local thermodynamic equilibria. We outline the general theory, highlight the connection to plasma fluid theories, and also give 2D and 3D numerical solutions of the nonlinear Fokker-Planck equation. A broad spectrum of applications for the new method is anticipated in both astrophysical and laboratory plasmas. In particular, we believe that the RBF method may provide a new bridge between fluid and kinetic descriptions of magnetized plasma. Work supported in part by US DOE under DE-FG02-08ER54963.
Bruni, S.; Llombart, N.; Neto, A.; Gerini, G.; Maci, S.
2004-01-01
A method is proposed for the analysis of arrays of linear printed antennas. After the formulation of pertinent set of integral equations, the appropriate equivalent currents of the Method of Moments are represented in terms of two sets of entire domain basis functions. These functions synthesize on
Symmetric multivariate polynomials as a basis for three-boson light-front wave functions.
Chabysheva, Sophia S; Elliott, Blair; Hiller, John R
2013-12-01
We develop a polynomial basis to be used in numerical calculations of light-front Fock-space wave functions. Such wave functions typically depend on longitudinal momentum fractions that sum to unity. For three particles, this constraint limits the two remaining independent momentum fractions to a triangle, for which the three momentum fractions act as barycentric coordinates. For three identical bosons, the wave function must be symmetric with respect to all three momentum fractions. Therefore, as a basis, we construct polynomials in two variables on a triangle that are symmetric with respect to the interchange of any two barycentric coordinates. We find that, through the fifth order, the polynomial is unique at each order, and, in general, these polynomials can be constructed from products of powers of the second- and third-order polynomials. The use of such a basis is illustrated in a calculation of a light-front wave function in two-dimensional ϕ(4) theory; the polynomial basis performs much better than the plane-wave basis used in discrete light-cone quantization.
Non-linear cancer classification using a modified radial basis function classification algorithm.
Wang, Hong-Qiang; Huang, De-Shuang
2005-10-01
This paper proposes a modified radial basis function classification algorithm for non-linear cancer classification. In the algorithm, a modified simulated annealing method is developed and combined with the linear least square and gradient paradigms to optimize the structure of the radial basis function (RBF) classifier. The proposed algorithm can be adopted to perform non-linear cancer classification based on gene expression profiles and applied to two microarray data sets involving various human tumor classes: (1) Normal versus colon tumor; (2) acute myeloid leukemia (AML) versus acute lymphoblastic leukemia (ALL). Finally, accuracy and stability for the proposed algorithm are further demonstrated by comparing with the other cancer classification algorithms.
DEFF Research Database (Denmark)
Kim, Oleksiy S.; Jørgensen, Erik; Meincke, Peter
2004-01-01
An efficient higher-order method of moments (MoM) solution of volume integral equations is presented. The higher-order MoM solution is based on higher-order hierarchical Legendre basis functions and higher-order geometry modeling. An unstructured mesh composed of 8-node trilinear and/or curved 27...... of magnitude in comparison to existing higher-order hierarchical basis functions. Consequently, an iterative solver can be applied even for high expansion orders. Numerical results demonstrate excellent agreement with the analytical Mie series solution for a dielectric sphere as well as with results obtained...
ANALYTICAL SOLUTION OF BASIC SHIP HYDROSTATICS INTEGRALS USING POLYNOMIAL RADIAL BASIS FUNCTIONS
Directory of Open Access Journals (Sweden)
Dario Ban
2015-09-01
Full Text Available One of the main tasks of ship's computational geometry is calculation of basic integrals of ship's hydrostatics. In order to enable direct computation of those integrals it is necessary to describe geometry using analytical methods, like description using radial basis functions (RBF with L1 norm. Moreover, using the composition of cubic and linear Polynomial radial basis functions, it is possible to give analytical solution of general global 2D description of ship geometry with discontinuities in the form of polynomials, thus enabling direct calculation of basic integrals of ship hydrostatics.
Diagnostic Approach to Functional Recovery
DEFF Research Database (Denmark)
Havsteen, Inger; Madsen, Kristoffer H; Christensen, Hanne Krarup
2013-01-01
available and does not pose any adverse effects, repeated fMRI measurements provide unprecedented possibilities to prospectively assess the time course of reorganization in functional neural networks after stroke and relate the temporospatial dynamics of reorganization at the systems level to functional...
International Nuclear Information System (INIS)
Šula, Radek
2013-01-01
Introduction and objectives: • It is evident that the design basis area is from the point of view of knowledge sharing extremely complicated. • Time is changing and puts on us ever greater demands. • We have to analyze the near and remote surroundings and have to simplified the problem of knowledge sharing in that area. • I believe that it is graspable task for knowledge management and I will try to outline some possible context and approaches
International Nuclear Information System (INIS)
1991-03-01
This report summarizes the results of a deterministic assessment of earthquake ground motions at the Savannah River Site (SRS). The purpose of this study is to assist the Environmental Sciences Section of the Savannah River Laboratory in reevaluating the design basis earthquake (DBE) ground motion at SRS during approaches defined in Appendix A to 10 CFR Part 100. This work is in support of the Seismic Engineering Section's Seismic Qualification Program for reactor restart
Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao
2014-09-18
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.
Method of applying single higher order polynomial basis function over multiple domains
CSIR Research Space (South Africa)
Lysko, AA
2010-03-01
Full Text Available M) with higher-order polynomial basis functions, and applied to a surface form of the electrical field integral equation, under thin wire approximation. The main advantage of the proposed method is in permitting to reduce the required number of unknowns when...
Method of applying single higher order polynomial basis function over multiple domains
CSIR Research Space (South Africa)
Lysko, AA
2010-03-01
Full Text Available A novel method has been devised where one set of higher order polynomial-based basis functions can be applied over several wire segments, thus permitting to decouple the number of unknowns from the number of segments, and so from the geometrical...
Radial Basis Function Network Assisted Space-Time Equalisation for Dispersive Fading Environments
Wolfgang, A.; Chen, S.; Hanzo, L.
2004-01-01
A novel radial basis function network assisted decision-feedback aided space-time equaliser designed for receivers employing multiple antennas is presented. The proposed receiver structure outperforms the linear minimum mean-squared error benchmarker and is less sensitive to both error propagation and channel estimation errors.
High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid
Directory of Open Access Journals (Sweden)
J. Cabello
2012-01-01
Full Text Available Statistical iterative methods are a widely used method of image reconstruction in emission tomography. Traditionally, the image space is modelled as a combination of cubic voxels as a matter of simplicity. After reconstruction, images are routinely filtered to reduce statistical noise at the cost of spatial resolution degradation. An alternative to produce lower noise during reconstruction is to model the image space with spherical basis functions. These basis functions overlap in space producing a significantly large number of non-zero elements in the system response matrix (SRM to store, which additionally leads to long reconstruction times. These two problems are partly overcome by exploiting spherical symmetries, although computation time is still slower compared to non-overlapping basis functions. In this work, we have implemented the reconstruction algorithm using Graphical Processing Unit (GPU technology for speed and a precomputed Monte-Carlo-calculated SRM for accuracy. The reconstruction time achieved using spherical basis functions on a GPU was 4.3 times faster than the Central Processing Unit (CPU and 2.5 times faster than a CPU-multi-core parallel implementation using eight cores. Overwriting hazards are minimized by combining a random line of response ordering and constrained atomic writing. Small differences in image quality were observed between implementations.
A conceptual basis to encode and detect organic functional groups in XML.
Sankar, Punnaivanam; Krief, Alain; Vijayasarathi, Durairaj
2013-06-01
A conceptual basis to define and detect organic functional groups is developed. The basic model of a functional group is termed as a primary functional group and is characterized by a group center composed of one or more group center atoms bonded to terminal atoms and skeletal carbon atoms. The generic group center patterns are identified from the structures of known functional groups. Accordingly, a chemical ontology 'Font' is developed to organize the existing functional groups as well as the new ones to be defined by the chemists. The basic model is extended to accommodate various combinations of primary functional groups as functional group assemblies. A concept of skeletal group is proposed to define the characteristic groups composed of only carbon atoms to be regarded as equivalent to functional groups. The combination of primary functional groups with skeletal groups is categorized as skeletal group assembly. In order to make the model suitable for reaction modeling purpose, a Graphical User Interface (GUI) is developed to define the functional groups and to encode in XML format appropriate to detect them in chemical structures. The system is capable of detecting multiple instances of primary functional groups as well as the overlapping poly-functional groups as the respective assemblies. Copyright © 2013 Elsevier Inc. All rights reserved.
Hoyer, Chad E; Gagliardi, Laura; Truhlar, Donald G
2015-11-05
Time-dependent Kohn-Sham density functional theory (TD-KS-DFT) is useful for calculating electronic excitation spectra of large systems, but the low-energy spectra are often complicated by artificially lowered higher-energy states. This affects even the lowest energy excited states. Here, by calculating the lowest energy spin-conserving excited state for atoms from H to K and for formaldehyde, we show that this problem does not occur in multiconfiguration pair-density functional theory (MC-PDFT). We use the tPBE on-top density functional, which is a translation of the PBE exchange-correlation functional. We compare to a robust multireference method, namely, complete active space second-order perturbation theory (CASPT2), and to TD-KS-DFT with two popular exchange-correlation functionals, PBE and PBE0. We find for atoms that the mean unsigned error (MUE) of MC-PDFT with the tPBE functional improves from 0.42 to 0.40 eV with a double set of diffuse functions, whereas the MUEs for PBE and PBE0 drastically increase from 0.74 to 2.49 eV and from 0.45 to 1.47 eV, respectively.
Feller, David; Dixon, David A
2018-03-08
Two recent papers in this journal called into question the suitability of the correlation consistent basis sets for density functional theory (DFT) calculations, because the sets were designed for correlated methods such as configuration interaction, perturbation theory, and coupled cluster theory. These papers focused on the ability of the correlation consistent and other basis sets to reproduce total energies, atomization energies, and dipole moments obtained from "quasi-exact" multiwavelet results. Undesirably large errors were observed for the correlation consistent basis sets. One of the papers argued that basis sets specifically optimized for DFT methods were "essential" for obtaining high accuracy. In this work we re-examined the performance of the correlation consistent basis sets by resolving problems with the previous calculations and by making more appropriate basis set choices for the alkali and alkaline-earth metals and second-row elements. When this is done, the statistical errors with respect to the benchmark values and with respect to DFT optimized basis sets are greatly reduced, especially in light of the relatively large intrinsic error of the underlying DFT method. When judged with respect to high-quality Feller-Peterson-Dixon coupled cluster theory atomization energies, the PBE0 DFT method used in the previous studies exhibits a mean absolute deviation more than a factor of 50 larger than the quintuple zeta basis set truncation error.
Geuten, Koen; Irish, Vivian
2010-08-01
B-class MADS box genes specify petal and stamen identities in several core eudicot species. Members of the Solanaceae possess duplicate copies of these genes, allowing for diversification of function. To examine the changing roles of such duplicate orthologs, we assessed the functions of B-class genes in Nicotiana benthamiana and tomato (Solanum lycopersicum) using virus-induced gene silencing and RNA interference approaches. Loss of function of individual duplicates can have distinct phenotypes, yet complete loss of B-class gene function results in extreme homeotic transformations of petal and stamen identities. We also show that these duplicate gene products have qualitatively different protein-protein interaction capabilities and different regulatory roles. Thus, compensatory changes in B-class MADS box gene duplicate function have occurred in the Solanaceae, in that individual gene roles are distinct, but their combined functions are equivalent. Furthermore, we show that species-specific differences in the stamen regulatory network are associated with differences in the expression of the microRNA miR169. Whereas there is considerable plasticity in individual B-class MADS box transcription factor function, there is overall conservation in the roles of the multimeric MADS box B-class protein complexes, providing robustness in the specification of petal and stamen identities. Such hidden variability in gene function as we observe for individual B-class genes can provide a molecular basis for the evolution of regulatory functions that result in novel morphologies.
An enhanced radial basis function network for short-term electricity price forecasting
International Nuclear Information System (INIS)
Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang
2010-01-01
This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday and weekend. With the OED applied to learning rates in the ERBFN, the forecasting error can be reduced during the training process to improve both accuracy and reliability. This would mean that even the ''spikes'' could be tracked closely. The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance. Simulation results demonstrated the effectiveness of the proposed ERBFN to provide quality information in a price volatile environment. (author)
Machine learning of radial basis function neural network based on Kalman filter: Implementation
Directory of Open Access Journals (Sweden)
Vuković Najdan L.
2014-01-01
Full Text Available In this paper we test three new sequential machine learning algorithms for radial basis function (RBF neural network based on Kalman filter theory. Three new algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter. Having introduced and derived mathematical model of each algorithm in the previous part of the paper, in this part we test and assess their performance using standard test sets from machine learning community. RBF neural network and three developed algorithms are implemented in MATLAB® programming environment. Experimental results obtained on real data sets as well as on real engineering problem show that developed algorithms result in more accurate models of the problem being investigated based on radial basis function neural network.
Burken, John J.
2005-01-01
This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.
International Nuclear Information System (INIS)
Knigavko, V.G.; Pilipenko, M.Yi.
1993-01-01
The work is devoted to theoretical basis of determining physiologically essential values of liver, kidneys, central and cerebral hemodynamics functional state according to the results of dynamic studies, New stochastic models of radiopharmaceuticals (RP) kinetics in the organism systems, new schemes to obtain primary information during the investigation as well as subsequent or simultaneous injection of two testing RP with different characteristics and similar or different labels was used
Misganaw Abebe; Jun-Seok Yoon; Beom-Soo Kang
2017-01-01
Springback in multi-point dieless forming (MDF) is a common problem because of the small deformation and blank holder free boundary condition. Numerical simulations are widely used in sheet metal forming to predict the springback. However, the computational time in using the numerical tools is time costly to find the optimal process parameters value. This study proposes radial basis function (RBF) to replace the numerical simulation model by using statistical analyses that are based on a desi...
Diagnosis of Cervical Cancer Using the Median M-Type Radial Basis Function (MMRBF) Neural Network
Gómez-Mayorga, Margarita E.; Gallegos-Funes, Francisco J.; de-La-Rosa-Vázquez, José M.; Cruz-Santiago, Rene; Ponomaryov, Volodymyr
The automatic analysis of Pap smear microscopic images is one of the most interesting fields in biomedical image processing. In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) neural network in the classification of cervical cancer cells. From simulation results we observe that the MMRBF neural network has better classification capabilities in comparison with the Median RBF algorithm used as comparative.
A Novel Algorithm of Network Trade Customer Classification Based on Fourier Basis Functions
Li Xinwu; Guan Pengcheng
2013-01-01
Learning algorithm of neural network is always an important research contents in neural network theory research and application field, learning algorithm about the feed-forward neural network has no satisfactory solution in particular for its defects in calculation speed. The paper presents a new Fourier basis functions neural network algorithm and applied it to classify network trade customer. First, 21 customer classification indicators are designed, based on characteristics and behaviors a...
Directory of Open Access Journals (Sweden)
Wang Pidong
2016-01-01
Full Text Available Blind source separation is a hot topic in signal processing. Most existing works focus on dealing with linear combined signals, while in practice we always encounter with nonlinear mixed signals. To address the problem of nonlinear source separation, in this paper we propose a novel algorithm using radial basis function neutral network, optimized by multi-universe parallel quantum genetic algorithm. Experiments show the efficiency of the proposed method.
DEFF Research Database (Denmark)
Kim, Oleksiy S.; Meincke, Peter; Breinbjerg, Olav
2007-01-01
The problem of electromagnetic scattering by composite metallic and dielectric objects is solved using the coupled volume-surface integral equation (VSIE). The method of moments (MoM) based on higher-order hierarchical Legendre basis functions and higher-order curvilinear geometrical elements...... with the analytical Mie series solution. Scattering by more complex metal-dielectric objects are also considered to compare the presented technique with other numerical methods....
Machine learning of radial basis function neural network based on Kalman filter: Introduction
Directory of Open Access Journals (Sweden)
Vuković Najdan L.
2014-01-01
Full Text Available This paper analyzes machine learning of radial basis function neural network based on Kalman filtering. Three algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter. We emphasize basic properties of these estimation algorithms, demonstrate how their advantages can be used for optimization of network parameters, derive mathematical models and show how they can be applied to model problems in engineering practice.
A prediction method for the wax deposition rate based on a radial basis function neural network
Directory of Open Access Journals (Sweden)
Ying Xie
2017-06-01
Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.
Chen, Guo-qing; Wei, Bai-lin; Wang, Jun; Wu, Ya-min; Gao, Shu-mei; Kong, Yan; Zhu, Tuo
2010-01-01
Based on the experimental study, it was found that melamine solution excited by UV light can generate a strong fluorescence. The fluorescence spectrum is within a range from 310 to 600 nm, the peak wavelength of the fluorescence is about 420 nm, and the relationship between fluorescence intensity and melamine solution concentration is nonlinear. A method for the determination of melamine solution concentration was presented, which was based on fluorescence spectroscopy and radial basis function neural networks. For each sample, 30 emission wavelength values were selected, the fluorescence intensity corresponding to the selected wavelength was used as the network data, and a radial basis function neural network was trained and constructed. The trained radial basis function neural network was employed to predict the melamine solution concentration in five kinds of samples, and the relative errors of the results were 0.93%, 0.09%, 0.31%, 1.55% and 4.61%, respectively. The results show that this method can determine the content of melamine quickly and accurately. The whole research outcomes will provide a new method for determining the content of melamine and food safety supervision.
Application of natural basis functions to soft x-ray tomography
International Nuclear Information System (INIS)
Ingesson, L.
2000-03-01
Natural basis functions (NBFs), also known as natural pixels in the literature, have been applied in tomographic reconstructions of simulated measurements for the JET soft x-ray system, which has a total of about 200 detectors spread over 6 directions. Various types of NBFs, i.e. normal, generalized and orthonormal NBFs, are reviewed. The number of basis functions is roughly equal to the number of measurements. Therefore, little a priori information is required as regularization and truncated singular-value decomposition can be used for the tomographic inversion. The results of NBFs are compared with reconstructions by the same solution technique using local basis functions (LBFs), and with the reconstructions of a conventional constrained-optimization tomography method with many more LBFs that requires more a priori information. Although the results of the conventional method are superior due to the a priori information, the results of the NBF and other LBF methods are reasonable and show the main features. Therefore, NBFs are a promising way to assess whether features in reconstructions are real or artefacts resulting from the a priori information. Of the NBFs, regular triangular (generalized) NBFs give the most acceptable reconstructions, much better than traditional square pixels, although the reconstructions with pyramid-shaped LBFs are also reasonable and have slightly smaller reconstruction errors. A more-regular (virtual) viewing geometry improves the reconstructions. However, simulations with a viewing geometry with a total of 480 channels spread over 12 directions clearly show that a priori information still improves the reconstructions considerably. (author)
Rational quadratic trigonometric Bézier curve based on new basis with exponential functions
Directory of Open Access Journals (Sweden)
Wu Beibei
2017-06-01
Full Text Available We construct a rational quadratic trigonometric Bézier curve with four shape parameters by introducing two exponential functions into the trigonometric basis functions in this paper. It has the similar properties as the rational quadratic Bézier curve. For given control points, the shape of the curve can be flexibly adjusted by changing the shape parameters and the weight. Some conics can be exactly represented when the control points, the shape parameters and the weight are chosen appropriately. The C0, C1 and C2 continuous conditions for joining two constructed curves are discussed. Some examples are given.
The molecular basis of convergence in hemoglobin function in high-altitude Andean birds
DEFF Research Database (Denmark)
Storz, Jay; Natarajan, Chandrasekhar; Witt, Christopher C.
2016-01-01
was correct that adaptive modifications of Hb function are typically attributable to a small number of substitutions at key positions, then the clear prediction is that the same mutations will be preferentially fixed in different species that have independently evolved Hbs with similar functional properties....... For example, in high-altitude ertebrates that have convergently evolved elevated Hb-O2 affinities, Perutz’s hypothesis predicts that parallel amino acid substitutions should be pervasive. We investigated the predictability of genetic adaptation by examining the molecular basis of convergence in hemoglobin (Hb...
Nonequilibrium Green's functions approach to inhomogeneous systems
Balzer, Karsten
2013-01-01
This book offers a self-contained introduction to non-equilibrium quantum particle dynamics for inhomogeneous systems, including a survey of recent breakthroughs pioneered by the authors and others. The approach is based on real-time Green's functions.
Rates of Minimization of Error Functionals over Boolean Variable-Basis Functions
Czech Academy of Sciences Publication Activity Database
Kainen, P.C.; Kůrková, Věra; Sanguineti, M.
2005-01-01
Roč. 4, č. 4 (2005), s. 355-368 ISSN 1570-1166 R&D Projects: GA ČR GA201/02/0428; GA ČR GA201/05/0557 Grant - others:Area MC 6(EU) Project 22 Institutional research plan: CEZ:AV0Z10300504 Keywords : high-dimensional optimization * minimizing sequences * Boolean decision functions * decision tree Subject RIV: BA - General Mathematics
Basis of symmetric polynomials for many-boson light-front wave functions.
Chabysheva, Sophia S; Hiller, John R
2014-12-01
We provide an algorithm for the construction of orthonormal multivariate polynomials that are symmetric with respect to the interchange of any two coordinates on the unit hypercube and are constrained to the hyperplane where the sum of the coordinates is one. These polynomials form a basis for the expansion of bosonic light-front momentum-space wave functions, as functions of longitudinal momentum, where momentum conservation guarantees that the fractions are on the interval [0,1] and sum to one. This generalizes earlier work on three-boson wave functions to wave functions for arbitrarily many identical bosons. A simple application in two-dimensional ϕ(4) theory illustrates the use of these polynomials.
Boverman, Gregory; Miller, Eric L.; Brooks, Dana H.; Fang, Qianqian; Carp, S. A.; Selb, J. J.; Boas, David A.
2007-02-01
In the course of our experiments imaging the compressed breast in conjunction with digital tomosynthesis, we have noted that significant changes in tissue optical properties, on the order of 5%, occur during our imaging protocol. These changes seem to consistent with changes both in total Hemoglobin concentration as well as in oxygen saturation, as was the case for our standalone breast compression study, which made use of reflectance measurements. Simulation experiments show the importance of taking into account the temporal dynamics in the image reconstruction, and demonstrate the possibility of imaging the spatio-temporal dynamics of oxygen saturation and total Hemoglobin in the breast. In the image reconstruction, we make use of spatio-temporal basis functions, specifically a voxel basis for spatial imaging, and a cubic spline basis in time, and we reconstruct the spatio-temporal images using the entire data set simultaneously, making use of both absolute and relative measurements in the cost function. We have modified the sequence of sources used in our imaging acquisition protocol to improve our temporal resolution, and preliminary results are shown for normal subjects.
International Nuclear Information System (INIS)
Matsuyama, Eri; Tsai, Du-Yih; Lee, Yongbum; Fuse, Masashi; Kojima, Katsuyuki
2010-01-01
Noise reduction in nuclear medicine images can be achieved by increasing the counts or by filtering the images. In this paper, we employed an image filtering technique, a wavelet-based method, for reducing image noise. We selected eight various wavelet basis functions for our study. Wavelet transforms were applied to planar images using the universal soft-thresholding method. We used mutual information (MI) as an image-quality metric to conduct quantitative image analysis and comparison on the processed images obtained from the eight selected, wavelet basis functions. To validate the usefulness of the proposed metric, standard deviation rate and edge slope ratio of the processed images were calculated and compared. In this study, a computer-generated 2-D grid-pattern image and phantom images acquired with a standard inkjet printer, were served as original images. Simulation experiments and phantom experiments demonstrate that MI value can be used as a criterion to select an appropriate wavelet basis for image denoising. (author)
Directory of Open Access Journals (Sweden)
Ekkehard Krüger
2015-05-01
Full Text Available The paper presents the group theory of optimally-localized and symmetry-adapted Wannier functions in a crystal of any given space group G or magnetic group M. Provided that the calculated band structure of the considered material is given and that the symmetry of the Bloch functions at all of the points of symmetry in the Brillouin zone is known, the paper details whether or not the Bloch functions of particular energy bands can be unitarily transformed into optimally-localized Wannier functions symmetry-adapted to the space group G, to the magnetic group M or to a subgroup of G or M. In this context, the paper considers usual, as well as spin-dependent Wannier functions, the latter representing the most general definition of Wannier functions. The presented group theory is a review of the theory published by one of the authors (Ekkehard Krüger in several former papers and is independent of any physical model of magnetism or superconductivity. However, it is suggested to interpret the special symmetry of the optimally-localized Wannier functions in the framework of a nonadiabatic extension of the Heisenberg model, the nonadiabatic Heisenberg model. On the basis of the symmetry of the Wannier functions, this model of strongly-correlated localized electrons makes clear predictions of whether or not the system can possess superconducting or magnetic eigenstates.
Alexandridis, Nikolaos; Bacher, Cédric; Desroy, Nicolas; Jean, Fred
2017-03-01
The accurate reproduction of the spatial and temporal dynamics of marine benthic biodiversity requires the development of mechanistic models, based on the processes that shape macroinvertebrate communities. The modelled entities should, accordingly, be able to adequately represent the many functional roles that are performed by benthic organisms. With this goal in mind, we applied the emergent group hypothesis (EGH), which assumes functional equivalence within and functional divergence between groups of species. The first step of the grouping involved the selection of 14 biological traits that describe the role of benthic macroinvertebrates in 7 important community assembly mechanisms. A matrix of trait values for the 240 species that occurred in the Rance estuary (Brittany, France) in 1995 formed the basis for a hierarchical classification that generated 20 functional groups, each with its own trait values. The functional groups were first evaluated based on their ability to represent observed patterns of biodiversity. The two main assumptions of the EGH were then tested, by assessing the preservation of niche attributes among the groups and the neutrality of functional differences within them. The generally positive results give us confidence in the ability of the grouping to recreate functional diversity in the Rance estuary. A first look at the emergent groups provides insights into the potential role of community assembly mechanisms in shaping biodiversity patterns. Our next steps include the derivation of general rules of interaction and their incorporation, along with the functional groups, into mechanistic models of benthic biodiversity.
Functional integral approach to classical statistical dynamics
International Nuclear Information System (INIS)
Jensen, R.V.
1980-04-01
A functional integral method is developed for the statistical solution of nonlinear stochastic differential equations which arise in classical dynamics. The functional integral approach provides a very natural and elegant derivation of the statistical dynamical equations that have been derived using the operator formalism of Martin, Siggia, and Rose
Functional integral approach to classical statistical dynamics
Energy Technology Data Exchange (ETDEWEB)
Jensen, R.V.
1980-04-01
A functional integral method is developed for the statistical solution of nonlinear stochastic differential equations which arise in classical dynamics. The functional integral approach provides a very natural and elegant derivation of the statistical dynamical equations that have been derived using the operator formalism of Martin, Siggia, and Rose.
Molecular basis of the functional heterogeneity of the muscarinic acetylcholine receptor
International Nuclear Information System (INIS)
Numa, S.; Fukuda, K.; Kubo, T.; Maeda, A.; Akiba, I.; Bujo, H.; Nakai, J.; Mishina, M.; Higashida, H.
1988-01-01
The muscarinic acetylcholine receptor (mAChR) mediates a variety of cellular responses, including inhibition of adenylate cyclase, breakdown of phosphoinositides, and modulation of potassium channels, through the action of guanine-nucleotide-binding regulatory proteins (G proteins). The question then arises as to whether multiple mAChR species exist that are responsible for the various biochemical and physiological effects. In fact, pharmacologically distinguishable forms of the mAChR occur in different tissues and have been provisionally classified into M 1 (I), M 2 cardiac (II), and M 2 glandular (III) subtypes on the basis of their difference in apparent affinity for antagonists. Here, the authors have made attempts to understand the molecular basis of the functional heterogeneity of the mAChR, using recombinant DNA technology
Meng, Qinggang; Lee, M. H.
2007-03-01
Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.
An inverse approach for elucidating dendritic function
Directory of Open Access Journals (Sweden)
Benjamin Torben-Nielsen
2010-09-01
Full Text Available We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a-priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a `hypothesis generator' in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a `function confirmation' by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions.
National Research Council Canada - National Science Library
Kobayashi, Nobuhiko; Ozaki, Taisuke; Hirose, Kenji
2006-01-01
.... The electronic states are calculated using a numerical pseudo atomic orbital basis set in the frame work of the density functional theory, and the conductance is calculated using the Green's function method...
Fan, Wenqiao; Jiang, Yusong; Zhang, Meixia; Yang, Donglin; Chen, Zhongzhu; Sun, Hanchang; Lan, Xuelian; Yan, Fan; Xu, Jingming; Yuan, Wanan
2017-01-01
Skin as the first barrier against external invasions plays an essential role for the survival of amphibians on land. Understanding the genetic basis of skin function is significant in revealing the mechanisms underlying immunity of amphibians. In this study, we de novo sequenced and comparatively analyzed skin transcriptomes from three different amphibian species, Andrias davidianus, Bufo gargarizans, and Rana nigromaculata Hallowell. Functional classification of unigenes in each amphibian showed high accordance, with the most represented GO terms and KEGG pathways related to basic biological processes, such as binding and metabolism and immune system. As for the unigenes, GO and KEGG distributions of conserved orthologs in each species were similar, with the predominantly enriched pathways including RNA polymerase, nucleotide metabolism, and defense. The positively selected orthologs in each amphibian were also similar, which were primarily involved in stimulus response, cell metabolic, membrane, and catalytic activity. Furthermore, a total of 50 antimicrobial peptides from 26 different categories were identified in the three amphibians, and one of these showed high efficiency in inhibiting the growth of different bacteria. Our understanding of innate immune function of amphibian skin has increased basis on the immune-related unigenes, pathways, and antimicrobial peptides in amphibians.
Zhang, Meixia; Yang, Donglin; Chen, Zhongzhu; Lan, Xuelian; Yan, Fan; Xu, Jingming; Yuan, Wanan
2017-01-01
Skin as the first barrier against external invasions plays an essential role for the survival of amphibians on land. Understanding the genetic basis of skin function is significant in revealing the mechanisms underlying immunity of amphibians. In this study, we de novo sequenced and comparatively analyzed skin transcriptomes from three different amphibian species, Andrias davidianus, Bufo gargarizans, and Rana nigromaculata Hallowell. Functional classification of unigenes in each amphibian showed high accordance, with the most represented GO terms and KEGG pathways related to basic biological processes, such as binding and metabolism and immune system. As for the unigenes, GO and KEGG distributions of conserved orthologs in each species were similar, with the predominantly enriched pathways including RNA polymerase, nucleotide metabolism, and defense. The positively selected orthologs in each amphibian were also similar, which were primarily involved in stimulus response, cell metabolic, membrane, and catalytic activity. Furthermore, a total of 50 antimicrobial peptides from 26 different categories were identified in the three amphibians, and one of these showed high efficiency in inhibiting the growth of different bacteria. Our understanding of innate immune function of amphibian skin has increased basis on the immune-related unigenes, pathways, and antimicrobial peptides in amphibians. PMID:29267366
Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study.
Wang, Ping; Zhu, Xing-Ting; Qi, Zhigang; Huang, Silin; Li, Hui-Jie
2017-01-01
Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI) study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs) and twenty non-video game players (NVGPs) of 60 years of age or older participated in the present study, and there are no significant differences in age ( t = 0.62, p = 0.536), gender ratio ( t = 1.29, p = 0.206) and years of education ( t = 1.92, p = 0.062) between VGPs and NVGPs. The results show that older VGPs present significantly better behavioral performance than NVGPs. Older VGPs activate greater than NVGPs in brain regions, mainly in frontal-parietal areas, including the right dorsolateral prefrontal cortex, the left supramarginal gyrus, the right angular gyrus, the right precuneus and the left paracentral lobule. The present study reveals that video game experiences may have positive influences on older adults in behavioral performance and the underlying brain activation. These results imply the potential role that video games can play as an effective tool to improve cognitive ability in older adults.
Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Zhihong Liao
2017-11-01
Full Text Available A radial basis function network (RBFN method is proposed to reconstruct daily Sea surface temperatures (SSTs with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the Reynolds optimum interpolation (OI v2 daily 0.25° SST (OISST products according to the distribution of AVHRR L2p SST and in-situ SST data. Furthermore, an improved nearest neighbor cluster (INNC algorithm is designed to search for the optimal hidden knots for RBFNs from both the SST samples and the background fields. Then, the reconstructed SSTs from the RBFN method are compared with the results from the OI method. The statistical results show that the RBFN method has a better performance of reconstructing SST than the OI method in the study, and that the average RMSE is 0.48 °C for the RBFN method, which is quite smaller than the value of 0.69 °C for the OI method. Additionally, the RBFN methods with different basis functions and clustering algorithms are tested, and we discover that the INNC algorithm with multi-quadric function is quite suitable for the RBFN method to reconstruct SSTs when the SST samples are sparsely distributed.
Computing single step operators of logic programming in radial basis function neural networks
Energy Technology Data Exchange (ETDEWEB)
Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)
2014-07-10
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.
Computing single step operators of logic programming in radial basis function neural networks
Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong
2014-07-01
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.
Computing single step operators of logic programming in radial basis function neural networks
International Nuclear Information System (INIS)
Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong
2014-01-01
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T p :I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks
Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study
Directory of Open Access Journals (Sweden)
Ping Wang
2017-11-01
Full Text Available Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs and twenty non-video game players (NVGPs of 60 years of age or older participated in the present study, and there are no significant differences in age (t = 0.62, p = 0.536, gender ratio (t = 1.29, p = 0.206 and years of education (t = 1.92, p = 0.062 between VGPs and NVGPs. The results show that older VGPs present significantly better behavioral performance than NVGPs. Older VGPs activate greater than NVGPs in brain regions, mainly in frontal-parietal areas, including the right dorsolateral prefrontal cortex, the left supramarginal gyrus, the right angular gyrus, the right precuneus and the left paracentral lobule. The present study reveals that video game experiences may have positive influences on older adults in behavioral performance and the underlying brain activation. These results imply the potential role that video games can play as an effective tool to improve cognitive ability in older adults.
Wang, Pengbo
2017-11-01
In this paper, the radial basis function (RBF) neural network is used for the mechanical fault diagnosis of a gearbox. We introduce the basic principles of the RBF neural network which is used for pattern classification and features a fast learning pace and strong nonlinear mapping capability; thus, it can be employed for fault diagnosis. The gearbox is a widely-used piece of equipment in engineering, and diagnosing mechanical faults is of great significance for engineers. A numerical example is presented to demonstrate the capability of the proposed method. The results indicate that the mechanical faults of a gearbox can be correctly diagnosed with a trained RBF neural network.
Radial basis function neural networks with sequential learning MRAN and its applications
Sundararajan, N; Wei Lu Ying
1999-01-01
This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of t
Ni, Shengqiao; Lv, Jiancheng; Cheng, Zhehao; Li, Mao
2015-01-01
This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, and map the new data online. Furthermore, this method can deal with large datasets for the benefit of improved Topology Representing Network. Experiments illustrate the effectiveness of the proposed method. PMID:26161960
Directory of Open Access Journals (Sweden)
Shengqiao Ni
Full Text Available This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, and map the new data online. Furthermore, this method can deal with large datasets for the benefit of improved Topology Representing Network. Experiments illustrate the effectiveness of the proposed method.
Ni, Shengqiao; Lv, Jiancheng; Cheng, Zhehao; Li, Mao
2015-01-01
This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, and map the new data online. Furthermore, this method can deal with large datasets for the benefit of improved Topology Representing Network. Experiments illustrate the effectiveness of the proposed method.
Correlated basis functions theory of light nuclei. Pt. 2. Spectra of light nuclei
Energy Technology Data Exchange (ETDEWEB)
Guardiola, R.; Bosca, M.C.
1988-11-14
This work is a continuation of a previous one devoted to the study of ground-state energies of p-shell nuclei using the correlated basis functions theory. Here, the low-lying excited levels are computed and compared with experiment. This study has no free parameters, and everything is directly obtained from a realistic Reid V8 nucleon-nucleon interaction. As expected, we do not obtain quantitative agreement with the experimental levels. However, many of the qualitative characteristics of the spectrum emerge naturally.
Directory of Open Access Journals (Sweden)
Zhineng Hu
2014-01-01
Full Text Available Regional logistics prediction is the key step in regional logistics planning and logistics resources rationalization. Since regional economy is the inherent and determinative factor of regional logistics demand, it is feasible to forecast regional logistics demand by investigating economic indicators which can accelerate the harmonious development of regional logistics industry and regional economy. In this paper, the PSO-RBFNN model, a radial basis function neural network (RBFNN combined with particle swarm optimization (PSO algorithm, is studied. The PSO-RBFNN model is trained by indicators data in a region to predict the regional logistics demand. And the corresponding results indicate the model’s applicability and potential advantages.
A systemic approach for modeling soil functions
Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute
2018-03-01
The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.
International Nuclear Information System (INIS)
Davidson, G.; Palmer, T.S.
2005-01-01
In 1975, Wachspress developed basis functions that can be constructed upon very general zone shapes, including convex polygons and polyhedra, as well as certain zone shapes with curved sides and faces. Additionally, Adams has recently shown that weight functions with certain properties will produce solutions with full-resolution. Wachspress rational functions possess those necessary properties. Here we present methods to construct and integrate Wachspress rational functions on quadrilaterals. We also present an asymptotic analysis of a discontinuous finite element discretization on quadrilaterals, and we present 3 numerical results that confirm the predictions of our analysis. In the first test problem, we showed that Wachspress rational functions could give robust solutions for a strongly heterogeneous problem with both orthogonal and skewed meshes. This strongly heterogenous problem contained thick, diffusive regions, and the discretization provided full-resolution solutions. In the second test problem, we confirmed our asymptotic analysis by demonstrating that the transport solution will converge to the diffusion solution as the problem is made increasingly thick and diffusive. In the third test problem, we demonstrated that bilinear discontinuous based transport and Wachspress rational function based transport converge in the one-mesh limit
Interprofessional approach for teaching functional knee joint anatomy.
Meyer, Jakob J; Obmann, Markus M; Gießler, Marianne; Schuldis, Dominik; Brückner, Ann-Kathrin; Strohm, Peter C; Sandeck, Florian; Spittau, Björn
2017-03-01
Profound knowledge in functional and clinical anatomy is a prerequisite for efficient diagnosis in medical practice. However, anatomy teaching does not always consider functional and clinical aspects. Here we introduce a new interprofessional approach to effectively teach the anatomy of the knee joint. The presented teaching approach involves anatomists, orthopaedists and physical therapists to teach anatomy of the knee joint in small groups under functional and clinical aspects. The knee joint courses were implemented during early stages of the medical curriculum and medical students were grouped with students of physical therapy to sensitize students to the importance of interprofessional work. Evaluation results clearly demonstrate that medical students and physical therapy students appreciated this teaching approach. First evaluations of following curricular anatomy exams suggest a benefit of course participants in knee-related multiple choice questions. Together, the interprofessional approach presented here proves to be a suitable approach to teach functional and clinical anatomy of the knee joint and further trains interprofessional work between prospective physicians and physical therapists as a basis for successful healthcare management. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.
Machine learning (ML)-guided OPC using basis functions of polar Fourier transform
Choi, Suhyeong; Shim, Seongbo; Shin, Youngsoo
2016-03-01
With shrinking feature size, runtime has become a limitation of model-based OPC (MB-OPC). A few machine learning-guided OPC (ML-OPC) have been studied as candidates for next-generation OPC, but they all employ too many parameters (e.g. local densities), which set their own limitations. We propose to use basis functions of polar Fourier transform (PFT) as parameters of ML-OPC. Since PFT functions are orthogonal each other and well reflect light phenomena, the number of parameters can significantly be reduced without loss of OPC accuracy. Experiments demonstrate that our new ML-OPC achieves 80% reduction in OPC time and 35% reduction in the error of predicted mask bias when compared to conventional ML-OPC.
Multiquadric and Compactly Supported Radial Basis Functions for Shallow Water Equations
Alhuri, Y.; Taik, A.; Naji, A.
2009-04-01
Meshfree methods have gained much attention in recent years, not only in the mathematics but also in the engineering community. The computer and numerical methods are powerful tools of analysing wide rang of engineering and industrial application. For long time researchers recognised problems when using a mesh-based method. Developing the meshless methods overcome these problems. In the present paper, we present the application of both the global and the compactly supported radial basis functions (CSRBFs) for solving a system of shallow water hydrodynamic model for marine environments. As the technique is based on the collocation formulation and does not require the generation of a grid and any integral evaluation, the technique is considered as purely meshless method. The Computational efficiency and accuracy of both used functions are verified by comparing the analytic and observed solution.
Correlated basis functions theory of light nuclei. Pt. 1. General description and ground states
Energy Technology Data Exchange (ETDEWEB)
Bosca, M.C.; Guardiola, R.
1988-01-18
The correlated basis functions theory is applied to the description of light (p-shell) nuclei. The interaction used is the Reid potential, in the V8 (central, spin, tensor and spin-orbit) and V6 (no spin-orbit term) forms. Our work includes state-dependent correlation functions, and their radial components are determined by solving the corresponding Euler-Lagrange equations with a healing condition at distance d and with a null derivative; in addition, we impose the sequential condition or the Pauli condition so as to insure convergence. We present results corresponding to the ground state of all nuclei in the p-shell. Our results present a good qualitative behaviour, but are in clear disagreement with experimental values.
Li, Yang; Wang, Xu-Dong; Luo, Mei-Lin; Li, Ke; Yang, Xiao-Feng; Guo, Qi
2018-03-01
The automatic detection of epileptic seizures from electroencephalography (EEG) signals is crucial for the localization and classification of epileptic seizure activity. However, seizure processes are typically dynamic and nonstationary, and thus, distinguishing rhythmic discharges from nonstationary processes is one of the challenging problems. In this paper, an adaptive and localized time-frequency representation in EEG signals is proposed by means of multiscale radial basis functions (MRBF) and a modified particle swarm optimization (MPSO) to improve both time and frequency resolution simultaneously, which is a novel MRBF-MPSO framework of the time-frequency feature extraction for epileptic EEG signals. The dimensionality of extracted features can be greatly reduced by the principle component analysis algorithm before the most discriminative features selected are fed into a support vector machine (SVM) classifier with the radial basis function (RBF) in order to separate epileptic seizure from seizure-free EEG signals. The classification performance of the proposed method has been evaluated by using several state-of-art feature extraction algorithms and other five different classifiers like linear discriminant analysis, and logistic regression. The experimental results indicate that the proposed MRBF-MPSO-SVM classification method outperforms competing techniques in terms of classification accuracy, and shows the effectiveness of the proposed method for classification of seizure epochs and seizure-free epochs.
Sturmian functions in a L2 basis: Critical nuclear charge for N-electron atoms
International Nuclear Information System (INIS)
Frapiccini, A.L.; Gasaneo, G.; Colavecchia, F.D.; Mitnik, D.
2007-01-01
Two particle Sturmian functions [M. Rotenberg, Ann. Phys., NY 19 (1962) 262; S.V. Khristenko, Theor. Math. Fiz. 22 (1975) 31 (Engl. Transl. Theor. Math. Phys. 22, 21)] for a short range potentials are obtained by expanding the solution of the Schroedinger equation in a finite L 2 Laguerre-type basis. These functions are chosen to satisfy certain boundary conditions, such as regularity at the origin and the correct asymptotic behavior according to the energy domain: exponential decay for negative energy and outgoing (incoming or standing wave) for positive energy. The set of eigenvalues obtained is discrete for both positive and negative energies. This Sturmian basis is used to solve the Schroedinger equation for a one-particle model potential [A.V. Sergeev, S. Kais, J. Quant. Chem. 75 (1999) 533] to describe the motion of a loosely bound electron in a multielectron atom. Values of the two parameters of the potential are computed to represent the Helium isoelectronic series and the critical nuclear charge Z c is found, in good agreement with previous calculations
Design Methodology of a New Wavelet Basis Function for Fetal Phonocardiographic Signals
Chourasia, Vijay S.; Tiwari, Anil Kumar
2013-01-01
Fetal phonocardiography (fPCG) based antenatal care system is economical and has a potential to use for long-term monitoring due to noninvasive nature of the system. The main limitation of this technique is that noise gets superimposed on the useful signal during its acquisition and transmission. Conventional filtering may result into loss of valuable diagnostic information from these signals. This calls for a robust, versatile, and adaptable denoising method applicable in different operative circumstances. In this work, a novel algorithm based on wavelet transform has been developed for denoising of fPCG signals. Successful implementation of wavelet theory in denoising is heavily dependent on selection of suitable wavelet basis function. This work introduces a new mother wavelet basis function for denoising of fPCG signals. The performance of newly developed wavelet is found to be better when compared with the existing wavelets. For this purpose, a two-channel filter bank, based on characteristics of fPCG signal, is designed. The resultant denoised fPCG signals retain the important diagnostic information contained in the original fPCG signal. PMID:23766693
Directory of Open Access Journals (Sweden)
Dongliang Guo
2014-01-01
Full Text Available Indoor localization technique has received much attention in recent years. Many techniques have been developed to solve the problem. Among the recent proposed methods, radio frequency identification (RFID indoor localization technology has the advantages of low-cost, noncontact, non-line-of-sight, and high precision. This paper proposed two radial basis function (RBF neural network based indoor localization methods. The RBF neural networks are trained to learn the mapping relationship between received signal strength indication values and position of objects. Traditional method used the received signal strength directly as the input of neural network; we added another input channel by taking the difference of the received signal strength, thus improving the reliability and precision of positioning. Fuzzy clustering is used to determine the center of radial basis function. In order to reduce the impact of signal fading due to non-line-of-sight and multipath transmission in indoor environment, we improved the Gaussian filter to process received signal strength values. The experimental results show that the proposed method outperforms the existing methods as well as improves the reliability and precision of the RFID indoor positioning system.
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Kevin Dalmasse
2016-07-01
Full Text Available The Coronal Multichannel Polarimeter (CoMP routinely performs coronal polarimetric measurements using the Fe XIII 10747 $AA$ and 10798 $AA$ lines, which are sensitive to the coronal magnetic field. However, inverting such polarimetric measurements into magnetic field data is a difficult task because the corona is optically thin at these wavelengths and the observed signal is therefore the integrated emission of all the plasma along the line of sight. To overcome this difficulty, we take on a new approach that combines a parameterized 3D magnetic field model with forward modeling of the polarization signal. For that purpose, we develop a new, fast and efficient, optimization method for model-data fitting: the Radial-basis-functions Optimization Approximation Method (ROAM. Model-data fitting is achieved by optimizing a user-specified log-likelihood function that quantifies the differences between the observed polarization signal and its synthetic/predicted analogue. Speed and efficiency are obtained by combining sparse evaluation of the magnetic model with radial-basis-function (RBF decomposition of the log-likelihood function. The RBF decomposition provides an analytical expression for the log-likelihood function that is used to inexpensively estimate the set of parameter values optimizing it. We test and validate ROAM on a synthetic test bed of a coronal magnetic flux rope and show that it performs well with a significantly sparse sample of the parameter space. We conclude that our optimization method is well-suited for fast and efficient model-data fitting and can be exploited for converting coronal polarimetric measurements, such as the ones provided by CoMP, into coronal magnetic field data.
Irving, J.; Koepke, C.; Elsheikh, A. H.
2017-12-01
Bayesian solutions to geophysical and hydrological inverse problems are dependent upon a forward process model linking subsurface parameters to measured data, which is typically assumed to be known perfectly in the inversion procedure. However, in order to make the stochastic solution of the inverse problem computationally tractable using, for example, Markov-chain-Monte-Carlo (MCMC) methods, fast approximations of the forward model are commonly employed. This introduces model error into the problem, which has the potential to significantly bias posterior statistics and hamper data integration efforts if not properly accounted for. Here, we present a new methodology for addressing the issue of model error in Bayesian solutions to hydrogeophysical inverse problems that is geared towards the common case where these errors cannot be effectively characterized globally through some parametric statistical distribution or locally based on interpolation between a small number of computed realizations. Rather than focusing on the construction of a global or local error model, we instead work towards identification of the model-error component of the residual through a projection-based approach. In this regard, pairs of approximate and detailed model runs are stored in a dictionary that grows at a specified rate during the MCMC inversion procedure. At each iteration, a local model-error basis is constructed for the current test set of model parameters using the K-nearest neighbour entries in the dictionary, which is then used to separate the model error from the other error sources before computing the likelihood of the proposed set of model parameters. We demonstrate the performance of our technique on the inversion of synthetic crosshole ground-penetrating radar traveltime data for three different subsurface parameterizations of varying complexity. The synthetic data are generated using the eikonal equation, whereas a straight-ray forward model is assumed in the inversion
Green's function approach to neutron flux discontinuities
International Nuclear Information System (INIS)
Saad, E.A.; El-Wakil, S.A.
1980-01-01
The present work is devoted to the presentation of analytical method for the calculation of elastically and inelastically slowed down neutrons in an infinite non-absorbing medium. On the basis of the central limit theory (CLT) and the integral transform technique the slowing down equation including inelastic scattering, in terms of the Green function of elastic scattering, is solved. The Green function is decomposed according to the number of collisions. Placzec discontinuity associated with elastic scattering in addition to two discontinuities due to inelastic scattering are investigated. Numerical calculations for Fe 56 show that the elastic discontinuity produces about 41.8% change in the collision density whilst the ratio of the inelastic collision density discontinuity at qsub(o)sup(+) to the Placzec discontinuity at usub(o) + 1n 1/oc gives 55.7 percent change. (author)
A basis of common approach to the development of universal steganalysis methods for digital images
Directory of Open Access Journals (Sweden)
Alla А. Kobozeva
2014-12-01
Full Text Available In this paper a new common approach to the organization of steganalysis in digital images is developed. New features of formal parameters defining the image are identified, theoretically grounded and practically tested. For the first time characteristics of mutual disposition of the left and right singular vectors corresponding to the largest singular value of the matrix (block of matrix of an image and the vector composed of the singular values obtained as a result of normal singular decomposition of the matrix (block matrix are obtained. It is shown that for the majority of the blocks of the original image (regardless of the storage format — lossy, lossless the angle between the left (right singular vector and the vector composed of singular numbers is determined by the angle between the n-optimal vector and the standard space basis of the corresponding dimension. It is shown that the discovered feature is violated for the mentioned formal parameters in the disturbed image. This is an indicator of integrity violation, particularly steganotransformation, and it can be used to develop new universal steganalysis methods and algorithms. Their efficiency does not depend on the specifics of steganoalgorithm used for insertion of additional information.
Directory of Open Access Journals (Sweden)
Ángel Gutiérrez
2015-04-01
Full Text Available The data available in the average clinical study of a disease is very often small. This is one of the main obstacles in the application of neural networks to the classification of biological signals used for diagnosing diseases. A rule of thumb states that the number of parameters (weights that can be used for training a neural network should be around 15% of the available data, to avoid overlearning. This condition puts a limit on the dimension of the input space. Different authors have used different approaches to solve this problem, like eliminating redundancy in the data, preprocessing the data to find centers for the radial basis functions, or extracting a small number of features that were used as inputs. It is clear that the classification would be better the more features we could feed into the network. The approach utilized in this paper is incrementing the number of training elements with randomly expanding training sets. This way the number of original signals does not constraint the dimension of the input set in the radial basis network. Then we train the network using the method that minimizes the error function using the gradient descent algorithm and the method that uses the particle swarm optimization technique. A comparison between the two methods showed that for the same number of iterations on both methods, the particle swarm optimization was faster, it was learning to recognize only the sick people. On the other hand, the gradient method was not as good in general better at identifying those people.
An Incremental Radial Basis Function Network Based on Information Granules and Its Application
Directory of Open Access Journals (Sweden)
Myung-Won Lee
2016-01-01
Full Text Available This paper is concerned with the design of an Incremental Radial Basis Function Network (IRBFN by combining Linear Regression (LR and local RBFN for the prediction of heating load and cooling load in residential buildings. Here the proposed IRBFN is designed by building a collection of information granules through Context-based Fuzzy C-Means (CFCM clustering algorithm that is guided by the distribution of error of the linear part of the LR model. After adopting a construct of a LR as global model, refine it through local RBFN that captures remaining and more localized nonlinearities of the system to be considered. The experiments are performed on the estimation of energy performance of 768 diverse residential buildings. The experimental results revealed that the proposed IRBFN showed good performance in comparison to LR, the standard RBFN, RBFN with information granules, and Linguistic Model (LM.
Directory of Open Access Journals (Sweden)
Huaiqing Zhang
2014-01-01
Full Text Available The spectral leakage has a harmful effect on the accuracy of harmonic analysis for asynchronous sampling. This paper proposed a time quasi-synchronous sampling algorithm which is based on radial basis function (RBF interpolation. Firstly, a fundamental period is evaluated by a zero-crossing technique with fourth-order Newton’s interpolation, and then, the sampling sequence is reproduced by the RBF interpolation. Finally, the harmonic parameters can be calculated by FFT on the synchronization of sampling data. Simulation results showed that the proposed algorithm has high accuracy in measuring distorted and noisy signals. Compared to the local approximation schemes as linear, quadric, and fourth-order Newton interpolations, the RBF is a global approximation method which can acquire more accurate results while the time-consuming is about the same as Newton’s.
Selecting radial basis function network centers with recursive orthogonal least squares training.
Gomm, J B; Yu, D L
2000-01-01
Recursive orthogonal least squares (ROLS) is a numerically robust method for solving for the output layer weights of a radial basis function (RBF) network, and requires less computer memory than the batch alternative. In this paper, the use of ROLS is extended to selecting the centers of an RBF network. It is shown that the information available in an ROLS algorithm after network training can be used to sequentially select centers to minimize the network output error. This provides efficient methods for network reduction to achieve smaller architectures with acceptable accuracy and without retraining. Two selection methods are developed, forward and backward. The methods are illustrated in applications of RBF networks to modeling a nonlinear time series and a real multiinput-multioutput chemical process. The final network models obtained achieve acceptable accuracy with significant reductions in the number of required centers.
Radial basis functions in mathematical modelling of flow boiling in minichannels
Directory of Open Access Journals (Sweden)
Hożejowska Sylwia
2017-01-01
Full Text Available The paper addresses heat transfer processes in flow boiling in a vertical minichannel of 1.7 mm depth with a smooth heated surface contacting fluid. The heated element for FC-72 flowing in a minichannel was a 0.45 mm thick plate made of Haynes-230 alloy. An infrared camera positioned opposite the central, axially symmetric part of the channel measured the plate temperature. K-type thermocouples and pressure converters were installed at the inlet and outlet of the minichannel. In the study radial basis functions were used to solve a problem concerning heat transfer in a heated plate supplied with the controlled direct current. According to the model assumptions, the problem is treated as twodimensional and governed by the Poisson equation. The aim of the study lies in determining the temperature field and the heat transfer coefficient. The results were verified by comparing them with those obtained by the Trefftz method.
International Nuclear Information System (INIS)
Yang Xinglin; Wang Huacen; Chen Nan; Dai Wenhua; Li Jin
2006-01-01
High current linear induction accelerator (LIA) is a complicated experimental physics device. It is difficult to evaluate and predict its performance. this paper presents a method which combines wavelet packet transform and radial basis function (RBF) neural network to build fault diagnosis and performance evaluation in order to improve reliability of high current LIA. The signal characteristics vectors which are extracted based on energy parameters of wavelet packet transform can well present the temporal and steady features of pulsed power signal, and reduce data dimensions effectively. The fault diagnosis system for accelerating cell and the trend classification system for the beam current based on RBF networks can perform fault diagnosis and evaluation, and provide predictive information for precise maintenance of high current LIA. (authors)
THE ALGORITHM OF MESHFREE METHOD OF RADIAL BASIS FUNCTIONS IN TASKS OF UNDERGROUND HYDROMECHANICS
Directory of Open Access Journals (Sweden)
N. V. Medvid
2016-01-01
Full Text Available A Mathematical model of filtering consolidation in the body of soil dam with conduit andwashout zone in two-dimensional case is considered. The impact of such technogenic factors as temperature, salt concentration, subsidence of upper boundary and interior points of the dam with time is taken into account. The software to automate the calculation of numerical solution of the boundary problem by radial basis functions has been created, which enables to conduct numerical experiments by varying the input parameters and shape. The influence of the presence of conduit and washout zone on the pressure, temperature and concentration of salts in the dam body at different time intervals isinvestigated. A number of numerical experiments is conducted and the analysis of dam accidents is performed.
Upset Prediction in Friction Welding Using Radial Basis Function Neural Network
Directory of Open Access Journals (Sweden)
Wei Liu
2013-01-01
Full Text Available This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW, a radial basis function (RBF neural network was developed initially to predict the final upset for a number of welding parameters. The predicted joint upset by the RBF neural network was compared to validated finite element simulations, producing an error of less than 8.16% which is reasonable. Furthermore, the effects of initial rotational speed and axial pressure on the upset were investigated in relation to energy conversion with the RBF neural network. The developed RBF neural network was also applied to linear friction welding (LFW and continuous drive friction welding (CDFW. The correlation coefficients of RBF prediction for LFW and CDFW were 0.963 and 0.998, respectively, which further suggest that an RBF neural network is an effective method for upset prediction of friction welded joints.
Directory of Open Access Journals (Sweden)
Ruslan Skrynkovskyy
2017-12-01
Full Text Available The purpose of the article is to improve the model of the enterprise (institution, organization management process on the basis of general management functions. The graphic model of the process of management according to the process-structured management is presented. It has been established that in today's business environment, the model of the management process should include such general management functions as: 1 controlling the achievement of results; 2 planning based on the main goal; 3 coordination and corrective actions (in the system of organization of work and production; 4 action as a form of act (conscious, volitional, directed; 5 accounting system (accounting, statistical, operational-technical and managerial; 6 diagnosis (economic, legal with such subfunctions as: identification of the state and capabilities; analysis (economic, legal, systemic with argumentation; assessment of the state, trends and prospects of development. The prospect of further research in this direction is: 1 the formation of a system of interrelation of functions and management methods, taking into account the presented research results; 2 development of the model of effective and efficient communication business process of the enterprise.
Solution of the quantum fluid dynamical equations with radial basis function interpolation
International Nuclear Information System (INIS)
Hu, Xu-Guang; Ho, Tak-San; Rabitz, Herschel; Askar, Attila
2000-01-01
The paper proposes a numerical technique within the Lagrangian description for propagating the quantum fluid dynamical (QFD) equations in terms of the Madelung field variables R and S, which are connected to the wave function via the transformation ψ=exp{(R+iS)/(ℎ/2π)}. The technique rests on the QFD equations depending only on the form, not the magnitude, of the probability density ρ=|ψ| 2 and on the structure of R=(ℎ/2π)/2 ln ρ generally being simpler and smoother than ρ. The spatially smooth functions R and S are especially suitable for multivariate radial basis function interpolation to enable the implementation of a robust numerical scheme. Examples of two-dimensional model systems show that the method rivals, in both efficiency and accuracy, the split-operator and Chebychev expansion methods. The results on a three-dimensional model system indicates that the present method is superior to the existing ones, especially, for its low storage requirement and its uniform accuracy. The advantage of the new algorithm is expected to increase for higher dimensional systems to provide a practical computational tool. (c) 2000 The American Physical Society
Solution of the quantum fluid dynamical equations with radial basis function interpolation
Hu, Xu-Guang; Ho, Tak-San; Rabitz, Herschel; Askar, Attila
2000-05-01
The paper proposes a numerical technique within the Lagrangian description for propagating the quantum fluid dynamical (QFD) equations in terms of the Madelung field variables R and S, which are connected to the wave function via the transformation ψ=exp\\{(R+iS)/ħ\\}. The technique rests on the QFD equations depending only on the form, not the magnitude, of the probability density ρ=\\|ψ\\|2 and on the structure of R=ħ/2 ln ρ generally being simpler and smoother than ρ. The spatially smooth functions R and S are especially suitable for multivariate radial basis function interpolation to enable the implementation of a robust numerical scheme. Examples of two-dimensional model systems show that the method rivals, in both efficiency and accuracy, the split-operator and Chebychev expansion methods. The results on a three-dimensional model system indicates that the present method is superior to the existing ones, especially, for its low storage requirement and its uniform accuracy. The advantage of the new algorithm is expected to increase for higher dimensional systems to provide a practical computational tool.
Polarization functions for the modified m6-31G basis sets for atoms Ga through Kr.
Mitin, Alexander V
2013-09-05
The 2df polarization functions for the modified m6-31G basis sets of the third-row atoms Ga through Kr (Int J Quantum Chem, 2007, 107, 3028; Int J. Quantum Chem, 2009, 109, 1158) are proposed. The performances of the m6-31G, m6-31G(d,p), and m6-31G(2df,p) basis sets were examined in molecular calculations carried out by the density functional theory (DFT) method with B3LYP hybrid functional, Møller-Plesset perturbation theory of the second order (MP2), quadratic configuration interaction method with single and double substitutions and were compared with those for the known 6-31G basis sets as well as with the other similar 641 and 6-311G basis sets with and without polarization functions. Obtained results have shown that the performances of the m6-31G, m6-31G(d,p), and m6-31G(2df,p) basis sets are better in comparison with the performances of the known 6-31G, 6-31G(d,p) and 6-31G(2df,p) basis sets. These improvements are mainly reached due to better approximations of different electrons belonging to the different atomic shells in the modified basis sets. Applicability of the modified basis sets in thermochemical calculations is also discussed. © 2013 Wiley Periodicals, Inc.
Concepts of soil mapping as a basis for the assessment of soil functions
Baumgarten, Andreas
2014-05-01
Soil mapping systems in Europe have been designed mainly as a tool for the description of soil characteristics from a morphogenetic viewpoint. Contrasting to the American or FAO system, the soil development has been in the main focus of European systems. Nevertheless , recent developments in soil science stress the importance of the functions of soils with respect to the ecosystems. As soil mapping systems usually offer a sound and extensive database, the deduction of soil functions from "classic" mapping parameters can be used for local and regional assessments. According to the used pedo-transfer functions and mapping systems, tailored approaches can be chosen for different applications. In Austria, a system mainly for spatial planning purposes has been developed that will be presented and illustrated by means of best practice examples.
Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S
2017-06-01
Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.
Molecular basis sets - a general similarity-based approach for representing chemical spaces.
Raghavendra, Akshay S; Maggiora, Gerald M
2007-01-01
A new method, based on generalized Fourier analysis, is described that utilizes the concept of "molecular basis sets" to represent chemical space within an abstract vector space. The basis vectors in this space are abstract molecular vectors. Inner products among the basis vectors are determined using an ansatz that associates molecular similarities between pairs of molecules with their corresponding inner products. Moreover, the fact that similarities between pairs of molecules are, in essentially all cases, nonzero implies that the abstract molecular basis vectors are nonorthogonal, but since the similarity of a molecule with itself is unity, the molecular vectors are normalized to unity. A symmetric orthogonalization procedure, which optimally preserves the character of the original set of molecular basis vectors, is used to construct appropriate orthonormal basis sets. Molecules can then be represented, in general, by sets of orthonormal "molecule-like" basis vectors within a proper Euclidean vector space. However, the dimension of the space can become quite large. Thus, the work presented here assesses the effect of basis set size on a number of properties including the average squared error and average norm of molecular vectors represented in the space-the results clearly show the expected reduction in average squared error and increase in average norm as the basis set size is increased. Several distance-based statistics are also considered. These include the distribution of distances and their differences with respect to basis sets of differing size and several comparative distance measures such as Spearman rank correlation and Kruscal stress. All of the measures show that, even though the dimension can be high, the chemical spaces they represent, nonetheless, behave in a well-controlled and reasonable manner. Other abstract vector spaces analogous to that described here can also be constructed providing that the appropriate inner products can be directly
DSAEK: practical approach to choose the microkeratome head on the basis of donor cornea pachymetry.
Wisse, Robert P L; Achterberg, Jens A; Van der Lelij, Allegonda
2014-03-01
The aim of this study was to supply data on the relationship between Descemet stripping automated endothelial keratoplasty (DSAEK) graft thickness and its effects on visual acuity (VA), pace of visual recovery, endothelial cell densities (ECDs), and surgical complications. We additionally provide an approach for choosing the microkeratome blade thickness when multiple patients are scheduled for DSAEK. This is a retrospective analysis of all DSAEK procedures performed at our institute from January 2011 to December 2012. The VA was assessed at all postop visits. The ECD was assessed at 6 and 12 months postoperatively. An algorithm based on donor cornea pachymetry was used to assist in the choice of a microkeratome blade either 350 or 400 μm thick. Two groups were created on the basis of the microkeratome blade chosen. Outcomes were given per treatment group. One hundred two consecutive DSAEK procedures were performed; 60 grafts were prepared with the 350-μm blade and 39 with the 400-μm blade. Baseline characteristics did not differ materially. Grafts dissected using the 350-μm knife were significantly thicker than the grafts dissected with the 400-μm blade, with values of 257 ± 47 μm and 222 ± 33 μm, respectively (P = 0.01). The pace of visual recovery, VA at maximum follow-up, and ECD did not differ significantly between groups. Surgical complications were evenly distributed over both groups. This study indicates that using neither the 350-μm nor 400-μm microkeratome blade for the DSAEK altered the outcomes in terms of VA, ECD, and surgical complications. The algorithm presented in this study is helpful in equally distributing benefits from thinner grafting for all DSAEK-operated patients.
Response functions of a superlattice with a basis: A model for oxide superconductors
International Nuclear Information System (INIS)
Griffin, A.
1988-01-01
The new high-T/sub c/ oxide superconductors appear to be superlattice structures with a basis composed of metallic sheets as well as metallic chains. Using a simple free-electron-gas model for the sheets and chains, we obtain the dielectric function ε(q,ω) of such a multilayer system within the random-phase approximation (RPA). We give results valid for arbitrary wave vector q appropriate to sheets and chains (as in the orthorhombic phase of Y-Ba-Cu-O) as well as for two different kinds of sheets (such as may be present in the Bi-Ca-Sr-Cu-O superconductors). The occurrence of acoustic plasmons is a general phenomenon in such superlattices, as shown by an alternative formulation based on the exact response functions for the individual sheets and chains, in which only the interchain (sheet) Coulomb interaction is treated in the RPA. These results generalize the long-wavelength expressions recently given in the literature. We also briefly discuss the analogous results for two arrays of mutually perpendicular chains, such as found in Hg chain compounds
Online dimensionality reduction using competitive learning and Radial Basis Function network.
Tomenko, Vladimir
2011-06-01
The general purpose dimensionality reduction method should preserve data interrelations at all scales. Additional desired features include online projection of new data, processing nonlinearly embedded manifolds and large amounts of data. The proposed method, called RBF-NDR, combines these features. RBF-NDR is comprised of two modules. The first module learns manifolds by utilizing modified topology representing networks and geodesic distance in data space and approximates sampled or streaming data with a finite set of reference patterns, thus achieving scalability. Using input from the first module, the dimensionality reduction module constructs mappings between observation and target spaces. Introduction of specific loss function and synthesis of the training algorithm for Radial Basis Function network results in global preservation of data structures and online processing of new patterns. The RBF-NDR was applied for feature extraction and visualization and compared with Principal Component Analysis (PCA), neural network for Sammon's projection (SAMANN) and Isomap. With respect to feature extraction, the method outperformed PCA and yielded increased performance of the model describing wastewater treatment process. As for visualization, RBF-NDR produced superior results compared to PCA and SAMANN and matched Isomap. For the Topic Detection and Tracking corpus, the method successfully separated semantically different topics. Copyright © 2011 Elsevier Ltd. All rights reserved.
Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs
International Nuclear Information System (INIS)
Bollig, Evan F.; Flyer, Natasha; Erlebacher, Gordon
2012-01-01
This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.
Lawson, Sarah P; Sigle, Leah T; Lind, Abigail L; Legan, Andrew W; Mezzanotte, Jessica N; Honegger, Hans-Willi; Abbot, Patrick
2017-08-01
Some animals express a form of eusociality known as "fortress defense," in which defense rather than brood care is the primary social act. Aphids are small plant-feeding insects, but like termites, some species express division of labor and castes of aggressive juvenile "soldiers." What is the functional basis of fortress defense eusociality in aphids? Previous work showed that the acquisition of venoms might be a key innovation in aphid social evolution. We show that the lethality of aphid soldiers derives in part from the induction of exaggerated immune responses in insects they attack. Comparisons between closely related social and nonsocial species identified a number of secreted effector molecules that are candidates for immune modulation, including a convergently recruited protease described in unrelated aphid species with venom-like functions. These results suggest that aphids are capable of antagonizing conserved features of the insect immune response, and provide new insights into the mechanisms underlying the evolution of fortress defense eusociality in aphids. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
A Multivariate Approach to Functional Neuro Modeling
DEFF Research Database (Denmark)
Mørch, Niels J.S.
1998-01-01
by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...
ASSESSMENT OF WATER NETWORK FUNCTIONING ON THE BASIS OF WATER LOSSES
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Katarzyna PIETRUCHA-URBANIK
Full Text Available In the paper the analysis of water network functioning on the basis of water losses occurring in the exemplary water supply system is presented. Using the received operational data the balance of water production was shown, the individual water consumption was calculated, the basic indicators of water losses and the indicators of network hydraulic load were established, which referred to the values recommended, among others, by the American Water Works Association. On the basis of these indicators, the assessment of the state of tested water supply system was performed. The unitary volume indicators related to water losses are at the constant level. The unitary indicator of water losses for the years 2007-2015, on average, amounted to approx. 108 dm3·inh-1·d-1, the unitary indicator of water supplied into network takes values from 459,1 dm3 ·inh-1·d-1 in 2007 to 402.9 dm3·inh-1·d-1 in 2015, which means the decrease of approx. 12%. The unitary indicator of sold water is in the range from 288,9 to 419,5 dm3 ·inh-1·d-1. The infrastructure leakage index ILI, according to the criteria of World Bank Institute Banding System for developing countries, estimates the state of water supply system as good. The value of the ILI index for the analysed water supply system corresponds to national trends, which range from 3,13 to 16,52 [3, 8].
Mass Spectrometry-Based Approaches to Understand the Molecular Basis of Memory
Pontes, Arthur H.; de Sousa, Marcelo V.
2016-01-01
The central nervous system is responsible for an array of cognitive functions such as memory, learning, language, and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enabled the identification and quantification of thousands of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis. PMID:27790611
Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory
Directory of Open Access Journals (Sweden)
Arthur Henriques Pontes
2016-10-01
Full Text Available The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.
Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory
Pontes, Arthur; de Sousa, Marcelo
2016-10-01
The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.
Assessment of Cardiac Function--Basic Principles and Approaches.
Spinale, Francis G
2015-09-20
Increased access and ability to visualize the heart has provided a means to measure a myriad of cardiovascular parameters in real or near real time. However, without fundamental knowledge regarding the basis for cardiac contraction and how to evaluate cardiac function in terms of loading conditions and inotropic state, appropriate interpretation of these cardiovascular parameters can be difficult and can lead to misleading conclusions regarding the functional state of the cardiac muscle. Thus, in this series of Comprehensive Physiology, the basic properties of cardiac muscle function, the cardiac cycle, and determinants of pump function will be reviewed. These basic concepts will then be integrated by presenting approaches in which the effects of preload, afterload, and myocardial contractility can be examined. Moreover, the utility of the pressure-volume relation in terms of assessing both myocardial contractility as well as critical aspects of diastolic performance will be presented. Finally, a generalized approach for the assessment and interpretation of cardiac function within the intact cardiovascular system will be presented. Copyright © 2015 John Wiley & Sons, Inc.
Montiel, Mariana; Wilhelmi, Miguel R.; Vidakovic, Draga; Elstak, Iwan
2012-01-01
In a previous study, the onto-semiotic approach was employed to analyse the mathematical notion of different coordinate systems, as well as some situations and university students' actions related to these coordinate systems in the context of multivariate calculus. This study approaches different coordinate systems through the process of change of basis, as developed in the context of linear algebra, as well as the similarity relationship between the matrices that represent the same linear transformation with respect to different bases.
Craniofacial fibrous dysplasia surgery: a functional approach.
Béquignon, E; Cardinne, C; Lachiver, X; Wagner, I; Chabolle, F; Baujat, B
2013-09-01
Craniofacial fibrous dysplasia has not only esthetic but functional impact. Surgery is controversial, ranging from conservative to radical. It involves elevated hemorrhage risk, and should be progressive, based on an individual risk/benefit analysis with the aim of improving quality of life. Three patients (one male, two female; mean age, 35 years) with evolutive orbital-temporal maxillary dysplasia were treated between 2008 and 2009 in our department. All showed exophthalmia and nasal obstruction. In one patient, symptomatology was aggravated by a frontal sinus cyst within the dysplasia. Another had associated auditory canal obstruction inducing recurrent external otitis. Optic nerve decompression was achieved on a combined coronal and endonasal approach, assisted by neuronavigation. Complementary remodelling resection, dacryocystorhinostomy and internal optic nerve decompression were performed. Functional results showed 70 % improvement on a subjective scale for eye tension and nasal obstruction. Surgery was feasible in all patients, with no complications. Current surgical management allies esthetic and functional concerns. Remodeling resection is the reference technique. The coronal approach is a good primary option for optic nerve decompression. Endonasal surgery with neuronavigation improves nasal ventilation and lacrimal canal permeability. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
Wang, Zhiheng
2014-12-10
A meshless local radial basis function method is developed for two-dimensional incompressible Navier-Stokes equations. The distributed nodes used to store the variables are obtained by the philosophy of an unstructured mesh, which results in two main advantages of the method. One is that the unstructured nodes generation in the computational domain is quite simple, without much concern about the mesh quality; the other is that the localization of the obtained collocations for the discretization of equations is performed conveniently with the supporting nodes. The algebraic system is solved by a semi-implicit pseudo-time method, in which the convective and source terms are explicitly marched by the Runge-Kutta method, and the diffusive terms are implicitly solved. The proposed method is validated by several benchmark problems, including natural convection in a square cavity, the lid-driven cavity flow, and the natural convection in a square cavity containing a circular cylinder, and very good agreement with the existing results are obtained.
Directory of Open Access Journals (Sweden)
Misganaw Abebe
2017-11-01
Full Text Available Springback in multi-point dieless forming (MDF is a common problem because of the small deformation and blank holder free boundary condition. Numerical simulations are widely used in sheet metal forming to predict the springback. However, the computational time in using the numerical tools is time costly to find the optimal process parameters value. This study proposes radial basis function (RBF to replace the numerical simulation model by using statistical analyses that are based on a design of experiment (DOE. Punch holding time, blank thickness, and curvature radius are chosen as effective process parameters for determining the springback. The Latin hypercube DOE method facilitates statistical analyses and the extraction of a prediction model in the experimental process parameter domain. Finite element (FE simulation model is conducted in the ABAQUS commercial software to generate the springback responses of the training and testing samples. The genetic algorithm is applied to find the optimal value for reducing and compensating the induced springback for the different blank thicknesses using the developed RBF prediction model. Finally, the RBF numerical result is verified by comparing with the FE simulation result of the optimal process parameters and both results show that the springback is almost negligible from the target shape.
Physiological and genomic basis of mechanical-functional trade-off in plant vasculature
Directory of Open Access Journals (Sweden)
Sonali eSengupta
2014-05-01
Full Text Available Some areas in plant abiotic stress research are not frequently addressed by genomic and molecular tools. One such area is the cross reaction of gravitational force with upward capillary pull of water and the mechanical-functional trade-off in plant vasculature. Although frost, drought and flooding stress greatly impact these physiological processes and consequently plant performance, the genomic and molecular basis of such trade-off is only sporadically addressed and so is its adaptive value. Embolism resistance is an important multiple stress- opposition trait and do offer scopes for critical insight to unravel and modify the input of living cells in the process and their biotechnological intervention may be of great importance . Vascular plants employ different physiological strategies to cope with embolism and variation is observed across the kingdom . The genomic resources in this area have started to emerge and open up possibilities of synthesis, validation and utilization of the new knowledge-base. This review article assesses the research till date on this issue and discusses new possibilities for bridging physiology and genomics of a plant, and foresees its implementation in crop science.
Prediction of reservoir brine properties using radial basis function (RBF neural network
Directory of Open Access Journals (Sweden)
Afshin Tatar
2015-12-01
Full Text Available Aquifers, which play a prominent role as an effective tool to recover hydrocarbon from reservoirs, assist the production of hydrocarbon in various ways. In so-called water flooding methods, the pressure of the reservoir is intensified by the injection of water into the formation, increasing the capacity of the reservoir to allow for more hydrocarbon extraction. Some studies have indicated that oil recovery can be increased by modifying the salinity of the injected brine in water flooding methods. Furthermore, various characteristics of brines are required for different calculations used within the petroleum industry. Consequently, it is of great significance to acquire the exact information about PVT properties of brine extracted from reservoirs. The properties of brine that are of great importance are density, enthalpy, and vapor pressure. In this study, radial basis function neural networks assisted with genetic algorithm were utilized to predict the mentioned properties. The root mean squared error of 0.270810, 0.455726, and 1.264687 were obtained for reservoir brine density, enthalpy, and vapor pressure, respectively. The predicted values obtained by the proposed models were in great agreement with experimental values. In addition, a comparison between the proposed model in this study and a previously proposed model revealed the superiority of the proposed GA-RBF model.
McClements, David Julian; Gumus, Cansu Ekin
2016-08-01
There is increasing consumer pressure for commercial products that are more natural, sustainable, and environmentally friendly, including foods, cosmetics, detergents, and personal care products. Industry has responded by trying to identify natural alternatives to synthetic functional ingredients within these products. The focus of this review article is on the replacement of synthetic surfactants with natural emulsifiers, such as amphiphilic proteins, polysaccharides, biosurfactants, phospholipids, and bioparticles. In particular, the physicochemical basis of emulsion formation and stabilization by natural emulsifiers is discussed, and the benefits and limitations of different natural emulsifiers are compared. Surface-active polysaccharides typically have to be used at relatively high levels to produce small droplets, but the droplets formed are highly resistant to environmental changes. Conversely, surface-active proteins are typically utilized at low levels, but the droplets formed are highly sensitive to changes in pH, ionic strength, and temperature. Certain phospholipids are capable of producing small oil droplets during homogenization, but again the droplets formed are highly sensitive to changes in environmental conditions. Biosurfactants (saponins) can be utilized at low levels to form fine oil droplets that remain stable over a range of environmental conditions. Some nature-derived nanoparticles (e.g., cellulose, chitosan, and starch) are effective at stabilizing emulsions containing relatively large oil droplets. Future research is encouraged to identify, isolate, purify, and characterize new types of natural emulsifier, and to test their efficacy in food, cosmetic, detergent, personal care, and other products. Copyright © 2016 Elsevier B.V. All rights reserved.
Structural Basis of Wee Kinases Functionality and Inactivation by Diverse Small Molecule Inhibitors.
Zhu, Jin-Yi; Cuellar, Rebecca A; Berndt, Norbert; Lee, Hee Eun; Olesen, Sanne H; Martin, Mathew P; Jensen, Jeffrey T; Georg, Gunda I; Schönbrunn, Ernst
2017-09-28
Members of the Wee family of kinases negatively regulate the cell cycle via phosphorylation of CDK1 and are considered potential drug targets. Herein, we investigated the structure-function relationship of human Wee1, Wee2, and Myt1 (PKMYT1). Purified recombinant full-length proteins and kinase domain constructs differed substantially in phosphorylation states and catalytic competency, suggesting complex mechanisms of activation. A series of crystal structures reveal unique features that distinguish Wee1 and Wee2 from Myt1 and establish the structural basis of differential inhibition by the widely used Wee1 inhibitor MK-1775. Kinome profiling and cellular studies demonstrate that, in addition to Wee1 and Wee2, MK-1775 is an equally potent inhibitor of the polo-like kinase PLK1. Several previously unrecognized inhibitors of Wee kinases were discovered and characterized. Combined, the data provide a comprehensive view on the catalytic and structural properties of Wee kinases and a framework for the rational design of novel inhibitors thereof.
Directory of Open Access Journals (Sweden)
M. Safish Mary
2012-04-01
Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.
Directory of Open Access Journals (Sweden)
Tatar Afshin
2016-03-01
Full Text Available Raw natural gases usually contain water. It is very important to remove the water from these gases through dehydration processes due to economic reasons and safety considerations. One of the most important methods for water removal from these gases is using dehydration units which use Triethylene glycol (TEG. The TEG concentration at which all water is removed and dew point characteristics of mixture are two important parameters, which should be taken into account in TEG dehydration system. Hence, developing a reliable and accurate model to predict the performance of such a system seems to be very important in gas engineering operations. This study highlights the use of intelligent modeling techniques such as Multilayer perceptron (MLP and Radial Basis Function Neural Network (RBF-ANN to predict the equilibrium water dew point in a stream of natural gas based on the TEG concentration of stream and contractor temperature. Literature data set used in this study covers temperatures from 10 °C to 80 °C and TEG concentrations from 90.000% to 99.999%. Results showed that both models are accurate in prediction of experimental data and the MLP model gives more accurate predictions compared to RBF model.
Energy Technology Data Exchange (ETDEWEB)
Jacques Hugo; John Forester; David Gertman; Jeffrey Joe; Heather Medema; Julius Persensky; April Whaley
2013-04-01
This report presents preliminary research results from the investigation in to the development of new models and guidance for concepts of operations (ConOps) in advanced small modular reactor (aSMR) designs. In support of this objective, three important research areas were included: operating principles of multi-modular plants, functional allocation models and strategies that would affect the development of new, non-traditional concept of operations, and the requiremetns for human performance, based upon work domain analysis and current regulatory requirements. As part of the approach for this report, we outline potential functions, including the theoretical and operational foundations for the development of a new functional allocation model and the identification of specific regulatory requirements that will influence the development of future concept of operations. The report also highlights changes in research strategy prompted by confirmationof the importance of applying the work domain analysis methodology to a reference aSMR design. It is described how this methodology will enrich the findings from this phase of the project in the subsequent phases and help in identification of metrics and focused studies for the determination of human performance criteria that can be used to support the design process.
Turovtsev, V. V.; Orlov, Yu. D.; Tsirulev, A. N.
2015-08-01
The advantages of the orthonormal basis set of 2π-periodic Mathieu functions compared to the trigonometric basis set in calculations of torsional states of molecules are substantiated. Explicit expressions are derived for calculating the Hamiltonian matrix elements of a one-dimensional torsional Schrödinger equation with a periodic potential of the general form in the basis set of Mathieu functions. It is shown that variation of a parameter of Mathieu functions allows the rotation potential and the structural function to be approximated with a good accuracy by a small number of series terms. The conditions for the best choice of this parameter are specified, and approximations are obtained for torsional potentials of n-butane upon rotation about the central C-C bond and of its univalent radical n-butyl C2H5C·H2 upon rotation of the C·H2 group. All algorithms are implemented in the Maple package.
Political Economy of Piracy in Somalia: Basis for a Transformative Approach
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Gilberto Carvalho de Oliveira
2010-12-01
Full Text Available This article examines the current wave of piracy off the coast of Somalia in light of political economy framework proposed by Michael Pugh and Neil Cooper. According to these authors, three types of economies flourish in protracted conflicts - combat economy, shadow economy, and coping economy - whose aims are, respectively, to finance combat activities, generate personal profits and provide minimum resources to the subsistence of poor and marginalized people. Based on empirical evidences showing that piracy in Somalia performs these three functions, one argues that the current international intervention against piracy is not sustainable because it does not seek to transform the factors and dynamics that make piracy an economically attractive alternative for local populations. For this reason, one proposes a shift on the Somali piracy agenda by adopting a critical perspective where piracy is no longer treated exclusively as a mere disruption of order at sea. Instead, one suggests a transformative approach where piracy is understood in its political economy dimension taking into account not only the local aspects, but also their regional links.
Wightman, Jade; Julio, Flávia; Virués-Ortega, Javier
2014-05-01
Experimental functional analysis is an assessment methodology to identify the environmental factors that maintain problem behavior in individuals with developmental disabilities and in other populations. Functional analysis provides the basis for the development of reinforcement-based approaches to treatment. This article reviews the procedures, validity, and clinical implementation of the methodological variations of functional analysis and function-based interventions. We present six variations of functional analysis methodology in addition to the typical functional analysis: brief functional analysis, single-function tests, latency-based functional analysis, functional analysis of precursors, and trial-based functional analysis. We also present the three general categories of function-based interventions: extinction, antecedent manipulation, and differential reinforcement. Functional analysis methodology is a valid and efficient approach to the assessment of problem behavior and the selection of treatment strategies.
Stateczny, A.; Lubczonek, J.
2003-04-01
The basic problem in the construction of a numerical spatial sea chart is such transformation of the sounding data that it should be possible to determine the depth at any point of the bottom area. In recent years, much attention has been devoted to the problem of modelling the seabed shape in a numerical three-dimensional sea chart. Various methods for modelling the seabed shape are applied. These methods can be divided into analytical and neural. In the case of applying the model for navigational tasks, the selection of a suitable method should ensure high accuracy of surface projection. The model should be conformed to the surface shape, spatial distribution of the measurement points and their number. The application of universal methods like 'multiquadric' or 'kriging' does not ensure an optimal result either, as each of these methods can have a certain number of options and parameters, which frequently play a significant role during surface modelling. It is often difficult to optimise these factors and even experience does not guarantee a satisfactory result. This applies especially to modelling irregular surfaces, when it is difficult to select the method suitable for the surface shape that is sometimes unpredictable. It has been suggested that the method of selecting the shape parameter of the radial basis functions should be applied which makes it possible to minimise the mean square error of the approximated surface. The paper presents a new method of optimising the parameters of radial functions used for modelling the bottom surface. The accuracy of the surface projection obtained was the criterion for optimisation. The properties of self-organizing networks created the possibility of selecting testing points out of any set of measurement points and the determination of the minimum value of RMS error by means of the GRNN network. Optimisation of the shape parameter required building the proper polygon of the test points. For building such kind of polygon
Concept of the dealer-service network management on the system approach basis
Directory of Open Access Journals (Sweden)
Irina MAKAROVA
2011-01-01
Full Text Available In article the method of improvement of automobile service quality within the limits of a dealer-service network limits, by building of information-logistical system and feedback mechanism adjustment is considered. As operating influence application of the discounts` system calculated on the basis of forward orderings on spare parts arriving from the service centers is offered.
Directory of Open Access Journals (Sweden)
Minenkova Olena V.
2017-12-01
Full Text Available The article proposes the methodical approach to assessment of activity of enterprise on the basis of its models, based on the balanced scorecard. The content is presented and the following components of the methodical approach are formed: tasks, input information, list of methods and models, as well as results. Implementation of this methodical approach provides improvement of management and increase of results of enterprise activity. The place of assessment models in management of enterprise activity and formation of managerial decision has been defined. Recommendations as to the operations of decision-making procedures to increase the efficiency of enterprise have been provided.
Radial basis function regression methods for predicting quantitative traits using SNP markers.
Long, Nanye; Gianola, Daniel; Rosa, Guilherme J M; Weigel, Kent A; Kranis, Andreas; González-Recio, Oscar
2010-06-01
A challenge when predicting total genetic values for complex quantitative traits is that an unknown number of quantitative trait loci may affect phenotypes via cryptic interactions. If markers are available, assuming that their effects on phenotypes are additive may lead to poor predictive ability. Non-parametric radial basis function (RBF) regression, which does not assume a particular form of the genotype-phenotype relationship, was investigated here by simulation and analysis of body weight and food conversion rate data in broilers. The simulation included a toy example in which an arbitrary non-linear genotype-phenotype relationship was assumed, and five different scenarios representing different broad sense heritability levels (0.1, 0.25, 0.5, 0.75 and 0.9) were created. In addition, a whole genome simulation was carried out, in which three different gene action modes (pure additive, additive+dominance and pure epistasis) were considered. In all analyses, a training set was used to fit the model and a testing set was used to evaluate predictive performance. The latter was measured by correlation and predictive mean-squared error (PMSE) on the testing data. For comparison, a linear additive model known as Bayes A was used as benchmark. Two RBF models with single nucleotide polymorphism (SNP)-specific (RBF I) and common (RBF II) weights were examined. Results indicated that, in the presence of complex genotype-phenotype relationships (i.e. non-linearity and non-additivity), RBF outperformed Bayes A in predicting total genetic values using SNP markers. Extension of Bayes A to include all additive, dominance and epistatic effects could improve its prediction accuracy. RBF I was generally better than RBF II, and was able to identify relevant SNPs in the toy example.
Linear response calculation using the canonical-basis TDHFB with a schematic pairing functional
International Nuclear Information System (INIS)
Ebata, Shuichiro; Nakatsukasa, Takashi; Yabana, Kazuhiro
2011-01-01
A canonical-basis formulation of the time-dependent Hartree-Fock-Bogoliubov (TDHFB) theory is obtained with an approximation that the pair potential is assumed to be diagonal in the time-dependent canonical basis. The canonical-basis formulation significantly reduces the computational cost. We apply the method to linear-response calculations for even-even nuclei. E1 strength distributions for proton-rich Mg isotopes are systematically calculated. The calculation suggests strong Landau damping of giant dipole resonance for drip-line nuclei.
Radiological emergency response - a functional approach
International Nuclear Information System (INIS)
Chowdhury, P.
1998-01-01
The state of Louisiana's radiological emergency response programme is based on the federal guidance 'Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants' (NUREG-0654, FEMA-REP-1 Rev. 1). Over the past 14 years, the planning and implementation of response capabilities became more organized and efficient; the training programme has strengthened considerably; co-ordination with all participating agencies has assumed a more co-operative role, and as a result, a fairly well integrated response planning has evolved. Recently, a more 'functional' approach is being adopted to maximize the programme's efficiency not only for nuclear power plant emergency response, but radiological emergency response as a whole. First, several broad-based 'components' are identified; clusters of 'nodes' are generated for each component; these 'nodes' may be divided into 'sub-nodes' which will contain some 'attributes'; 'relational bonds' among the 'attributes' will exist. When executed, the process begins and continues with the 'nodes' assuming a functional and dynamic role based on the nature and characteristics of the 'attributes'. The typical response based on stand-alone elements is thus eliminated, the overlapping of functions is avoided, and a well structured and efficient organization is produced, that is essential for today's complex nature of emergency response. (author)
Design Basis Threat (DBT) Approach for the First NPP Security System in Indonesia
International Nuclear Information System (INIS)
Ign Djoko Irianto
2004-01-01
Design Basis Threat (DBT) is one of the main factors to be taken into account in the design of physical protection system of nuclear facility. In accordance with IAEA's recommendations outlined in INFCIRC/225/Rev.4 (Corrected), DBT is defined as: attributes and characteristics of potential insider and/or external adversaries, who might attempt unauthorized removal of nuclear material or sabotage against the nuclear facilities. There are three types of adversary that must be considered in DBT, such as adversary who comes from the outside (external adversary), adversary who comes from the inside (internal adversary), and adversary who comes from outside and colludes with insiders. Current situation in Indonesia, where many bomb attacks occurred, requires serious attention on DBT in the physical protection design of NPP which is to be built in Indonesia. This paper is intended to describe the methodology on how to create and implement a Design Basis Threat in the design process of NPP physical protection in Indonesia. (author)
Directory of Open Access Journals (Sweden)
Eyad K Almaita
2017-03-01
Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application. International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17
Fragment approach to constrained density functional theory calculations using Daubechies wavelets
International Nuclear Information System (INIS)
Ratcliff, Laura E.; Genovese, Luigi; Mohr, Stephan; Deutsch, Thierry
2015-01-01
In a recent paper, we presented a linear scaling Kohn-Sham density functional theory (DFT) code based on Daubechies wavelets, where a minimal set of localized support functions are optimized in situ and therefore adapted to the chemical properties of the molecular system. Thanks to the systematically controllable accuracy of the underlying basis set, this approach is able to provide an optimal contracted basis for a given system: accuracies for ground state energies and atomic forces are of the same quality as an uncontracted, cubic scaling approach. This basis set offers, by construction, a natural subset where the density matrix of the system can be projected. In this paper, we demonstrate the flexibility of this minimal basis formalism in providing a basis set that can be reused as-is, i.e., without reoptimization, for charge-constrained DFT calculations within a fragment approach. Support functions, represented in the underlying wavelet grid, of the template fragments are roto-translated with high numerical precision to the required positions and used as projectors for the charge weight function. We demonstrate the interest of this approach to express highly precise and efficient calculations for preparing diabatic states and for the computational setup of systems in complex environments
Approach to ''Mind'' using functional neuroimaging
International Nuclear Information System (INIS)
Matsuda, Hiroshi
2006-01-01
This review mainly describes authors' recent investigations concerning neuroimages approaching to even human ''mind'' using techniques of PET, SPECT and functional MRI (fMRI). Progress of such studies greatly owes to the development of image statistics of the brain like statistical parametric mapping (www.fil.ion.ucl.ac.uk/spm/), and brain standards (www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html, and ric.uthscsa.edu/projects/talairach daemon.html). The author discusses and presents images in cases of hallucinations (SPECT and H 2 15 O-PET), autism (SPECT), sleep, depression, and its therapy by transcaranial magnetic stimulation. These studies are expected to contribute to diagnosis and therapy of endogenous neurological disorders. (T.I.)
Quantum anharmonic oscillator: The airy function approach
Energy Technology Data Exchange (ETDEWEB)
Maiz, F., E-mail: fethimaiz@gmail.com [King Khalid University, Faculty of Science, Physics Department, PO Box 9004, Abha 61413, Asseer (Saudi Arabia); University of Cartage, Nabeul Engineering Preparatory Institute, Merazka, 8000 Nabeul (Tunisia); AlFaify, S. [King Khalid University, Faculty of Science, Physics Department, PO Box 9004, Abha 61413, Asseer (Saudi Arabia)
2014-05-15
New and simple numerical method is being reported to solve anharmonic oscillator problems. The method is setup to approach the real potential V(x) of the anharmonic oscillator system as a piecewise linear potential u(x) and to solve the Schrödinger equation of the system using the Airy function. Then, solutions continuity conditions lead to the energy quantification condition, and consequently, the energy eigenvalues. For testing purpose, the method was applied on the sextic and octic oscillators systems. The proposed method is found to be realistic, computationally simple, and having high degrees of accuracy. In addition, it can be applied to any form of potential. The results obtained by the proposed method were seen closely agreeing with results reached by other complicated methods.
Directory of Open Access Journals (Sweden)
Ali Mansourkhaki
2018-01-01
Full Text Available Noise pollution is a level of environmental noise which is considered as a disturbing and annoying phenomenon for human and wildlife. It is one of the environmental problems which has not been considered as harmful as the air and water pollution. Compared with other pollutants, the attempts to control noise pollution have largely been unsuccessful due to the inadequate knowledge of its effectson humans, as well as the lack of clear standards in previous years. However, with an increase of traveling vehicles, the adverse impact of increasing noise pollution on human health is progressively emerging. Hence, investigators all around the world are seeking to findnew approaches for predicting, estimating and controlling this problem and various models have been proposed. Recently, developing learning algorithms such as neural network has led to novel solutions for this challenge. These algorithms provide intelligent performance based on the situations and input data, enabling to obtain the best result for predicting noise level. In this study, two types of neural networks – multilayer perceptron and radial basis function – were developed for predicting equivalent continuous sound level (LA eq by measuring the traffivolume, average speed and percentage of heavy vehicles in some roads in west and northwest of Tehran. Then, their prediction results were compared based on the coefficienof determination (R 2 and the Mean Squared Error (MSE. Although both networks are of high accuracy in prediction of noise level, multilayer perceptron neural network based on selected criteria had a better performance.
International Nuclear Information System (INIS)
Roshani, G.H.; Nazemi, E.; Roshani, M.M.
2017-01-01
In this paper, a novel method is proposed for predicting the density of liquid phase in stratified regime of liquid-gas two phase flows by utilizing dual modality densitometry technique and artificial neural network (ANN) model of radial basis function (RBF). The detection system includes a 137 Cs radioactive source and two NaI(Tl) detectors for registering transmitted and scattered photons. At the first step, a Monte Carlo simulation model was utilized to obtain the optimum position for the scattering detector in dual modality densitometry configuration. At the next step, an experimental setup was designed based on obtained optimum position for detectors from simulation in order to generate the required data for training and testing the ANN. The results show that the proposed approach could be successfully applied for predicting the density of liquid phase in stratified regime of gas-liquid two phase flows with mean relative error (MRE) of less than 0.701. - Highlights: • Density of liquid phase in stratified regime of two phase flows was predicted. • Combination of dual modality densitometry technique and ANN was utilized. • Detection system includes a 137 Cs radioactive source and two NaI(Tl) detectors. • MCNP simulation was done to obtain the optimum position for the scattering detector. • An experimental setup was designed to generate the required data for training the ANN.
Belderrar, Ahmed; Hazzab, Abdeldjebar
2017-07-01
Controlling hospital high length of stay outliers can provide significant benefits to hospital management resources and lead to cost reduction. The strongest predictive factors influencing high length of stay outliers should be identified to build a high-performance prediction model for hospital outliers. We highlight the application of the hierarchical genetic algorithm to provide the main predictive factors and to define the optimal structure of the prediction model fuzzy radial basis function neural network. To establish the prediction model, we used a data set of 26,897 admissions from five different intensive care units with discharges between 2001 and 2012. We selected and analyzed the high length of stay outliers using the trimming method geometric mean plus two standard deviations. A total of 28 predictive factors were extracted from the collected data set and investigated. High length of stay outliers comprised 5.07% of the collected data set. The results indicate that the prediction model can provide effective forecasting. We found 10 common predictive factors within the studied intensive care units. The obtained main predictive factors include patient demographic characteristics, hospital characteristics, medical events, and comorbidities. The main initial predictive factors available at the time of admission are useful in evaluating high length of stay outliers. The proposed approach can provide a practical tool for healthcare providers, and its application can be extended to other hospital predictions, such as readmissions and cost.
``Green's function'' approach & low-mode asymmetries
Masse, Laurent; Clark, Dan; Salmonson, Jay; MacLaren, Steve; Ma, Tammy; Khan, Shahab; Pino, Jesse; Ralph, Jo; Czajka, C.; Tipton, Robert; Landen, Otto; Kyrala, Georges; 2 Team; 1 Team
2017-10-01
Long wavelength, low mode asymmetries are believed to play a leading role in limiting the performance of current ICF implosions on NIF. These long wavelength modes are initiated and driven by asymmetries in the x-ray flux from the hohlraum; however, the underlying hydrodynamics of the implosion also act to amplify these asymmetries. The work presented here aim to deepen our understanding of the interplay of the drive asymmetries and the underlying implosion hydrodynamics in determining the final imploded configuration. This is accomplished through a synthesis of numerical modeling, analytic theory, and experimental data. In detail, we use a Green's function approach to connect the drive asymmetry seen by the capsule to the measured inflight and hot spot symmetries. The approach has been validated against a suite of numerical simulations. Ultimately, we hope this work will identify additional measurements to further constrain the asymmetries and increase hohlraum illumination design flexibility on the NIF. The technique and derivation of associated error bars will be presented. LLC, (LLNS) Contract No. DE-AC52-07NA27344.
EMG-based facial gesture recognition through versatile elliptic basis function neural network.
Hamedi, Mahyar; Salleh, Sh-Hussain; Astaraki, Mehdi; Noor, Alias Mohd
2013-07-17
Recently, the recognition of different facial gestures using facial neuromuscular activities has been proposed for human machine interfacing applications. Facial electromyograms (EMGs) analysis is a complicated field in biomedical signal processing where accuracy and low computational cost are significant concerns. In this paper, a very fast versatile elliptic basis function neural network (VEBFNN) was proposed to classify different facial gestures. The effectiveness of different facial EMG time-domain features was also explored to introduce the most discriminating. In this study, EMGs of ten facial gestures were recorded from ten subjects using three pairs of surface electrodes in a bi-polar configuration. The signals were filtered and segmented into distinct portions prior to feature extraction. Ten different time-domain features, namely, Integrated EMG, Mean Absolute Value, Mean Absolute Value Slope, Maximum Peak Value, Root Mean Square, Simple Square Integral, Variance, Mean Value, Wave Length, and Sign Slope Changes were extracted from the EMGs. The statistical relationships between these features were investigated by Mutual Information measure. Then, the feature combinations including two to ten single features were formed based on the feature rankings appointed by Minimum-Redundancy-Maximum-Relevance (MRMR) and Recognition Accuracy (RA) criteria. In the last step, VEBFNN was employed to classify the facial gestures. The effectiveness of single features as well as the feature sets on the system performance was examined by considering the two major metrics, recognition accuracy and training time. Finally, the proposed classifier was assessed and compared with conventional methods support vector machines and multilayer perceptron neural network. The average classification results showed that the best performance for recognizing facial gestures among all single/multi-features was achieved by Maximum Peak Value with 87.1% accuracy. Moreover, the results proved a
Gerist, Saleheh; Maheri, Mahmoud R.
2016-12-01
In order to solve structural damage detection problem, a multi-stage method using particle swarm optimization is presented. First, a new spars recovery method, named Basis Pursuit (BP), is utilized to preliminarily identify structural damage locations. The BP method solves a system of equations which relates the damage parameters to the structural modal responses using the sensitivity matrix. Then, the results of this stage are subsequently enhanced to the exact damage locations and extents using the PSO search engine. Finally, the search space is reduced by elimination of some low damage variables using micro search (MS) operator embedded in the PSO algorithm. To overcome the noise present in structural responses, a method known as Basis Pursuit De-Noising (BPDN) is also used. The efficiency of the proposed method is investigated by three numerical examples: a cantilever beam, a plane truss and a portal plane frame. The frequency response is used to detect damage in the examples. The simulation results demonstrate the accuracy and efficiency of the proposed method in detecting multiple damage cases and exhibit its robustness regarding noise and its advantages compared to other reported solution algorithms.
Density functional response approach for the linear and nonlinear electric properties of molecules
Sophy, K. B.; Pal, Sourav
2003-06-01
This is a preliminary study toward implementation of analytic density functional response approach for molecules to obtain linear and nonlinear electric properties. The Kohn-Sham framework has been used with Gaussian basis sets. We propose a fully variational approach to obtain the response of electronic density in terms of the atomic orbital basis (contracted Gaussians). As a first step, this derivative of the Kohn-Sham operator is obtained by a finite field method using five different values of electric field. Using this, we obtain the energy derivatives up to third order using fully analytic expressions. We calculate the dipole moment, polarizability, and hyperpolarizability of the hydrogen fluoride (HF) molecule as a test case using different exchange-correlation functionals and basis sets within the present methodology. We also explore the feasibility of this response approach by studying the properties of the HF molecule for different H-F distances.
DEFF Research Database (Denmark)
Lee, Kyo-Beum; Bae, C.H.; Blaabjerg, Frede
2005-01-01
A scheme to estimate the moment of inertia in a servo motor drive system at very low speed is proposed. The typical speed estimation scheme used in most servo systems operated at low speed is highly sensitive to variations in the moment of inertia. An observer that uses a radial basis function...
Czech Academy of Sciences Publication Activity Database
Bucha, B.; Bezděk, Aleš; Sebera, Josef; Janak, J.
2015-01-01
Roč. 36, č. 6 (2015), s. 773-801 ISSN 0169-3298 R&D Projects: GA ČR GA13-36843S Grant - others:SAV(SK) VEGA 1/0954/15 Institutional support: RVO:67985815 Keywords : spherical radial basis functions * spherical harmonics * geopotential Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 3.622, year: 2015
Directory of Open Access Journals (Sweden)
Yu Peiqiang
2012-12-01
Full Text Available Abstract In complex feed structures, there exist main chemical functional groups which are associated with nutrient utilization and availability and functionality. Each functional group has unique molecular structure therefore produce unique molecular vibration spectral profile. Feed processing has been used to improve nutrient utilization for many years. However, to date, there was little study on processing-induced changes of feed intrinsic structure and functional groups on a molecular basis within intact tissue. This is because limited research technique is available to study inherent structure on a molecular basis. Recently bioanalytical techniques: such as Synchrotron Infrared Microspectroscopy as well as Diffuse Reflectance Infrared Fourier Transform molecular spectroscopy have been developed. These techniques enable to detect molecular structure change within intact tissues. These techniques can prevent destruction or alteration of the intrinsic protein structures during processing for analysis. However, these techniques have not been used in animal feed and nutrition research. The objective of this review was show that with the advanced technique, sensitivity and responses of functional groups to feed processing on a molecular basis could be detected in my research team. These functional groups are highly associated with nutrient utilization in animals.
Joosten, S.M.M.; van den Berg, Klaas; Mulder, F.
1990-01-01
Aan de Universiteit Twente is de afgelopen vier jaar geëxperimenteerd met een inleidende kursus in het programmeren, op basis van funktioneel programmeren. Dit artikel gaat in op het waarom van deze aanpak, de doelstelling van het programmeeronderwijs, de opzet en inhoud van de kursusonderdelen en
Estimasi Nilai Basis Pajak Bumi dan Bangunan di Kota Jambi: Pendekatan Hedonic Price Function
Directory of Open Access Journals (Sweden)
Arman Delis
2015-03-01
Full Text Available This research is aimed to identify the most dominant factors which determine the rate of price of lands and buildings, to measure the ratio between the price of lands and buildings based on price set on Income Tax Payable (SPPT. The estimated value taxpayer on land and buildings and the value of the estimation is based on the hedonic price function. Estimates of the level of the price of land and buildings carried out with the hedonic price function approach. The data used is the cross-sectional data obtained from the results of a field survey of 100 owners of land and buildings are scattered in the subdistrict Telanaipura, Pelayangan, Pasar Jambi and Kota Baru subdistrict. The results showed that the level of the price of land and buildings in the district are highest and lowest Jambi Market in Subdsitrict Pelayangan. The most dominant variable that determines the level of the price of land is population density, distance to the city center location of the land and the type of road that passes through the location of the land, while the price level is determined by the building floor area of the house, the type of home and the availability of the garage wall. On average, the ratio of the price of land in the SPT to the actual price of the desired land owners and the price of each prediction is 29.30 percent and 44.13 percent, while the ratio of the price of houses for the price of the actual building and the price of the average prediction of 39.57 percent and 33.04 percent. The relatively low Figures of ratio indicates that the price of land and buildings are set by the government on the tax return in the calculation of taxable value mostly still too far away when compared with the price of land and building the desired owners and price prediction. This means that the potential increase in the Land and Property Tax in the city of Jambi is still very large.
Soil eukaryotic functional diversity, a metatranscriptomic approach.
Bailly, Julie; Fraissinet-Tachet, Laurence; Verner, Marie-Christine; Debaud, Jean-Claude; Lemaire, Marc; Wésolowski-Louvel, Micheline; Marmeisse, Roland
2007-11-01
To appreciate the functional diversity of communities of soil eukaryotic micro-organisms we evaluated an experimental approach based on the construction and screening of a cDNA library using polyadenylated mRNA extracted from a forest soil. Such a library contains genes that are expressed by each of the different organisms forming the community and represents its metatranscriptome. The diversity of the organisms that contributed to this library was evaluated by sequencing a portion of the 18S rDNA gene amplified from either soil DNA or reverse-transcribed RNA. More than 70% of the sequences were from fungi and unicellular eukaryotes (protists) while the other most represented group was the metazoa. Calculation of richness estimators suggested that more than 180 species could be present in the soil samples studied. Sequencing of 119 cDNA identified genes with no homologues in databases (32%) and genes coding proteins involved in different biochemical and cellular processes. Surprisingly, the taxonomic distribution of the cDNA and of the 18S rDNA genes did not coincide, with a marked under-representation of the protists among the cDNA. Specific genes from such an environmental cDNA library could be isolated by expression in a heterologous microbial host, Saccharomyces cerevisiae. This is illustrated by the functional complementation of a histidine auxotrophic yeast mutant by two cDNA originating possibly from an ascomycete and a basidiomycete fungal species. Study of the metatranscriptome has the potential to uncover adaptations of whole microbial communities to local environmental conditions. It also gives access to an abundant source of genes of biotechnological interest.
Directory of Open Access Journals (Sweden)
Monika GARG
2012-08-01
Full Text Available In this paper, an integrated approach is proposed for non-recursive formulation of connection coefficients of different orthogonal functions in terms of a generic orthogonal function. The application of these coefficients arises when the product of two orthogonal basis functions are to be expressed in terms of single basis functions. Two significant advantages are achieved; one, the non-recursive formulations avoid memory and stack overflows in computer implementations; two, the integrated approach provides for digital hardware once-designed can be used for different functions. Computational savings achieved with the proposed non-recursive formulation vis-à-vis recursive formulation, reported in the literature so far, have been demonstrated using MATLAB PROFILER.
An editor for the maintenance and use of a bank of contracted Gaussian basis set functions
International Nuclear Information System (INIS)
Taurian, O.E.
1984-01-01
A bank of basis sets to be used in ab-initio calculations has been created. The bases are sets of contracted Gaussian type orbitals to be used as input to any molecular integral package. In this communication we shall describe the organization of the bank and a portable editor program which was designed for its maintenance and use. This program is operated by commands and it may be used to obtain any kind of information about the bases in the bank as well as to produce output to be directly used as input for different integral programs. The editor may also be used to format basis sets in the conventional way utilized in publications, as well as to generate a complete, or partial, manual of the contents of the bank if so desired. (orig.)
Basis for the safety approach for design and assessment of Generation IV nuclear systems
International Nuclear Information System (INIS)
Fiorini, G.L.; Leahy, T.
2009-01-01
The primary objective of the RSWG is the implementation of a harmonized approach on long-term safety, and to address risk and regulatory issues in development of the next generation of nuclear systems. To this end, the group is proposing safety goals and evaluation methodology applicable for the design and assessment of future systems. The paper resumes the content of the first RSWG report which provides insights for the safety approach and assists the GIF Systems Steering Committee as well as the GIF Experts Group and the GIF Policy Group for the definition of the most adequate safety related Gen IV R and D. The document is also an essential contributor to help identifying the needed supportive crosscut R and D effort (i.e. applicable to all the innovative nuclear technologies). Although the report presents a number of thoughts and recommendations, it really represents only the start of the efforts for the RSWG. (author)
New Approach to Conflicts within and between Belief Functions
Daniel, Milan
2009-01-01
This study deals with conflicts of belief functions. Internal conflicts of belief functions and conflicts between belief functions are described and analyzed here. Differences of belief functions are distinguished from conflicts between them. Three new different approaches to conflicts are presented: combinational, plausibility and comparative. The presented approaches to conflicts are compared to Liu's interpretation of conflicts.
Directory of Open Access Journals (Sweden)
Aset A. Bekhoeva
2017-03-01
Full Text Available The paper describes the experience of designing a program for developing professional teacher-training reflection and its practical approbation. The main trends of the study of professional teacher-training reflection in Russian psychological pedagogical science are described, the approaches to the description of methods and techniques that contribute to the development of professional teacher-training reflection in students are disclosed, and the conditions for its development are listed on the basis of literary data. Based on the review of the available research, it is necessary to search for a theoretical and methodological foundations for designing the development of professional teacher-training reflection in future teachers. The author proposes a reflexive activity approach. The program developed on the basis of this approach assumes a change in modeling classes on the main subjects of the psychological and pedagogical cycle, and on the other hand, the introduction of an innovative educational complex aimed at consolidating the competences received. The complex received the title of «Fundamentals of Personality-Oriented Learning». The paper describes the technology of modeling training sessions and the principles of building an educational complex. Approbation of the program was held on the basis of Khetagurov North Ossetian State University. The control and experimental group included third and fourth year university students (N= 342. A diagnostic tool was developed to assess the levels of reflection, reflexive abilities and self-esteem. Analysing experimental work has shown that the students of the experimental group have a significant increase in the level of each of the reflection components, which confirms the effectiveness of the proposed approach to the development of professional teacher-training reflection of future teachers.
Cost management as basis of harmonious approaches to the development of the construction business
Directory of Open Access Journals (Sweden)
Matveev Nikita Mikhaylovich
2016-11-01
Full Text Available The management of construction companies’ development is rarely aimed at harmonization of business and at the development of the ways of its sustainable development. Case studies and the application scope for harmonization as an approach allowing systematic and balanced development of business showed its practical relevance. The use of this approach allows not only correlating the objectives, clarifying the mission, structuring the problems, or determining the optimal salary of employees, but also correlating the costs to each other, which is particularly important in light of the need for rapid transformation of the building production methods. They are based on competent use of system properties of the systems. The properties of emergence, resonance, measurability, and others are of particular importance. Their accounting allows achieving the optimal cost outlay required in the process of investment and construction activities. It complies with the requirements and conditions of the market economy. The mentioned advantages of the use of harmonization technologies to ensure the stability and sustainability of investment and construction activities enable to confirm the hypothesis of the impossibility to achieve the optimum cost, for example, for the implementation of an investment and construction project without implementation of the system properties of a harmonious approach.
Estimasi Nilai Basis Pajak Bumi dan Bangunan di Kota Jambi: Pendekatan Hedonic Price Function
Directory of Open Access Journals (Sweden)
Arman Delis
2015-03-01
and buildings carried out with the hedonic price function approach. The data used is the cross-sectional data obtained from the results of a field survey of 100 owners of land and buildings are scattered in the subdistrict Telanaipura, Pelayangan, Pasar Jambi and Kota Baru subdistrict. The results showed that the level of the price of land and buildings in the district are highest and lowest Jambi Market in Subdsitrict Pelayangan. The most dominant variable that determines the level of the price of land is population density, distance to the city center location of the land and the type of road that passes through the location of the land, while the price level is determined by the building floor area of the house, the type of home and the availability of the garage wall. On average, the ratio of the price of land in the SPT to the actual price of the desired land owners and the price of each prediction is 29.30 percent and 44.13 percent, while the ratio of the price of houses for the price of the actual building and the price of the average prediction of 39.57 percent and 33.04 percent. The relatively low Figures of ratio indicates that the price of land and buildings are set by the government on the tax return in the calculation of taxable value mostly still too far away when compared with the price of land and building the desired owners and price prediction. This means that the potential increase in the Land and Property Tax in the city of Jambi is still very large. Keywords: actual price, desired price, prediction price
Approaches toward functional fluid supported lipid bilayers
Weng, Kevin Chun-I.
Planar supported lipid bilayers (PSLBs) have attracted immense interest for their properties as model cell membranes and for potential applications in biosensors and lab-on-a-chip devices. Our study covers three aspects of the construction, characterization, and application of functional PSLBs. First, a combination of micro-fabrication, the Langmuir-Blodgett (LB) technique, and fusion of extruded small unilamellar vesicle (E-SUVs) in sequence was used to create polymer-cushioned PSLBs in a microarray format. Random lipo-glycocopolymer mixed with L-alpha-phosphatidylcholine (egg PC) was compressed at the air-water interface and transferred onto the photoresist-patterned substrate by the LB technique to achieve spatially directed deposition. Construction of planar bilayers in an aqueous environment was subsequently completed by vesicle fusion. Epifluorescence microscopy, fluorescence recovery after photobleaching (FRAP), and electrophoresis-relaxation were employed to examine the resulting patterns as well as to verify the two-dimensional mobility of the supported membrane systems. This approach could possibly provide a useful route to create functional arrays of polymer-supported lipid bilayers. Second, we report the formation of fluid planar biomembranes on hydrophilic silica aerogels and xerogels. When the aerogel/xerogel was pre-hydrated and then allowed to incubate in egg PC E-SUV solution, lipid bilayers were formed due to the favorable interaction of vesicles with the hydroxyl-abundant silica surface. FRAP was used to determine the lateral diffusivity of membranes on aerogels. Quartz crystal microbalance with dissipation monitoring (QCM-D) was used to monitor the kinetics of the irreversible adsorption and fusion of vesicles into bilayers on xerogel thin films. Finally, we compared the formation of PSLBs with and without incorporation of monosialoganglioside GM1 (GM1) as the antigen for in situ antibody binding. Quantifiable differences were observed in the
Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis
Gluhih, I. N.; Akhmadulin, R. K.
2017-07-01
One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.
A hybrid radial basis function-pseudospectral method for thermal convection in a 3-D spherical shell
Wright, G. B.
2010-07-01
A novel hybrid spectral method that combines radial basis function (RBF) and Chebyshev pseudospectral methods in a "2 + 1" approach is presented for numerically simulating thermal convection in a 3-D spherical shell. This is the first study to apply RBFs to a full 3-D physical model in spherical geometry. In addition to being spectrally accurate, RBFs are not defined in terms of any surface-based coordinate system such as spherical coordinates. As a result, when used in the lateral directions, as in this study, they completely circumvent the pole issue with the further advantage that nodes can be "scattered" over the surface of a sphere. In the radial direction, Chebyshev polynomials are used, which are also spectrally accurate and provide the necessary clustering near the boundaries to resolve boundary layers. Applications of this new hybrid methodology are given to the problem of convection in the Earth\\'s mantle, which is modeled by a Boussinesq fluid at infinite Prandtl number. To see whether this numerical technique warrants further investigation, the study limits itself to an isoviscous mantle. Benchmark comparisons are presented with other currently used mantle convection codes for Rayleigh number (Ra) 7 × 10^{3} and 10^{5}. Results from a Ra = 10^{6} simulation are also given. The algorithmic simplicity of the code (mostly due to RBFs) allows it to be written in less than 400 lines of MATLAB and run on a single workstation. We find that our method is very competitive with those currently used in the literature. Copyright 2010 by the American Geophysical Union.
Whole-organ isolation approach as a basis for tissue-specific analyses in Schistosoma mansoni.
Directory of Open Access Journals (Sweden)
Steffen Hahnel
molecules that may represent potential targets for novel intervention strategies. Furthermore, gonads and other tissues are a basis for cell isolation, opening new perspectives for establishing cell lines, one of the tools desperately needed in the post-genomic era.
Neurophysiological basis of creativity in healthy elderly people: a multiscale entropy approach.
Ueno, Kanji; Takahashi, Tetsuya; Takahashi, Koichi; Mizukami, Kimiko; Tanaka, Yuji; Wada, Yuji
2015-03-01
Creativity, which presumably involves various connections within and across different neural networks, reportedly underpins the mental well-being of older adults. Multiscale entropy (MSE) can characterize the complexity inherent in EEG dynamics with multiple temporal scales. It can therefore provide useful insight into neural networks. Given that background, we sought to clarify the neurophysiological bases of creativity in healthy elderly subjects by assessing EEG complexity with MSE, with emphasis on assessment of neural networks. We recorded resting state EEG of 20 healthy elderly subjects. MSE was calculated for each subject for continuous 20-s epochs. Their relevance to individual creativity was examined concurrently with intellectual function. Higher individual creativity was linked closely to increased EEG complexity across higher temporal scales, but no significant relation was found with intellectual function (IQ score). Considering the general "loss of complexity" theory of aging, our finding of increased EEG complexity in elderly people with heightened creativity supports the idea that creativity is associated with activated neural networks. Results reported here underscore the potential usefulness of MSE analysis for characterizing the neurophysiological bases of elderly people with heightened creativity. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
V. M. Kornev
2016-01-01
Full Text Available The concept of Business Intelligence (BI is the most effective decision for optimization of processes of preparation of the analytical reporting in the growing companies now. The organization of access for end users and the analysis of the structured quantitative data on business is the cornerstone of the BI technology. Business Intelligence has a wide range of users at the enterprise, including heads, economists and analysts. In the conditions of the continuous growth of volumes of business the number of "small" reports grows, generating a set of the mistakes and divergences caused by the conflicts of interests of separate divisions. One of the advanced approaches of the solution of this problem is the concept of KPI allowing to define the purposes of the company in general and also its structural divisions on various periods, quickly to correct these purposes and to reconstruct system of the reporting as appropriate. One more important point in BI system – information delivery systems to the end user. They can be developed by own forces, however such approach in modern realities of narrow specialization is inefficient from the point of view of a ratio of expenses and quality of a product. In the software market there are some large producers of the Business Discovery appendices, for example – Qlik Tech and Tableau Software offering products by means of which it is possible to develop own system of visualization quickly enough. The cost of these products will pay off quickly enough as it is significantly lower than costs of own team of developers or of the appendices which are specially developed for this company. The expenses connected with support of the appendix in case of use of the Business Discovery platform will be also lower as for updating of the application one trained employee in staff suffices.
The lateral calcaneal artery: Anatomic basis for planning safe surgical approaches.
Elsaidy, Mohamed A; El-Shafey, Khaled
2009-10-01
The proximity of the lateral calcaneal artery (LCA) to surgical incisions applied to the lateral hindfoot makes it vulnerable to iatrogenic injury and subsequent postoperative skin necrosis. This study aimed to investigate the course of the LCA and to define anatomical points that can be used by surgeons during lateral approaches to the calcaneus. Thirteen leg-ankle-foot specimens were dissected and the superficial course of the LCA was outlined by three anatomic points: (a) tip of lateral malleolus, (b) the point where it pierces the deep fascia, and (c) the point where it crosses the line connecting the lateral malleolus with the insertion of Achilles tendon. Fifteen healthy volunteers were investigated by color Doppler ultrasound where the diameter and depth of LCA were measured. The LCA pierced the deep fascia at a maximum height of 4.5 cm (mean 3.78) above the midpoint of a line extending from the lateral malleolus to the insertion of Achilles tendon. It crossed the previous line at a maximum distance of 3 cm (mean 2.6) posterior to lateral malleolus. At this point, its mean diameter was 1.75 mm on the right and 1.73 mm on the left sides, while its mean depth was 7.73 mm on the right and 8.0 mm on the left sides. A dangerous triangle that contained the superficial course of the artery was mapped out in the lower lateral part of the leg. This triangle should be considered during surgical approaches applied to the lateral hindfoot to avoid damage of the LCA. (c) 2009 Wiley-Liss, Inc.
DEFF Research Database (Denmark)
Xu, Chunsheng; Zhang, Dongfeng; Tian, Xiaocao
2017-01-01
Although the correlation between cognition and physical function has been well studied in the general population, the genetic and environmental nature of the correlation has been rarely investigated. We conducted a classical twin analysis on cognitive and physical function, including forced...
Physiological and biochemical basis of clinical liver function tests: a review
Hoekstra, Lisette T.; de Graaf, Wilmar; Nibourg, Geert A. A.; Heger, Michal; Bennink, Roelof J.; Stieger, Bruno; van Gulik, Thomas M.
2013-01-01
To review the literature on the most clinically relevant and novel liver function tests used for the assessment of hepatic function before liver surgery. Postoperative liver failure is the major cause of mortality and morbidity after partial liver resection and develops as a result of insufficient
The functional basis of wing patterning in Heliconius butterflies: the molecules behind mimicry.
Kronforst, Marcus R; Papa, Riccardo
2015-05-01
Wing-pattern mimicry in butterflies has provided an important example of adaptation since Charles Darwin and Alfred Russell Wallace proposed evolution by natural selection >150 years ago. The neotropical butterfly genus Heliconius played a central role in the development of mimicry theory and has since been studied extensively in the context of ecology and population biology, behavior, and mimicry genetics. Heliconius species are notable for their diverse color patterns, and previous crossing experiments revealed that much of this variation is controlled by a small number of large-effect, Mendelian switch loci. Recent comparative analyses have shown that the same switch loci control wing-pattern diversity throughout the genus, and a number of these have now been positionally cloned. Using a combination of comparative genetic mapping, association tests, and gene expression analyses, variation in red wing patterning throughout Heliconius has been traced back to the action of the transcription factor optix. Similarly, the signaling ligand WntA has been shown to control variation in melanin patterning across Heliconius and other butterflies. Our understanding of the molecular basis of Heliconius mimicry is now providing important insights into a variety of additional evolutionary phenomena, including the origin of supergenes, the interplay between constraint and evolvability, the genetic basis of convergence, the potential for introgression to facilitate adaptation, the mechanisms of hybrid speciation in animals, and the process of ecological speciation. Copyright © 2015 by the Genetics Society of America.
The Functional Basis of Wing Patterning in Heliconius Butterflies: The Molecules Behind Mimicry
Kronforst, Marcus R.; Papa, Riccardo
2015-01-01
Wing-pattern mimicry in butterflies has provided an important example of adaptation since Charles Darwin and Alfred Russell Wallace proposed evolution by natural selection >150 years ago. The neotropical butterfly genus Heliconius played a central role in the development of mimicry theory and has since been studied extensively in the context of ecology and population biology, behavior, and mimicry genetics. Heliconius species are notable for their diverse color patterns, and previous crossing experiments revealed that much of this variation is controlled by a small number of large-effect, Mendelian switch loci. Recent comparative analyses have shown that the same switch loci control wing-pattern diversity throughout the genus, and a number of these have now been positionally cloned. Using a combination of comparative genetic mapping, association tests, and gene expression analyses, variation in red wing patterning throughout Heliconius has been traced back to the action of the transcription factor optix. Similarly, the signaling ligand WntA has been shown to control variation in melanin patterning across Heliconius and other butterflies. Our understanding of the molecular basis of Heliconius mimicry is now providing important insights into a variety of additional evolutionary phenomena, including the origin of supergenes, the interplay between constraint and evolvability, the genetic basis of convergence, the potential for introgression to facilitate adaptation, the mechanisms of hybrid speciation in animals, and the process of ecological speciation. PMID:25953905
Geuten, Koen; Irish, Vivian
2010-01-01
B-class MADS box genes specify petal and stamen identities in several core eudicot species. Members of the Solanaceae possess duplicate copies of these genes, allowing for diversification of function. To examine the changing roles of such duplicate orthologs, we assessed the functions of B-class genes in Nicotiana benthamiana and tomato (Solanum lycopersicum) using virus-induced gene silencing and RNA interference approaches. Loss of function of individual duplicates can have distinct phenotypes, yet complete loss of B-class gene function results in extreme homeotic transformations of petal and stamen identities. We also show that these duplicate gene products have qualitatively different protein–protein interaction capabilities and different regulatory roles. Thus, compensatory changes in B-class MADS box gene duplicate function have occurred in the Solanaceae, in that individual gene roles are distinct, but their combined functions are equivalent. Furthermore, we show that species-specific differences in the stamen regulatory network are associated with differences in the expression of the microRNA miR169. Whereas there is considerable plasticity in individual B-class MADS box transcription factor function, there is overall conservation in the roles of the multimeric MADS box B-class protein complexes, providing robustness in the specification of petal and stamen identities. Such hidden variability in gene function as we observe for individual B-class genes can provide a molecular basis for the evolution of regulatory functions that result in novel morphologies. PMID:20807882
Introducing Linear Functions: An Alternative Statistical Approach
Nolan, Caroline; Herbert, Sandra
2015-01-01
The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be "threshold concepts". There is recognition that linear functions can be taught in context through the exploration of linear…
Ferenczy, György G
2013-04-05
The application of the local basis equation (Ferenczy and Adams, J. Chem. Phys. 2009, 130, 134108) in mixed quantum mechanics/molecular mechanics (QM/MM) and quantum mechanics/quantum mechanics (QM/QM) methods is investigated. This equation is suitable to derive local basis nonorthogonal orbitals that minimize the energy of the system and it exhibits good convergence properties in a self-consistent field solution. These features make the equation appropriate to be used in mixed QM/MM and QM/QM methods to optimize orbitals in the field of frozen localized orbitals connecting the subsystems. Calculations performed for several properties in divers systems show that the method is robust with various choices of the frozen orbitals and frontier atom properties. With appropriate basis set assignment, it gives results equivalent with those of a related approach [G. G. Ferenczy previous paper in this issue] using the Huzinaga equation. Thus, the local basis equation can be used in mixed QM/MM methods with small size quantum subsystems to calculate properties in good agreement with reference Hartree-Fock-Roothaan results. It is shown that bond charges are not necessary when the local basis equation is applied, although they are required for the self-consistent field solution of the Huzinaga equation based method. Conversely, the deformation of the wave-function near to the boundary is observed without bond charges and this has a significant effect on deprotonation energies but a less pronounced effect when the total charge of the system is conserved. The local basis equation can also be used to define a two layer quantum system with nonorthogonal localized orbitals surrounding the central delocalized quantum subsystem. Copyright © 2013 Wiley Periodicals, Inc.
Krishnamurthy, Thiagarajan
2005-01-01
Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.
Development of a Technical Basis and Guidance for Advanced SMR Function Allocation
Energy Technology Data Exchange (ETDEWEB)
Jacques Hugo; David Gertman; Jeffrey Joe; Ronal Farris; April Whaley; Heather Medema
2013-09-01
This report presents the results from three key activities for FY13 that influence the definition of new concepts of operations for advanced Small Modular Reactors (AdvSMR: a) the development of a framework for the analysis of the functional environmental, and structural attributes, b) the effect that new technologies and operational concepts would have on the way functions are allocated to humans or machines or combinations of the two, and c) the relationship between new concepts of operations, new function allocations, and human performance requirements.
Development of Antiatherosclerotic Drugs on the basis of Natural Products Using Cell Model Approach
Directory of Open Access Journals (Sweden)
Alexander N. Orekhov
2015-01-01
Full Text Available Atherosclerosis including its subclinical form is one of the key medical and social problems. At present, there is no therapy available for widespread use against subclinical atherosclerosis. The use of synthetic drugs for the prevention of arteriosclerosis in its early stages is not sufficient because of the limited indications for severe side effects and high cost of treatment. Obviously, effective antiatherosclerotic drugs based on natural products would be a preferred alternative. Simple cell-based models for testing different natural products have been developed and the ability of natural products to prevent intracellular lipid accumulation in primary cell culture was evaluated. This approach utilizing cell models allowed to test effects of such direct antiatherosclerotic therapy, analyzing the effects mimicking those which can occur “at the level” of arterial wall via the inhibition of intracellular lipid deposition. The data from the carried out clinical trials support a point of view that the identification of antiatherosclerotic activity of natural products might offer a great opportunity for the prevention and treatment of atherosclerotic disease, reducing cardiovascular morbidity and mortality.
Innovative Development of Kazakhstan on The Basis of Triple Helix and Cluster Approach
Directory of Open Access Journals (Sweden)
Farkhat Musayevich Dnishev
2015-06-01
Full Text Available The aim of the research is to study the Triple Helix model feasibility in developing innovations and using cluster approach in Kazakhstan. There are possible points of the emergence of clusters in Kazakhstan. However, there are a lot of constraining factors. First of all, institutional and social factors: the culture of business, unfair competition, low trust of economic agents to each other and to power institutes, low psychological readiness for cooperation of the enterprises of various branches and regions, poor development of chambers of commerce, and industrial associations. For the time being, the majority of regions of Kazakhstan are characterized by a limited set of high technology industrial branches, and a sharp shortage of universities generating innovation and research institutes. The research results show that the open innovation model is realized in a limited scale that does not allow to export innovations into external markets, to participate in global technology chains and international research networks. At the same time, some interaction schemes and preconditions for the development of the Triple Helix model are emerging. However, in general, the innovation policy is not systemic; it does not unite actions in the sphere of science and technology, education, industry, and regional initiatives. As the result of the research, some policy implications are given. For the development of clusters in Kazakhstan, it is desirable to use such a way, as integration into global cluster networks. It is necessary to make use of foreign experience at which various specialized state agencies become participants of clusters. It is necessary to focus not only on science but also industry, which should play the central role in the innovation process.
International Nuclear Information System (INIS)
Caruso, Mark A.; Cheok, Michael C.; Cunningham, Mark A.; Holahan, Gary M.; King, Thomas L.; Parry, Gareth W.; Ramey-Smith, Ann M.; Rubin, Mark P.; Thadani, Ashok C.
1999-01-01
This paper discusses an acceptable approach that the US Nuclear Regulatory Commission staff has proposed for using Probabilistic Risk Assessment in making decisions on changes to the licensing basis of a nuclear power plant. First, the overall philosophy of risk-informed decision-making, and the process framework are described. The philosophy is encapsulated in five principles, one of which states that, if the proposed change leads to an increase in core damage frequency or risk, the increases must be small and consistent with the intent of the Nuclear Regulatory Commission's Safety Goal Policy Statement. The second part of the paper discusses the use of PRA to demonstrate that this principle has been met. The discussion focuses on the acceptance guidelines, and on comparison of the PRA results with those guidelines. The difficulties that arise because of limitations in scope and analytical uncertainties are discussed and approaches to accommodate these difficulties in the decision-making are described
Hybrid model decomposition of speech and noise in a radial basis function neural model framework
DEFF Research Database (Denmark)
Sørensen, Helge Bjarup Dissing; Hartmann, Uwe
1994-01-01
The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...
International Nuclear Information System (INIS)
R.J. Garrett
2002-01-01
As part of the internal Integrated Safety Management Assessment verification process, it was determined that there was a lack of documentation that summarizes the safety basis of the current Yucca Mountain Project (YMP) site characterization activities. It was noted that a safety basis would make it possible to establish a technically justifiable graded approach to the implementation of the requirements identified in the Standards/Requirements Identification Document. The Standards/Requirements Identification Documents commit a facility to compliance with specific requirements and, together with the hazard baseline documentation, provide a technical basis for ensuring that the public and workers are protected. This Safety Basis Report has been developed to establish and document the safety basis of the current site characterization activities, establish and document the hazard baseline, and provide the technical basis for identifying structures, systems, and components (SSCs) that perform functions necessary to protect the public, the worker, and the environment from hazards unique to the YMP site characterization activities. This technical basis for identifying SSCs serves as a grading process for the implementation of programs such as Conduct of Operations (DOE Order 5480.19) and the Suspect/Counterfeit Items Program. In addition, this report provides a consolidated summary of the hazards analyses processes developed to support the design, construction, and operation of the YMP site characterization facilities and, therefore, provides a tool for evaluating the safety impacts of changes to the design and operation of the YMP site characterization activities
Energy Technology Data Exchange (ETDEWEB)
R.J. Garrett
2002-01-14
As part of the internal Integrated Safety Management Assessment verification process, it was determined that there was a lack of documentation that summarizes the safety basis of the current Yucca Mountain Project (YMP) site characterization activities. It was noted that a safety basis would make it possible to establish a technically justifiable graded approach to the implementation of the requirements identified in the Standards/Requirements Identification Document. The Standards/Requirements Identification Documents commit a facility to compliance with specific requirements and, together with the hazard baseline documentation, provide a technical basis for ensuring that the public and workers are protected. This Safety Basis Report has been developed to establish and document the safety basis of the current site characterization activities, establish and document the hazard baseline, and provide the technical basis for identifying structures, systems, and components (SSCs) that perform functions necessary to protect the public, the worker, and the environment from hazards unique to the YMP site characterization activities. This technical basis for identifying SSCs serves as a grading process for the implementation of programs such as Conduct of Operations (DOE Order 5480.19) and the Suspect/Counterfeit Items Program. In addition, this report provides a consolidated summary of the hazards analyses processes developed to support the design, construction, and operation of the YMP site characterization facilities and, therefore, provides a tool for evaluating the safety impacts of changes to the design and operation of the YMP site characterization activities.
Directory of Open Access Journals (Sweden)
Paul Kussmaul
2008-04-01
Full Text Available In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for transposition, we are faced with a translation problem. In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for
Pirmoradi, Zhila; Haji Hajikolaei, Kambiz; Wang, G. Gary
2015-10-01
Product family design is cost-efficient for achieving the best trade-off between commonalization and diversification. However, for computationally intensive design functions which are viewed as black boxes, the family design would be challenging. A two-stage platform configuration method with generalized commonality is proposed for a scale-based family with unknown platform configuration. Unconventional sensitivity analysis and information on variation in the individual variants' optimal design are used for platform configuration design. Metamodelling is employed to provide the sensitivity and variable correlation information, leading to significant savings in function calls. A family of universal electric motors is designed for product performance and the efficiency of this method is studied. The impact of the employed parameters is also analysed. Then, the proposed method is modified for obtaining higher commonality. The proposed method is shown to yield design solutions with better objective function values, allowable performance loss and higher commonality than the previously developed methods in the literature.
Pupil filter design by using a Bessel functions basis at the image plane.
Canales, Vidal F; Cagigal, Manuel P
2006-10-30
Many applications can benefit from the use of pupil filters for controlling the light intensity distribution near the focus of an optical system. Most of the design methods for such filters are based on a second-order expansion of the Point Spread Function (PSF). Here, we present a new procedure for designing radially-symmetric pupil filters. It is more precise than previous procedures as it considers the exact expression of the PSF, expanded as a function of first-order Bessel functions. Furthermore, this new method presents other advantages: the height of the side lobes can be easily controlled, it allows the design of amplitude-only, phase-only or hybrid filters, and the coefficients of the PSF expansion can be directly related to filter parameters. Finally, our procedure allows the design of filters with very different behaviours and optimal performance.
Cammi, Roberto
2013-01-01
This Brief presents the main aspects of the response functions theory (RFT) for molecular solutes described within the framework of the Polarizable Continuum Model (PCM). PCM is a solvation model for a Quantum Mechanical molecular system in which the solvent is represented as a continuum distribution of matter. Particular attention is devoted to the description of the basic features of the PCM model, and to the problems characterizing the study of the response function theory for molecules in solution with respect to the analogous theory on isolated molecules.
Bilocal functional approach to dynamical symmetry breaking
International Nuclear Information System (INIS)
Ebert, D.; Pervushin, V.N.
1977-01-01
The Abelian gauge theory of massless fermions (''quarks'') interacting with a massless neutral vector (''gluon'') field is considered. The Green two-particle functions of the quarks and vector gluons are computed. The graphical expression of the bilocal propagator and that of different terms in the expansion of path integrals for these functions are given
Modeling of the Gross Regional Product on the Basis of Production Functions
Sadovin, Nikolay S.; Kokotkina, Tatiana N.; Barkalova, Tatiana G.; Tsaregorodsev, Evgeny I.
2016-01-01
The article is devoted to elaboration and construction of a static model of macroeconomics in which economics is considered as an unstructured holistic unit, the input of which receives the resources, and the output is the result of the functioning of economics in the form of gross domestic product or gross regional product. Resources are…
MISMATCH: A basis for semi-automatic functional mixed-signal test-pattern generation
Kerkhoff, Hans G.; Tangelder, R.J.W.T.; Speek, Han; Engin, N.
1996-01-01
This paper describes a tool which assists the designer in the rapid generation of functional tests for mixed-signal circuits down to the actual test-signals for the tester. The tool is based on manipulating design data, making use of macro-based test libraries and tester resources provided by the
International Nuclear Information System (INIS)
Keppler, Jan Horst; Meunier, William; Coquentin, Alexandre
2017-01-01
Interconnections for cross-border electricity flows are at the heart of the project to create a common European electricity market. At the time, increase in production from variable renewables clustered during a limited numbers of hours reduces the availability of existing transport infrastructures. This calls for higher levels of optimal interconnection capacity than in the past. In complement to existing scenario-building exercises such as the TYNDP that respond to the challenge of determining optimal levels of infrastructure provision, the present paper proposes a new empirically-based methodology to perform Cost-Benefit analysis for the determination of optimal interconnection capacity, using as an example the French-German cross-border trade. Using a very fine dataset of hourly supply and demand curves (aggregated auction curves) for the year 2014 from the EPEX Spot market, it constructs linearized net export (NEC) and net import demand curves (NIDC) for both countries. This allows assessing hour by hour the welfare impacts for incremental increases in interconnection capacity. Summing these welfare increases over the 8 760 hours of the year, this provides the annual total for each step increase of interconnection capacity. Confronting welfare benefits with the annual cost of augmenting interconnection capacity indicated the socially optimal increase in interconnection capacity between France and Germany on the basis of empirical market micro-data. (authors)
Specific neural basis of Chinese idioms processing: an event-related functional MRI study
International Nuclear Information System (INIS)
Chen Shaoqi; Zhang Yanzhen; Xiao Zhuangwei; Zhang Xuexin
2007-01-01
Objective: To address the neural basis of Chinese idioms processing with different kinds of stimuli using an event-related fMRI design. Methods: Sixteen native Chinese speakers were asked to perform a semantic decision task during fMRI scanning. Three kinds of stimuli were used: Real idioms (Real-idiom condition); Literally plausible phrases (Pseudo-idiom condition, the last character of a real idiom was replaced by a character with similar meaning); Literally implausible strings (Non-idiom condition, the last character of a real idiom was replaced by a character with unrelated meaning). Reaction time and correct rate were recorded at the same time. Results: The error rate was 2.6%, 5.2% and 0.9% (F=3.51, P 0.05) for real idioms, pseudo-idioms and wrong idioms, respectively. Similar neural network was activated in all of the three conditions. However, the right hippocampus was only activated in the real idiom condition, and significant activations were found in anterior portion of left inferior frontal gyms (BA47) in real-and pseudo-idiom conditions, but not in non-idiom condition. Conclusion: The right hippocampus plays a specific role in the particular wording of the Chinese idioms. And the left anterior inferior frontal gyms (BA47) may be engaged in the semantic processing of Chinese idioms. The results support the notion that there were specific neural bases for Chinese idioms processing. (authors)
Directory of Open Access Journals (Sweden)
Lisa Schindler
2018-05-01
Full Text Available Macrophage migration inhibitory factor (MIF is a chemokine-like protein and an important mediator in the inflammatory response. Unlike most other pro-inflammatory cytokines, a number of cell types constitutively express MIF and secretion occurs from preformed stores. MIF is an evolutionarily conserved protein that shows a remarkable functional diversity, including specific binding to surface CD74 and chemokine receptors and the presence of two intrinsic tautomerase and oxidoreductase activities. Several studies have shown that MIF is subject to post-translational modification, particularly redox-dependent modification of the catalytic proline and cysteine residues. In this review, we summarize and discuss MIF post-translational modifications and their effects on the biological properties of this protein. We propose that the redox-sensitive residues in MIF will be modified at sites of inflammation and that this will add further depth to the functional diversity of this intriguing cytokine.
Multiconfigurational Green's function approaches in quantum chemistry
International Nuclear Information System (INIS)
Yeager, D.L.
1984-01-01
The author discusses multiconfigurational Green's function techniques and generalizations. In particular he is interested in developing and applying these techniques for isolated atoms and small molecules. Furthermore, he develops formalisms that are fairly clear, accurate, and capable of being applied to open-shell and highly-correlated systems as well as to closed-shell systems with little electronic correlation. The two kinds of Green's functions that this article discusses are the single-particle Green's function and the retarded two-time Green's function in the energy representation. The poles of the former give the ionization potentials and electron affinities while the poles of the latter give the excitation energies. The multiconfigurational approximations are known as the multiconfigurational electron propagator (MCEP) and the multiconfigurational time-dependent Hartree-Fock (MCTDHF) (also known as the multiconfigurational random phase approximation (MCRPA) or the multiconfigurational linear response), respectively. 44 references
DEFF Research Database (Denmark)
Skulason, Egill; Tripkovic, Vladimir; Björketun, Mårten
2010-01-01
Density functional theory calculations have been performed for the three elementary steps―Tafel, Heyrovsky, and Volmer―involved in the hydrogen oxidation reaction (HOR) and its reverse, the hydrogen evolution reaction (HER). For the Pt(111) surface a detailed model consisting of a negatively...... charged Pt(111) slab and solvated protons in up to three water bilayers is considered and reaction energies and activation barriers are determined by using a newly developed computational scheme where the potential can be kept constant during a charge transfer reaction. We determine the rate limiting...
International Nuclear Information System (INIS)
Oda, Ryuichi; Ishida, Shin; Wada, Hiroaki; Yamada, Kenji; Sekiguchi, Motoo
1999-01-01
We examine mass spectra and wave functions of the nn-bar, cc-bar and bb-bar meson systems within the framework of the covariant oscillator quark model with the boosted LS-coupling scheme. We solve nonperturbatively an eigenvalue problem for the squared-mass operator, which incorporates the four-dimensional color-Coulomb-type interaction, by taking a set of covariant oscillator wave functions as an expansion basis. We obtain mass spectra of these meson systems, which reproduce quite well their experimental behavior. The resultant manifestly covariant wave functions, which are applicable to analyses of various reaction phenomena, are given. Our results seem to suggest that the present model may be considered effectively as a covariant version of the nonrelativistic linear-plus-Coulomb potential quark model. (author)
Structure-Functional Basis of Ion Transport in Sodium–Calcium Exchanger (NCX Proteins
Directory of Open Access Journals (Sweden)
Moshe Giladi
2016-11-01
Full Text Available The membrane-bound sodium–calcium exchanger (NCX proteins shape Ca2+ homeostasis in many cell types, thus participating in a wide range of physiological and pathological processes. Determination of the crystal structure of an archaeal NCX (NCX_Mj paved the way for a thorough and systematic investigation of ion transport mechanisms in NCX proteins. Here, we review the data gathered from the X-ray crystallography, molecular dynamics simulations, hydrogen–deuterium exchange mass-spectrometry (HDX-MS, and ion-flux analyses of mutants. Strikingly, the apo NCX_Mj protein exhibits characteristic patterns in the local backbone dynamics at particular helix segments, thereby possessing characteristic HDX profiles, suggesting structure-dynamic preorganization (geometric arrangements of catalytic residues before the transition state of conserved α1 and α2 repeats at ion-coordinating residues involved in transport activities. Moreover, dynamic preorganization of local structural entities in the apo protein predefines the status of ion-occlusion and transition states, even though Na+ or Ca2+ binding modifies the preceding backbone dynamics nearby functionally important residues. Future challenges include resolving the structural-dynamic determinants governing the ion selectivity, functional asymmetry and ion-induced alternating access. Taking into account the structural similarities of NCX_Mj with the other proteins belonging to the Ca2+/cation exchanger superfamily, the recent findings can significantly improve our understanding of ion transport mechanisms in NCX and similar proteins.
The functional and structural neural basis of individual differences in loss aversion.
Canessa, Nicola; Crespi, Chiara; Motterlini, Matteo; Baud-Bovy, Gabriel; Chierchia, Gabriele; Pantaleo, Giuseppe; Tettamanti, Marco; Cappa, Stefano F
2013-09-04
Decision making under risk entails the anticipation of prospective outcomes, typically leading to the greater sensitivity to losses than gains known as loss aversion. Previous studies on the neural bases of choice-outcome anticipation and loss aversion provided inconsistent results, showing either bidirectional mesolimbic responses of activation for gains and deactivation for losses, or a specific amygdala involvement in processing losses. Here we focused on loss aversion with the aim to address interindividual differences in the neural bases of choice-outcome anticipation. Fifty-six healthy human participants accepted or rejected 104 mixed gambles offering equal (50%) chances of gaining or losing different amounts of money while their brain activity was measured with functional magnetic resonance imaging (fMRI). We report both bidirectional and gain/loss-specific responses while evaluating risky gambles, with amygdala and posterior insula specifically tracking the magnitude of potential losses. At the individual level, loss aversion was reflected both in limbic fMRI responses and in gray matter volume in a structural amygdala-thalamus-striatum network, in which the volume of the "output" centromedial amygdala nuclei mediating avoidance behavior was negatively correlated with monetary performance. We conclude that outcome anticipation and ensuing loss aversion involve multiple neural systems, showing functional and structural individual variability directly related to the actual financial outcomes of choices. By supporting the simultaneous involvement of both appetitive and aversive processing in economic decision making, these results contribute to the interpretation of existing inconsistencies on the neural bases of anticipating choice outcomes.
Integral equations of hadronic correlation functions a functional- bootstrap approach
Manesis, E K
1974-01-01
A reasonable 'microscopic' foundation of the Feynman hadron-liquid analogy is offered, based on a class of models for hadron production. In an external field formalism, the equivalence (complementarity) of the exclusive and inclusive descriptions of hadronic reactions is specifically expressed in a functional-bootstrap form, and integral equations between inclusive and exclusive correlation functions are derived. Using the latest CERN-ISR data on the two-pion inclusive correlation function, and assuming rapidity translational invariance for the exclusive one, the simplest integral equation is solved in the 'central region' and an exclusive correlation length in rapidity predicted. An explanation is also offered for the unexpected similarity observed between pi /sup +/ pi /sup -/ and pi /sup -/ pi /sup -/ inclusive correlations. (31 refs).
Functional renormalization group approach to neutron matter
Directory of Open Access Journals (Sweden)
Matthias Drews
2014-11-01
Full Text Available The chiral nucleon-meson model, previously applied to systems with equal number of neutrons and protons, is extended to asymmetric nuclear matter. Fluctuations are included in the framework of the functional renormalization group. The equation of state for pure neutron matter is studied and compared to recent advanced many-body calculations. The chiral condensate in neutron matter is computed as a function of baryon density. It is found that, once fluctuations are incorporated, the chiral restoration transition for pure neutron matter is shifted to high densities, much beyond three times the density of normal nuclear matter.
Energy Technology Data Exchange (ETDEWEB)
Biplab Dey, Michael E. McCracken, David G. Ireland, Curtis A. Meyer
2011-05-01
The complete expression for the intensity in pseudo-scalar meson photoproduction with a polarized beam, target, and recoil baryon is derived using a density matrix approach that offers great economy of notation. A Cartesian basis with spins for all particles quantized along a single direction, the longitudinal beam direction, is used for consistency and clarity in interpretation. A single spin-quantization axis for all particles enables the amplitudes to be written in a manifestly covariant fashion with simple relations to those of the well-known CGLN formalism. Possible sign discrepancies between theoretical amplitude-level expressions and experimentally measurable intensity profiles are dealt with carefully. Our motivation is to provide a coherent framework for coupled-channel partial-wave analysis of several meson photoproduction reactions, incorporating recently published and forthcoming polarization data from Jefferson Lab.
International Nuclear Information System (INIS)
2013-01-01
This Workshop had a strategic focus on identifying and clarifying long-term issues and objectives related to our collective responsibilities to ensure that both existing nuclear facilities and future new build projects properly address life-cycle management of plant design basis knowledge (i.e. from design to decommissioning). The workshop attempted to bring together key stakeholders and build a better collective understanding, recognizing that very different perspectives exist and there are a wide range of national contexts and approaches. The various issues and challenges related to this topic and facing the nuclear energy sector both today and in the long-term were discussed in a senior management context and at strategic level
Nanocomposites based on thermoplastic elastomers with functional basis of nano titanium dioxide
Energy Technology Data Exchange (ETDEWEB)
Yulovskaya, V. D.; Kuz’micheva, G. M., E-mail: galina-kuzmicheva@list.ru [Federal State Budget Educational Institution of Higher Education “Moscow Technological University” (Russian Federation); Klechkovskaya, V. V. [Russian Academy of Sciences, Shubnikov Institute of Crystallography (Russian Federation); Orekhov, A. S.; Zubavichus, Ya. V. [National Research Centre “Kurchatov Institute” (Russian Federation); Domoroshchina, E. N.; Shegay, A. V. [Federal State Budget Educational Institution of Higher Education “Moscow Technological University” (Russian Federation)
2016-03-15
Nanocomposites based on a thermoplastic elastomer (TPE) (low-density polyethylene (LDPE) and 1,2-polybutadiene in a ratio of 60/40) with functional titanium dioxide nanoparticles of different nature, TiO{sub 2}/TPE, have been prepared and investigated by a complex of methods (X-ray diffraction analysis using X-ray and synchrotron radiation beams, scanning electron microscopy, transmission electron microscopy, and X-ray energy-dispersive spectroscopy). The morphology of the composites is found to be somewhat different, depending on the TiO{sub 2} characteristics. It is revealed that nanocomposites with cellular or porous structures containing nano-TiO{sub 2} aggregates with a large specific surface and large sizes of crystallites and nanoparticles exhibit the best deformation‒strength and fatigue properties and stability to the effect of active media under conditions of ozone and vapor‒air aging.
An estimating function approach to linkage heterogeneity
Indian Academy of Sciences (India)
X chromosome. Science 230, 753–758. Fujii Y. 1994 On homogeneity test using estimating function. Bull. Informat. Cybern. 26, 101–107. Grice D. E., Halmi K. A., Fichter M. M., Strober M., Woodside. D. B., Treasure J. T. et al. 2002 Evidence for a susceptibility gene for anorexia nervosa on chromosome 1. Am. J. Hum. Genet.
Neural basis of functional fixedness during creative idea generation: an EEG study.
Camarda, Anaëlle; Salvia, Émilie; Vidal, Julie; Weil, Benoit; Poirel, Nicolas; Houdé, Olivier; Borst, Grégoire; Cassotti, Mathieu
2018-03-09
Decades of problem solving and creativity research have converged to show that the ability to generate new and useful ideas can be blocked or impeded by intuitive biases leading to mental fixations. The present study aimed at investigating the neural bases of the processes involved in overcoming fixation effects during creative idea generation. Using the AU task adapted for EEG recording, we examined whether participant's ability to provide original ideas was related to alpha power changes in both the frontal and temporo-parietal regions. Critically, for half of the presented objects, the classical use of the object was primed orally, and a picture of the classical use was presented visually to increase functional fixedness (Fixation Priming condition). For the other half, only the name of the object and a picture of the object was provided to the participants (control condition). As expected, priming the classical use of an object before the generation of creative alternative uses of the object impeded participants' performances in terms of remoteness. In the control condition, while the frontal alpha synchronization was maintained across all successive time windows in participants with high remoteness scores, the frontal alpha synchronization decreased in participants with low remoteness scores. In the Fixation Priming condition, in which functional fixedness was maximal, both participants with high and low remoteness scores maintained frontal alpha synchronization throughout the period preceding their answer. Whereas participants with high remoteness scores maintained alpha synchronization in the temporo-parietal regions throughout the creative idea generation period, participants with low remoteness scores displayed alpha desynchronization in the same regions during this period. We speculate that individuals with high remoteness scores might generate more creative ideas than individuals with low remoteness scores because they rely more on internal semantic
Arosh, J A; Banu, S K; Chapdelaine, P; Madore, E; Sirois, J; Fortier, M A
2004-05-01
The corpus luteum (CL) is a transient ovarian endocrine gland formed from the ovulated follicle. Progesterone is the primary secretory product of CL and is essential for establishment of pregnancy in mammals. In the cyclic female, the life span of CL is characterized by luteal development, maintenance, and regression regulated by complex interactions between luteotrophic and luteolytic mediators. It is universally accepted that prostaglandin (PG) F(2a) is the luteolysin whereas PGE(2) is considered as a luteotropin in most mammals. New emerging concepts emphasize the autocrine and paracrine actions of luteal PGs in CL function. However, there is no report on selective biosynthesis and cellular transport of luteal PGE(2) and PGF(2alpha) in the CL of any species. We have studied the expression of enzymes involved in the metabolism of PGE(2) and PGF(2alpha), cyclooxygenase (COX)-1 and -2, PGE and F synthases, PG 15-dehydrogenase, and PG transporter as well as receptors (EP2, EP3, and FP) throughout the CL life span using a bovine model. COX-1, PGF synthase, and PG 15-dehydrogenase are expressed at constant levels whereas COX-2, PGE synthase, PG transporter, EP2, EP3, and FP are highly modulated during different phases of the CL life span. The PG components are preferentially expressed in large luteal cells. The results indicate that PGE(2) biosynthesis, transport, and signaling cascades are selectively activated during luteal maintenance. By contrast the PGF(2alpha) system is activated during luteal regression. Collectively, our results suggest an integrated role for luteal PGE(2) and PGF(2alpha) in autoregulation of CL function.
Seghouane, Abd-Krim; Iqbal, Asif
2017-09-01
Sequential dictionary learning algorithms have been successfully applied to functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are, however, structured data matrices with the notions of temporal smoothness in the column direction. This prior information, which can be converted into a constraint of smoothness on the learned dictionary atoms, has seldomly been included in classical dictionary learning algorithms when applied to fMRI data analysis. In this paper, we tackle this problem by proposing two new sequential dictionary learning algorithms dedicated to fMRI data analysis by accounting for this prior information. These algorithms differ from the existing ones in their dictionary update stage. The steps of this stage are derived as a variant of the power method for computing the SVD. The proposed algorithms generate regularized dictionary atoms via the solution of a left regularized rank-one matrix approximation problem where temporal smoothness is enforced via regularization through basis expansion and sparse basis expansion in the dictionary update stage. Applications on synthetic data experiments and real fMRI data sets illustrating the performance of the proposed algorithms are provided.
Functional RG approach to the Potts model
Ben Alì Zinati, Riccardo; Codello, Alessandro
2018-01-01
The critical behavior of the (n+1) -states Potts model in d-dimensions is studied with functional renormalization group techniques. We devise a general method to derive β-functions for continuous values of d and n and we write the flow equation for the effective potential (LPA’) when instead n is fixed. We calculate several critical exponents, which are found to be in good agreement with Monte Carlo simulations and ɛ-expansion results available in the literature. In particular, we focus on Percolation (n\\to0) and Spanning Forest (n\\to-1) which are the only non-trivial universality classes in d = 4,5 and where our methods converge faster.
Energy Technology Data Exchange (ETDEWEB)
Radaj, D.; Flade, D. [Daimler-Benz AG, Stuttgart (Germany). Forschung und Technik; Sonsino, C.M. [Fraunhofer-Inst. fuer Betriebsfestigkeit LBF, Darmstadt (Germany)
1997-12-31
Welded multiple pipe joints are particularly crucial component parts of offshore drilling platforms. Compared to the drilling platforms in the Carribean Sea, such structures in the North Sea are subject to much stronger wave forces amd thus higher stresses affecting fatigue life. The paper discusses the applicability of the notch stress and notch strain impact approach for assessment of the fatigue strength of those complex pipe welds, which represent hot spots of marine structures. The major aspect examined is the applicability of available approaches for assessment, rather than a new method of assessment. The examination presented here refers to the variants of the notch stress impact approach elaborated by Lawrence, Radaj, Seeger, and Sonsino, and to modifications of the notch strain impact approach published by Lawrence, Seeger, and Sonsino, focusing on notch strain impacts. (orig./CB) [Deutsch] Geschweisste Rohrknoten sind ein besonders wichtiges Bauteil von Erdoelbohrinseln in den Weltmeeren. Eine Besonderheit der Bauwerke in der Nordsee gegenueber den Vorgaengern in der Karibik ist die staerkere Beanspruchung auf Ermuedung durch den Wellengang. In diesem Beitrag wird der Frage nach der Anwendbarkeit des Kerbspannungs- und Kerbdehnungskonzepts zur Beurteilung der Betriebsfestigkeit des Rohrknotens, der als Beispiel fuer eine komplexe Schweisskonstruktion steht, nachgegangen. Es geht um die Darstellung und Klaerung von Fragen der Konzeptanwendung, nicht um eine Neubewertung des als Beispiel gewaehlten Rohrknotens. Das Kerbspannungskonzept liegt in Versionen nach Lawrence, Radaj, Seeger und Sonsino vor, das Kerbdehnungskonzept in Versionen nach Lawrence, Seeger und Sonsino. Die Betrachtung konzentriert sich auf die Anwendung des Kerbdehnungskonzepts. (orig./MM)
Directory of Open Access Journals (Sweden)
Lars H. Wegner
2017-03-01
Full Text Available Current concepts of plant membrane transport are based on the assumption that water and solutes move across membranes via separate pathways. According to this view, coupling between the fluxes is more or less exclusively constituted via the osmotic force that solutes exert on water transport. This view is questioned here, and experimental evidence for a cotransport of water and solutes is reviewed. The overview starts with ion channels that provide pathways for both ion and water transport, as exemplified for maxi K+ channels from cytoplasmic droplets of Chara corallina. Aquaporins are usually considered to be selective for water (just allowing for slippage of some other small, neutral molecules. Recently, however, a “dual function” aquaporin has been characterized from Arabidopsis thaliana (AtPIP2.1 that translocates water and at the same time conducts cations, preferentially Na+. By analogy with mammalian physiology, other candidates for solute-water flux coupling are cation-chloride cotransporters of the CCC type, and transporters of sugars and amino acids. The last part is dedicated to possible physiological functions that could rely on solute-water cotransport. Among these are the generation of root pressure, refilling of embolized xylem vessels, fast turgor-driven movements of leaves, cell elongation (growth, osmoregulation and adjustment of buoyancy in marine algae. This review will hopefully initiate further research in the field.
The Structural Basis for Tight Control of PP2A Methylation and Function by LCMT-1
Energy Technology Data Exchange (ETDEWEB)
V Stanevich; L Jiang; K Satyshur; Y Li; P Jeffrey; Z Li; P Menden; M Semmelhack; Y Xing
2011-12-31
Proper formation of protein phosphatase 2A (PP2A) holoenzymes is essential for the fitness of all eukaryotic cells. Carboxyl methylation of the PP2A catalytic subunit plays a critical role in regulating holoenzyme assembly; methylation is catalyzed by PP2A-specific methyltransferase LCMT-1, an enzyme required for cell survival. We determined crystal structures of human LCMT-1 in isolation and in complex with PP2A stabilized by a cofactor mimic. The structures show that the LCMT-1 active-site pocket recognizes the carboxyl terminus of PP2A, and, interestingly, the PP2A active site makes extensive contacts to LCMT-1. We demonstrated that activation of the PP2A active site stimulates methylation, suggesting a mechanism for efficient conversion of activated PP2A into substrate-specific holoenzymes, thus minimizing unregulated phosphatase activity or formation of inactive holoenzymes. A dominant-negative LCMT-1 mutant attenuates the cell cycle without causing cell death, likely by inhibiting uncontrolled phosphatase activity. Our studies suggested mechanisms of LCMT-1 in tight control of PP2A function, important for the cell cycle and cell survival.
The Structural Basis for Tight Control of PP2A Methylation and Function by LCMT-1
Energy Technology Data Exchange (ETDEWEB)
Stanevich, Vitali; Jiang, Li; Satyshur, Kenneth A.; Li, Yongfeng; Jeffrey, Philip D.; Li, Zhu; Menden, Patrick; Semmelhack, Martin F.; Xing, Yongna (UW); (Princeton); (UQ); (Signum)
2012-05-29
Proper formation of protein phosphatase 2A (PP2A) holoenzymes is essential for the fitness of all eukaryotic cells. Carboxyl methylation of the PP2A catalytic subunit plays a critical role in regulating holoenzyme assembly; methylation is catalyzed by PP2A-specific methyltransferase LCMT-1, an enzyme required for cell survival. We determined crystal structures of human LCMT-1 in isolation and in complex with PP2A stabilized by a cofactor mimic. The structures show that the LCMT-1 active-site pocket recognizes the carboxyl terminus of PP2A, and, interestingly, the PP2A active site makes extensive contacts to LCMT-1. We demonstrated that activation of the PP2A active site stimulates methylation, suggesting a mechanism for efficient conversion of activated PP2A into substrate-specific holoenzymes, thus minimizing unregulated phosphatase activity or formation of inactive holoenzymes. A dominant-negative LCMT-1 mutant attenuates the cell cycle without causing cell death, likely by inhibiting uncontrolled phosphatase activity. Our studies suggested mechanisms of LCMT-1 in tight control of PP2A function, important for the cell cycle and cell survival.
Shek, Roger; Dattmore, Devon A; Stives, Devin P; Jackson, Ashley L; Chatfield, Christa H; Hicks, Katherine A; French, Jarrod B
2017-12-26
Campylobacter jejuni is the most common bacterial cause of gastroenteritis and a major contributor to infant mortality in the developing world. The increasing incidence of antibiotic-resistant C. jejuni only adds to the urgency to develop effective therapies. Because of the essential role that polyamines play, particularly in protection from oxidative stress, enzymes involved in the biosynthesis of these metabolites are emerging as promising antibiotic targets. The recent description of an alternative pathway for polyamine synthesis, distinct from that in human cells, in C. jejuni suggests this pathway could be a target for novel therapies. To that end, we determined X-ray crystal structures of C. jejuni agmatine deiminase (CjADI) and demonstrated that loss of CjADI function contributes to antibiotic sensitivity, likely because of polyamine starvation. The structures provide details of key molecular features of the active site of this protein. Comparison of the unliganded structure (2.1 Å resolution) to that of the CjADI-agmatine complex (2.5 Å) reveals significant structural rearrangements that occur upon substrate binding. The shift of two helical regions of the protein and a large conformational change in a loop near the active site generate a narrow binding pocket around the bound substrate. This change optimally positions the substrate for catalysis. In addition, kinetic analysis of this enzyme demonstrates that CjADI is an iminohydrolase that effectively deiminates agmatine. Our data suggest that C. jejuni agmatine deiminase is a potentially important target for combatting antibiotic resistance, and these results provide a valuable framework for guiding future drug development.
The conceptual basis of mathematics in cardiology: (I) algebra, functions and graphs.
Bates, Jason H T; Sobel, Burton E
2003-02-01
This is the first in a series of four articles developed for the readers of. Without language ideas cannot be articulated. What may not be so immediately obvious is that they cannot be formulated either. One of the essential languages of cardiology is mathematics. Unfortunately, medical education does not emphasize, and in fact, often neglects empowering physicians to think mathematically. Reference to statistics, conditional probability, multicompartmental modeling, algebra, calculus and transforms is common but often without provision of genuine conceptual understanding. At the University of Vermont College of Medicine, Professor Bates developed a course designed to address these deficiencies. The course covered mathematical principles pertinent to clinical cardiovascular and pulmonary medicine and research. It focused on fundamental concepts to facilitate formulation and grasp of ideas. This series of four articles was developed to make the material available for a wider audience. The articles will be published sequentially in Coronary Artery Disease. Beginning with fundamental axioms and basic algebraic manipulations they address algebra, function and graph theory, real and complex numbers, calculus and differential equations, mathematical modeling, linear system theory and integral transforms and statistical theory. The principles and concepts they address provide the foundation needed for in-depth study of any of these topics. Perhaps of even more importance, they should empower cardiologists and cardiovascular researchers to utilize the language of mathematics in assessing the phenomena of immediate pertinence to diagnosis, pathophysiology and therapeutics. The presentations are interposed with queries (by Coronary Artery Disease, abbreviated as CAD) simulating the nature of interactions that occurred during the course itself. Each article concludes with one or more examples illustrating application of the concepts covered to cardiovascular medicine and
The electron-propagator approach to conceptual density-functional ...
Indian Academy of Sciences (India)
Unknown
(4), the external potential is fixed by identity of the molecular system and is thus treated as a parameter and not a variable. Equation (4) is an exact expres- sion for the ...... the virtual spin-orbitals, and {χp} is a set of ortho- normal basis functions. The expression for the third- order correction is more complicated. Because the.
Functional Problems of the Visually Impaired: A Research Approach.
Bikson, Thomas H.; Bikson, Tora K.
Capabilities and limitations of 251 severely visually impaired persons (senior high school age or older) were assessed on a range of visual environmental adaptation problems to learn how they are organized and influenced. Factor analyses indicated that problems can be grouped on the basis of eight functional domains, among which an independent…
A Constructive Sharp Approach to Functional Quantization of Stochastic Processes
Junglen, Stefan; Luschgy, Harald
2010-01-01
We present a constructive approach to the functional quantization problem of stochastic processes, with an emphasis on Gaussian processes. The approach is constructive, since we reduce the infinite-dimensional functional quantization problem to a finite-dimensional quantization problem that can be solved numerically. Our approach achieves the sharp rate of the minimal quantization error and can be used to quantize the path space for Gaussian processes and also, for example, Lévy processes.
Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario
2018-04-01
Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.
Kuwahara, Riichi; Tadokoro, Yoichi; Ohno, Kaoru
2014-08-28
In this paper, we calculate kinetic and potential energy contributions to the electronic ground-state total energy of several isolated atoms (He, Be, Ne, Mg, Ar, and Ca) by using the local density approximation (LDA) in density functional theory, the Hartree-Fock approximation (HFA), and the self-consistent GW approximation (GWA). To this end, we have implemented self-consistent HFA and GWA routines in our all-electron mixed basis code, TOMBO. We confirm that virial theorem is fairly well satisfied in all of these approximations, although the resulting eigenvalue of the highest occupied molecular orbital level, i.e., the negative of the ionization potential, is in excellent agreement only in the case of the GWA. We find that the wave function of the lowest unoccupied molecular orbital level of noble gas atoms is a resonating virtual bound state, and that of the GWA spreads wider than that of the LDA and thinner than that of the HFA.
Energy Technology Data Exchange (ETDEWEB)
Kwak, Jeong Keun [KHNP, Ulsan (Korea, Republic of)
2016-10-15
In nuclear history, before Chernobyl Accident, Three Mile Island (TMI) Accident was the severest accident. For this reason, to resolve the disclosed or potential possibilities of nuclear accident, more than one hundred countermeasures were proposed by United States Nuclear Regulatory Commission (USNRC). Among various recommendations by USNRC, one suggestion was related to training aspect. It was Systematic Approach to Training (SAT) and this event was the initiation of SAT methodology in the world. In Korea, upcoming June 2017, Kori Unit-1 NPP is scheduled to be shut down and it will experience NPP decommissioning for the first time. Present study aims to establish concrete training foundation for NPP decommissioning engineers based on Systematic Approach to Training (SAT) methodology, in particular, Task to Training Matrix (TTM). The objective of this paper is to organize TTM on the basis of SAT for NPP decommissioning engineer. For this reason, eighteen tasks are yielded through Job and Task Analysis (JTA) process. After that, for the settlement of Task to Training Matrix (TTM), various data are determined such as element, condition, standard, knowledge and skill, learning objective and training setting. When it comes to training in nuclear industry, SAT methodology has been the unwavering principle in Korea since NPPs export to UAE.
International Nuclear Information System (INIS)
Vrankar, L.; Turk, G.; Runovc, F.; Kansa, E.J.
2006-01-01
Many heat-transfer problems involve a change of phase of material due to solidification or melting. Applications include: the safety studies of nuclear reactors (molten core concrete interaction), the drilling of high ice-content soil, the storage of thermal energy, etc. These problems are often called Stefan's or moving boundary value problems. Mathematically, the interface motion is expressed implicitly in an equation for the conservation of thermal energy at the interface (Stefan's conditions). This introduces a non-linear character to the system which treats each problem somewhat uniquely. The exact solution of phase change problems is limited exclusively to the cases in which e.g. the heat transfer regions are infinite or semi-infinite one dimensional-space. Therefore, solution is obtained either by approximate analytical solution or by numerical methods. Finite-difference methods and finite-element techniques have been used extensively for numerical solution of moving boundary problems. Recently, the numerical methods have focused on the idea of using a mesh-free methodology for the numerical solution of partial differential equations based on radial basis functions. In our case we will study solid-solid transformation. The numerical solutions will be compared with analytical solutions. Actually, in our work we will examine usefulness of radial basis functions (especially multiquadric-MQ) for one-dimensional Stefan's problems. The position of the moving boundary will be simulated by moving grid method. The resultant system of RBF-PDE will be solved by affine space decomposition. (author)
A New Approach for Predicting the Variance of Random Decrement Functions
DEFF Research Database (Denmark)
Asmussen, J. C.; Brincker, Rune
mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...
A New Approach for Predicting the Variance of Random Decrement Functions
DEFF Research Database (Denmark)
Asmussen, J. C.; Brincker, Rune
1998-01-01
mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...
Liang, Xia; Zou, Qihong; He, Yong; Yang, Yihong
2013-01-29
Human brain functional networks contain a few densely connected hubs that play a vital role in transferring information across regions during resting and task states. However, the relationship of these functional hubs to measures of brain physiology, such as regional cerebral blood flow (rCBF), remains incompletely understood. Here, we used functional MRI data of blood-oxygenation-level-dependent and arterial-spin-labeling perfusion contrasts to investigate the relationship between functional connectivity strength (FCS) and rCBF during resting and an N-back working-memory task. During resting state, functional brain hubs with higher FCS were identified, primarily in the default-mode, insula, and visual regions. The FCS showed a striking spatial correlation with rCBF, and the correlation was stronger in the default-mode network (DMN; including medial frontal-parietal cortices) and executive control network (ECN; including lateral frontal-parietal cortices) compared with visual and sensorimotor networks. Moreover, the relationship was connection-distance dependent; i.e., rCBF correlated stronger with long-range hubs than short-range ones. It is notable that several DMN and ECN regions exhibited higher rCBF per unit connectivity strength (rCBF/FCS ratio); whereas, this index was lower in posterior visual areas. During the working-memory experiment, both FCS-rCBF coupling and rCBF/FCS ratio were modulated by task load in the ECN and/or DMN regions. Finally, task-induced changes of FCS and rCBF in the lateral-parietal lobe positively correlated with behavioral performance. Together, our results indicate a tight coupling between blood supply and brain functional topology during rest and its modulation in response to task demands, which may shed light on the physiological basis of human brain functional connectome.
Directory of Open Access Journals (Sweden)
Azam Farmani
2014-07-01
Full Text Available Objectives: The aim of the present study is to examine the prediction of the reminiscence functions in older adults on the basis of the five personality factor model. Methods & Materials: 242 elderly adults older than 60 were recruited from retirement clubs of the city of Shiraz via available sampling method. The participants completed the Reminiscence Functions Scale and Goldberg's International Personality Item Pool. Forty participants were deleted from the sample because they did not complete the questionnaires fully. All the participants took part in the study with their conscious consent. To conduct the necessary descriptive and inferential statistical operations, SPSS (Version 16 was used. Mean, standard deviation and Pearson correlation coefficient were utilized to analyze the data in the descriptive statistics section, And in inferential statistics section, simultaneous multiple regression was used to predict reminiscence functions. Results: According to the results of the multiple regression analysis, Neuroticism predicted the reminiscence functions of Bitterness Revival (β=0.28, P≤0.001 and Intimacy Maintenance (β=0.25, P≤0.001 and Extraversion predicted the reminiscence functions of Teach/Inform (β=0.18, P<0.05. Conclusion: The results indicated that people with higher levels of psychological distress tend to rehash and ruminate on bitter memories and hold onto memories of intimate social relations who are no longer part of their lives. Moreover, extravert people tend to share memories to transmit a lesson of life and share personal ideologies and experiences. Clinicians should focus on more adaptive functions of reminiscence (e.g., identity, problem solving and teach/inform and teach such functions.
Toward Intelligent Hemodynamic Monitoring: A Functional Approach
Directory of Open Access Journals (Sweden)
Pierre Squara
2012-01-01
Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?
A probabilistic approach to delineating functional brain regions
DEFF Research Database (Denmark)
Kalbitzer, Jan; Svarer, Claus; Frokjaer, Vibe G
2009-01-01
The purpose of this study was to develop a reliable observer-independent approach to delineating volumes of interest (VOIs) for functional brain regions that are not identifiable on structural MR images. The case is made for the raphe nuclei, a collection of nuclei situated in the brain stem known......-independent, reliable approach to delineating regions that can be identified only by functional imaging, here exemplified by the raphe nuclei. This approach can be used in future studies to create functional VOI maps based on neuroreceptor fingerprints retrieved through in vivo brain imaging Udgivelsesdato: 2009/6...
Oberhofer, Harald; Blumberger, Jochen
2010-12-28
We present a plane wave basis set implementation for the calculation of electronic coupling matrix elements of electron transfer reactions within the framework of constrained density functional theory (CDFT). Following the work of Wu and Van Voorhis [J. Chem. Phys. 125, 164105 (2006)], the diabatic wavefunctions are approximated by the Kohn-Sham determinants obtained from CDFT calculations, and the coupling matrix element calculated by an efficient integration scheme. Our results for intermolecular electron transfer in small systems agree very well with high-level ab initio calculations based on generalized Mulliken-Hush theory, and with previous local basis set CDFT calculations. The effect of thermal fluctuations on the coupling matrix element is demonstrated for intramolecular electron transfer in the tetrathiafulvalene-diquinone (Q-TTF-Q(-)) anion. Sampling the electronic coupling along density functional based molecular dynamics trajectories, we find that thermal fluctuations, in particular the slow bending motion of the molecule, can lead to changes in the instantaneous electron transfer rate by more than an order of magnitude. The thermal average, ()(1/2)=6.7 mH, is significantly higher than the value obtained for the minimum energy structure, |H(ab)|=3.8 mH. While CDFT in combination with generalized gradient approximation (GGA) functionals describes the intermolecular electron transfer in the studied systems well, exact exchange is required for Q-TTF-Q(-) in order to obtain coupling matrix elements in agreement with experiment (3.9 mH). The implementation presented opens up the possibility to compute electronic coupling matrix elements for extended systems where donor, acceptor, and the environment are treated at the quantum mechanical (QM) level.
Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario
2018-04-01
This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.
CSIR Research Space (South Africa)
Lysko, AA
2008-07-01
Full Text Available and integration by parts expressions, as well as to give an estimate for the maximum error due to the developed combined approach. To enhance performance, the recursive properties found in the expressions have been utilized and the resulting algorithm... implemented in Matlab [12]. Comparison with the output from a commercial program WIPL-D [10] has shown high efficiency of this algorithm. 2 Derivations 2.1. The Function Under Consideration Computing the far field from the polynomial- approximated...
Painter, K J; Hunt, G S; Wells, K L; Johansson, J A; Headon, D J
2012-08-06
In his seminal 1952 paper, 'The Chemical Basis of Morphogenesis', Alan Turing lays down a milestone in the application of theoretical approaches to understand complex biological processes. His deceptively simple demonstration that a system of reacting and diffusing chemicals could, under certain conditions, generate spatial patterning out of homogeneity provided an elegant solution to the problem of how one of nature's most intricate events occurs: the emergence of structure and form in the developing embryo. The molecular revolution that has taken place during the six decades following this landmark publication has now placed this generation of theoreticians and biologists in an excellent position to rigorously test the theory and, encouragingly, a number of systems have emerged that appear to conform to some of Turing's fundamental ideas. In this paper, we describe the history and more recent integration between experiment and theory in one of the key models for understanding pattern formation: the emergence of feathers and hair in the skins of birds and mammals.
DEFF Research Database (Denmark)
Vairetti, G.; van Waterschoot, T.; Moonen, M.
2014-01-01
include knowledge about the room resonances as a set of poles, which appear nonlinearly in the structure. A novel algorithm is pro-posed, that avoids this nonlinear problem by iteratively estimating the poles and building the model. Some of the properties of OBF models, such as orthogonality and linearity......Orthonormal Basis Function (OBF) models are used to define stable fixed-poles infinite impulse response filter structures that allow to incorporate knowledge about the resonant characteristics of a stable, causal and linear system. In the approximation of a room impulse response, OBF models can......-in-the-parameters, are exploited and the final model has the favorable property of being scalable. The OBF model provides a longer response than the all-zero model and is particularly suited in approximating the early response and the predominant resonances for relatively small model orders....
Shankar, Varun; Wright, Grady B; Kirby, Robert M; Fogelson, Aaron L
2016-06-01
In this paper, we present a method based on Radial Basis Function (RBF)-generated Finite Differences (FD) for numerically solving diffusion and reaction-diffusion equations (PDEs) on closed surfaces embedded in ℝ d . Our method uses a method-of-lines formulation, in which surface derivatives that appear in the PDEs are approximated locally using RBF interpolation. The method requires only scattered nodes representing the surface and normal vectors at those scattered nodes. All computations use only extrinsic coordinates, thereby avoiding coordinate distortions and singularities. We also present an optimization procedure that allows for the stabilization of the discrete differential operators generated by our RBF-FD method by selecting shape parameters for each stencil that correspond to a global target condition number. We show the convergence of our method on two surfaces for different stencil sizes, and present applications to nonlinear PDEs simulated both on implicit/parametric surfaces and more general surfaces represented by point clouds.
Piret, Cécile
2012-05-01
Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper, we investigate methods to solve PDEs on arbitrary stationary surfaces embedded in . R3 using the RBF method. We present three RBF-based methods that easily discretize surface differential operators. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent the most complex geometries in any dimension. Two out of the three methods, which we call the orthogonal gradients (OGr) methods are the result of our work and are hereby presented for the first time. © 2012 Elsevier Inc.
DEFF Research Database (Denmark)
Lee, Kyo-Beum; Blaabjerg, Frede
2005-01-01
A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The speed estimation scheme in most servo drive systems for low speed operation is sensitive to the variation of machine parameter, especially the moment of inertia....... To estimate the motor inertia value, the observer using the Radial Basis Function Network (RBFN) is applied. A control law for stabilizing the system and adaptive laws for updating both of the weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable...... in the sense of Lyapunov. The effectiveness of the proposed inertia estimation is verified by simulations and experiments. It is concluded that the speed control performance in low speed region is improved with the proposed disturbance observer using RBFN....
Directory of Open Access Journals (Sweden)
Meina Li
2016-09-01
Full Text Available Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR and movement index (MI monitoring. The embedded incremental network includes linear regression (LR and RBFNN based on context-based fuzzy c-means (CFCM clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.
Chen, Qian; Liu, Guohai; Xu, Dezhi; Xu, Liang; Xu, Gaohong; Aamir, Nazir
2018-05-01
This paper proposes a new decoupled control for a five-phase in-wheel fault-tolerant permanent magnet (IW-FTPM) motor drive, in which radial basis function neural network inverse (RBF-NNI) and internal model control (IMC) are combined. The RBF-NNI system is introduced into original system to construct a pseudo-linear system, and IMC is used as a robust controller. Hence, the newly proposed control system incorporates the merits of the IMC and RBF-NNI methods. In order to verify the proposed strategy, an IW-FTPM motor drive is designed based on dSPACE real-time control platform. Then, the experimental results are offered to verify that the d-axis current and the rotor speed are successfully decoupled. Besides, the proposed motor drive exhibits strong robustness even under load torque disturbance.
Vavalle, Nicholas A; Schoell, Samantha L; Weaver, Ashley A; Stitzel, Joel D; Gayzik, F Scott
2014-11-01
Human body finite element models (FEMs) are a valuable tool in the study of injury biomechanics. However, the traditional model development process can be time-consuming. Scaling and morphing an existing FEM is an attractive alternative for generating morphologically distinct models for further study. The objective of this work is to use a radial basis function to morph the Global Human Body Models Consortium (GHBMC) average male model (M50) to the body habitus of a 95th percentile male (M95) and to perform validation tests on the resulting model. The GHBMC M50 model (v. 4.3) was created using anthropometric and imaging data from a living subject representing a 50th percentile male. A similar dataset was collected from a 95th percentile male (22,067 total images) and was used in the morphing process. Homologous landmarks on the reference (M50) and target (M95) geometries, with the existing FE node locations (M50 model), were inputs to the morphing algorithm. The radial basis function was applied to morph the FE model. The model represented a mass of 103.3 kg and contained 2.2 million elements with 1.3 million nodes. Simulations of the M95 in seven loading scenarios were presented ranging from a chest pendulum impact to a lateral sled test. The morphed model matched anthropometric data to within a rootmean square difference of 4.4% while maintaining element quality commensurate to the M50 model and matching other anatomical ranges and targets. The simulation validation data matched experimental data well in most cases.
Defining mental disorder. Exploring the 'natural function' approach
Directory of Open Access Journals (Sweden)
Varga Somogy
2011-01-01
Full Text Available Abstract Due to several socio-political factors, to many psychiatrists only a strictly objective definition of mental disorder, free of value components, seems really acceptable. In this paper, I will explore a variant of such an objectivist approach to defining metal disorder, natural function objectivism. Proponents of this approach make recourse to the notion of natural function in order to reach a value-free definition of mental disorder. The exploration of Christopher Boorse's 'biostatistical' account of natural function (1 will be followed an investigation of the 'hybrid naturalism' approach to natural functions by Jerome Wakefield (2. In the third part, I will explore two proposals that call into question the whole attempt to define mental disorder (3. I will conclude that while 'natural function objectivism' accounts fail to provide the backdrop for a reliable definition of mental disorder, there is no compelling reason to conclude that a definition cannot be achieved.
Defining mental disorder. Exploring the 'natural function' approach.
Varga, Somogy
2011-01-21
Due to several socio-political factors, to many psychiatrists only a strictly objective definition of mental disorder, free of value components, seems really acceptable. In this paper, I will explore a variant of such an objectivist approach to defining metal disorder, natural function objectivism. Proponents of this approach make recourse to the notion of natural function in order to reach a value-free definition of mental disorder. The exploration of Christopher Boorse's 'biostatistical' account of natural function (1) will be followed an investigation of the 'hybrid naturalism' approach to natural functions by Jerome Wakefield (2). In the third part, I will explore two proposals that call into question the whole attempt to define mental disorder (3). I will conclude that while 'natural function objectivism' accounts fail to provide the backdrop for a reliable definition of mental disorder, there is no compelling reason to conclude that a definition cannot be achieved.
Configuration interaction wave functions: A seniority number approach
Energy Technology Data Exchange (ETDEWEB)
Alcoba, Diego R. [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Universitaria, 1428 Buenos Aires (Argentina); Torre, Alicia; Lain, Luis, E-mail: qfplapel@lg.ehu.es [Departamento de Química Física, Facultad de Ciencia y Tecnología, Universidad del País Vasco, Apdo. 644, E-48080 Bilbao (Spain); Massaccesi, Gustavo E. [Departamento de Ciencias Exactas, Ciclo Básico Común, Universidad de Buenos Aires, Ciudad Universitaria, 1428 Buenos Aires (Argentina); Oña, Ofelia B. [Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas, Universidad Nacional de La Plata, CCT La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Diag. 113 y 64 (S/N), Sucursal 4, CC 16, 1900 La Plata (Argentina)
2014-06-21
This work deals with the configuration interaction method when an N-electron Hamiltonian is projected on Slater determinants which are classified according to their seniority number values. We study the spin features of the wave functions and the size of the matrices required to formulate states of any spin symmetry within this treatment. Correlation energies associated with the wave functions arising from the seniority-based configuration interaction procedure are determined for three types of molecular orbital basis: canonical molecular orbitals, natural orbitals, and the orbitals resulting from minimizing the expectation value of the N-electron seniority number operator. The performance of these bases is analyzed by means of numerical results obtained from selected N-electron systems of several spin symmetries. The comparison of the results highlights the efficiency of the molecular orbital basis which minimizes the mean value of the seniority number for a state, yielding energy values closer to those provided by the full configuration interaction procedure.
Configuration interaction wave functions: A seniority number approach
International Nuclear Information System (INIS)
Alcoba, Diego R.; Torre, Alicia; Lain, Luis; Massaccesi, Gustavo E.; Oña, Ofelia B.
2014-01-01
This work deals with the configuration interaction method when an N-electron Hamiltonian is projected on Slater determinants which are classified according to their seniority number values. We study the spin features of the wave functions and the size of the matrices required to formulate states of any spin symmetry within this treatment. Correlation energies associated with the wave functions arising from the seniority-based configuration interaction procedure are determined for three types of molecular orbital basis: canonical molecular orbitals, natural orbitals, and the orbitals resulting from minimizing the expectation value of the N-electron seniority number operator. The performance of these bases is analyzed by means of numerical results obtained from selected N-electron systems of several spin symmetries. The comparison of the results highlights the efficiency of the molecular orbital basis which minimizes the mean value of the seniority number for a state, yielding energy values closer to those provided by the full configuration interaction procedure
A Functional Approach to the Choice between Descriptive ...
African Journals Online (AJOL)
Different types of prescription, description and proscription are discussed with specific reference to their potential use in dictionaries with text reception and text production as functions. Preferred approaches for the different functions are indicated. It is shown how an optimal use of a prescriptive, descriptive or proscriptive ...
Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli
2013-03-01
Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.
Ortigue, S; Bianchi-Demicheli, F; Hamilton, A F de C; Grafton, S T
2007-07-01
Throughout the ages, love has been defined as a motivated and goal-directed mechanism with explicit and implicit mechanisms. Recent evidence demonstrated that the explicit representation of love recruits subcorticocortical pathways mediating reward, emotion, and motivation systems. However, the neural basis of the implicit (unconscious) representation of love remains unknown. To assess this question, we combined event-related functional magnetic resonance imaging (fMRI) with a behavioral subliminal priming paradigm embedded in a lexical decision task. In this task, the name of either a beloved partner, a neutral friend, or a passionate hobby was subliminally presented before a target stimulus (word, nonword, or blank), and participants were required to decide if the target was a word or not. Behavioral results showed that subliminal presentation of either a beloved's name (love prime) or a passion descriptor (passion prime) enhanced reaction times in a similar fashion. Subliminal presentation of a friend's name (friend prime) did not show any beneficial effects. Functional results showed that subliminal priming with a beloved's name (as opposed to either a friend's name or a passion descriptor) specifically recruited brain areas involved in abstract representations of others and the self, in addition to motivation circuits shared with other sources of passion. More precisely, love primes recruited the fusiform and angular gyri. Our findings suggest that love, as a subliminal prime, involves a specific neural network that surpasses a dopaminergic-motivation system.
Two-body Schrödinger wave functions in a plane-wave basis via separation of dimensions
Jerke, Jonathan; Poirier, Bill
2018-03-01
Using a combination of ideas, the ground and several excited electronic states of the helium atom and the hydrogen molecule are computed to chemical accuracy—i.e., to within 1-2 mhartree or better. The basic strategy is very different from the standard electronic structure approach in that the full two-electron six-dimensional (6D) problem is tackled directly, rather than starting from a single-electron Hartree-Fock approximation. Electron correlation is thus treated exactly, even though computational requirements remain modest. The method also allows for exact wave functions to be computed, as well as energy levels. From the full-dimensional 6D wave functions computed here, radial distribution functions and radial correlation functions are extracted—as well as a 2D probability density function exhibiting antisymmetry for a single Cartesian component. These calculations support a more recent interpretation of Hund's rule, which states that the lower energy of the higher spin-multiplicity states is actually due to reduced screening, rather than reduced electron-electron repulsion. Prospects for larger systems and/or electron dynamics applications appear promising.
International Nuclear Information System (INIS)
Lee, Jae Sung; Nam, Hyun Woo; Lee, Dong Soo; Lee, Sang Kun; Jang, Myoung Jin; Ahn, Ji Young; Park, Kwang Suk; Chung, June Key; Lee, Myung Chul
2000-01-01
Episodic memory is described as an 'autobiographical' memory responsible for storing a record of the events in our lives. We performed functional brain activation study using H 2 1 5O PET to reveal the neural basis of the encoding and the retrieval of episodic memory in human normal volunteers. Four repeated H 2 1 5O PET scans with two reference and two activation tasks were performed on 6 normal volunteers to activate brain areas engaged in encoding and retrieval with verbal materials. Images from the same subject were spatially registered and normalized using linear and nonlinear transformation. Using the means and variances for every condition which were adjusted with analysis of covariance, t-statistic analysis were performed voxel-wise. Encoding of episodic memory activated the opercular and triangular parts of left inferior frontal gyrus, right prefrontal cortex, medial frontal area, cingulate gyrus, posterior middle and inferior temporal gyri, and cerebellum, and both primary visual and visual association areas. Retrieval of episodic memory activated the triangular part of left inferior frontal gyrus and inferior temporal gyrus, right prefrontal cortex and medial temporal ares, and both cerebellum and primary visual and visual association areas. The activations in the opercular part of left inferior frontal gyrus and the right prefrontal cortex meant the essential role of these areas in the encoding and retrieval of episodic memeory. We could localize the neural basis of the encoding and retrieval of episodic memory using H 2 1 5O PET, which was partly consistent with the hypothesis of hemispheric encoding/retrieval asymmetry.=20
Energy Technology Data Exchange (ETDEWEB)
Witte, Jonathon [Department of Chemistry, University of California, Berkeley, California 94720 (United States); Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Neaton, Jeffrey B. [Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States); Department of Physics, University of California, Berkeley, California 94720 (United States); Kavli Energy Nanosciences Institute at Berkeley, Berkeley, California 94720 (United States); Head-Gordon, Martin, E-mail: mhg@cchem.berkeley.edu [Department of Chemistry, University of California, Berkeley, California 94720 (United States); Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States)
2016-05-21
With the aim of systematically characterizing the convergence of common families of basis sets such that general recommendations for basis sets can be made, we have tested a wide variety of basis sets against complete-basis binding energies across the S22 set of intermolecular interactions—noncovalent interactions of small and medium-sized molecules consisting of first- and second-row atoms—with three distinct density functional approximations: SPW92, a form of local-density approximation; B3LYP, a global hybrid generalized gradient approximation; and B97M-V, a meta-generalized gradient approximation with nonlocal correlation. We have found that it is remarkably difficult to reach the basis set limit; for the methods and systems examined, the most complete basis is Jensen’s pc-4. The Dunning correlation-consistent sequence of basis sets converges slowly relative to the Jensen sequence. The Karlsruhe basis sets are quite cost effective, particularly when a correction for basis set superposition error is applied: counterpoise-corrected def2-SVPD binding energies are better than corresponding energies computed in comparably sized Dunning and Jensen bases, and on par with uncorrected results in basis sets 3-4 times larger. These trends are exhibited regardless of the level of density functional approximation employed. A sense of the magnitude of the intrinsic incompleteness error of each basis set not only provides a foundation for guiding basis set choice in future studies but also facilitates quantitative comparison of existing studies on similar types of systems.
Zhang, Chuan-Biao; Ming, Li; Xin, Zhou
2015-12-01
Ensemble simulations, which use multiple short independent trajectories from dispersive initial conformations, rather than a single long trajectory as used in traditional simulations, are expected to sample complex systems such as biomolecules much more efficiently. The re-weighted ensemble dynamics (RED) is designed to combine these short trajectories to reconstruct the global equilibrium distribution. In the RED, a number of conformational functions, named as basis functions, are applied to relate these trajectories to each other, then a detailed-balance-based linear equation is built, whose solution provides the weights of these trajectories in equilibrium distribution. Thus, the sufficient and efficient selection of basis functions is critical to the practical application of RED. Here, we review and present a few possible ways to generally construct basis functions for applying the RED in complex molecular systems. Especially, for systems with less priori knowledge, we could generally use the root mean squared deviation (RMSD) among conformations to split the whole conformational space into a set of cells, then use the RMSD-based-cell functions as basis functions. We demonstrate the application of the RED in typical systems, including a two-dimensional toy model, the lattice Potts model, and a short peptide system. The results indicate that the RED with the constructions of basis functions not only more efficiently sample the complex systems, but also provide a general way to understand the metastable structure of conformational space. Project supported by the National Natural Science Foundation of China (Grant No. 11175250).
Sánchez-Sesma, Francisco J.
2017-07-01
Microtremor H/ V spectral ratio (MHVSR) has gained popularity to assess the dominant frequency of soil sites. It requires measurement of ground motion due to seismic ambient noise at a site and a relatively simple processing. Theory asserts that the ensemble average of the autocorrelation of motion components belonging to a diffuse field at a given receiver gives the directional energy densities (DEDs) which are proportional to the imaginary parts of the Green's function components when both source and receiver are the same point and the directions of force and response coincide. Therefore, the MHVSR can be modeled as the square root of 2 × Im G 11/Im G 33, where Im G 11 and Im G 33 are the imaginary parts of Green's functions at the load point for the horizontal (sub-index 1) and vertical (sub-index 3) components, respectively. This connection has physical implications that emerge from the duality DED force and allows understanding the behavior of the MHVSR. For a given model, the imaginary parts of the Green's functions are integrals along a radial wavenumber. To deal with these integrals, we have used either the popular discrete wavenumber method or the Cauchy's residue theorem at the poles that account for surface waves normal modes giving the contributions due to Rayleigh and Love waves. For the retrieval of the velocity structure, one can minimize the weighted differences between observations and calculated values using the strategy of an inversion scheme. In this research, we used simulated annealing but other optimization techniques can be used as well. This last approach allows computing separately the contributions of different wave types. An example is presented for the mouth of Andarax River at Almería, Spain. [Figure not available: see fulltext.
Barka, André; Picard, Clément
2008-03-01
In this paper, we discuss several improvements of a substructuring Domain Decomposition Method (DDM) devoted to Electromagnetic computations, based on the Boundary Element Method (BEM) and the Finite Element Method (FEM). This computation procedure is applied to the analysis of antenna performance on board vehicles as well as Radar Cross Section (RCS). The benefits of the subdomain Computational Electromagnetic Method are mainly the ability to deal with collaborative studies involving several companies, and the reduction of the computation costs by one or more orders of magnitude, especially in the context of parametric studies. Furthermore, this paper proposes a Spectral Basis Function (SBF) defined on fictitious surfaces surrounding equipment, to deal with both the computation of antenna far field patterns and RCS in a multi-domain mode. By masking the complexity of the equipment (wires, thin surfaces, materials, supply network, weapons) the external domain of the vehicle can be closed so that the Combined Field Integral Equation (CFIE) can be used, which is better conditioned than the Electric Field Integral Equation (EFIE). This calculation procedure leads to a faster convergence when using iterative Multi Level Fast Multiple Algorithms (MLFMA). The accuracy and efficiency of this technique is assessed by performing the computation of the diffraction and radiation of several test-objects in a multi-domain way cross compared with reference integral equation results.
Smith, Christopher P; Thorsness, Peter E
2008-07-01
AAC2 is one of three paralogs encoding mitochondrial ADP/ATP carriers in the yeast Saccharomyces cerevisiae, and because it is required for respiratory growth it has been the most extensively studied. To comparatively examine the relative functionality of Aac1, Aac2, and Aac3 in vivo, the gene encoding each isoform was expressed from the native AAC2 locus in aac1Delta aac3Delta yeast. Compared to Aac2, Aac1 exhibited reduced capacity to support growth of yeast lacking mitochondrial DNA or of yeast lacking the ATP/Mg-P(i) carrier, both conditions requiring ATP import into the mitochondrial matrix through the ADP/ATP carrier. Sixteen AAC1/AAC2 chimeric genes were constructed and analyzed to determine the key differences between residues or sections of Aac1 and Aac2. On the basis of the growth rate differences of yeast expressing different chimeras, the C1 and M2 loops of the ADP/ATP carriers contain divergent residues that are responsible for the difference(s) between Aac1 and Aac2. One chimeric gene construct supported growth on nonfermentable carbon sources but failed to support growth of yeast lacking mitochondrial DNA. We identified nine independent intragenic mutations in this chimeric gene that suppressed the growth phenotype of yeast lacking mitochondrial DNA, identifying regions of the carrier important for nucleotide exchange activities.
Directory of Open Access Journals (Sweden)
Deliang Yu
2017-01-01
Full Text Available This paper presents a new method to diagnose oil well pump faults using a modified radial basis function neural network. With the development of submersible linear motor technology, rodless pumping units have been widely used in oil exploration. However, the ground indicator diagram method cannot be used to diagnose the working conditions of rodless pumping units because it is based on the load change of the polished rod suspension point and its displacement. To solve this problem, this paper presents a new method that is applicable to rodless oil pumps. The advantage of this new method is its use of a simple feature extraction method and advanced genetic algorithm to optimize the threshold and weight of the RBF neural network. In this paper, we extract the characteristic value from the operation parameters of the submersible linear motor and oil wellhead as the input vector of the fault diagnosis model. Through experimental analysis, the proposed method is proven to have good convergence performance, high accuracy, and high reliability.
Directory of Open Access Journals (Sweden)
Seng-Chi Chen
2014-01-01
Full Text Available Studies on active magnetic bearing (AMB systems are increasing in popularity and practical applications. Magnetic bearings cause less noise, friction, and vibration than the conventional mechanical bearings; however, the control of AMB systems requires further investigation. The magnetic force has a highly nonlinear relation to the control current and the air gap. This paper proposes an intelligent control method for positioning an AMB system that uses a neural fuzzy controller (NFC. The mathematical model of an AMB system comprises identification followed by collection of information from this system. A fuzzy logic controller (FLC, the parameters of which are adjusted using a radial basis function neural network (RBFNN, is applied to the unbalanced vibration in an AMB system. The AMB system exhibited a satisfactory control performance, with low overshoot, and produced improved transient and steady-state responses under various operating conditions. The NFC has been verified on a prototype AMB system. The proposed controller can be feasibly applied to AMB systems exposed to various external disturbances; demonstrating the effectiveness of the NFC with self-learning and self-improving capacities is proven.
International Nuclear Information System (INIS)
Vaziri, Nima; Hojabri, Alireza; Erfani, Ali; Monsefi, Mehrdad; Nilforooshan, Behnam
2007-01-01
Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported
Schmidt, J.; Piret, C.; Zhang, N.; Kadlec, B. J.; Liu, Y.; Yuen, D. A.; Wright, G. B.; Sevre, E. O.
2008-12-01
The faster growth curves in the speed of GPUs relative to CPUs in recent years and its rapidly gained popularity has spawned a new area of development in computational technology. There is much potential in utilizing GPUs for solving evolutionary partial differential equations and producing the attendant visualization. We are concerned with modeling tsunami waves, where computational time is of extreme essence, for broadcasting warnings. In order to test the efficacy of the GPU on the set of shallow-water equations, we employed the NVIDIA board 8600M GT on a MacBook Pro. We have compared the relative speeds between the CPU and the GPU on a single processor for two types of spatial discretization based on second-order finite-differences and radial basis functions. RBFs are a more novel method based on a gridless and a multi- scale, adaptive framework. Using the NVIDIA 8600M GT, we received a speed up factor of 8 in favor of GPU for the finite-difference method and a factor of 7 for the RBF scheme. We have also studied the atmospheric dynamics problem of swirling flows over a spherical surface and found a speed-up of 5.3 using the GPU. The time steps employed for the RBF method are larger than those used in finite-differences, because of the much fewer number of nodal points needed by RBF. Thus, in modeling the same physical time, RBF acting in concert with GPU would be the fastest way to go.
Rai, H. M.; Trivedi, A.; Chatterjee, K.; Shukla, S.
2014-01-01
This paper employed the Daubechies wavelet transform (WT) for R-peak detection and radial basis function neural network (RBFNN) to classify the electrocardiogram (ECG) signals. Five types of ECG beats: normal beat, paced beat, left bundle branch block (LBBB) beat, right bundle branch block (RBBB) beat and premature ventricular contraction (PVC) were classified. 500 QRS complexes were arbitrarily extracted from 26 records in Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, which are available on Physionet website. Each and every QRS complex was represented by 21 points from p1 to p21 and these QRS complexes of each record were categorized according to types of beats. The system performance was computed using four types of parameter evaluation metrics: sensitivity, positive predictivity, specificity and classification error rate. The experimental result shows that the average values of sensitivity, positive predictivity, specificity and classification error rate are 99.8%, 99.60%, 99.90% and 0.12%, respectively with RBFNN classifier. The overall accuracy achieved for back propagation neural network (BPNN), multilayered perceptron (MLP), support vector machine (SVM) and RBFNN classifiers are 97.2%, 98.8%, 99% and 99.6%, respectively. The accuracy levels and processing time of RBFNN is higher than or comparable with BPNN, MLP and SVM classifiers.
Directory of Open Access Journals (Sweden)
Jingwen Tian
2013-02-01
Full Text Available Since the control system of the welding gun pose in whole-position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN and expert system (ES is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN and the ES. The ADXRS300 micro-mechanical gyro is used as the welding gun position sensor in this system. When the welding gun position is obtained, an appropriate pitch angle can be obtained through expert knowledge and the numeric reasoning capacity of the IRBFNN. ARM is used as the controller to drive the welding gun pitch angle step motor in order to adjust the pitch angle of the welding gun in real-time. The experiment results show that the intelligent control system of the welding gun pose using the IRBFNN and expert system is feasible and it enhances the welding quality. This system has wide prospects for application.
A review of function modeling: Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delin...
Energy Technology Data Exchange (ETDEWEB)
Chauvin, C
2005-11-15
This thesis is devoted to the definition and the implementation of a multi-resolution method to determine the fundamental state of a system composed of nuclei and electrons. In this work, we are interested in the Density Functional Theory (DFT), which allows to express the Hamiltonian operator with the electronic density only, by a Coulomb potential and a non-linear potential. This operator acts on orbitals, which are solutions of the so-called Kohn-Sham equations. Their resolution needs to express orbitals and density on a set of functions owing both physical and numerical properties, as explained in the second chapter. One can hardly satisfy these two properties simultaneously, that is why we are interested in orthogonal and bi-orthogonal wavelets basis, whose properties of interpolation are presented in the third chapter. We present in the fourth chapter three dimensional solvers for the Coulomb's potential, using not only the preconditioning property of wavelets, but also a multigrid algorithm. Determining this potential allows us to solve the self-consistent Kohn-Sham equations, by an algorithm presented in chapter five. The originality of our method consists in the construction of the stiffness matrix, combining a Galerkin formulation and a collocation scheme. We analyse the approximation properties of this method in case of linear Hamiltonian, such as harmonic oscillator and hydrogen, and present convergence results of the DFT for small electrons. Finally we show how orbital compression reduces considerably the number of coefficients to keep, while preserving a good accuracy of the fundamental energy. (author)
Liu, Yin; Belkina, Natalya V; Graham, Caroline; Shaw, Stephen
2006-04-28
Activation loop phosphorylation plays critical regulatory roles for many kinases. Unlike other protein kinase Cs (PKC), PKC-delta does not require phosphorylation of its activation loop (Thr-507) for in vitro activity. We investigated the structural basis for this unusual capacity and its relevance to PKC-delta function in intact cells. Mutational analysis demonstrated that activity without Thr-507 phosphorylation depends on 20 residues N-terminal to the kinase domain and a pair of phenylalanines (Phe-500/Phe-527) unique to PKC-delta in/near the activation loop. Molecular modeling demonstrated that these elements stabilize the activation loop by forming a hydrophobic chain of interactions from the C-lobe to activation loop to N-terminal (helical) extension. In cells PKC-delta mediates both apoptosis and transcription regulation. We found that the T507A mutant of the PKC-delta kinase domain resembled the corresponding wild type in mediating apoptosis in transfected HEK293T cells. But the T507A mutant was completely defective in AP-1 and NF-kappaB reporter assays. A novel assay in which the kinase domain of PKC-delta and its substrate (a fusion protein of PKC substrate peptide with green fluorescent protein) were co-targeted to lipid rafts revealed a major substrate-selective defect of the T507A mutant in phosphorylating the substrate in cells. In vitro analysis showed strong product inhibition on the T507A mutant with particular substrates whose characteristics suggest it contributes to the substrate selective defect of the PKC-delta T507A mutant in cells. Thus, activation loop phosphorylation of PKC-delta may regulate its function in cells in a novel way.
Estimating variability in functional images using a synthetic resampling approach
International Nuclear Information System (INIS)
Maitra, R.; O'Sullivan, F.
1996-01-01
Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods
A Green's function approach to giant-dipole systems
Stielow, Thomas; Scheel, Stefan; Kurz, Markus
2018-01-01
In this work we perform a Green’s function analysis of giant-dipole systems. First, we derive the Green’s functions of different magnetically field-dressed systems, in particular of electronically highly excited atomic species in crossed electric and magnetic fields—so-called giant-dipole states. We determine the dynamical polarizability of atomic giant-dipole states as well as the adiabatic potential energy surfaces of giant-dipole molecules in the framework of the Green’s function approach. Furthermore, we perform an comparative analysis of the latter to an exact diagonalization scheme and show the general divergence behavior of the widely applied Fermi-pseudopotential approach. Finally, we derive the giant-dipole’s regularized Green’s function representation.
Kashinski, D. O.; Nelson, R. G.; Chase, G. M.; di Nallo, O. E.; Byrd, E. F. C.
2017-04-01
We propose new approximate global multiplicative scaling factors for the DFT calculation of harmonic vibrational frequencies using functionals from the TPSS, M06, and M11 functional families with standard Correlation Consistent cc-pV xZ and aug-cc-pV xZ (x = D, T and Q), 6-311G split valence family, as well as Sadlej, and Sapporo polarized triple- ζ basis sets. A total of 99 harmonic frequencies are being calculated for 26 gas phase organic and non-organic molecules typically found in detonated solid propellant residue. The approximate multiplicative scaling factors and associated uncertainties are being determined using a least squares approach comparing the computed harmonic frequencies to experimental counterparts well established in the scientific literature. A comparison of our work to previously published global scaling factors will be made to verify method reliability and the applicability of our molecular test set. An update on the progress of this work will be given at the meeting. work supported by the ARL, DoD-HPCMP, and USMA.
Directory of Open Access Journals (Sweden)
Saúl Gómez-Manzo
2017-05-01
Full Text Available G6PD deficiency is the most common enzymopathy, leading to alterations in the first step of the pentose phosphate pathway, which interferes with the protection of the erythrocyte against oxidative stress and causes a wide range of clinical symptoms of which hemolysis is one of the most severe. The G6PD deficiency causes several abnormalities that range from asymptomatic individuals to more severe manifestations that can lead to death. Nowadays, only 9.2% of all recognized variants have been related to clinical manifestations. It is important to understand the molecular basis of G6PD deficiency to understand how gene mutations can impact structure, stability, and enzymatic function. In this work, we reviewed and compared the functional and structural data generated through the characterization of 20 G6PD variants using different approaches. These studies showed that severe clinical manifestations of G6PD deficiency were related to mutations that affected the catalytic and structural nicotinamide adenine dinucleotide phosphate (NADPH binding sites, and suggests that the misfolding or instability of the 3D structure of the protein could compromise the half-life of the protein in the erythrocyte and its activity.
Estimating Money Demand Function in Cambodia: ARDL Approach
Samreth, Sovannroeun
2008-01-01
This paper empirically estimates the money demand function in Cambodia. We adopt the money demand model that includes exchange rate. For the analysis, Autoregressive Distributed Lag (ARDL) approach to cointegration is employed. Our results indicate that there is cointegration among variables in money demand function. CUSUM and CUSUMSQ tests roughly support the stability of estimated model. However, in the long-run, even the sign of estimated coefficient of exchange rate support the currency s...
Pediatrician's knowledge on the approach of functional constipation
Vieira, Mario C.; Negrelle, Isadora Carolina Krueger; Webber, Karla Ulaf; Gosdal, Marjorie; Truppel, Sabine Krüger; Kusma, Solena Ziemer
2016-01-01
Abstract Objective: To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. Methods: A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297) randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. Results: The majority of the p...
A Novel Synchronization-Based Approach for Functional Connectivity Analysis
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Angela Lombardi
2017-01-01
Full Text Available Complex network analysis has become a gold standard to investigate functional connectivity in the human brain. Popular approaches for quantifying functional coupling between fMRI time series are linear zero-lag correlation methods; however, they might reveal only partial aspects of the functional links between brain areas. In this work, we propose a novel approach for assessing functional coupling between fMRI time series and constructing functional brain networks. A phase space framework is used to map couples of signals exploiting their cross recurrence plots (CRPs to compare the trajectories of the interacting systems. A synchronization metric is extracted from the CRP to assess the coupling behavior of the time series. Since the functional communities of a healthy population are expected to be highly consistent for the same task, we defined functional networks of task-related fMRI data of a cohort of healthy subjects and applied a modularity algorithm in order to determine the community structures of the networks. The within-group similarity of communities is evaluated to verify whether such new metric is robust enough against noise. The synchronization metric is also compared with Pearson’s correlation coefficient and the detected communities seem to better reflect the functional brain organization during the specific task.
Zhang, Gaigong; Lin, Lin; Hu, Wei; Yang, Chao; Pask, John E.
2017-04-01
Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn-Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann-Feynman forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann-Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H2 and liquid Al-Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.
International Nuclear Information System (INIS)
Srikannathasan, Velupillai; English, Grant; Bui, Nhat Khai; Trunk, Katharina; O’Rourke, Patrick E. F.; Rao, Vincenzo A.; Vollmer, Waldemar; Coulthurst, Sarah J.; Hunter, William N.
2013-01-01
Crystal structures of type VI secretion system-associated immunity proteins, a peptidoglycan endopeptidase and a complex of the endopeptidase and its cognate immunity protein are reported together with assays of endopeptidase activity and functional assessment. Some Gram-negative bacteria target their competitors by exploiting the type VI secretion system to extrude toxic effector proteins. To prevent self-harm, these bacteria also produce highly specific immunity proteins that neutralize these antagonistic effectors. Here, the peptidoglycan endopeptidase specificity of two type VI secretion-system-associated effectors from Serratia marcescens is characterized. These small secreted proteins, Ssp1 and Ssp2, cleave between γ-d-glutamic acid and l-meso-diaminopimelic acid with different specificities. Ssp2 degrades the acceptor part of cross-linked tetratetrapeptides. Ssp1 displays greater promiscuity and cleaves monomeric tripeptides, tetrapeptides and pentapeptides and dimeric tetratetra and tetrapenta muropeptides on both the acceptor and donor strands. Functional assays confirm the identity of a catalytic cysteine in these endopeptidases and crystal structures provide information on the structure–activity relationships of Ssp1 and, by comparison, of related effectors. Functional assays also reveal that neutralization of these effectors by their cognate immunity proteins, which are called resistance-associated proteins (Raps), contributes an essential role to cell fitness. The structures of two immunity proteins, Rap1a and Rap2a, responsible for the neutralization of Ssp1 and Ssp2-like endopeptidases, respectively, revealed two distinct folds, with that of Rap1a not having previously been observed. The structure of the Ssp1–Rap1a complex revealed a tightly bound heteromeric assembly with two effector molecules flanking a Rap1a dimer. A highly effective steric block of the Ssp1 active site forms the basis of effector neutralization. Comparisons with Ssp2–Rap2
Energy Technology Data Exchange (ETDEWEB)
Srikannathasan, Velupillai; English, Grant [University of Dundee, Dundee DD1 5EH, Scotland (United Kingdom); Bui, Nhat Khai [Newcastle University, Newcastle upon Tyne NE2 4HH (United Kingdom); Trunk, Katharina; O’Rourke, Patrick E. F.; Rao, Vincenzo A. [University of Dundee, Dundee DD1 5EH, Scotland (United Kingdom); Vollmer, Waldemar [Newcastle University, Newcastle upon Tyne NE2 4HH (United Kingdom); Coulthurst, Sarah J., E-mail: s.j.coulthurst@dundee.ac.uk; Hunter, William N., E-mail: s.j.coulthurst@dundee.ac.uk [University of Dundee, Dundee DD1 5EH, Scotland (United Kingdom)
2013-12-01
Crystal structures of type VI secretion system-associated immunity proteins, a peptidoglycan endopeptidase and a complex of the endopeptidase and its cognate immunity protein are reported together with assays of endopeptidase activity and functional assessment. Some Gram-negative bacteria target their competitors by exploiting the type VI secretion system to extrude toxic effector proteins. To prevent self-harm, these bacteria also produce highly specific immunity proteins that neutralize these antagonistic effectors. Here, the peptidoglycan endopeptidase specificity of two type VI secretion-system-associated effectors from Serratia marcescens is characterized. These small secreted proteins, Ssp1 and Ssp2, cleave between γ-d-glutamic acid and l-meso-diaminopimelic acid with different specificities. Ssp2 degrades the acceptor part of cross-linked tetratetrapeptides. Ssp1 displays greater promiscuity and cleaves monomeric tripeptides, tetrapeptides and pentapeptides and dimeric tetratetra and tetrapenta muropeptides on both the acceptor and donor strands. Functional assays confirm the identity of a catalytic cysteine in these endopeptidases and crystal structures provide information on the structure–activity relationships of Ssp1 and, by comparison, of related effectors. Functional assays also reveal that neutralization of these effectors by their cognate immunity proteins, which are called resistance-associated proteins (Raps), contributes an essential role to cell fitness. The structures of two immunity proteins, Rap1a and Rap2a, responsible for the neutralization of Ssp1 and Ssp2-like endopeptidases, respectively, revealed two distinct folds, with that of Rap1a not having previously been observed. The structure of the Ssp1–Rap1a complex revealed a tightly bound heteromeric assembly with two effector molecules flanking a Rap1a dimer. A highly effective steric block of the Ssp1 active site forms the basis of effector neutralization. Comparisons with Ssp2–Rap2
Energy Technology Data Exchange (ETDEWEB)
King, J.L.
1990-04-01
The Department of Energy has proposed a methodology for developing a ground-motion design basis for prospective facilities at Yucca Mountain that are important to safety. The methodology utilizes a quasi-deterministic construct that is designed to provide a conservative, robust, and reproducible estimate of ground motion that has a one-in-ten chance of occurring during the preclosure period. This estimate is intended to define a ground-motion level for which the seismic design would ensure minimal disruption to operations; engineering analyses to ensure safe performance in the unlikely event that the design basis is exceeded are a part of the proposed methodology. 8 refs.
The Feynman-Vernon Influence Functional Approach in QED
International Nuclear Information System (INIS)
Biryukov, Alexander; Shleenkov, Mark
2016-01-01
In the path integral approach we describe evolution of interacting electromagnetic and fermionic fields by the use of density matrix formalism. The equation for density matrix and transitions probability for fermionic field is obtained as average of electromagnetic field influence functional. We obtain a formula for electromagnetic field influence functional calculating for its various initial and final state. We derive electromagnetic field influence functional when its initial and final states are vacuum. We present Lagrangian for relativistic fermionic field under influence of electromagnetic field vacuum
Coupled cluster approach to the single-particle Green's function
International Nuclear Information System (INIS)
Nooijen, M.; Snijders, J.G.
1992-01-01
Diagrammatic and coupled cluster techniques are used to develop an approach to the single-particle Green's function G which concentrates on G directly rather than first approximating the irreducible self-energy and then solving Dyson's equation. As a consequence the ionization and attachment parts of the Green's function satisfy completely decoupled sets of equations. The proposed coupled cluster Green's function method (CCGF) is intimately connected to both coupled cluster linear response theory (CCLRT) and the normal coupled cluster method (NCCM). These relations are discussed in detail
Mo, Yirong; Gao, Jiali; Peyerimhoff, Sigrid D.
2000-04-01
An energy decomposition scheme based on the block-localized wave function (BLW) method is proposed. The key of this scheme is the definition and the full optimization of the diabatic state wave function, where the charge transfer among interacting molecules is deactivated. The present energy decomposition (ED), BLW-ED, method is similar to the Morokuma decomposition scheme in definition of the energy terms, but differs in implementation and the computational algorithm. In addition, in the BLW-ED approach, the basis set superposition error is fully taken into account. The application of this scheme to the water dimer and the lithium cation-water clusters reveals that there is minimal charge transfer effect in hydrogen-bonded complexes. At the HF/aug-cc-PVTZ level, the electrostatic, polarization, and charge-transfer effects contribute 65%, 24%, and 11%, respectively, to the total bonding energy (-3.84 kcal/mol) in the water dimer. On the other hand, charge transfer effects are shown to be significant in Lewis acid-base complexes such as H3NSO3 and H3NBH3. In this work, the effect of basis sets used on the energy decomposition analysis is addressed and the results manifest that the present energy decomposition scheme is stable with a modest size of basis functions.
A review of function modeling : Approaches and applications
Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.
2008-01-01
This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research
Questionnaire of Executive Function for Dancers: An Ecological Approach
Wong, Alina; Rodriguez, Mabel; Quevedo, Liliana; de Cossio, Lourdes Fernandez; Borges, Ariel; Reyes, Alicia; Corral, Roberto; Blanco, Florentino; Alvarez, Miguel
2012-01-01
There is a current debate about the ecological validity of executive function (EF) tests. Consistent with the verisimilitude approach, this research proposes the Ballet Executive Scale (BES), a self-rating questionnaire that assimilates idiosyncratic executive behaviors of classical dance community. The BES was administrated to 149 adolescents,…
International Nuclear Information System (INIS)
Roshani, G.H.; Nazemi, E.; Roshani, M.M.
2017-01-01
Changes of fluid properties (especially density) strongly affect the performance of radiation-based multiphase flow meter and could cause error in recognizing the flow pattern and determining void fraction. In this work, we proposed a methodology based on combination of multi-beam gamma ray attenuation and dual modality densitometry techniques using RBF neural network in order to recognize the flow regime and determine the void fraction in gas-liquid two phase flows independent of the liquid phase changes. The proposed system is consisted of one 137 Cs source, two transmission detectors and one scattering detector. The registered counts in two transmission detectors were used as the inputs of one primary Radial Basis Function (RBF) neural network for recognizing the flow regime independent of liquid phase density. Then, after flow regime identification, three RBF neural networks were utilized for determining the void fraction independent of liquid phase density. Registered count in scattering detector and first transmission detector were used as the inputs of these three RBF neural networks. Using this simple methodology, all the flow patterns were correctly recognized and the void fraction was predicted independent of liquid phase density with mean relative error (MRE) of less than 3.28%. - Highlights: • Flow regime and void fraction were determined in two phase flows independent of the liquid phase density changes. • An experimental structure was set up and the required data was obtained. • 3 detectors and one gamma source were used in detection geometry. • RBF networks were utilized for flow regime and void fraction determination.
Garcia-Seisdedos, Hector; Ibarra-Molero, Beatriz; Sanchez-Ruiz, Jose M.
2012-01-01
Protein promiscuity is of considerable interest due its role in adaptive metabolic plasticity, its fundamental connection with molecular evolution and also because of its biotechnological applications. Current views on the relation between primary and promiscuous protein activities stem largely from laboratory evolution experiments aimed at increasing promiscuous activity levels. Here, on the other hand, we attempt to assess the main features of the simultaneous modulation of the primary and promiscuous functions during the course of natural evolution. The computational/experimental approach we propose for this task involves the following steps: a function-targeted, statistical coupling analysis of evolutionary data is used to determine a set of positions likely linked to the recruitment of a promiscuous activity for a new function; a combinatorial library of mutations on this set of positions is prepared and screened for both, the primary and the promiscuous activities; a partial-least-squares reconstruction of the full combinatorial space is carried out; finally, an approximation to the Pareto set of variants with optimal primary/promiscuous activities is derived. Application of the approach to the emergence of folding catalysis in thioredoxin scaffolds reveals an unanticipated scenario: diverse patterns of primary/promiscuous activity modulation are possible, including a moderate (but likely significant in a biological context) simultaneous enhancement of both activities. We show that this scenario can be most simply explained on the basis of the conformational diversity hypothesis, although alternative interpretations cannot be ruled out. Overall, the results reported may help clarify the mechanisms of the evolution of new functions. From a different viewpoint, the partial-least-squares-reconstruction/Pareto-set-prediction approach we have introduced provides the computational basis for an efficient directed-evolution protocol aimed at the simultaneous
An evolutionary computation approach to examine functional brain plasticity
Directory of Open Access Journals (Sweden)
Arnab eRoy
2016-04-01
Full Text Available One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN and the executive control network (ECN during recovery from traumatic brain injury (TBI; the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in
Belov, A. N.; Turovtsev, V. V.; Orlov, Yu. D.
2017-10-01
An analytical method for calculating the matrix elements of the Hamiltonian of the torsion Schrödinger equation in a basis of Mathieu functions is developed. The matrix elements are represented by integrals of the product of three Mathieu functions, and also the derivatives of these functions. Analytical expressions for the matrix elements are obtained by approximating the Mathieu functions by Fourier series and are products of the corresponding Fourier expansion coefficients. It is shown that replacing high-order Mathieu functions by one harmonic leads to insignificant errors in the calculation.
MacKenzie, Anne I.; Rao, Sadasiva M.; Baginski, Michael E.
2007-01-01
A pair of basis functions is presented for the surface integral, method of moment solution of scattering by arbitrarily-shaped, three-dimensional dielectric bodies. Equivalent surface currents are represented by orthogonal unit pulse vectors in conjunction with triangular patch modeling. The electric field integral equation is employed with closed geometries for dielectric bodies; the method may also be applied to conductors. Radar cross section results are shown for dielectric bodies having canonical spherical, cylindrical, and cubic shapes. Pulse basis function results are compared to results by other methods.
“Organization Complexity Level”: a Well-Known Idea as the Basis of a New Scientific Approach
Directory of Open Access Journals (Sweden)
Shchapova Yulia L.
2012-03-01
Full Text Available A scientific concept based on the notion of hierarchical systems is analyzed in the article. Three types of hierarchical systems, which differ in terms of organization complexity and the nature of relationships and interactions between endogenous elements, are described. The notion of organization complexity is elucidated. On the basis of this theoretical framework, the author demonstrates the various ways the data of natural and mathematical sciences could be used in historical and archaeological research.
COMPUTATIONAL APPROACHES FOR RATIONAL DESIGN OF PROTEINS WITH NOVEL FUNCTIONALITIES
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Manish Kumar Tiwari
2012-09-01
Full Text Available Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes.
Elements of a function analytic approach to probability.
Energy Technology Data Exchange (ETDEWEB)
Ghanem, Roger Georges (University of Southern California, Los Angeles, CA); Red-Horse, John Robert
2008-02-01
We first provide a detailed motivation for using probability theory as a mathematical context in which to analyze engineering and scientific systems that possess uncertainties. We then present introductory notes on the function analytic approach to probabilistic analysis, emphasizing the connections to various classical deterministic mathematical analysis elements. Lastly, we describe how to use the approach as a means to augment deterministic analysis methods in a particular Hilbert space context, and thus enable a rigorous framework for commingling deterministic and probabilistic analysis tools in an application setting.
Nourani, Vahid; Mousavi, Shahram; Dabrowska, Dominika; Sadikoglu, Fahreddin
2017-05-01
As an innovation, both black box and physical-based models were incorporated into simulating groundwater flow and contaminant transport. Time series of groundwater level (GL) and chloride concentration (CC) observed at different piezometers of study plain were firstly de-noised by the wavelet-based de-noising approach. The effect of de-noised data on the performance of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) was evaluated. Wavelet transform coherence was employed for spatial clustering of piezometers. Then for each cluster, ANN and ANFIS models were trained to predict GL and CC values. Finally, considering the predicted water heads of piezometers as interior conditions, the radial basis function as a meshless method which solves partial differential equations of GFCT, was used to estimate GL and CC values at any point within the plain where there is not any piezometer. Results indicated that efficiency of ANFIS based spatiotemporal model was more than ANN based model up to 13%.
Anderson, Lindsey N; Oviedo, M Belén; Wong, Bryan M
2017-04-11
The treatment of atomic anions with Kohn-Sham density functional theory (DFT) has long been controversial because the highest occupied molecular orbital (HOMO) energy, E HOMO , is often calculated to be positive with most approximate density functionals. We assess the accuracy of orbital energies and electron affinities for all three rows of elements in the periodic table (H-Ar) using a variety of theoretical approaches and customized basis sets. Among all of the theoretical methods studied here, we find that a nonempirically tuned range-separated approach (constructed to satisfy DFT-Koopmans' theorem for the anionic electron system) provides the best accuracy for a variety of basis sets, even for small basis sets where most functionals typically fail. Previous approaches to solve this conundrum of positive E HOMO values have utilized non-self-consistent methods; however, electronic properties, such as electronic couplings/gradients (which require a self-consistent potential and energy), become ill-defined with these approaches. In contrast, the nonempirically tuned range-separated procedure used here yields well-defined electronic couplings/gradients and correct E HOMO values because both the potential and resulting electronic energy are computed self-consistently. Orbital energies and electron affinities are further analyzed in the context of the electronic energy as a function of electronic number (including fractional numbers of electrons) to provide a stringent assessment of self-interaction errors for these complex anion systems.
Transfer function approach to signal discrimination of ULF geomagnetic data
Harada, M.; Hattori, K.; Isezaki, N.
In order to study earthquake-related ULF geomagnetic field changes, it is important to discriminate the noises such as magnetic pulsations originated from solar-terrestrial interactions and artificial noises from DC-driven trains and factories. For this aim, the interstation transfer functions and wavelet transform method have been proposed and applied to the data obtained at the ULF electromagnetic sensor array at the Boso Peninsula, Japan. It is concluded that this interstation transfer function approach has a capacity for signal discrimination; that is, it shows effectiveness to eliminate noises originated from the external ionospheric sources and its secondary effects.
Green-function approach for scattering quantum walks
Energy Technology Data Exchange (ETDEWEB)
Andrade, F. M. [Departamento de Matematica e Estatistica, Universidade Estadual de Ponta Grossa, 84030-900 Ponta Grossa-PR (Brazil); Luz, M. G. E. da [Departamento de Fisica, Universidade Federal do Parana, C.P. 19044, 81531-980 Curitiba-PR (Brazil)
2011-10-15
In this work a Green-function approach for scattering quantum walks is developed. The exact formula has the form of a sum over paths and always can be cast into a closed analytic expression for arbitrary topologies and position-dependent quantum amplitudes. By introducing the step and path operators, it is shown how to extract any information about the system from the Green function. The method's relevant features are demonstrated by discussing in detail an example, a general diamond-shaped graph.
Functional connectivity and brain activation: a synergistic approach.
Tomasi, Dardo; Wang, Ruiliang; Wang, Gene-Jack; Volkow, Nora D
2014-10-01
Traditional functional magnetic resonance imaging (fMRI) studies exploit endogenous brain activity for mapping brain activation during "periodic" cognitive/emotional challenges or brain functional connectivity during the "resting state". Previous studies demonstrated that these approaches provide a limited view of brain function which can be complemented by each other. We hypothesized that graph theory functional connectivity density (FCD) mapping would demonstrate regional FCD decreases between resting-state scan and a continuous "task-state" scan. Forty-five healthy volunteers underwent functional connectivity MRI during resting-state as well as a continuous visual attention task, and standard fMRI with a blocked version of the visual attention task. High-resolution data-driven FCD mapping was used to measure task-related connectivity changes without a priori hypotheses. Results demonstrate that task performance was associated with FCD decreases in brain regions weakly activated/deactivated by the task. Furthermore, a pronounced negative correlation between blood oxygen level-dependent-fMRI activation and task-related FCD decreases emerged across brain regions that also suggest the disconnection of task-irrelevant networks during task performance. The correlation between improved accuracy and stronger FCD decreases further suggests the disconnection of task-irrelevant networks during task performance. Functional connectivity can potentiate traditional fMRI studies and offer a more complete picture of brain function. Published by Oxford University Press 2013. This work is written by (a) US Government employee(s) and is in the public domain in the US.
New approach to equipment quality evaluation method with distinct functions
Directory of Open Access Journals (Sweden)
Milisavljević Vladimir M.
2016-01-01
Full Text Available The paper presents new approach for improving method for quality evaluation and selection of equipment (devices and machinery by applying distinct functions. Quality evaluation and selection of devices and machinery is a multi-criteria problem which involves the consideration of numerous parameters of various origins. Original selection method with distinct functions is based on technical parameters with arbitrary evaluation of each parameter importance (weighting. Improvement of this method, presented in this paper, addresses the issue of weighting of parameters by using Delphi Method. Finally, two case studies are provided, which included quality evaluation of standard boilers for heating and evaluation of load-haul-dump (LHD machines, to demonstrate applicability of this approach. Analytical Hierarchical Process (AHP is used as a control method.
A minimalist functional group (MFG) approach for surrogate fuel formulation
Abdul Jameel, Abdul Gani
2018-03-20
Surrogate fuel formulation has drawn significant interest due to its relevance towards understanding combustion properties of complex fuel mixtures. In this work, we present a novel approach for surrogate fuel formulation by matching target fuel functional groups, while minimizing the number of surrogate species. Five key functional groups; paraffinic CH, paraffinic CH, paraffinic CH, naphthenic CH–CH and aromatic C–CH groups in addition to structural information provided by the Branching Index (BI) were chosen as matching targets. Surrogates were developed for six FACE (Fuels for Advanced Combustion Engines) gasoline target fuels, namely FACE A, C, F, G, I and J. The five functional groups present in the fuels were qualitatively and quantitatively identified using high resolution H Nuclear Magnetic Resonance (NMR) spectroscopy. A further constraint was imposed in limiting the number of surrogate components to a maximum of two. This simplifies the process of surrogate formulation, facilitates surrogate testing, and significantly reduces the size and time involved in developing chemical kinetic models by reducing the number of thermochemical and kinetic parameters requiring estimation. Fewer species also reduces the computational expenses involved in simulating combustion in practical devices. The proposed surrogate formulation methodology is denoted as the Minimalist Functional Group (MFG) approach. The MFG surrogates were experimentally tested against their target fuels using Ignition Delay Times (IDT) measured in an Ignition Quality Tester (IQT), as specified by the standard ASTM D6890 methodology, and in a Rapid Compression Machine (RCM). Threshold Sooting Index (TSI) and Smoke Point (SP) measurements were also performed to determine the sooting propensities of the surrogates and target fuels. The results showed that MFG surrogates were able to reproduce the aforementioned combustion properties of the target FACE gasolines across a wide range of conditions
A Goal-Function Approach to Analysis of Control Situations
DEFF Research Database (Denmark)
Lind, Morten
2010-01-01
processes situations should identify operational aspects relevant for control agent’s decision making in plant supervision and control. Control situations can be understood as recurrent and interconnected patterns of control with important implications for control and HMI design. Goal-Function approaches...... to systems modeling like Multilevel Flow Modeling can be used to represent control situations. The paper will describe an action theoretical foundation for MFM and its use for the development of a theory of control situations....
A zeta function approach to the semiclassical quantization of maps
International Nuclear Information System (INIS)
Smilansky, Uzi.
1993-11-01
The quantum analogue of an area preserving map on a compact phase space is a unitary (evolution) operator which can be represented by a matrix of dimension L∝ℎ -1 . The semiclassical theory for spectrum of the evolution operator will be reviewed with special emphasize on developing a dynamical zeta function approach, similar to the one introduced recently for a semiclassical quantization of hamiltonian systems. (author)
Functional Foods and Lifestyle Approaches for Diabetes Prevention and Management.
Alkhatib, Ahmad; Tsang, Catherine; Tiss, Ali; Bahorun, Theeshan; Arefanian, Hossein; Barake, Roula; Khadir, Abdelkrim; Tuomilehto, Jaakko
2017-12-01
Functional foods contain biologically active ingredients associated with physiological health benefits for preventing and managing chronic diseases, such as type 2 diabetes mellitus (T2DM). A regular consumption of functional foods may be associated with enhanced anti-oxidant, anti-inflammatory, insulin sensitivity, and anti-cholesterol functions, which are considered integral to prevent and manage T2DM. Components of the Mediterranean diet (MD)-such as fruits, vegetables, oily fish, olive oil, and tree nuts-serve as a model for functional foods based on their natural contents of nutraceuticals, including polyphenols, terpenoids, flavonoids, alkaloids, sterols, pigments, and unsaturated fatty acids. Polyphenols within MD and polyphenol-rich herbs-such as coffee, green tea, black tea, and yerba maté-have shown clinically-meaningful benefits on metabolic and microvascular activities, cholesterol and fasting glucose lowering, and anti-inflammation and anti-oxidation in high-risk and T2DM patients. However, combining exercise with functional food consumption can trigger and augment several metabolic and cardiovascular protective benefits, but it is under-investigated in people with T2DM and bariatric surgery patients. Detecting functional food benefits can now rely on an "omics" biological profiling of individuals' molecular, genetics, transcriptomics, proteomics, and metabolomics, but is under-investigated in multi-component interventions. A personalized approach for preventing and managing T2DM should consider biological and behavioral models, and embed nutrition education as part of lifestyle diabetes prevention studies. Functional foods may provide additional benefits in such an approach.
Functional Foods and Lifestyle Approaches for Diabetes Prevention and Management
Directory of Open Access Journals (Sweden)
Ahmad Alkhatib
2017-12-01
Full Text Available Functional foods contain biologically active ingredients associated with physiological health benefits for preventing and managing chronic diseases, such as type 2 diabetes mellitus (T2DM. A regular consumption of functional foods may be associated with enhanced anti-oxidant, anti-inflammatory, insulin sensitivity, and anti-cholesterol functions, which are considered integral to prevent and manage T2DM. Components of the Mediterranean diet (MD—such as fruits, vegetables, oily fish, olive oil, and tree nuts—serve as a model for functional foods based on their natural contents of nutraceuticals, including polyphenols, terpenoids, flavonoids, alkaloids, sterols, pigments, and unsaturated fatty acids. Polyphenols within MD and polyphenol-rich herbs—such as coffee, green tea, black tea, and yerba maté—have shown clinically-meaningful benefits on metabolic and microvascular activities, cholesterol and fasting glucose lowering, and anti-inflammation and anti-oxidation in high-risk and T2DM patients. However, combining exercise with functional food consumption can trigger and augment several metabolic and cardiovascular protective benefits, but it is under-investigated in people with T2DM and bariatric surgery patients. Detecting functional food benefits can now rely on an “omics” biological profiling of individuals’ molecular, genetics, transcriptomics, proteomics, and metabolomics, but is under-investigated in multi-component interventions. A personalized approach for preventing and managing T2DM should consider biological and behavioral models, and embed nutrition education as part of lifestyle diabetes prevention studies. Functional foods may provide additional benefits in such an approach.
Tensor function approach to constitutive equations of inelasticity
International Nuclear Information System (INIS)
Murakami, S.
1979-01-01
Though various theories for elaborated engineering constitutive models have been proposed so far to improve the description of inelastic response of engineering materials, most of them have been formulated within the framework of the classical theories of plasticity and creep. In these cases, the expressions of flow potentials and hardening rules are usually modified a priori by adding some additional terms, and the related material constants are determined by experiments. The difficulties of such approaches consist in the lack of generality and pertinence, besides that they are considerably laborious. In the field of non-linear continuum mechanics, on the other hand, there has been a continuos development of more powerful approaches which are applicable to these problems. It is the aim of the present paper to show the utility of the tensor function approach to the development of the non-classical constitutive equations of inelasticity and to elucidate the practical procedures and some new results of it. (orig.)
Fuzzy set approach to quality function deployment: An investigation
Masud, Abu S. M.
1992-01-01
The final report of the 1992 NASA/ASEE Summer Faculty Fellowship at the Space Exploration Initiative Office (SEIO) in Langley Research Center is presented. Quality Function Deployment (QFD) is a process, focused on facilitating the integration of the customer's voice in the design and development of a product or service. Various input, in the form of judgements and evaluations, are required during the QFD analyses. All the input variables in these analyses are treated as numeric variables. The purpose of the research was to investigate how QFD analyses can be performed when some or all of the input variables are treated as linguistic variables with values expressed as fuzzy numbers. The reason for this consideration is that human judgement, perception, and cognition are often ambiguous and are better represented as fuzzy numbers. Two approaches for using fuzzy sets in QFD have been proposed. In both cases, all the input variables are considered as linguistic variables with values indicated as linguistic expressions. These expressions are then converted to fuzzy numbers. The difference between the two approaches is due to how the QFD computations are performed with these fuzzy numbers. In Approach 1, the fuzzy numbers are first converted to their equivalent crisp scores and then the QFD computations are performed using these crisp scores. As a result, the output of this approach are crisp numbers, similar to those in traditional QFD. In Approach 2, all the QFD computations are performed with the fuzzy numbers and the output are fuzzy numbers also. Both the approaches have been explained with the help of illustrative examples of QFD application. Approach 2 has also been applied in a QFD application exercise in SEIO, involving a 'mini moon rover' design. The mini moon rover is a proposed tele-operated vehicle that will traverse and perform various tasks, including autonomous operations, on the moon surface. The output of the moon rover application exercise is a
Directory of Open Access Journals (Sweden)
Bohdan STADNYK
2016-04-01
Full Text Available After proving the existence of Temperature Quantum the next step would be the study of possibility of Temperature Standard creation. We consider the general principles of design and operation of such advanced Temperature Standard constructed on the basis of Quantum Temperature Unit. The latter is determined solely via the fundamental physical constants. Approach to the mentioned Standard is developed in this paper.
Prasad, Viki Kumar; Otero-de-la-Roza, Alberto; DiLabio, Gino A
2018-02-13
We present a computational methodology based on atom-centered potentials (ACPs) for the efficient and accurate structural modeling of large molecular systems. ACPs are atom-centered one-electron potentials that have the same functional form as effective-core potentials. In recent works, we showed that ACPs can be used to produce a correction to the ground-state wave function and electronic energy to alleviate shortcomings in the underlying model chemistry. In this work, we present ACPs for H, C, N, and O atoms that are specifically designed to predict accurate non-covalent binding energies and inter- and intramolecular geometries when combined with dispersion-corrected Hartree-Fock (HF-D3) and a minimal basis-set (scaled MINI or MINIs). For example, the combined HF-D3/MINIs-ACP method demonstrates excellent performance, with mean absolute errors of 0.36 and 0.28 kcal/mol for the S22x5 and S66x8 benchmark sets, respectively, relative to highly correlated complete-basis-set data. The application of ACPs results in a significant decrease in error compared to uncorrected HF-D3/MINIs for all benchmark sets examined. In addition, HF-D3/MINIs-ACP, has a cost only slightly higher than a minimal-basis-set HF calculation and can be used with any electronic structure program for molecular quantum chemistry that uses Gaussian basis sets and effective-core potentials.
Novel approaches in function-driven single-cell genomics.
Doud, Devin F R; Woyke, Tanja
2017-07-01
Deeper sequencing and improved bioinformatics in conjunction with single-cell and metagenomic approaches continue to illuminate undercharacterized environmental microbial communities. This has propelled the 'who is there, and what might they be doing' paradigm to the uncultivated and has already radically changed the topology of the tree of life and provided key insights into the microbial contribution to biogeochemistry. While characterization of 'who' based on marker genes can describe a large fraction of the community, answering 'what are they doing' remains the elusive pinnacle for microbiology. Function-driven single-cell genomics provides a solution by using a function-based screen to subsample complex microbial communities in a targeted manner for the isolation and genome sequencing of single cells. This enables single-cell sequencing to be focused on cells with specific phenotypic or metabolic characteristics of interest. Recovered genomes are conclusively implicated for both encoding and exhibiting the feature of interest, improving downstream annotation and revealing activity levels within that environment. This emerging approach has already improved our understanding of microbial community functioning and facilitated the experimental analysis of uncharacterized gene product space. Here we provide a comprehensive review of strategies that have been applied for function-driven single-cell genomics and the future directions we envision. © FEMS 2017.
Zeta-function approach to Casimir energy with singular potentials
International Nuclear Information System (INIS)
Khusnutdinov, Nail R.
2006-01-01
In the framework of zeta-function approach the Casimir energy for three simple model system: single delta potential, step function potential and three delta potentials are analyzed. It is shown that the energy contains contributions which are peculiar to the potentials. It is suggested to renormalize the energy using the condition that the energy of infinitely separated potentials is zero which corresponds to subtraction all terms of asymptotic expansion of zeta-function. The energy obtained in this way obeys all physically reasonable conditions. It is finite in the Dirichlet limit, and it may be attractive or repulsive depending on the strength of potential. The effective action is calculated, and it is shown that the surface contribution appears. The renormalization of the effective action is discussed
Yakovlev, Aleksandr
2016-04-01
list of requirements can be divided into two areas: - the standards and norms of environmental assessment for all components of environment, - requirements to the level of environmental stress on the land when designing the system of nature management. Environmental requirements for components of the environment are based primarily on stringent environmental and health standards (maximum permissible concentration, permissible residual oil content in the soil, etc.), compliance of which involves the maintenance of the ecological state of nature in close to background rates. The assessment of environmental stress in planning and land management is not provided with official regulations and is based primarily on expert opinions. However, projects and land use programs must pass the corresponding procedure of environmental expertise. Rating, ranking and regulation of soil and land quality allow to establish the level of its disturbance and the ability to heal itself, according to the methodological approach developed and adopted by several Russian Agencies (Environmental, Agricultural and Land use Agencies). The basis for assessing the ecological status of soils was based on the five-level evaluation scale according to which a fairly conventional boundary of reversibility is considered to be the third (threshold) level, and irreversible accumulation of environmental damage occurs when reaching . fourth and fifth level of loss of environmental quality of soils. According to a separate study in the field of environmental regulation irreversible changes occur in the loss of more than a quarter of Bioorganic capacity of soils. The main condition for sustainable development is the development, which does not cause irreversible damage to nature and society, based on compliance with environmental quality requirements for components of the environment, particularly soils and lands and secure planning and safe placement of the productive forces. Acknowledgments: This study was
Plessner, Henning; Schweizer, Geoffrey; Brand, Ralf; O'Hare, David
2009-01-01
A significant proportion of all referee decisions during a soccer match are about fouls and misconduct. We argue that most of these decisions can be considered as a perceptual-categorization task in which the referee has to categorize a set of features into two discrete classes (foul/no-foul). Due to the dynamic nature of tackling situations in football, these features share a probabilistic rather that a deterministic relationship with the decision criteria. Accordingly, these processes can be studied on the basis of a multiple-cue learning framework as proposed by Brunswick (1955), which focuses among others on how people learn from repeated exposure to probabilistic information. Such learning processes have been studied on a wide range of tasks, but until now not (to our knowledge) in the area of judging sport performance. We suggest that decision accuracy of referees can be improved by creating a learning environment that fits the requirements of this theoretical perspective.
Shakuto, Elena A.; Dorozhkin, Evgenij M.; Kozlova, Anastasia A.
2016-01-01
The relevance of the subject under analysis is determined by the lack of theoretical development of the problem of management of teacher scientific-methodical work in vocational educational institutions based upon innovative approaches in the framework of project paradigm. The purpose of the article is to develop and test a science-based…
Gromova, Chulpan R.; Saitova, Lira R.
2016-01-01
The relevance of research problem is due to the need for music teacher with a high level of formation of professional competence determination of the content and principles of an interdisciplinary approach to its formation. The aim of the article lies in development and testing of complex of the pedagogical conditions in formation of professional…
Physiotherapeutic approach and functional performance after breast cancer surgery
Directory of Open Access Journals (Sweden)
Mariana Tirolli Rett
Full Text Available Abstract Introduction: Surgery for breast cancer can impair range of motion (ROM and functionality of upper limb (UL. Objective: To compare ROM and functional performance of homolateral UL after physiotherapeutic approach and to correlate these variables. Methods: A non-randomized clinical trial study enrolled 33 women who were submitted to mastectomy or quadrantectomy associated with axillary lymphadenectomy. ROM was assessed by homolateral UL and contralateral limb (control goniometry. Functional performance was assessed by “Disability of arm, shoulder and hand” (DASH questionnaire. The protocol consisted in 10 sessions (3 sessions per week during 60 minutes, involving passive mobilization of glenohumeral and scapulothoracic joint, soft tissue mobilization, neck muscles and upper limb muscles stretching, exercises in all planes of motion, applied alone or in combination. Weight bearing exercise with elastic bands and dumbbells from 0.5 to 1.0 kilograms were also applied. Results: There was a meaningful increase in ROM of all movements after physiotherapy; however, flexion, abduction and lateral rotation remained lower than control limb. DASH score decreased significantly from 28.06 ± 16.1 to 15.71 ± 10.7 (p = 0.001 meaning an improvement in functional performance of UL. No correlation was observed between ROM and DASH. Conclusion: Functional performance and ROM, after 10 physiotherapy sessions, improved significantly, however, a long-term follow-up can contribute to further improvement.
Correlation functions of the spin chains. Algebraic Bethe Ansatz approach
International Nuclear Information System (INIS)
Kitanine, N.
2007-09-01
Spin chains are the basic elements of integrable quantum models. These models have direct applications in condense matter theory, in statistical physics, in quantum optics, in field theory and even in string theory but they are also important because they enable us to solve, in an exact manner, non-perturbative phenomena that otherwise would stay unresolved. The method described in this work is based on the algebraic Bethe Ansatz. It is shown how this method can be used for the computation of null temperature correlation functions of the Heisenberg 1/2 spin chain. The important point of this approach is the solution of the inverse quantum problem given by the XXZ spin chain. This solution as well as a simple formulae for the scalar product of the Bethe states, have enabled us to get the most basic correlation functions under the form of multiple integrals. The formalism of multiple integrals open the way for asymptotic analysis for a few physical quantities like the probability of vacuum formation. It is worth noticing that this formalism can give exact results for two-point functions that are the most important correlation functions for applications. A relationship has been discovered between these multiple integrals and the sum of the form factors. The results have been extended to dynamical correlation functions. (A.C.)
Energy Technology Data Exchange (ETDEWEB)
Werhahn, Johannes
2009-07-01
The currently high cost of fuel cells is determined by expensive materials and low production volume. A detailed understanding of the cost structures reveals unexploited potential that can reduce costs in future. However, this requires a method of predicting costs that can be applied with little effort and which offers both a sufficient degree of detail and also good accuracy. Existing forecasting methods do not, however, fulfil these requirements. The major objective of the present work was to apply mass-specific cost forecasting to fuel cell systems for the first time and to modify the approach for this application. In this method, the cost of an object is estimated solely by means of the object mass with the aid of empirical values (Euro/kg). The advantages of the method are its simple application and the accuracy of the forecast. Due to the considerable complexity of the fuel cell and the heterogeneity of the materials used, the application of mass-specific cost forecasting does not provide the desired benefits on the level of the aggregated system. The mass-specific cost forecast approach was therefore expanded and optimized. Instead of determining costs on the level of the aggregated system, the cost forecast was applied directly to the individual components. Cost parameters were also embedded in the method in order to include component-internal cost-relevant differences. Due to the great influence of the production rate on the manufacturing costs, an additional dependence on number of units was also integrated. Expanding the empirical values from discrete values to distribution functions enabled a detailed error analysis to be performed and also a statistical localization of the predicted production costs. Empirical values are necessary in order to implement the modified method and therefore an extensive data search was performed. To this end, a methodology was developed which comprehensively described the data acquisition and the required data evaluation on
Ganguly, Enakshi; Ganguly, Bhaskar
2016-01-01
The present Zika virus (ZIKV) pandemic is being associated with increased incidence of microcephaly in newborns. However, a molecular basis for such pathogenesis is distinctly lacking. Comparative nucleic acid sequence analysis showed similarity between regions of non-structural protein 4B (ns4b) gene of ZIKV and human astrotactin2 (astn2) gene. Based on these findings, a molecular target of Zika viral microcephaly is being proposed.
International Nuclear Information System (INIS)
Hollauer, E.; Nascimento, M.A.C.
1985-01-01
The photoionization cross-section and dynamic polarizability for lithium atom are calculated using a discrete basis set to represent both the bound and the continuum-states of the atom, to construct an approximation to the dynamic polarizability. From the imaginary part of the complex dynamic polarizability one extracts the photoionization cross-section and from its real part the dynamic polarizability. The results are in good agreement with the experiments and other more elaborate calculations (Author) [pt
Dual Approach to the Study of Land Market Functioning
Directory of Open Access Journals (Sweden)
Liliya Oganesovna Oganesyan
2015-12-01
Full Text Available The article reveals the essence, the structural elements and features of the mechanism of functioning of the market of agricultural land. The authors present the supplementing idea on the structural dichotomy of the agricultural land market. In contrast to neoclassical approaches, it is proposed to explore the market based on its structural dichotomy – market property rights and market rights of management. In this context, the mechanism of functioning of agricultural lands market performs the function of a basic element in the system of land relations to ensure market circulation of agricultural land through alienation and assign full or partial rights of land ownership. The use of the institutional approach to the study of market structures justifies the dual nature of the mechanism of functioning of the market of agricultural land due to the fact that on the one hand, the market is slow and limited in the market space of the rare economic good or factor of production, and on the other hand, it is a dynamic institutional and economic system within which the specification of property rights to land is implemented. The structure of the mechanism of functioning and development of agricultural land market is considered as a system of interrelated and interacting elements of state regulation and market self-regulation, based on the principles of coordination and harmonization of personalized economic interests and market law of supply and demand. The combination of elements of market self-regulation and state regulation allows in practice to justify the choice of model combinations of stable and changing elements of the mechanism. This combination complies with the institutional conditions for the functioning of the market of agricultural land considering the dominance of regulated sustainable standards at the market of property rights and in the frames of informal institutions at the market of the management rights. The authors prove the
Sensorimotor integration for functional recovery and the Bobath approach.
Levin, Mindy F; Panturin, Elia
2011-04-01
Bobath therapy is used to treat patients with neurological disorders. Bobath practitioners use hands-on approaches to elicit and reestablish typical movement patterns through therapist-controlled sensorimotor experiences within the context of task accomplishment. One aspect of Bobath practice, the recovery of sensorimotor function, is reviewed within the framework of current motor control theories. We focus on the role of sensory information in movement production, the relationship between posture and movement and concepts related to motor recovery and compensation with respect to this therapeutic approach. We suggest that a major barrier to the evaluation of the therapeutic effectiveness of the Bobath concept is the lack of a unified framework for both experimental identification and treatment of neurological motor deficits. More conclusive analysis of therapeutic effectiveness requires the development of specific outcomes that measure movement quality.
Developmental Programming of Renal Function and Re-Programming Approaches.
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to "re-program" renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin-angiotensin-aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application. Early
Developmental Programming of Renal Function and Re-Programming Approaches
Directory of Open Access Journals (Sweden)
Eva Nüsken
2018-02-01
Full Text Available Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated
Developmental Programming of Renal Function and Re-Programming Approaches
Nüsken, Eva; Dötsch, Jörg; Weber, Lutz T.; Nüsken, Kai-Dietrich
2018-01-01
Chronic kidney disease affects more than 10% of the population. Programming studies have examined the interrelationship between environmental factors in early life and differences in morbidity and mortality between individuals. A number of important principles has been identified, namely permanent structural modifications of organs and cells, long-lasting adjustments of endocrine regulatory circuits, as well as altered gene transcription. Risk factors include intrauterine deficiencies by disturbed placental function or maternal malnutrition, prematurity, intrauterine and postnatal stress, intrauterine and postnatal overnutrition, as well as dietary dysbalances in postnatal life. This mini-review discusses critical developmental periods and long-term sequelae of renal programming in humans and presents studies examining the underlying mechanisms as well as interventional approaches to “re-program” renal susceptibility toward disease. Clinical manifestations of programmed kidney disease include arterial hypertension, proteinuria, aggravation of inflammatory glomerular disease, and loss of kidney function. Nephron number, regulation of the renin–angiotensin–aldosterone system, renal sodium transport, vasomotor and endothelial function, myogenic response, and tubuloglomerular feedback have been identified as being vulnerable to environmental factors. Oxidative stress levels, metabolic pathways, including insulin, leptin, steroids, and arachidonic acid, DNA methylation, and histone configuration may be significantly altered by adverse environmental conditions. Studies on re-programming interventions focused on dietary or anti-oxidative approaches so far. Further studies that broaden our understanding of renal programming mechanisms are needed to ultimately develop preventive strategies. Targeted re-programming interventions in animal models focusing on known mechanisms will contribute to new concepts which finally will have to be translated to human application
Directory of Open Access Journals (Sweden)
Johanna Rhodes
2017-04-01
Full Text Available Recurrence of meningitis due to Cryptococcus neoformans after treatment causes substantial mortality in HIV/AIDS patients across sub-Saharan Africa. In order to determine whether recurrence occurred due to relapse of the original infecting isolate or reinfection with a different isolate weeks or months after initial treatment, we used whole-genome sequencing (WGS to assess the genetic basis of infection in 17 HIV-infected individuals with recurrent cryptococcal meningitis (CM. Comparisons revealed a clonal relationship for 15 pairs of isolates recovered before and after recurrence showing relapse of the original infection. The two remaining pairs showed high levels of genetic heterogeneity; in one pair we found this to be a result of infection by mixed genotypes, while the second was a result of nonsense mutations in the gene encoding the DNA mismatch repair proteins MSH2, MSH5, and RAD5. These nonsense mutations led to a hypermutator state, leading to dramatically elevated rates of synonymous and nonsynonymous substitutions. Hypermutator phenotypes owing to nonsense mutations in these genes have not previously been reported in C. neoformans, and represent a novel pathway for rapid within-host adaptation and evolution of resistance to first-line antifungal drugs.
Rhodes, Johanna; Beale, Mathew A; Vanhove, Mathieu; Jarvis, Joseph N; Kannambath, Shichina; Simpson, John A; Ryan, Anthea; Meintjes, Graeme; Harrison, Thomas S; Fisher, Matthew C; Bicanic, Tihana
2017-04-03
Recurrence of meningitis due to Cryptococcus neoformans after treatment causes substantial mortality in HIV/AIDS patients across sub-Saharan Africa. In order to determine whether recurrence occurred due to relapse of the original infecting isolate or reinfection with a different isolate weeks or months after initial treatment, we used whole-genome sequencing (WGS) to assess the genetic basis of infection in 17 HIV-infected individuals with recurrent cryptococcal meningitis (CM). Comparisons revealed a clonal relationship for 15 pairs of isolates recovered before and after recurrence showing relapse of the original infection. The two remaining pairs showed high levels of genetic heterogeneity; in one pair we found this to be a result of infection by mixed genotypes, while the second was a result of nonsense mutations in the gene encoding the DNA mismatch repair proteins MSH2 , MSH5 , and RAD5 These nonsense mutations led to a hypermutator state, leading to dramatically elevated rates of synonymous and nonsynonymous substitutions. Hypermutator phenotypes owing to nonsense mutations in these genes have not previously been reported in C. neoformans , and represent a novel pathway for rapid within-host adaptation and evolution of resistance to first-line antifungal drugs. Copyright © 2017 Rhodes et al.
Barki, Anum; Kendricks, Kimberly; Tuttle, Ronald F.; Bunker, David J.; Borel, Christoph C.
2013-05-01
This research highlights the results obtained from applying the method of inverse kinematics, using Groebner basis theory, to the human gait cycle to extract and identify lower extremity gait signatures. The increased threat from suicide bombers and the force protection issues of today have motivated a team at Air Force Institute of Technology (AFIT) to research pattern recognition in the human gait cycle. The purpose of this research is to identify gait signatures of human subjects and distinguish between subjects carrying a load to those subjects without a load. These signatures were investigated via a model of the lower extremities based on motion capture observations, in particular, foot placement and the joint angles for subjects affected by carrying extra load on the body. The human gait cycle was captured and analyzed using a developed toolkit consisting of an inverse kinematic motion model of the lower extremity and a graphical user interface. Hip, knee, and ankle angles were analyzed to identify gait angle variance and range of motion. Female subjects exhibited the most knee angle variance and produced a proportional correlation between knee flexion and load carriage.
Matrix converter controlled with the direct transfer function approach
DEFF Research Database (Denmark)
Rodriguez, J.; Silva, E.; Blaabjerg, Frede
2005-01-01
Power electronics is an emerging technology. New power circuits are invented and have to be introduced into the power electronics curriculum. One of the interesting new circuits is the matrix converter (MC), and this paper analyses its working principles. A simple model is proposed to represent...... the power circuit, including the input filter. The power semiconductors are modelled as ideal bidirectional switches and the MC is controlled using a direct transfer function approach. The modulation strategy of the converter is explained in a complete and clear form. The commutation problem of two switches...
A Model-Based Approach to Constructing Music Similarity Functions
West, Kris; Lamere, Paul
2006-12-01
Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
The Use of Modeling Approach for Teaching Exponential Functions
Nunes, L. F.; Prates, D. B.; da Silva, J. M.
2017-12-01
This work presents a discussion related to the teaching and learning of mathematical contents related to the study of exponential functions in a freshman students group enrolled in the first semester of the Science and Technology Bachelor’s (STB of the Federal University of Jequitinhonha and Mucuri Valleys (UFVJM). As a contextualization tool strongly mentioned in the literature, the modelling approach was used as an educational teaching tool to produce contextualization in the teaching-learning process of exponential functions to these students. In this sense, were used some simple models elaborated with the GeoGebra software and, to have a qualitative evaluation of the investigation and the results, was used Didactic Engineering as a methodology research. As a consequence of this detailed research, some interesting details about the teaching and learning process were observed, discussed and described.
Study of the nuclear-coulomb low-energy scattering parameters on the basis of the p-matrix approach
International Nuclear Information System (INIS)
Babenko, V.A.; Petrov, N.M.
1993-01-01
The P-matrix approach application to the description of two charged strongly interacting particles nuclear-Coulomb scattering parameters is considered. The nuclear-Coulomb scattering length and effective range explicit expressions in terms of the P-matrix parameters are found. The nuclear-Coulomb low-energy parameters expansions in powers of small parameter β ≡ R/a b , involving terms with big logarithms, are obtained. The nuclear-Coulomb scattering length and effective range for the square-well and the delta-shell short range potentials are found in an explicit form. (author). 21 refs
Levenson, Steven A
2010-02-01
While many aspects of nursing home care have improved over time, numerous issues persist. Presently, a potpourri of approaches and a push to "fix" the problem have overshadowed efforts to correctly define the issues and identify their diverse causes. Together, the two segments of this fourth and final article (divided between this month's issue and the next one) in the series identify strategies that should tie reform efforts together. This Segment 1 of Article 4 discusses the need to judge initiatives and proposals by how well they support and/or promote critical elements such as the care delivery process and clinical problem solving and decision making activities. It also covers the need to critically scrutinize and modify the conventional wisdom and to suppress "political correctness" thatcontinues to inhibit vital critical inquiry and dialogue that are needed to define issues correctly and make further progress. Ultimately, relatively uncomplicated and inexpensive strategies have the potential to bring dramatic progress. But there needs to be more willingness to rethink the issues and reconsider current approaches. Copyright 2010 American Medical Directors Association. Published by Elsevier Inc. All rights reserved.
The Navier-Stokes equations an elementary functional analytic approach
Sohr, Hermann
2001-01-01
The primary objective of this monograph is to develop an elementary and self contained approach to the mathematical theory of a viscous incompressible fluid in a domain 0 of the Euclidean space ]Rn, described by the equations of Navier Stokes. The book is mainly directed to students familiar with basic functional analytic tools in Hilbert and Banach spaces. However, for readers' convenience, in the first two chapters we collect without proof some fundamental properties of Sobolev spaces, distributions, operators, etc. Another important objective is to formulate the theory for a completely general domain O. In particular, the theory applies to arbitrary unbounded, non-smooth domains. For this reason, in the nonlinear case, we have to restrict ourselves to space dimensions n = 2,3 that are also most significant from the physical point of view. For mathematical generality, we will develop the lin earized theory for all n 2 2. Although the functional-analytic approach developed here is, in principle, known ...
Optimal Approaches for Measuring Tongue-Pressure Functional Reserve
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Catriona M. Steele
2013-01-01
Full Text Available Tongue-palate pressure is a parameter of considerable interest in the field of dysphagia. Maximum isometric tongue-palate pressures (MIPs decline in healthy aging and in dysphagia. Functional reserve (FR is the difference between MIPs and swallowing pressures. Reduced FR is thought to constitute a risk for developing functional swallowing impairments. We compare different approaches for calculating FR and recommend an optimal approach. Tongue-palate pressure data were collected from 78 healthy adults (4060 during anterior and posterior MIPs, regular (RESS and effortful (ESS saliva swallows, and water swallows (4 repetitions per task. Six different measures of reserve were calculated using maximum anterior MIPs or ESS pressures at the top, and mean or maximum RESS or water swallow pressures at the bottom of the range. Correlations with age and MIPs were explored to confirm suitability for measuring FR. The impact of normalization to maximum MIP range was explored. We conclude that an optimal measure of FR involves the comparison of maximum MIP with mean saliva swallowing pressures. This parameter declines with age, but when normalized to an individual’s MIP range, the relationship is no longer evident. This suggests that FR does not necessarily decline in healthy aging.
Hutter, Jürg
2003-03-01
An efficient formulation of time-dependent linear response density functional theory for the use within the plane wave basis set framework is presented. The method avoids the transformation of the Kohn-Sham matrix into the canonical basis and references virtual orbitals only through a projection operator. Using a Lagrangian formulation nuclear derivatives of excited state energies within the Tamm-Dancoff approximation are derived. The algorithms were implemented into a pseudo potential/plane wave code and applied to the calculation of adiabatic excitation energies, optimized geometries and vibrational frequencies of three low lying states of formaldehyde. An overall good agreement with other time-dependent density functional calculations, multireference configuration interaction calculations and experimental data was found.
Arbitrariness is not enough: towards a functional approach to the genetic code.
Lacková, Ľudmila; Matlach, Vladimír; Faltýnek, Dan
2017-12-01
Arbitrariness in the genetic code is one of the main reasons for a linguistic approach to molecular biology: the genetic code is usually understood as an arbitrary relation between amino acids and nucleobases. However, from a semiotic point of view, arbitrariness should not be the only condition for definition of a code, consequently it is not completely correct to talk about "code" in this case. Yet we suppose that there exist a code in the process of protein synthesis, but on a higher level than the nucleic bases chains. Semiotically, a code should be always associated with a function and we propose to define the genetic code not only relationally (in basis of relation between nucleobases and amino acids) but also in terms of function (function of a protein as meaning of the code). Even if the functional definition of meaning in the genetic code has been discussed in the field of biosemiotics, its further implications have not been considered. In fact, if the function of a protein represents the meaning of the genetic code (the sign's object), then it is crucial to reconsider the notion of its expression (the sign) as well. In our contribution, we will show that the actual model of the genetic code is not the only possible and we will propose a more appropriate model from a semiotic point of view.
Finite frequency Seebeck coefficient of metals: A memory function approach
Bhalla, Pankaj; Kumar, Pradeep; Das, Nabyendu; Singh, Navinder
2017-10-01
We study the dynamical thermoelectric transport in metals subjected to the electron-impurity and the electron-phonon interactions using the memory function formalism. We introduce a generalized Drude form for the Seebeck coefficient in terms of thermoelectric memory function and calculate the latter in various temperature and frequency limits. In the zero frequency and high temperature limit, we find that our results are consistent with the experimental findings and with the traditional Boltzmann equation approach. In the low temperature limit, we find that the Seebeck coefficient is quadratic in temperature. In the finite frequency regime, we report new results: In the electron-phonon interaction case, we find that the Seebeck coefficient shows frequency independent behavior both in the high frequency regime (ω ≫ωD , where ωD is the Debye frequency) and in the low frequency regime (ω ≪ωD), whereas in the intermediate frequencies, it is a monotonically increasing function of frequency. In the case of the electron-impurity interaction, first it decays and then after passing through a minimum it increases with the increase in frequency and saturates at high frequencies.
Pediatrician's knowledge on the approach of functional constipation.
Vieira, Mario C; Negrelle, Isadora Carolina Krueger; Webber, Karla Ulaf; Gosdal, Marjorie; Truppel, Sabine Krüger; Kusma, Solena Ziemer
2016-12-01
To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297) randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. The majority of the participants were females, the mean age was 44.1 years, the mean time of professional practice was 18.8 years; 56.9% were Board Certified by the Brazilian Society of Pediatrics. Additional tests were ordered by 40.4%; including abdominal radiography (19.5%), barium enema (10.4%), laboratory tests (9.8%), abdominal ultrasound (6.7%), colonoscopy (2.4%), manometry and rectal biopsy (both 1.7%). The most common interventions included lactulose (26.6%), mineral oil (17.5%), polyethylene glycol (14.5%), fiber supplement (9.1%) and milk of magnesia (5.4%). Nutritional guidance (84.8%), fecal disimpaction (17.2%) and toilet training (19.5%) were also indicated. Our results show that pediatricians do not adhere to current recommendations for the management of childhood functional constipation, as unnecessary tests were ordered and the first-line treatment was not prescribed. Copyright © 2016. Publicado por Elsevier Editora Ltda.
Pediatrician's knowledge on the approach of functional constipation
Directory of Open Access Journals (Sweden)
Mario C. Vieira
Full Text Available Abstract Objective: To evaluate the pediatrician's knowledge regarding the diagnostic and therapeutic approach of childhood functional constipation. Methods: A descriptive cross-sectional study was performed with the application of a self-administered questionnaire concerning a hypothetical clinical case of childhood functional constipation with fecal incontinence to physicians (n=297 randomly interviewed at the 36th Brazilian Congress of Pediatrics in 2013. Results: The majority of the participants were females, the mean age was 44.1 years, the mean time of professional practice was 18.8 years; 56.9% were Board Certified by the Brazilian Society of Pediatrics. Additional tests were ordered by 40.4%; including abdominal radiography (19.5%, barium enema (10.4%, laboratory tests (9.8%, abdominal ultrasound (6.7%, colonoscopy (2.4%, manometry and rectal biopsy (both 1.7%. The most common interventions included lactulose (26.6%, mineral oil (17.5%, polyethylene glycol (14.5%, fiber supplement (9.1% and milk of magnesia (5.4%. Nutritional guidance (84.8%, fecal disimpaction (17.2% and toilet training (19.5% were also indicated. Conclusions: Our results show that pediatricians do not adhere to current recommendations for the management of childhood functional constipation, as unnecessary tests were ordered and the first-line treatment was not prescribed.
Evarestov, R A; Losev, M V
2009-12-01
For the first time the convergence of the phonon frequencies and dispersion curves in terms of the supercell size is studied in ab initio frozen phonon calculations on LiF crystal. Helmann-Feynman forces over atomic displacements are found in all-electron calculations with the localized atomic functions (LCAO) basis using CRYSTAL06 program. The Parlinski-Li-Kawazoe method and FROPHO program are used to calculate the dynamical matrix and phonon frequencies of the supercells. For fcc lattice, it is demonstrated that use of the full supercell space group (including the supercell inner translations) enables to reduce essentially the number of the displacements under consideration. For Hartree-Fock (HF), PBE and hybrid PBE0, B3LYP, and B3PW exchange-correlation functionals the atomic basis set optimization is performed. The supercells up to 216 atoms (3 x 3 x 3 conventional unit cells) are considered. The phonon frequencies using the supercells of different size and shape are compared. For the commensurate with supercell k-points the best agreement of the theoretical results with the experimental data is found for B3PW exchange-correlation functional calculations with the optimized basis set. The phonon frequencies at the most non-commensurate k-points converged for the supercell consisting of 4 x 4 x 4 primitive cells and ensures the accuracy 1-2% in the thermodynamic properties calculated (the Helmholtz free energy, entropy, and heat capacity at the room temperature). (c) 2009 Wiley Periodicals, Inc.
Rosolen, A.; Peco, C.; Arroyo, M.
2013-01-01
We present an adaptive meshfree method to approximate phase-field models of biomembranes. In such models, the Helfrich curvature elastic energy, the surface area, and the enclosed volume of a vesicle are written as functionals of a continuous phase-field, which describes the interface in a smeared manner. Such functionals involve up to second-order spatial derivatives of the phase-field, leading to fourth-order Euler–Lagrange partial differential equations (PDE). The solutions develop sharp i...
Functionally informative tag SNP selection using a Pareto-optimal approach.
Lee, Phil Hyoun; Jung, Jae-Yoon; Shatkay, Hagit
2010-01-01
Selecting a representative set of single nucleotide polymorphism (SNP) markers for facilitating association studies is an important step to uncover the genetic basis of human disease. Tag SNP selection and functional SNP selection are the two main approaches for addressing the SNP selection problem. However, little was done so far to effectively combine these distinct and possibly competing approaches. Here, we present a new multiobjective optimization framework for identifying SNPs that are both informative tagging and have functional significance (FS). Our selection algorithm is based on the notion of Pareto optimality, which has been extensively used for addressing multiobjective optimization problems in game theory, economics, and engineering. We applied our method to 34 disease-susceptibility genes for lung cancer and compared the performance with that of other systems which support both tag SNP selection and functional SNP selection methods. The comparison shows that our algorithm always finds a subset of SNPs that improves upon the subset selected by other state-of-the-art systems with respect to both selection objectives.
Directory of Open Access Journals (Sweden)
Lêda Regis
2008-02-01
Full Text Available A new approach to dengue vector surveillance based on permanent egg-collection using a modified ovitrap and Bacillus thuringiensis israelensis(Bti was evaluated in different urban landscapes in Recife, Northeast Brazil. From April 2004 to April 2005, 13 egg-collection cycles of four weeks were carried out. Geo-referenced ovitraps containing grass infusion, Bti and three paddles were placed at fixed sampling stations distributed over five selected sites. Continuous egg-collections yielded more than four million eggs laid into 464 sentinel-ovitraps over one year. The overall positive ovitrap index was 98.5% (over 5,616 trap observations. The egg density index ranged from 100 to 2,500 eggs per trap-cycle, indicating a wide spread and high density of Aedes aegypti (Diptera: Culicidae breeding populations in all sites. Fluctuations in population density over time were observed, particularly a marked increase from January on, or later, according to site. Massive egg-collection carried out at one of the sites prevented such a population outbreak. At intra-site level, egg counts made it possible to identify spots where the vector population is consistently concentrated over the time, pinpointing areas that should be considered high priority for control activities. The results indicate that these could be promising strategies for detecting and preventing Ae. aegypti population outbreaks.
Patenaude, Johane; Legault, Georges-Auguste; Beauvais, Jacques; Bernier, Louise; Béland, Jean-Pierre; Boissy, Patrick; Chenel, Vanessa; Daniel, Charles-Étienne; Genest, Jonathan; Poirier, Marie-Sol; Tapin, Danielle
2015-04-01
The genetically manipulated organism (GMO) crisis demonstrated that technological development based solely on the law of the marketplace and State protection against serious risks to health and safety is no longer a warrant of ethical acceptability. In the first part of our paper, we critique the implicitly individualist social-acceptance model for State regulation of technology and recommend an interdisciplinary approach for comprehensive analysis of the impacts and ethical acceptability of technologies. In the second part, we present a framework for the analysis of impacts and acceptability, devised-with the goal of supporting the development of specific nanotechnological applications-by a team of researchers from various disciplines. At the conceptual level, this analytic framework is intended to make explicit those various operations required in preparing a judgement about the acceptability of technologies that have been implicit in the classical analysis of toxicological risk. On a practical level, we present a reflective tool that makes it possible to take into account all the dimensions involved and understand the reasons invoked in determining impacts, assessing them, and arriving at a judgement about acceptability.
International Nuclear Information System (INIS)
McCulloch, J.P.
2002-01-01
There are five major watersheds in Oakland County. They are the Clinton, Flint, Huron, Rouge and Shiawassee. Included in these watersheds are 61 individual cities, villages and townships. Actions taken by one community within the watershed have a significant impact on other communities in the watershed. Consequently, a multi-community approach needs to be identified and utilized to comprehensively address public health and water quality issues. Some of the issues faced by these communities individually include stormwater management, flooding, drainage, and river and stream management. Failing septic systems, illicit connections causing groundwater contamination, and habitat and wetland degradation are also primary concerns. Finally, wastewater treatment capacity and sanitary sewer service also are regularly dealt with by these communities. Traditionally, short-term solutions to these often urgent problems required the construction of relief sewers or temporary retention structures. Unfortunately, solving the problem in one area often meant the creation of new problems downstream. Coordinating efforts among these 61 individual communities is difficult. These difficult challenges are best met with a coordinated, comprehensive plan. (author)
DEFF Research Database (Denmark)
Nielsen, Henrik Bjørn; Mundy, J.; Willenbrock, Hanni
2007-01-01
for deriving 'Functional Association(s) by Response Overlap' (FARO) between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability...... to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates...
Neethiraj, Ramprasad; Hornett, Emily A; Hill, Jason A; Wheat, Christopher W
2017-10-01
While large-scale genomic approaches are increasingly revealing the genetic basis of polymorphic phenotypes such as colour morphs, such approaches are almost exclusively conducted in species with high-quality genomes and annotations. Here, we use Pool-Seq data for both genome assembly and SNP frequency estimation, followed by scanning for F ST outliers to identify divergent genomic regions. Using paired-end, short-read sequencing data from two groups of individuals expressing divergent phenotypes, we generate a de novo rough-draft genome, identify SNPs and calculate genomewide F ST differences between phenotypic groups. As genomes generated by Pool-Seq data are highly fragmented, we also present an approach for super-scaffolding contigs using existing protein-coding data sets. Using this approach, we reanalysed genomic data from two recent studies of birds and butterflies investigating colour pattern variation and replicated their core findings, demonstrating the accuracy and power of a Pool-Seq-only approach. Additionally, we discovered new regions of high divergence and new annotations that together suggest novel parallels between birds and butterflies in the origins of their colour pattern variation. © 2017 John Wiley & Sons Ltd.
Gisquet-Verrier, Pascale; Tolédano, Daniel; Le Dorze, Claire
2017-06-01
Post-traumatic stress disorder (PTSD) and addiction to drugs of abuse are two common diseases, showing high comorbidity rates. This review presents a number of evidence showing similarities between these two pathologies, especially the hyper-responsiveness to environmental cues inducing a reactivation of the target memory leading either to re-experiencing (PTSD), or drug craving. Accordingly, PTSD and addiction to drug of abuse might by considered as memory pathologies, underlined by the same physiological process. We propose that these two pathologies rely on an uncoupling of the monoaminergic systems. According to this hypothesis, exposure to extreme conditions, either negative (trauma) or positive (drugs) induced a loss of the reciprocal control that one system usually exerts on the other monoaminergic system, resulting to an uncoupling between the noradrenergic and the serotonergic systems. Results obtained in our laboratory, using animal models of these pathologies, demonstrate that after a trauma, such as after repeated drug injections, rats developed both a behavioral sensitization (increases of the locomotion in response to a stimulation of the monoaminergic systems) and a pharmacological sensitization (increases of noradrenergic release within the prefrontal cortex). These results support our hypothesis and led us to propose new and innovative therapeutic approaches consisting either to induce a re-coupling of the monoaminergic systems, or to modify the pathological memories by using an emotional memory remodeling. Extremely encouraging results have already been obtained in rats and in humans, opening new and promising therapeutic avenues. Copyright © 2016 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.
Directory of Open Access Journals (Sweden)
Galieva Аnna B.
2018-01-01
Full Text Available This paper presents the issues of the inspection, creation of drawings and 3D model of the building in the absence thereof a technical documentation for the object of reconstruction. An approach based on the use of laser scanning technologies and information modeling of objects is proposed. The laser scanning of facades of residential buildings, objects of cultural heritage, industrial enterprises is considered. The proposed approach makes it possible to improve safety during the work on the inspection of building structures, to execute a construction project drawings and specifications with the maximum degree of detail. On the basis of the created three-dimensional model of the object it is possible to subsequently make a static calculation of the building’s structures.
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O. O. Matusevich
2014-06-01
maintenance and repairing of the equipment of traction substations, power points and sectioning posts of the electrified railways "CE-0024", this approach for organizing and conducting the maintenance and repairing of the TS is not considered. Practical value. Implementation of this system allows: to increase the main indicators of maintenance and repairing; decrease operating costs of the power equipment by using maintenance and repairing at a basis of the actual technical state; improve the reliability of equipment and the power supply system of TS of electrified railways, obtain economic benefit, and so on.
Directory of Open Access Journals (Sweden)
Mićanović Veselin
2015-01-01
Full Text Available The paper deals with the cognitivist approach to the development of functional thinking from the period of preschool and early school age. Some recent scientific results on the capacity of child's brain undoubtedly indicate the fact that the experience that children receive on a daily basis, the way they receive and respond to the outside impressions and the stimuli to which they react shape their brain and influence the development of their general personality. A continuous fight for dominance takes place among the brain neurons, the result of which is creation the new connections between active neurons and new brain controls. The principal intention of the author is to stress the importance of a correct approach to an early-age development at the point of which the most intense development of the brain cells takes place and the paths for the total development of personality are traced out. Therefore, what happens to a child in this period is consequential for further development. The goal of this work is to stress that total cognitive development is conditioned by the development thinking at an early age. Therefore, the way we stimulate the child's functional thinking at an early pre-school age is extremely important and requires a more serious approach. Logical tasks and problem-solving situations are of special importance for the development of logical cognitive structures. The child's natural and social environments stimulate several sensory cooperative activities and increase the impact on perception, thus increasing a number of synapses. A methodological approach to activities to result in a functional thinking of children at an early age should be developed in such a way as to satisfy some higher demands than is the case with the current ones, i.e. it should stimulate children's further cognitive development.
Baddari, Kamel; Makdeche, Said; Bellalem, Fouzi
2013-02-01
Based on the moment magnitude scale, a probabilistic model was developed to predict the occurrences of strong earthquakes in the seismoactive area of Zemmouri, Algeria. Firstly, the distributions of earthquake magnitudes M i were described using the distribution function F 0(m), which adjusts the magnitudes considered as independent random variables. Secondly, the obtained result, i.e., the distribution function F 0(m) of the variables M i was used to deduce the distribution functions G(x) and H(y) of the variables Y i = Log M 0,i and Z i = M 0,i , where (Y i)i and (Z i)i are independent. Thirdly, some forecast for moments of the future earthquakes in the studied area is given.
Robotic approaches for rehabilitation of hand function after stroke.
Lum, Peter S; Godfrey, Sasha B; Brokaw, Elizabeth B; Holley, Rahsaan J; Nichols, Diane
2012-11-01
The goal of this review was to discuss the impairments in hand function after stroke and present previous work on robot-assisted approaches to movement neurorehabilitation. Robotic devices offer a unique training environment that may enhance outcomes beyond what is possible with conventional means. Robots apply forces to the hand, allowing completion of movements while preventing inappropriate movement patterns. Evidence from the literature is emerging that certain characteristics of the human-robot interaction are preferable. In light of this evidence, the robotic hand devices that have undergone clinical testing are reviewed, highlighting the authors' work in this area. Finally, suggestions for future work are offered. The ability to deliver therapy doses far higher than what has been previously tested is a potentially key advantage of robotic devices that needs further exploration. In particular, more efforts are needed to develop highly motivating home-based devices, which can increase access to high doses of assisted movement therapy.
CLARM: An integrative approach for functional modules discovery
Salem, Saeed M.
2011-01-01
Functional module discovery aims to find well-connected subnetworks which can serve as candidate protein complexes. Advances in High-throughput proteomic technologies have enabled the collection of large amount of interaction data as well as gene expression data. We propose, CLARM, a clustering algorithm that integrates gene expression profiles and protein protein interaction network for biological modules discovery. The main premise is that by enriching the interaction network by adding interactions between genes which are highly co-expressed over a wide range of biological and environmental conditions, we can improve the quality of the discovered modules. Protein protein interactions, known protein complexes, and gene expression profiles for diverse environmental conditions from the yeast Saccharomyces cerevisiae were used for evaluate the biological significance of the reported modules. Our experiments show that the CLARM approach is competitive to wellestablished module discovery methods. Copyright © 2011 ACM.
International Nuclear Information System (INIS)
Meenakshisundaram, V.; Jose, M. T.
2008-01-01
detector for gas activity monitors (unique for FBRs) should be compensated type ion chambers and not the NaI(T1) based ones, the energy threshold criteria for the installed radiation monitors meant for detection of primary sodium, further possibility of reduction in man-rem expenditure etc., are presented. The experiences gained would serve as a guide for a safe approach and in determining the criteria from the point of view of radiation protection for future LMFBRs. (author)
Promoting a functional macroinvertebrate approach in the biomonitoring of Italian lotic systems
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Richard W. Merritt
2016-06-01
Full Text Available Over fifty years of research on freshwater macroinvertebrates has been driven largely by the state of the taxonomy of these organisms. Significant advances have been and continue to be made in developing ever more refined keys to macroinvertebrate groups. When advances in macroinvertebrate ecological research are restricted by the level of detail in identifications, then analysis by function is a viable alternative. The focus on function, namely adaptations of macroinvertebrates to habitats and the utilization of food resources, has facilitated ecological evaluation of freshwater ecosystems. This classification is based not on what insects eat, but how they obtain their food. These categories are called 'functional feeding groups', as the name implies, denoting their functional role when describing how and where they feed. This is the basis for the functional feeding group (FFG method that was initially developed in the early 1960s. Taxonomy is applied only to the level of detail that allows assignment to one of five functional feeding group categories: detrital shredders, scrapers, filtering collectors, gatherers, and predators. The aim of this short communication, originating from the presentation of R.W. Merritt at the Biomonitoring Symposium in Rome, 2015, is to promote the use of a functional approach in biomonitoring, especially in Italian and European lotic systems. Here, we present two case studies and we discuss the advantages of the method, especially considering the great availability of quantitative data on macroinvertebrates after the implementation of the WFD 2000/60. We are confident that the increase of functional assessment of ecosystem attributes could have important and direct repercussions in the understanding and management of running waters.
Energy Technology Data Exchange (ETDEWEB)
Joseph Ivanic; Gregory J. Atchity; Klaus Ruedenberg
2007-02-12
A coherent, intrinsic, basis-set-independent analysis is developed for the invariants of the first-order density matrix of an accurate molecular electronic wavefunction. From the hierarchical ordering of the natural orbitals, the zeroth-order orbital space is deduced, which generates the zeroth-order wavefunction, typically an MCSCF function in the full valence space. It is shown that intrinsically embedded in such wavefunctions are elements that are local in bond regions and elements that are local in atomic regions. Basis-set-independent methods are given that extract and exhibit the intrinsic bond orbitals and the intrinsic minimal-basis quasi-atomic orbitals in terms of which the wavefunction can be exactly constructed. The quasi-atomic orbitals are furthermore oriented by a basis-set independent method (viz. maximization of the sum of the fourth powers of all off-diagonal density matrix elements) so as to exhibit clearly the chemical interactions. The unbiased nature of the method allows for the adaptation of the localized and directed orbitals to changing geometries.
Convergent approaches for defining functional imaging endophenotypes in schizophrenia
Directory of Open Access Journals (Sweden)
Godfrey Pearlson
2009-11-01
Full Text Available In complex genetic disorders such as schizophrenia, endophenotypes have potential utility both in identifying risk genes and in illuminating pathophysiology. This is due to their presumed status as closer in the etiopathological pathway to the causative genes than is the currently defining clinical phenomenology of the illness and thus their simpler genetic architecture than that of the full syndrome. There, many genes conferring slight individual risk are additive or epistatic (interactive with regard to cumulative schizophrenia risk. In addition the use of endophenotypes has encouraged a conceptual shift away from the exclusive study of categorical diagnoses in manifestly ill patients, towards the study of quantitative traits in patients, unaffected relatives and healthy controls. A more recently employed strategy is thus to study unaffected first degree relatives of schizophrenia patients, who share some of the genetic diathesis without illness-related confounds that may themselves impact fMRI task performance. Consistent with the multiple biological abnormalities associated with the disorder, many candidate endophenotypes have been advanced for schizophrenia, including measures derived from structural brain imaging, EEG, sensorimotor integration, eye movements and cognitive performance (Allen 2009, but recent data derived from quantitative functional brain imaging measures present additional attractive putative endophenotypes. We will review two major, conceptually different approaches that use fMRI in this context. One, the dominant paradigm, employs defined cognitive tasks on which schizophrenia patients perform poorly as “cognitive stress tests”. The second uses very simple probes or “task-free” approaches where performance in patients and controls is equal. We explore the potential advantages and disadvantages of each method, the associated data analytic approaches and recent studies exploring their interface with the genetic
Zanin, Elia; Riva, Marco; Bambini, Valentina; Cappa, Stefano F; Magrassi, Lorenzo; Moro, Andrea
2017-09-01
A wide range of studies on language assessment during awake brain surgery is nowadays available. Yet, a consensus on a standardized protocol for intraoperative language mapping is still lacking. More specifically, very limited information is offered about intraoperative assessment of a crucial component of language such as syntax. This review aims at critically analyzing the intraoperative studies investigating the cerebral basis of syntactic processing. A comprehensive query was performed on the literature, returning a total of 18 studies. These papers were analyzed according to two complementary criteria, based on the distinction between morphosyntax and syntax. The first criterion focused on the tasks and stimuli employed intraoperatively. Studies were divided into three different groups: group 1 included those studies that overtly aimed at investigating morphosyntactic processes; group 2 included studies that did not explicitly focus on syntax, yet employed stimuli requiring morphosyntactic processing; and group 3 included studies reporting some generic form of syntactic deficit, although not further investigated. The second criterion focused on the syntactic structures of the sentences assessed intraoperatively, analyzing the canonicity of sentence structure (i.e., canonical versus non-canonical word order). The global picture emerging from our analysis indicates that what was investigated in the intraoperative literature is morphosyntactic processing, rather than pure syntax. The study of the neurobiology of syntax during awake surgery seems thus to be still at an early stage, in need of systematic, linguistically grounded investigations.
Energy Technology Data Exchange (ETDEWEB)
Li, Minjing [School; Qian, Wei-jun [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Gao, Yuqian [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Shi, Liang [School; Liu, Chongxuan [Pacific Northwest National Laboratory, Richland, Washington 99354, United States; School
2017-09-28
The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates
A Model-Based Approach to Constructing Music Similarity Functions
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Lamere Paul
2007-01-01
Full Text Available Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
Network approaches to the functional analysis of microbial proteins.
Hallinan, J S; James, K; Wipat, A
2011-01-01
Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes. Copyright © 2011 Elsevier Ltd. All rights reserved.
Lee-Tobin, Peta A; Ogeil, Rowan P; Savic, Michael; Lubman, Dan I
2017-11-15
Sleep applications (apps) have proliferated in online spaces, but few studies have examined the validity of the information contained within the apps. This study aimed to examine the information and functions found within sleep apps, determine if the information is based on empirical evidence, and whether or not user ratings were affected by these factors. Sleep apps found in the Google Play store (n = 76) were coded using content analysis to examine the types of information, functions, and evidence base of each app. Only 32.9% of sleep apps contained empirical evidence supporting their claims, 15.8% contained clinical input, and 13.2% contained links to sleep literature. Apps also contained information on how sleep is affected by alcohol or drugs (23.7%), food (13.2%), daily activities (13.2), and stress (13.2%). A mean difference in average user rating was found between apps that contained at least one source of information compared those that did not. App user ratings were not associated with an app having multiple functions, or from an app drawing on multiple sources of evidence (except for sleep literature only). Last, there was a higher average user rating among apps that contained a sleep tip function. Sleep apps are increasingly popular, demonstrated by the large number of downloads in the Google Play store. Users favored apps that contained sleep tips; however, these tips and other information in the apps were generally not based on empirical evidence. Future research in the area of sleep apps should consider constructing sleep apps derived from empirical evidence and examining their effectiveness. © 2017 American Academy of Sleep Medicine
Energy Technology Data Exchange (ETDEWEB)
Steinbeck, T.; Rohr, J. [m.u.t. GmbH, Wedel (Germany)
2005-06-01
Quantum cascade lasers represent an almost ideal light source for infrared gas analysis. They allow sensitive and selective measurements in the mid-infrared. The detection of combustion gases for early fire detection represents an interesting field of application, where further technologic benefits are shown to advantage. The focus of this report is on the technical realization of a functional model and the electronic components. (orig.)
Directory of Open Access Journals (Sweden)
Xiao-Bing eGao
2015-10-01
Full Text Available The neuronal system that resides in the perifornical and lateral hypothalamus (Pf/LH and synthesizes the neuropeptide hypocretin/orexin participates in critical brain functions across species from fish to human. The hypocretin system regulates neural activity responsible for daily functions (such as sleep/wake homeostasis, energy balance, appetite, etc and long-term behavioral changes (such as reward seeking and addiction, stress response, etc in animals. The most recent evidence suggests that the hypocretin system undergoes substantial plastic changes in response to both daily fluctuations (such as food intake and sleep-wake regulation and long-term changes (such as cocaine seeking in neuronal activity in the brain. The understanding of these changes in the hypocretin system is essential in addressing the role of the hypocretin system in normal physiological functions and pathological conditions in animals and humans. In this review, the evidence demonstrating that neural plasticity occurs in hypocretin-containing neurons in the Pf/LH will be presented and possible physiological behavioral, and mental health implications of these findings will be discussed.
Gao, Xiao-Bing; Hermes, Gretchen
2015-01-01
The neuronal system that resides in the perifornical and lateral hypothalamus (Pf/LH) and synthesizes the neuropeptide hypocretin/orexin participates in critical brain functions across species from fish to human. The hypocretin system regulates neural activity responsible for daily functions (such as sleep/wake homeostasis, energy balance, appetite, etc.) and long-term behavioral changes (such as reward seeking and addiction, stress response, etc.) in animals. The most recent evidence suggests that the hypocretin system undergoes substantial plastic changes in response to both daily fluctuations (such as food intake and sleep-wake regulation) and long-term changes (such as cocaine seeking) in neuronal activity in the brain. The understanding of these changes in the hypocretin system is essential in addressing the role of the hypocretin system in normal physiological functions and pathological conditions in animals and humans. In this review, the evidence demonstrating that neural plasticity occurs in hypocretin-containing neurons in the Pf/LH will be presented and possible physiological, behavioral, and mental health implications of these findings will be discussed. PMID:26539086
From Process Understanding Via Soil Functions to Sustainable Soil Management - A Systemic Approach
Wollschlaeger, U.; Bartke, S.; Bartkowski, B.; Daedlow, K.; Helming, K.; Kogel-Knabner, I.; Lang, B.; Rabot, E.; Russell, D.; Stößel, B.; Weller, U.; Wiesmeier, M.; Rabot, E.; Vogel, H. J.
2017-12-01
Fertile soils are central resources for the production of biomass and the provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for both, food and bio-energy, which requires preserving and improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained: filter for clean water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these soil functions result from the interaction of a multitude of physical, chemical and biological processes that are not yet sufficiently understood. In addition, we lack understanding about the interplay between the socio-economic system and the soil system and how soil functions benefit human wellbeing. Hence, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management to finally be able to develop site-specific options for sustainable soil management. We present an integrated modeling approach that investigates the influence of soil management on the ensemble of soil functions. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. As the evidence base required for feeding the model is for the most part stored in the existing scientific literature, another central component of our work is to set up a public "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive knowledge base on soil processes as a basis for model developments. The connection to the socio-economic system is established using the Drivers-Pressures-Impacts-States-Responses (DPSIR) framework where our improved understanding about soil ecosystem processes is linked to ecosystem services and resource efficiency via the soil functions.
RENAL FUNCTION TEST ON THE BASIS OF SERUM CREATININE AND UREA IN TYPE-2 DIABETICS AND NONDIABETICS
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P. Singh
2014-01-01
Full Text Available Background: Type-2 diabetes mellitus has quickly become a global health problem due to rapidly increasing population growth, aging, urbanization and increasing prevalence of obesity and physical inactivity. Diabetic nephropathy is one of the major causes of chronic renal failure. Both serum urea and creatinine are widely used to assess the function of kidney. This study was conducted to observe the impaired renal function in type 2 diabetics and compare with non-diabetics controls. Method: To determine the incidence of renal dysfunction in diabetics in Nepalgunj medical college and Hospital , Nepalgunj , Banke, Nepal , blood samples from 100 diabetic subjects and 100 non-diabetic controls were taken between the period 1st February , 2012 to 31st January , 2013 for investigation of plasma glucose fasting(FPG, blood urea and serum creatinine. These biochemical parameters were determined by using a fully automated clinical chemistry analyzer. Results: Our findings showed that the level of blood urea (P<0.0001, 95%Cl and serum creatinine (P≈0.0004,95%Cl were significantly higher in type 2 diabetics as compared to non-diabetics in both male and female. There was no significant difference between diabetic male and female. 15 out of 100 diabetes samples have high urea level whereas 7 out of 100 had increased creatinine level. In control only 3 samples had high urea value and 1 had high creatinine level. There was statistical signiﬁcant increased in urea level with increased in blood sugar level. Conclusion: Blood urea and creatinine is widely accepted to assess the renal functions. Good control of blood glucose level is absolute requirement to prevent progressive renal impairment.
Feierstein, C E; Portugues, R; Orger, M B
2015-06-18
In recent years, the zebrafish has emerged as an appealing model system to tackle questions relating to the neural circuit basis of behavior. This can be attributed not just to the growing use of genetically tractable model organisms, but also in large part to the rapid advances in optical techniques for neuroscience, which are ideally suited for application to the small, transparent brain of the larval fish. Many characteristic features of vertebrate brains, from gross anatomy down to particular circuit motifs and cell-types, as well as conserved behaviors, can be found in zebrafish even just a few days post fertilization, and, at this early stage, the physical size of the brain makes it possible to analyze neural activity in a comprehensive fashion. In a recent study, we used a systematic and unbiased imaging method to record the pattern of activity dynamics throughout the whole brain of larval zebrafish during a simple visual behavior, the optokinetic response (OKR). This approach revealed the broadly distributed network of neurons that were active during the behavior and provided insights into the fine-scale functional architecture in the brain, inter-individual variability, and the spatial distribution of behaviorally relevant signals. Combined with mapping anatomical and functional connectivity, targeted electrophysiological recordings, and genetic labeling of specific populations, this comprehensive approach in zebrafish provides an unparalleled opportunity to study complete circuits in a behaving vertebrate animal. Copyright © 2014. Published by Elsevier Ltd.
Czech Academy of Sciences Publication Activity Database
Li, F.; Wang, L.; Zhao, J.; Xie, J. R. H.; Riley, Kevin Eugene; Chen, Z.
2011-01-01
Roč. 130, 2/3 (2011), s. 341-352 ISSN 1432-881X Institutional research plan: CEZ:AV0Z40550506 Keywords : water cluster * density functional theory * MP2 . CCSD(T) * basis set * relative energies Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.162, year: 2011
Li, Ranran; Lai, Youzhi; Zhang, Yumei; Yao, Li; Wu, Xia
2017-01-01
Leukoaraiosis (LA) describes diffuse white matter abnormalities apparent in computed tomography (CT) or magnetic resonance (MR) brain scans. Patients with LA generally show varying degrees of cognitive impairment, which can be classified as cognitively normal (CN), mild cognitive impairment (MCI), and dementia. However, a consistent relationship between the degree of LA and the level of cognitive impairment has not yet been established. We used functional magnetic resonance imaging (fMRI) to explore possible neuroimaging biomarkers for classification of cognitive level in LA. Functional connectivity (FC) between brain regions was calculated using Pearson's correlation coefficient (PCC), maximal information coefficient (MIC), and extended maximal information coefficient (eMIC). Next, FCs with high discriminative power for different cognitive levels in LA were used as features for classification based on support vector machine. CN and MCI were classified with accuracies of 75.0, 61.9, and 91.1% based on features from PCC, MIC, and eMIC, respectively. MCI and dementia were classified with accuracies of 80.1, 86.2, and 87.4% based on features from PCC, MIC, and eMIC, respectively. CN and dementia were classified with accuracies of 80.1, 89.9, and 94.4% based on features from PCC, MIC, and eMIC, respectively. Our results suggest that features extracted from fMRI were efficient for classification of cognitive impairment level in LA, especially, when features were based on a non-linear method (eMIC).
Wang, Shujun; Wang, Jinrong; Yu, Jinglin; Wang, Shuo
2016-01-01
The effects of three saturated fatty acids on functional properties of normal wheat and waxy wheat starches were investigated. The complexing index (CI) of normal wheat starch-fatty acid complexes decreased with increasing carbon chain length. In contrast, waxy wheat starch-fatty acid complexes presented much lower CI. V-type crystalline polymorphs were formed between normal wheat starch and three fatty acids, with shorter chain fatty acids producing more crystalline structure. FTIR and Raman spectroscopy presented the similar results with XRD. The formation of amylose-fatty acid complex inhibited granule swelling, gelatinization progression, retrogradation and pasting development of normal wheat starch, with longer chain fatty acids showing greater inhibition. Amylopectin can also form complexes with fatty acids, but the amount of complex was too little to be detected by XRD, FTIR, Raman and DSC. As a consequence, small changes were observed in the functional properties of waxy wheat starch with the addition of fatty acids. Copyright © 2015 Elsevier Ltd. All rights reserved.
Chebyshev matrix product state approach for spectral functions
Holzner, Andreas; Weichselbaum, Andreas; McCulloch, Ian P.; Schollwöck, Ulrich; von Delft, Jan
2011-05-01
We show that recursively generated Chebyshev expansions offer numerically efficient representations for calculating zero-temperature spectral functions of one-dimensional lattice models using matrix product state (MPS) methods. The main features of this Chebyshev matrix product state (CheMPS) approach are as follows: (i) it achieves uniform resolution over the spectral function’s entire spectral width; (ii) it can exploit the fact that the latter can be much smaller than the model’s many-body bandwidth; (iii) it offers a well-controlled broadening scheme that allows finite-size effects to be either resolved or smeared out, as desired; (iv) it is based on using MPS tools to recursively calculate a succession of Chebyshev vectors |tn>, (v) the entanglement entropies of which were found to remain bounded with increasing recursion order n for all cases analyzed here; and (vi) it distributes the total entanglement entropy that accumulates with increasing n over the set of Chebyshev vectors |tn>, which need not be combined into a single vector. In this way, the growth in entanglement entropy that usually limits density matrix renormalization group (DMRG) approaches is packaged into conveniently manageable units. We present zero-temperature CheMPS results for the structure factor of spin-(1)/(2) antiferromagnetic Heisenberg chains and perform a detailed finite-size analysis. Making comparisons to three benchmark methods, we find that CheMPS (a) yields results comparable in quality to those of correction-vector DMRG, at dramatically reduced numerical cost; (b) agrees well with Bethe ansatz results for an infinite system, within the limitations expected for numerics on finite systems; and (c) can also be applied in the time domain, where it has potential to serve as a viable alternative to time-dependent DMRG (in particular, at finite temperatures). Finally, we present a detailed error analysis of CheMPS for the case of the noninteracting resonant level model.
Deakyne, Julianna S; Malecka, Kimberly A; Messick, Troy E; Lieberman, Paul M
2017-10-01
Epstein-Barr virus (EBV) establishes a stable latent infection that can persist for the life of the host. EBNA1 is required for the replication, maintenance, and segregation of the latent episome, but the structural features of EBNA1 that confer each of these functions are not completely understood. Here, we have solved the X-ray crystal structure of an EBNA1 DNA-binding domain (DBD) and discovered a novel hexameric ring oligomeric form. The oligomeric interface pivoted around residue T585 as a joint that links and stabilizes higher-order EBNA1 complexes. Substitution mutations around the interface destabilized higher-order complex formation and altered the cooperative DNA-binding properties of EBNA1. Mutations had both positive and negative effects on EBNA1-dependent DNA replication and episome maintenance with OriP. We found that one naturally occurring polymorphism in the oligomer interface (T585P) had greater cooperative DNA binding in vitro , minor defects in DNA replication, and pronounced defects in episome maintenance. The T585P mutant was compromised for binding to OriP in vivo as well as for assembling the origin recognition complex subunit 2 (ORC2) and trimethylated histone 3 lysine 4 (H3K4me3) at OriP. The T585P mutant was also compromised for forming stable subnuclear foci in living cells. These findings reveal a novel oligomeric structure of EBNA1 with an interface subject to naturally occurring polymorphisms that modulate EBNA1 functional properties. We propose that EBNA1 dimers can assemble into higher-order oligomeric structures important for diverse functions of EBNA1. IMPORTANCE Epstein-Barr virus is a human gammaherpesvirus that is causally associated with various cancers. Carcinogenic properties are linked to the ability of the virus to persist in the latent form for the lifetime of the host. EBNA1 is a sequence-specific DNA-binding protein that is consistently expressed in EBV tumors and is the only viral protein required to maintain the viral
Directory of Open Access Journals (Sweden)
Jaime Alberto Echeverri Arias
2009-07-01
Full Text Available La eliminación del ruido impulsivo es un problema clásico del procesado no lineal para el mejoramiento de imágenes y las funciones de base radial de soporte global son útiles para enfrentarlo. Este trabajo presenta una técnica de interpolación que disminuye eficientemente el ruido impulsivo en imágenes, mediante el uso de interpolante obtenido por funciones de base radial en el marco de la investigación enfocada en el desarrollo de un Sistema de recuperación de imágenes de recursos acuáticos amazónicos. Esta técnica primero etiqueta los píxeles de la imagen que son ruidosos y, mediante la interpolación, genera un valor de reconstrucción de dicho píxel usando sus vecinos. Los resultados obtenidos son comparables y muchas veces mejores que otras técnicas ya publicadas y reconocidas. Según el análisis de resultados, se puede aplicar a imágenes con altas tasas de ruido, manteniendo un bajo error de reconstrucción de los píxeles "ruidosos", así como la calidad visual.Global support radial base functions are effective in eliminating impulsive noise in non-linear processing. This paper introduces an interpolation technique which efficiently reduces image impulsive noise by means of an interpolant obtained through radial base functions. These functions have been used in a research project designed to develop a system for the recovery of images of Amazonian aquatic resources. This technique starts with the tagging by interpolation of noisy image pixels. Thus, a value of reconstruction for the noisy pixels is generated using neighboring pixels. The results obtained with this technique have proved comparable and often better than those obtained with previously known techniques. According to results analysis, this technique can be successfully applied on images with high noise levels. The results are low error in noisy pixel reconstruction and better visual quality.
Executive Function and Food Approach Behavior in Middle Childhood
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Karoline eGroppe
2014-05-01
Full Text Available Executive function (EF has long been considered to be a unitary, domain-general cognitive ability. However, recent research suggests differentiating ‘hot’ affective and ‘cool’ cognitive aspects of EF. Yet, findings regarding this two-factor construct are still inconsistent. In particular, the development of this factor structure remains unclear and data on school-aged children is lacking. Furthermore, studies linking EF and overweight or obesity suggest that EF contributes to the regulation of eating behavior. So far, however, the links between EF and eating behavior have rarely been investigated in children and non-clinical populations.First, we examined whether EF can be divided into hot and cool factors or whether they actually correspond to a unitary construct in middle childhood. Second, we examined how hot and cool EF are associated with different eating styles that put children at risk of becoming overweight during development. Hot and cool EF were assessed experimentally in a non-clinical population of 1,657 elementary-school children (aged 6-11 years. The ‘food approach’ behavior was rated mainly via parent questionnaires.Findings indicate that hot EF is distinguishable from cool EF. However, only cool EF seems to represent a coherent functional entity, whereas hot EF does not seem to be a homogenous construct. This was true for a younger and an older subgroup of children. Furthermore, different EF components were correlated with eating styles, such as responsiveness to food, desire to drink, and restrained eating in girls but not in boys. This shows that lower levels of EF are not only seen in clinical populations of obese patients but are already associated with food approach styles in a normal population of elementary school-aged girls. Although the direction of effect still has to be clarified, results point to the possibility that EF constitutes a risk factor for eating styles contributing to the development of
Molecular basis for the functions of a bacterial MutS2 in DNA repair and recombination.
Wang, Ge; Maier, Robert J
2017-09-01
Bacterial MutS2 proteins, consisting of functional domains for ATPase, DNA-binding, and nuclease activities, play roles in DNA recombination and repair. Here we observe a mechanism for generating MutS2 expression diversity in the human pathogen Helicobacter pylori, and identify a unique MutS2 domain responsible for specific DNA-binding. H. pylori strains differ in mutS2 expression due to variations in the DNA upstream sequence containing short sequence repeats. Based on Western blots, mutS2 in some strains appears to be co-translated with the upstream gene, but in other strains (e.g. UA948) such translational coupling does not occur. Accordingly, strain UA948 had phenotypes similar to its ΔmutS2 derivative, whereas expression of MutS2 at a separate locus in UA948 (the genetically complemented strain) displayed a lower mutation rate and lower transformation frequency than did ΔmutS2. A series of truncated HpMutS2 proteins were purified and tested for their specific abilities to bind 8-oxoG-containing DNA (GO:C) and Holiday Junction structures (HJ). The specific DNA binding domain was localized to an area adjacent to the Smr nuclease domain, and it encompasses 30-amino-acid-residues containing a "KPPKNKFKPPK" motif. Gel shift assays and competition assays supported that a truncated version of HpMutS2-C12 (∼12kDa protein containing the specific DNA-binding domain) has much greater capacity to bind to HJ or GO:C DNA than to normal double stranded DNA. By studying the in vivo roles of the separate domains of HpMutS2, we observed that the truncated versions were unable to complement the ΔmutS2 strain, suggesting the requirement for coordinated function of all the domains in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Avery, John Scales; Rettrup, Sten; Avery, James Emil
In theoretical physics, theoretical chemistry and engineering, one often wishes to solve partial differential equations subject to a set of boundary conditions. This gives rise to eigenvalue problems of which some solutions may be very difficult to find. For example, the problem of finding...... in such problems can be much reduced by making use of symmetry-adapted basis functions. The conventional method for generating symmetry-adapted basis sets is through the application of group theory, but this can be difficult. This book describes an easier method for generating symmetry-adapted basis sets...
Valdes, Felipe
2011-04-01
A new high-order Calderón multiplicative preconditioner (HO-CMP) for the electric field integral equation (EFIE) is presented. In contrast to previous CMPs, the proposed preconditioner allows for high-order surface representations and current expansions by using a novel set of high-order quasi curl-conforming basis functions. Like its predecessors, the HO-CMP can be seamlessly integrated into existing EFIE codes. Numerical results demonstrate that the linear systems of equations obtained using the proposed HO-CMP converge rapidly, regardless of the mesh density and of the order of the current expansion. © 2006 IEEE.
Selectionist and evolutionary approaches to brain function: a critical appraisal
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Chrisantha Thomas Fernando
2012-04-01
Full Text Available We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity and variability as the most powerful mechanism in a sparsely occupied search space. Examples of why parallel competitive search with information transfer among the units is efficient are given. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise.
Harnessing systems biology approaches to engineer functional microvascular networks.
Sefcik, Lauren S; Wilson, Jennifer L; Papin, Jason A; Botchwey, Edward A
2010-06-01
Microvascular remodeling is a complex process that includes many cell types and molecular signals. Despite a continued growth in the understanding of signaling pathways involved in the formation and maturation of new blood vessels, approximately half of all compounds entering clinical trials will fail, resulting in the loss of much time, money, and resources. Most pro-angiogenic clinical trials to date have focused on increasing neovascularization via the delivery of a single growth factor or gene. Alternatively, a focus on the concerted regulation of whole networks of genes may lead to greater insight into the underlying physiology since the coordinated response is greater than the sum of its parts. Systems biology offers a comprehensive network view of the processes of angiogenesis and arteriogenesis that might enable the prediction of drug targets and whether or not activation of the targets elicits the desired outcome. Systems biology integrates complex biological data from a variety of experimental sources (-omics) and analyzes how the interactions of the system components can give rise to the function and behavior of that system. This review focuses on how systems biology approaches have been applied to microvascular growth and remodeling, and how network analysis tools can be utilized to aid novel pro-angiogenic drug discovery.
Remodeling Functional Connectivity in Multiple Sclerosis: A Challenging Therapeutic Approach
Directory of Open Access Journals (Sweden)
Mario Stampanoni Bassi
2017-12-01
Full Text Available Neurons in the central nervous system are organized in functional units interconnected to form complex networks. Acute and chronic brain damage disrupts brain connectivity producing neurological signs and/or symptoms. In several neurological diseases, particularly in Multiple Sclerosis (MS, structural imaging studies cannot always demonstrate a clear association between lesion site and clinical disability, originating the “clinico-radiological paradox.” The discrepancy between structural damage and disability can be explained by a complex network perspective. Both brain networks architecture and synaptic plasticity may play important roles in modulating brain networks efficiency after brain damage. In particular, long-term potentiation (LTP may occur in surviving neurons to compensate network disconnection. In MS, inflammatory cytokines dramatically interfere with synaptic transmission and plasticity. Importantly, in addition to acute and chronic structural damage, inflammation could contribute to reduce brain networks efficiency in MS leading to worse clinical recovery after a relapse and worse disease progression. These evidence suggest that removing inflammation should represent the main therapeutic target in MS; moreover, as synaptic plasticity is particularly altered by inflammation, specific strategies aimed at promoting LTP mechanisms could be effective for enhancing clinical recovery. Modulation of plasticity with different non-invasive brain stimulation (NIBS techniques has been used to promote recovery of MS symptoms. Better knowledge of features inducing brain disconnection in MS is crucial to design specific strategies to promote recovery and use NIBS with an increasingly tailored approach.
de Lima, Andrea Cristina; de Azevedo Neto, Raymundo Machado; Teixeira, Luis Augusto
2010-10-01
In order to evaluate the effects of uncertainty about direction of mechanical perturbation and supra-postural task constraint on postural control, young adults had their upright stance perturbed while holding a tray in a horizontal position. Stance was perturbed by moving forward or backward a supporting platform, contrasting situations of certainty versus uncertainty of direction of displacement. Increased constraint on postural stability was imposed by a supra-postural task of equilibrating a cylinder on the tray. Performance was assessed through EMG of anterior leg muscles, angular displacement of the main joints involved in the postural reactions and displacement of the tray. Results showed that both certainty on the direction of perturbation and increased supra-postural task constraint led to decreased angular displacement of the knee and the hip. Furthermore, combination of certainty and high supra-postural task constraint produced shorter latency of muscular activation. Such postural responses were paralleled by decreased displacement of the tray. These results suggest a functional integration between the tasks, with central set priming reactive postural responses from contextual cues and increased stability demand. Copyright © 2010 Elsevier B.V. All rights reserved.
The overlapped radial basis function-finite difference (RBF-FD) method: A generalization of RBF-FD
Shankar, Varun
2017-08-01
We present a generalization of the RBF-FD method that computes RBF-FD weights in finite-sized neighborhoods around the centers of RBF-FD stencils by introducing an overlap parameter δ ∈ (0 , 1 ] such that δ = 1 recovers the standard RBF-FD method and δ = 0 results in a full decoupling of stencils. We provide experimental evidence to support this generalization, and develop an automatic stabilization procedure based on local Lebesgue functions for the stable selection of stencil weights over a wide range of δ values. We provide an a priori estimate for the speedup of our method over RBF-FD that serves as a good predictor for the true speedup. We apply our method to parabolic partial differential equations with time-dependent inhomogeneous boundary conditions - Neumann in 2D, and Dirichlet in 3D. Our results show that our method can achieve as high as a 60× speedup in 3D over existing RBF-FD methods in the task of forming differentiation matrices.
Lukas, Jan; Giese, Anne-Katrin; Markoff, Arseni; Grittner, Ulrike; Kolodny, Ed; Mascher, Hermann; Lackner, Karl J; Meyer, Wolfgang; Wree, Phillip; Saviouk, Viatcheslav; Rolfs, Arndt
2013-01-01
Fabry disease (FD) is an X-linked hereditary defect of glycosphingolipid storage caused by mutations in the gene encoding the lysosomal hydrolase α-galactosidase A (GLA, α-gal A). To date, over 400 mutations causing amino acid substitutions have been described. Most of these mutations are related to the classical Fabry phenotype. Generally in lysosomal storage disorders a reliable genotype/phenotype correlation is difficult to achieve, especially in FD with its X-linked mode of inheritance. In order to predict the metabolic consequence of a given mutation, we combined in vitro enzyme activity with in vivo biomarker data. Furthermore, we used the pharmacological chaperone (PC) 1-deoxygalactonojirimycin (DGJ) as a tool to analyse the influence of individual mutations on subcellular organelle-trafficking and stability. We analysed a significant number of mutations and correlated the obtained properties to the clinical manifestation related to the mutation in order to improve our knowledge of the identity of functional relevant amino acids. Additionally, we illustrate the consequences of different mutations on plasma lyso-globotriaosylsphingosine (lyso-Gb3) accumulation in the patients' plasma, a biomarker proven to reflect the impaired substrate clearance caused by specific mutations. The established system enables us to provide information for the clinical relevance of PC therapy for a given mutant. Finally, in order to generate reliable predictions of mutant GLA defects we compared the different data sets to reveal the most coherent system to reflect the clinical situation.
Directory of Open Access Journals (Sweden)
Armand Krasniqi
2015-07-01
Full Text Available Legal regulation of market mechanisms and the implementation of economic policies for a fair competition in TEs is a challenging issue. The competition is a complex economic phenomenon that is manifested and characterized by the strength and content that gives to the market economy. In Kosovo specific economic entities, in one way or another, are tempted to gain as much buyers or markets and create much more profits. The problem is connected with the irregularity. Such behavior and unfair actions are not only damaging the image of the country but are a serious threat the harmonious development of the national economy and the country’s accession process to the EU. The parliament of Kosovo established the Kosovo Competition Authority as an independent institution with special competences to control and fight this negative phenomenon. Based to official data it turns out that the effectiveness of this institution is not only incomplete but also non-functional. This is because of the “ignorance” and non-adequate treatment that is reserved for this authority by the parliamentary and governmental institutions. All this because the members are not elected based to regular procedures and not allocating the necessary financial means to operate. At least so far, the Kosovo Competition Authority was not allowed to hire professionals with clear competences to act and investigate the negative phenomenon of unfair competition. Certainly, this situation does not guarantee effective implementation of laws and quality protection of competition. Therefore, the mobilization of parliamentary and governmental levels is needed to enhance professional capacities and increase their competence in scope of the investigation including cooperation with prosecutors and courts. These actions should be reconsidered with the aim of creating a competitive safe environment for all operators. To conclude, the loyal competition policies and legislative framework should be
A desirability functions-based approach for simultaneous ...
African Journals Online (AJOL)
In order to improve product quality, all these quantitative and qualitative responses must be optimized simultaneously. ... Few researchers have proposed some alternative approaches for optimizing an ... quantitative and ordinal response variables simultaneously under Taguchi's framework of robust design approach.
Lorenz, Marco; Fürst, Christine; Thiel, Enrico
2013-09-01
Regarding increasing pressures by global societal and climate change, the assessment of the impact of land use and land management practices on land degradation and the related decrease in sustainable provision of ecosystem services gains increasing interest. Existing approaches to assess agricultural practices focus on the assessment of single crops or statistical data because spatially explicit information on practically applied crop rotations is mostly not available. This provokes considerable uncertainties in crop production models as regional specifics have to be neglected or cannot be considered in an appropriate way. In a case study in Saxony, we developed an approach to (i) derive representative regional crop rotations by combining different data sources and expert knowledge. This includes the integration of innovative crop sequences related to bio-energy production or organic farming and different soil tillage, soil management and soil protection techniques. Furthermore, (ii) we developed a regionalization approach for transferring crop rotations and related soil management strategies on the basis of statistical data and spatially explicit data taken from so called field blocks. These field blocks are the smallest spatial entity for which agricultural practices must be reported to apply for agricultural funding within the frame of the European Agricultural Fund for Rural Development (EAFRD) program. The information was finally integrated into the spatial decision support tool GISCAME to assess and visualize in spatially explicit manner the impact of alternative agricultural land use strategies on soil erosion risk and ecosystem services provision. Objective of this paper is to present the approach how to create spatially explicit information on agricultural management practices for a study area around Dresden, the capital of the German Federal State Saxony. Copyright © 2013 Elsevier Ltd. All rights reserved.
Farzaneh, Saeed; Forootan, Ehsan
2018-03-01
The computerized ionospheric tomography is a method for imaging the Earth's ionosphere using a sounding technique and computing the slant total electron content (STEC) values from data of the global positioning system (GPS). The most common approach for ionospheric tomography is the voxel-based model, in which (1) the ionosphere is divided into voxels, (2) the STEC is then measured along (many) satellite signal paths, and finally (3) an inversion procedure is applied to reconstruct the electron density distribution of the ionosphere. In this study, a computationally efficient approach is introduced, which improves the inversion procedure of step 3. Our proposed method combines the empirical orthogonal function and the spherical Slepian base functions to describe the vertical and horizontal distribution of electron density, respectively. Thus, it can be applied on regional and global case studies. Numerical application is demonstrated using the ground-based GPS data over South America. Our results are validated against ionospheric tomography obtained from the constellation observing system for meteorology, ionosphere, and climate (COSMIC) observations and the global ionosphere map estimated by international centers, as well as by comparison with STEC derived from independent GPS stations. Using the proposed approach, we find that while using 30 GPS measurements in South America, one can achieve comparable accuracy with those from COSMIC data within the reported accuracy (1 × 1011 el/cm3) of the product. Comparisons with real observations of two GPS stations indicate an absolute difference is less than 2 TECU (where 1 total electron content unit, TECU, is 1016 electrons/m2).
Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar
2017-12-01
The present study aims at predicting and optimizing exergetic efficiency of TiO2-Al2O3/water nanofluid at different Reynolds numbers, volume fractions and twisted ratios using Artificial Neural Networks (ANN) and experimental data. Central Composite Design (CCD) and cascade Radial Basis Function (RBF) were used to display the significant levels of the analyzed factors on the exergetic efficiency. The size of TiO2-Al2O3/water nanocomposite was 20-70 nm. The parameters of ANN model were adapted by a training algorithm of radial basis function (RBF) with a wide range of experimental data set. Total mean square error and correlation coefficient were used to evaluate the results which the best result was obtained from double layer perceptron neural network with 30 neurons in which total Mean Square Error(MSE) and correlation coefficient (R2) were equal to 0.002 and 0.999, respectively. This indicated successful prediction of the network. Moreover, the proposed equation for predicting exergetic efficiency was extremely successful. According to the optimal curves, the optimum designing parameters of double pipe heat exchanger with inner twisted tape and nanofluid under the constrains of exergetic efficiency 0.937 are found to be Reynolds number 2500, twisted ratio 2.5 and volume fraction(v/v%) 0.05.
International Nuclear Information System (INIS)
Souza, T.J.; Medeiros, J.A.C.C.; Gonçalves, A.C.
2017-01-01
Highlights: • An alternative model capable of identifying the control rod that has accidentally dropped. • The identification model is based in readings of the thermocouples. • Radial basis function neural network is applied to predict the temperatures in control rod positions. - Abstract: The accidental dropping of a control rod may cause the reactor to operate unsafely. In this type of event, there is a distortion in the distribution of power and temperature in the core may exceed operating limits reactor safe. This work aims to develop an alternative model capable of identifying, at any time of the cycle, the control rod that has accidentally dropped at the core of a PWR reactor, using the readings of the thermocouples in order to minimize possible losses. The model assumes that in a possible drop of a control rod, the largest temperature change occurs in the position where the control rod is inserted. Considering the fact that there are no temperature gauges in all control rod positions, the proposed model uses radial basis function (RBF) neural networks to make a reconstruction of temperatures in these positions from the measurements of the thermocouples at the time of the accidental drop. The study found that the predictions of the temperatures made by the RBF neural networks showed good results, which enables the identification of the control rod dropped accidentally in the core, by simple inference of the fuel assembly of lowest temperature among temperatures reconstructed.
Directory of Open Access Journals (Sweden)
Lu Gan
2017-12-01
Full Text Available A renewable energy (RE project has been brought into focus in recent years. Although there is quite a lot of research to assist investors in assessing the economic feasibility of the project, because of the lack of consideration of consumer utility, the existing approaches may still cause a biased result. In order to promote further development, this study focuses on the economic feasibility analysis of the RE project on the basis of consumer utility in the whole life cycle. Therefore, an integrated approach is proposed, which consists of triangular fuzzy numbers (TFNs, an analytic hierarchy process (AHP and data envelopment analysis (DEA. The first step is to determine the comprehensive cost index weights of DEA by TFN–AHP. Secondly, to solve the problem, the first DEA model, which is proposed by A. Charnes, W. W. Cooper and E. Rhodes (C2R, is established to calculate the DEA effectiveness. Then, the third task involves designing a computer-based intelligent interface (CBII to simplify realistic application and ensure performance efficiency. Finally, a solar water heater case study is demonstrated to validate the effectiveness of the entire method’s system. The study shows that this could make investors’ lives easier by using the CBII scientifically, reasonably and conveniently. Moreover, the research results could be easily extended to more complex real-world applications.
A Geometric Approach to Visualization of Variability in Functional Data
Xie, Weiyi
2016-12-19
We propose a new method for the construction and visualization of boxplot-type displays for functional data. We use a recent functional data analysis framework, based on a representation of functions called square-root slope functions, to decompose observed variation in functional data into three main components: amplitude, phase, and vertical translation. We then construct separate displays for each component, using the geometry and metric of each representation space, based on a novel definition of the median, the two quartiles, and extreme observations. The outlyingness of functional data is a very complex concept. Thus, we propose to identify outliers based on any of the three main components after decomposition. We provide a variety of visualization tools for the proposed boxplot-type displays including surface plots. We evaluate the proposed method using extensive simulations and then focus our attention on three real data applications including exploratory data analysis of sea surface temperature functions, electrocardiogram functions and growth curves.
International Nuclear Information System (INIS)
Finesso, Roberto; Spessa, Ezio
2015-01-01
Highlights: • Control-oriented method to estimate injected quantities from in-cylinder pressure. • Able to calculate the injected quantities for multiple injection strategies. • Based on the inversion of a heat-release predictive model. • Low computational time demanding. - Abstract: A new control-oriented methodology has been developed to estimate the injected fuel quantities, in real-time, in multiple injection DI diesel engines on the basis of the measured in-cylinder pressure. The method is based on the inversion of a predictive combustion model that was previously developed by the authors, and that is capable of estimating the heat release rate and the in-cylinder pressure on the basis of the injection rate. The model equations have been rewritten in order to derive the injected mass as an output quantity, starting from use of the measured in-cylinder pressure as input. It has been verified that the proposed method is capable of estimating the injected mass of pilot pulses with an uncertainty of the order of ±0.15 mg/cyc, and the total injected mass with an uncertainty of the order of ±0.9 mg/cyc. The main sources of uncertainty are related to the estimation of the in-cylinder heat transfer and of the isentropic coefficient γ = c p /c v . The estimation of the actual injected quantities in the combustion chamber can represent a powerful means to diagnose the behavior of the injectors during engine operation, and offers the possibility of monitoring effects, such as injector ageing and injector coking, as well as of allowing an accurate control of the pilot injected quantities to be obtained; the latter are in fact usually characterized by a large dispersion, with negative consequences on the combustion quality and emission formation. The approach is characterized by a very low computational time, and is therefore suitable for control-oriented applications.
Generic metrics and quantitative approaches for system resilience as a function of time
International Nuclear Information System (INIS)
Henry, Devanandham; Emmanuel Ramirez-Marquez, Jose
2012-01-01
Resilience is generally understood as the ability of an entity to recover from an external disruptive event. In the system domain, a formal definition and quantification of the concept of resilience has been elusive. This paper proposes generic metrics and formulae for quantifying system resilience. The discussions and graphical examples illustrate that the quantitative model is aligned with the fundamental concept of resilience. Based on the approach presented it is possible to analyze resilience as a time dependent function in the context of systems. The paper describes the metrics of network and system resilience, time for resilience and total cost of resilience. Also the paper describes the key parameters necessary to analyze system resilience such as the following: disruptive events, component restoration and overall resilience strategy. A road network example is used to demonstrate the applicability of the proposed resilience metrics and how these analyses form the basis for developing effective resilience design strategies. The metrics described are generic enough to be implemented in a variety of applications as long as appropriate figures-of-merit and the necessary system parameters, system decomposition and component parameters are defined. - Highlights: ► Propose a graphical model for the understanding of the resilience process. ► Mathematical description of resilience as a function of time. ► Identification of necessary concepts to define and evaluate network resilience. ► Development of cost and time to recovery metrics based on resilience formulation.
A Fuzzy Rule-Based Penalty Function Approach for Constrained Evolutionary Optimization.
Saha, Chiranjib; Das, Swagatam; Pal, Kunal; Mukherjee, Satrajit
2016-12-01
This paper proposes a novel fuzzy rule-based penalty function approach for solving single-objective nonlinearly constrained optimization problems. Of all the existing state-of-the-art constraint handling techniques, the conventional method of penalty can be easily implemented because of its simplicity but suffers from the lack of robustness. To mitigate the problem of parameter dependency, several forms of adaptive penalties have been suggested in literature. Instead of identifying a complex mathematical function to compute the penalty for constraint violation, we propose a Mamdani type IF-THEN rule-based fuzzy inference system that incorporates all the required criteria of self-adaptive penalty without formulating an explicit mapping. Effectiveness of the proposed constrained optimization algorithm has been empirically validated on the basis of the standard optimality theorems from the literature on mathematical programming. Simulation results show that fuzzy penalty not only surpasses its existing counterpart i.e., self adaptive penalty, but also remain competitive against several other standard as well as currently developed complex constraint handling strategies.
A desirability functions-based approach for simultaneous ...
African Journals Online (AJOL)
simultaneous optimization of quantitative and ordinal response variables. But none of these approaches results in an efficient optimal solution with respect to the desirability values of all the individual response variables. It motivated us to develop a more useful approach for simultaneously optimizing industrial processes ...
Molecular basis of neural function
International Nuclear Information System (INIS)
Tucek, S.; Stipek, S.; Stastny, F.; Krivanek, J.
1986-01-01
The conference proceedings contain abstracts of plenary lectures, of young neurochemists' ESN honorary lectures, lectures at symposia and workshops and poster communications. Twenty abstracts were inputted in INIS. The subject of these were the use of autoradiography for the determination of receptors, cholecystokinin, nicotine, adrenaline, glutamate, aspartate, tranquilizers, for distribution and pharmacokinetics of obidoxime-chloride, for cell proliferation, mitosis of brain cells, DNA repair; radioimmunoassay of cholinesterase, tyrosinase; positron computed tomography of the brain; biological radiation effects on cholinesterase activity; tracer techniques for determination of adrenaline; and studies of the biological repair of nerves. (J.P.)
Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei
2017-06-01
To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (Plogistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Behloul, F.; Boudraa, A.; Janier, M.; Unterreiner, R.
1998-01-01
A self-organized Radial Basis Function Network (RBFN) is proposed for the problem of object extraction in Positron Emission Tomography Images of the heart. RBENs are supervised-learning networks. However, viewing the output of the networks as a fuzzy set, we have able to compute the error of the system using fuzziness measures. Thus, there is no need of target output for training the network. Besides the self-organizing feature of the network, our RBFN has a non linear output layer trained using the back-propagation algorithm. Two mathematical models of fuzzy measures have been considered: the index of fuzziness and fuzzy entropy. Preliminary results show that entropy measure produced a better extraction of healthy myocardium. (authors)
A Transtextual Approach to Lexicographic Functions | Gouws | Lexikos
African Journals Online (AJOL)
The development of theoretical lexicography clearly indicates a movement towards a more general recognition of the role of lexicographic functions. A consistent application of lexico-graphic functions has a major influence on the contents of dictionary articles but also on the data distribution and even the typological ...
Measurement of dynamic efficiency: a directional distance function parametric approach
Serra, T.; Oude Lansink, A.G.J.M.; Stefanou, S.E.
2011-01-01
This research proposes a parametric estimation of the structural dynamic efficiency measures proposed by Silva and Oude Lansink (2009). Overall, technical and allocative efficiency measurements are derived based on a directional distance function and the duality between this function and the optimal
Persuading by addressing: a functional approach to speech-act ...
African Journals Online (AJOL)
The phatic function, which, according to Jakobson (1960), provides the appropriate channel for communication, is of particular importance in this respect. If the channel does not work properly, the persuasive function will never fulfil its aim. In the following paper, a small corpus of English, Spanish and German advertising ...