An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

Decay width of hadronic molecule structure for quarks

NASA Astrophysics Data System (ADS)

Chen, Xiaozhao; Lü, Xiaofu

2018-06-01

Based on the general form of the Bethe-Salpeter wave functions for the bound states consisting of two vector fields, we obtain the general formulas for the decay widths of molecular states composed of two heavy vector mesons with arbitrary spin and parity into a heavy meson plus a light meson. In this approach, our attention is still focused on the internal structure of heavy vector mesons in the molecular state. According to the molecule state model of exotic meson, we give the generalized Bethe-Salpeter wave function of molecular state as a four-quark state. Then the observed Y (3940 ) state is considered as a molecular state consisting of two heavy vector mesons D*0D¯*0 and the strong Y (3940 )→J /ψ ω decay width is calculated. The numerical result is consistent with the experimental values.

Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.

PubMed

Liu, Jing; Zhou, Weidong; Juwono, Filbert H

2017-05-08

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.

Light scattering of rectangular slot antennas: parallel magnetic vector vs perpendicular electric vector

NASA Astrophysics Data System (ADS)

Lee, Dukhyung; Kim, Dai-Sik

2016-01-01

We study light scattering off rectangular slot nano antennas on a metal film varying incident polarization and incident angle, to examine which field vector of light is more important: electric vector perpendicular to, versus magnetic vector parallel to the long axis of the rectangle. While vector Babinet’s principle would prefer magnetic field along the long axis for optimizing slot antenna function, convention and intuition most often refer to the electric field perpendicular to it. Here, we demonstrate experimentally that in accordance with vector Babinet’s principle, the incident magnetic vector parallel to the long axis is the dominant component, with the perpendicular incident electric field making a small contribution of the factor of 1/|ε|, the reciprocal of the absolute value of the dielectric constant of the metal, owing to the non-perfectness of metals at optical frequencies.

Steering of Frequency Standards by the Use of Linear Quadratic Gaussian Control Theory

NASA Technical Reports Server (NTRS)

Koppang, Paul; Leland, Robert

1996-01-01

Linear quadratic Gaussian control is a technique that uses Kalman filtering to estimate a state vector used for input into a control calculation. A control correction is calculated by minimizing a quadratic cost function that is dependent on both the state vector and the control amount. Different penalties, chosen by the designer, are assessed by the controller as the state vector and control amount vary from given optimal values. With this feature controllers can be designed to force the phase and frequency differences between two standards to zero either more or less aggressively depending on the application. Data will be used to show how using different parameters in the cost function analysis affects the steering and the stability of the frequency standards.

Mathematical solution of multilevel fractional programming problem with fuzzy goal programming approach

NASA Astrophysics Data System (ADS)

Lachhwani, Kailash; Poonia, Mahaveer Prasad

2012-08-01

In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.

A MATLAB implementation of the minimum relative entropy method for linear inverse problems

NASA Astrophysics Data System (ADS)

Neupauer, Roseanna M.; Borchers, Brian

2001-08-01

The minimum relative entropy (MRE) method can be used to solve linear inverse problems of the form Gm= d, where m is a vector of unknown model parameters and d is a vector of measured data. The MRE method treats the elements of m as random variables, and obtains a multivariate probability density function for m. The probability density function is constrained by prior information about the upper and lower bounds of m, a prior expected value of m, and the measured data. The solution of the inverse problem is the expected value of m, based on the derived probability density function. We present a MATLAB implementation of the MRE method. Several numerical issues arise in the implementation of the MRE method and are discussed here. We present the source history reconstruction problem from groundwater hydrology as an example of the MRE implementation.

A phenomenological calculus of Wiener description space.

PubMed

Richardson, I W; Louie, A H

2007-10-01

The phenomenological calculus is a categorical example of Robert Rosen's modeling relation. This paper is an alligation of the phenomenological calculus and generalized harmonic analysis, another categorical example. Our epistemological exploration continues into the realm of Wiener description space, in which constitutive parameters are extended from vectors to vector-valued functions of a real variable. Inherent in the phenomenology are fundamental representations of time and nearness to equilibrium.

Obstacle-avoiding navigation system

DOEpatents

Borenstein, Johann; Koren, Yoram; Levine, Simon P.

1991-01-01

A system for guiding an autonomous or semi-autonomous vehicle through a field of operation having obstacles thereon to be avoided employs a memory for containing data which defines an array of grid cells which correspond to respective subfields in the field of operation of the vehicle. Each grid cell in the memory contains a value which is indicative of the likelihood, or probability, that an obstacle is present in the respectively associated subfield. The values in the grid cells are incremented individually in response to each scan of the subfields, and precomputation and use of a look-up table avoids complex trigonometric functions. A further array of grid cells is fixed with respect to the vehicle form a conceptual active window which overlies the incremented grid cells. Thus, when the cells in the active window overly grid cell having values which are indicative of the presence of obstacles, the value therein is used as a multiplier of the precomputed vectorial values. The resulting plurality of vectorial values are summed vectorially in one embodiment of the invention to produce a virtual composite repulsive vector which is then summed vectorially with a target-directed vector for producing a resultant vector for guiding the vehicle. In an alternative embodiment, a plurality of vectors surrounding the vehicle are computed, each having a value corresponding to obstacle density. In such an embodiment, target location information is used to select between alternative directions of travel having low associated obstacle densities.

Using Redundancy To Reduce Errors in Magnetometer Readings

NASA Technical Reports Server (NTRS)

Kulikov, Igor; Zak, Michail

2004-01-01

A method of reducing errors in noisy magnetic-field measurements involves exploitation of redundancy in the readings of multiple magnetometers in a cluster. By "redundancy"is meant that the readings are not entirely independent of each other because the relationships among the magnetic-field components that one seeks to measure are governed by the fundamental laws of electromagnetism as expressed by Maxwell's equations. Assuming that the magnetometers are located outside a magnetic material, that the magnetic field is steady or quasi-steady, and that there are no electric currents flowing in or near the magnetometers, the applicable Maxwell 's equations are delta x B = 0 and delta(raised dot) B = 0, where B is the magnetic-flux-density vector. By suitable algebraic manipulation, these equations can be shown to impose three independent constraints on the values of the components of B at the various magnetometer positions. In general, the problem of reducing the errors in noisy measurements is one of finding a set of corrected values that minimize an error function. In the present method, the error function is formulated as (1) the sum of squares of the differences between the corrected and noisy measurement values plus (2) a sum of three terms, each comprising the product of a Lagrange multiplier and one of the three constraints. The partial derivatives of the error function with respect to the corrected magnetic-field component values and the Lagrange multipliers are set equal to zero, leading to a set of equations that can be put into matrix.vector form. The matrix can be inverted to solve for a vector that comprises the corrected magnetic-field component values and the Lagrange multipliers.

Computation of convex bounds for present value functions with random payments

NASA Astrophysics Data System (ADS)

Ahcan, Ales; Darkiewicz, Grzegorz; Goovaerts, Marc; Hoedemakers, Tom

2006-02-01

In this contribution we study the distribution of the present value function of a series of random payments in a stochastic financial environment. Such distributions occur naturally in a wide range of applications within fields of insurance and finance. We obtain accurate approximations by developing upper and lower bounds in the convex-order sense for present value functions. Technically speaking, our methodology is an extension of the results of Dhaene et al. [Insur. Math. Econom. 31(1) (2002) 3-33, Insur. Math. Econom. 31(2) (2002) 133-161] to the case of scalar products of mutually independent random vectors.

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis.

PubMed

Wang, Shuai; Zhang, Yan; Lv, Luxian; Wu, Renrong; Fan, Xiaoduo; Zhao, Jingping; Guo, Wenbin

2018-02-01

Structural and functional abnormalities have been reported in the brain of patients with adolescent-onset schizophrenia (AOS). The brain regional functional synchronization in patients with AOS remains unclear. We analyzed resting-state functional magnetic resonance scans in 48 drug-naive patients with AOS and 31 healthy controls by using regional homogeneity (ReHo), a measurement that reflects brain local functional connectivity or synchronization and indicates regional integration of information processing. Then, receiver operating characteristic curves and support vector machines were used to evaluate the effect of abnormal regional homogeneity in differentiating patients from controls. Patients with AOS showed significantly increased ReHo values in the bilateral superior medial prefrontal cortex (MPFC) and significantly decreased ReHo values in the left superior temporal gyrus (STG), right precentral lobule, right inferior parietal lobule (IPL), and left paracentral lobule when compared with controls. A combination of the ReHo values in bilateral superior MPFC, left STG, and right IPL was able to discriminate patients from controls with the sensitivity of 88.24%, specificity of 91.89%, and accuracy of 90.14%. The brain regional functional synchronization abnormalities exist in drug-naive patients with AOS. A combination of ReHo values in these abnormal regions might serve as potential imaging biomarker to identify patients with AOS. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression

NASA Astrophysics Data System (ADS)

Kavitha, A.; Sujatha, C. M.; Ramakrishnan, S.

2010-01-01

In this work, prediction of forced expiratory volume in 1 second (FEV1) in pulmonary function test is carried out using the spirometer and support vector regression analysis. Pulmonary function data are measured with flow volume spirometer from volunteers (N=175) using a standard data acquisition protocol. The acquired data are then used to predict FEV1. Support vector machines with polynomial kernel function with four different orders were employed to predict the values of FEV1. The performance is evaluated by computing the average prediction accuracy for normal and abnormal cases. Results show that support vector machines are capable of predicting FEV1 in both normal and abnormal cases and the average prediction accuracy for normal subjects was higher than that of abnormal subjects. Accuracy in prediction was found to be high for a regularization constant of C=10. Since FEV1 is the most significant parameter in the analysis of spirometric data, it appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.

Skeletonization and Partitioning of Digital Images Using Discrete Morse Theory.

PubMed

Delgado-Friedrichs, Olaf; Robins, Vanessa; Sheppard, Adrian

2015-03-01

We show how discrete Morse theory provides a rigorous and unifying foundation for defining skeletons and partitions of grayscale digital images. We model a grayscale image as a cubical complex with a real-valued function defined on its vertices (the voxel values). This function is extended to a discrete gradient vector field using the algorithm presented in Robins, Wood, Sheppard TPAMI 33:1646 (2011). In the current paper we define basins (the building blocks of a partition) and segments of the skeleton using the stable and unstable sets associated with critical cells. The natural connection between Morse theory and homology allows us to prove the topological validity of these constructions; for example, that the skeleton is homotopic to the initial object. We simplify the basins and skeletons via Morse-theoretic cancellation of critical cells in the discrete gradient vector field using a strategy informed by persistent homology. Simple working Python code for our algorithms for efficient vector field traversal is included. Example data are taken from micro-CT images of porous materials, an application area where accurate topological models of pore connectivity are vital for fluid-flow modelling.

Complex matrix multiplication operations with data pre-conditioning in a high performance computing architecture

DOEpatents

Eichenberger, Alexandre E; Gschwind, Michael K; Gunnels, John A

2014-02-11

Mechanisms for performing a complex matrix multiplication operation are provided. A vector load operation is performed to load a first vector operand of the complex matrix multiplication operation to a first target vector register. The first vector operand comprises a real and imaginary part of a first complex vector value. A complex load and splat operation is performed to load a second complex vector value of a second vector operand and replicate the second complex vector value within a second target vector register. The second complex vector value has a real and imaginary part. A cross multiply add operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the complex matrix multiplication operation. The partial product is accumulated with other partial products and a resulting accumulated partial product is stored in a result vector register.

How should spin-weighted spherical functions be defined?

NASA Astrophysics Data System (ADS)

Boyle, Michael

2016-09-01

Spin-weighted spherical functions provide a useful tool for analyzing tensor-valued functions on the sphere. A tensor field can be decomposed into complex-valued functions by taking contractions with tangent vectors on the sphere and the normal to the sphere. These component functions are usually presented as functions on the sphere itself, but this requires an implicit choice of distinguished tangent vectors with which to contract. Thus, we may more accurately say that spin-weighted spherical functions are functions of both a point on the sphere and a choice of frame in the tangent space at that point. The distinction becomes extremely important when transforming the coordinates in which these functions are expressed, because the implicit choice of frame will also transform. Here, it is proposed that spin-weighted spherical functions should be treated as functions on the spin or rotation groups, which simultaneously tracks the point on the sphere and the choice of tangent frame by rotating elements of an orthonormal basis. In practice, the functions simply take a quaternion argument and produce a complex value. This approach more cleanly reflects the geometry involved, and allows for a more elegant description of the behavior of spin-weighted functions. In this form, the spin-weighted spherical harmonics have simple expressions as elements of the Wigner 𝔇 representations, and transformations under rotation are simple. Two variants of the angular-momentum operator are defined directly in terms of the spin group; one is the standard angular-momentum operator L, while the other is shown to be related to the spin-raising operator ð.

Optimal four-impulse rendezvous between coplanar elliptical orbits

NASA Astrophysics Data System (ADS)

Wang, JianXia; Baoyin, HeXi; Li, JunFeng; Sun, FuChun

2011-04-01

Rendezvous in circular or near circular orbits has been investigated in great detail, while rendezvous in arbitrary eccentricity elliptical orbits is not sufficiently explored. Among the various optimization methods proposed for fuel optimal orbital rendezvous, Lawden's primer vector theory is favored by many researchers with its clear physical concept and simplicity in solution. Prussing has applied the primer vector optimization theory to minimum-fuel, multiple-impulse, time-fixed orbital rendezvous in a near circular orbit and achieved great success. Extending Prussing's work, this paper will employ the primer vector theory to study trajectory optimization problems of arbitrary eccentricity elliptical orbit rendezvous. Based on linearized equations of relative motion on elliptical reference orbit (referred to as T-H equations), the primer vector theory is used to deal with time-fixed multiple-impulse optimal rendezvous between two coplanar, coaxial elliptical orbits with arbitrary large eccentricity. A parameter adjustment method is developed for the prime vector to satisfy the Lawden's necessary condition for the optimal solution. Finally, the optimal multiple-impulse rendezvous solution including the time, direction and magnitudes of the impulse is obtained by solving the two-point boundary value problem. The rendezvous error of the linearized equation is also analyzed. The simulation results confirmed the analyzed results that the rendezvous error is small for the small eccentricity case and is large for the higher eccentricity. For better rendezvous accuracy of high eccentricity orbits, a combined method of multiplier penalty function with the simplex search method is used for local optimization. The simplex search method is sensitive to the initial values of optimization variables, but the simulation results show that initial values with the primer vector theory, and the local optimization algorithm can improve the rendezvous accuracy effectively with fast convergence, because the optimal results obtained by the primer vector theory are already very close to the actual optimal solution. If the initial values are taken randomly, it is difficult to converge to the optimal solution.

CONSTRUCTION OF SCALAR AND VECTOR FINITE ELEMENT FAMILIES ON POLYGONAL AND POLYHEDRAL MESHES

PubMed Central

GILLETTE, ANDREW; RAND, ALEXANDER; BAJAJ, CHANDRAJIT

2016-01-01

We combine theoretical results from polytope domain meshing, generalized barycentric coordinates, and finite element exterior calculus to construct scalar- and vector-valued basis functions for conforming finite element methods on generic convex polytope meshes in dimensions 2 and 3. Our construction recovers well-known bases for the lowest order Nédélec, Raviart-Thomas, and Brezzi-Douglas-Marini elements on simplicial meshes and generalizes the notion of Whitney forms to non-simplicial convex polygons and polyhedra. We show that our basis functions lie in the correct function space with regards to global continuity and that they reproduce the requisite polynomial differential forms described by finite element exterior calculus. We present a method to count the number of basis functions required to ensure these two key properties. PMID:28077939

CONSTRUCTION OF SCALAR AND VECTOR FINITE ELEMENT FAMILIES ON POLYGONAL AND POLYHEDRAL MESHES.

PubMed

Gillette, Andrew; Rand, Alexander; Bajaj, Chandrajit

2016-10-01

We combine theoretical results from polytope domain meshing, generalized barycentric coordinates, and finite element exterior calculus to construct scalar- and vector-valued basis functions for conforming finite element methods on generic convex polytope meshes in dimensions 2 and 3. Our construction recovers well-known bases for the lowest order Nédélec, Raviart-Thomas, and Brezzi-Douglas-Marini elements on simplicial meshes and generalizes the notion of Whitney forms to non-simplicial convex polygons and polyhedra. We show that our basis functions lie in the correct function space with regards to global continuity and that they reproduce the requisite polynomial differential forms described by finite element exterior calculus. We present a method to count the number of basis functions required to ensure these two key properties.

SEMIPARAMETRIC QUANTILE REGRESSION WITH HIGH-DIMENSIONAL COVARIATES

PubMed Central

Zhu, Liping; Huang, Mian; Li, Runze

2012-01-01

This paper is concerned with quantile regression for a semiparametric regression model, in which both the conditional mean and conditional variance function of the response given the covariates admit a single-index structure. This semiparametric regression model enables us to reduce the dimension of the covariates and simultaneously retains the flexibility of nonparametric regression. Under mild conditions, we show that the simple linear quantile regression offers a consistent estimate of the index parameter vector. This is a surprising and interesting result because the single-index model is possibly misspecified under the linear quantile regression. With a root-n consistent estimate of the index vector, one may employ a local polynomial regression technique to estimate the conditional quantile function. This procedure is computationally efficient, which is very appealing in high-dimensional data analysis. We show that the resulting estimator of the quantile function performs asymptotically as efficiently as if the true value of the index vector were known. The methodologies are demonstrated through comprehensive simulation studies and an application to a real dataset. PMID:24501536

Geographic Information Systems: A Primer

DTIC Science & Technology

1990-10-01

AVAILABILITY OF REPORT Approved for public release; distribution 2b DECLASSjFICATION/ DOWNGRADING SCHEDULE unlimited. 4 PERFORMING ORGANIZATION REPORT...utilizing sophisticated integrated databases (usually vector-based), avoid the indirect value coding scheme by recognizing names or direct magnitudes...intricate involvement required by the operator in order to establish a functional coding scheme . A simple raster system, in which cell values indicate

A vector matching method for analysing logic Petri nets

NASA Astrophysics Data System (ADS)

Du, YuYue; Qi, Liang; Zhou, MengChu

2011-11-01

Batch processing function and passing value indeterminacy in cooperative systems can be described and analysed by logic Petri nets (LPNs). To directly analyse the properties of LPNs, the concept of transition enabling vector sets is presented and a vector matching method used to judge the enabling transitions is proposed in this article. The incidence matrix of LPNs is defined; an equation about marking change due to a transition's firing is given; and a reachable tree is constructed. The state space explosion is mitigated to a certain extent from directly analysing LPNs. Finally, the validity and reliability of the proposed method are illustrated by an example in electronic commerce.

FIBER AND INTEGRATED OPTICS. FIBER WAVEGUIDE DEVICES: Vector solitons in fiber waveguides with a random birefringence

NASA Astrophysics Data System (ADS)

Kivshar', Yu S.; Konotop, V. V.

1990-12-01

A study is made of the propagation of soliton pulses in single-mode fiber waveguides with a birefringence that gives rise to a nonlinear interaction between the polarizations and to a difference between their group velocities. It is shown that a vector soliton decays if a parameter representing the birefringence intensity exceeds a certain critical value. The case when the birefringence can be described by a random function is of special interest. It is demonstrated that fluctuations of the birefringence then split the vector solitons into separate polarizations and the characteristic distance governing such splitting is calculated analytically.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data

PubMed Central

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Abstract Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density (d), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction. PMID:29707064

A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data.

PubMed

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density ( d ), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction.

Energy theorem for (2+1)-dimensional gravity.

NASA Astrophysics Data System (ADS)

Menotti, P.; Seminara, D.

1995-05-01

We prove a positive energy theorem in (2+1)-dimensional gravity for open universes and any matter energy-momentum tensor satisfying the dominant energy condition. We consider on the space-like initial value surface a family of widening Wilson loops and show that the energy-momentum of the enclosed subsystem is a future directed time-like vector whose mass is an increasing function of the loop, until it reaches the value 1/4G corresponding to a deficit angle of 2π. At this point the energy-momentum of the system evolves, depending on the nature of a zero norm vector appearing in the evolution equations, either into a time-like vector of a universe which closes kinematically or into a Gott-like universe whose energy momentum vector, as first recognized by Deser, Jackiw, and 't Hooft (1984) is space-like. This treatment generalizes results obtained by Carroll, Fahri, Guth, and Olum (1994) for a system of point-like spinless particle, to the most general form of matter whose energy-momentum tensor satisfies the dominant energy condition. The treatment is also given for the anti-de Sitter (2+1)-dimensional gravity.

Detection of outliers in water quality monitoring samples using functional data analysis in San Esteban estuary (Northern Spain).

PubMed

Díaz Muñiz, C; García Nieto, P J; Alonso Fernández, J R; Martínez Torres, J; Taboada, J

2012-11-15

Water quality controls involve large number of variables and observations, often subject to some outliers. An outlier is an observation that is numerically distant from the rest of the data or that appears to deviate markedly from other members of the sample in which it occurs. An interesting analysis is to find those observations that produce measurements that are different from the pattern established in the sample. Therefore, identification of atypical observations is an important concern in water quality monitoring and a difficult task because of the multivariate nature of water quality data. Our study provides a new method for detecting outliers in water quality monitoring parameters, using oxygen and turbidity as indicator variables. Until now, methods were based on considering the different parameters as a vector whose components were their concentration values. Our approach lies in considering water quality monitoring through time as curves instead of vectors, that is to say, the data set of the problem is considered as a time-dependent function and not as a set of discrete values in different time instants. The methodology, which is based on the concept of functional depth, was applied to the detection of outliers in water quality monitoring samples in San Esteban estuary. Results were discussed in terms of origin, causes, etc., and compared with those obtained using the conventional method based on vector comparison. Finally, the advantages of the functional method are exposed. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of vector-valued rational approximations to the matrix eigenvalue problem and connections with Krylov subspace methods

NASA Technical Reports Server (NTRS)

Sidi, Avram

1992-01-01

Let F(z) be a vectored-valued function F: C approaches C sup N, which is analytic at z=0 and meromorphic in a neighborhood of z=0, and let its Maclaurin series be given. We use vector-valued rational approximation procedures for F(z) that are based on its Maclaurin series in conjunction with power iterations to develop bona fide generalizations of the power method for an arbitrary N X N matrix that may be diagonalizable or not. These generalizations can be used to obtain simultaneously several of the largest distinct eigenvalues and the corresponding invariant subspaces, and present a detailed convergence theory for them. In addition, it is shown that the generalized power methods of this work are equivalent to some Krylov subspace methods, among them the methods of Arnoldi and Lanczos. Thus, the theory provides a set of completely new results and constructions for these Krylov subspace methods. This theory suggests at the same time a new mode of usage for these Krylov subspace methods that were observed to possess computational advantages over their common mode of usage.

Classification of subsurface objects using singular values derived from signal frames

DOEpatents

Chambers, David H; Paglieroni, David W

2014-05-06

The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N.times.N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.

Nonlinear Dynamics and Control of Wings and Panels.

DTIC Science & Technology

1996-12-04

y, z, t) = fluid velocity potential d31 = piezoelectric constant T&(x, y) = modal expansion functions H,•(t) = aerodynamic influence function h...thickness Subscripts l,(t) = aerodynamic influence function a = aerodynamic i = output current vector m, n = modal indices K = stiffness matrix p...acting on a piston in a tube: As an example, suppose the values of the influence function H,,.(iT) are used to solve for the filter coefficients in Eq

Geodesic synchrotron radiation in the Kerr geometry by the method of asymptotically factorized Green's functions

NASA Technical Reports Server (NTRS)

Chrzanowski, P. L.; Misner, C. W.

1974-01-01

The scalar, electromagnetic, and gravitational geodesic-synchrotron-radiation (GSR) spectra are determined for the case of a test particle moving on a highly relativistic circular orbit about a rotating (Kerr) black hole. It is found that the spectral shape depends only weakly on the value of the angular-momentum parameter (a/M) of the black hole, but the total radiated power drops unexpectedly for a value of at least 0.95 and vanishes as the value approaches unity. A spin-dependent factor (involving the inner product of the polarization of a radiated quantum with the source) is isolated to explain the dependence of the spectral shape on the spin of the radiated field. Although the scalar wave equation is solved by separation of variables, this procedure is avoided for the vector and tensor cases by postulating a sum-over-states expansion for the Green's function similar to that found to hold in the scalar case. The terms in this sum, significant for GSR, can then be evaluated in the geometric-optics approximation without requiring the use of vector or tensor spherical harmonics.

Offline handwritten word recognition using MQDF-HMMs

NASA Astrophysics Data System (ADS)

Ramachandrula, Sitaram; Hambarde, Mangesh; Patial, Ajay; Sahoo, Dushyant; Kochar, Shaivi

2015-01-01

We propose an improved HMM formulation for offline handwriting recognition (HWR). The main contribution of this work is using modified quadratic discriminant function (MQDF) [1] within HMM framework. In an MQDF-HMM the state observation likelihood is calculated by a weighted combination of MQDF likelihoods of individual Gaussians of GMM (Gaussian Mixture Model). The quadratic discriminant function (QDF) of a multivariate Gaussian can be rewritten by avoiding the inverse of covariance matrix by using the Eigen values and Eigen vectors of it. The MQDF is derived from QDF by substituting few of badly estimated lower-most Eigen values by an appropriate constant. The estimation errors of non-dominant Eigen vectors and Eigen values of covariance matrix for which the training data is insufficient can be controlled by this approach. MQDF has been successfully shown to improve the character recognition performance [1]. The usage of MQDF in HMM improves the computation, storage and modeling power of HMM when there is limited training data. We have got encouraging results on offline handwritten character (NIST database) and word recognition in English using MQDF HMMs.

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2015-03-31

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

Bayesian statistics and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Koch, K. R.

2018-03-01

The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

GPU-accelerated adjoint algorithmic differentiation

NASA Astrophysics Data System (ADS)

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2016-03-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the ;tape;. Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography.

GPU-Accelerated Adjoint Algorithmic Differentiation.

PubMed

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2016-03-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the "tape". Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography.

GPU-Accelerated Adjoint Algorithmic Differentiation

PubMed Central

Gremse, Felix; Höfter, Andreas; Razik, Lukas; Kiessling, Fabian; Naumann, Uwe

2015-01-01

Many scientific problems such as classifier training or medical image reconstruction can be expressed as minimization of differentiable real-valued cost functions and solved with iterative gradient-based methods. Adjoint algorithmic differentiation (AAD) enables automated computation of gradients of such cost functions implemented as computer programs. To backpropagate adjoint derivatives, excessive memory is potentially required to store the intermediate partial derivatives on a dedicated data structure, referred to as the “tape”. Parallelization is difficult because threads need to synchronize their accesses during taping and backpropagation. This situation is aggravated for many-core architectures, such as Graphics Processing Units (GPUs), because of the large number of light-weight threads and the limited memory size in general as well as per thread. We show how these limitations can be mediated if the cost function is expressed using GPU-accelerated vector and matrix operations which are recognized as intrinsic functions by our AAD software. We compare this approach with naive and vectorized implementations for CPUs. We use four increasingly complex cost functions to evaluate the performance with respect to memory consumption and gradient computation times. Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity. The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation. The GPU version achieved an additional speedup of 7.5 ± 4.4, showing that the processing power of GPUs can be utilized for AAD using this concept. Furthermore, we show how this software can be systematically extended for more complex problems such as nonlinear absorption reconstruction for fluorescence-mediated tomography. PMID:26941443

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

Hybrid approach of selecting hyperparameters of support vector machine for regression.

PubMed

Jeng, Jin-Tsong

2006-06-01

To select the hyperparameters of the support vector machine for regression (SVR), a hybrid approach is proposed to determine the kernel parameter of the Gaussian kernel function and the epsilon value of Vapnik's epsilon-insensitive loss function. The proposed hybrid approach includes a competitive agglomeration (CA) clustering algorithm and a repeated SVR (RSVR) approach. Since the CA clustering algorithm is used to find the nearly "optimal" number of clusters and the centers of clusters in the clustering process, the CA clustering algorithm is applied to select the Gaussian kernel parameter. Additionally, an RSVR approach that relies on the standard deviation of a training error is proposed to obtain an epsilon in the loss function. Finally, two functions, one real data set (i.e., a time series of quarterly unemployment rate for West Germany) and an identification of nonlinear plant are used to verify the usefulness of the hybrid approach.

Ground states of larger nuclei

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pieper, S.C.; Wiringa, R.B.; Pandharipande, V.R.

1995-08-01

The methods used for the few-body nuclei require operations on the complete spin-isospin vector; the size of this vector makes such methods impractical for nuclei with A > 8. During the last few years we developed cluster expansion methods that do not require operations on the complete vector. We use the same Hamiltonians as for the few-body nuclei and variational wave functions of form similar to the few-body wave functions. The cluster expansions are made for the noncentral parts of the wave functions and for the operators whose expectation values are being evaluated. The central pair correlations in the wavemore » functions are treated exactly and this requires the evaluation of 3A-dimensional integrals which are done with Monte Carlo techniques. Most of our effort was on {sup 16}O, other p-shell nuclei, and {sup 40}Ca. In 1993 the Mathematics and Computer Science Division acquired a 128-processor IBM SP which has a theoretical peak speed of 16 Gigaflops (GFLOPS). We converted our program to run on this machine. Because of the large memory on each node of the SP, it was easy to convert the program to parallel form with very low communication overhead. Considerably more effort was needed to restructure the program from one oriented towards long vectors for the Cray computers at NERSC to one that makes efficient use of the cache of the RS6000 architecture. The SP made possible complete five-body cluster calculations of {sup 16}O for the first time; previously we could only do four-body cluster calculations. These calculations show that the expectation value of the two-body potential is converging less rapidly than we had thought, while that of the three-body potential is more rapidly convergent; the net result is no significant change to our predicted binding energy for {sup 16}O using the new Argonne v{sub 18} potential and the Urbana IX three-nucleon potential. This result is in good agreement with experiment.« less

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT. [NASA scatterometer

NASA Technical Reports Server (NTRS)

Shaffer, Scott; Dunbar, R. Scott; Hsiao, S. Vincent; Long, David G.

1989-01-01

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

Engineering Room-temperature Superconductors Via ab-initio Calculations

NASA Astrophysics Data System (ADS)

Gulian, Mamikon; Melkonyan, Gurgen; Gulian, Armen

The BCS, or bosonic model of superconductivity, as Little and Ginzburg have first argued, can bring in superconductivity at room temperatures in the case of high-enough frequency of bosonic mode. It was further elucidated by Kirzhnitset al., that the condition for existence of high-temperature superconductivity is closely related to negative values of the real part of the dielectric function at finite values of the reciprocal lattice vectors. In view of these findings, the task is to calculate the dielectric function for real materials. Then the poles of this function will indicate the existence of bosonic excitations which can serve as a "glue" for Cooper pairing, and if the frequency is high enough, and the dielectric matrix is simultaneously negative, this material is a good candidate for very high-Tc superconductivity. Thus, our approach is to elaborate a methodology of ab-initio calculation of the dielectric function of various materials, and then point out appropriate candidates. We used the powerful codes (TDDF with the DP package in conjunction with ABINIT) for computing dielectric responses at finite values of the wave vectors in the reciprocal lattice space. Though our report is concerned with the particular problem of superconductivity, the application range of the data processing methodology is much wider. The ability to compute the dielectric function of existing and still non-existing (though being predicted!) materials will have many more repercussions not only in fundamental sciences but also in technology and industry.

EMMA: An Extensible Mammalian Modular Assembly Toolkit for the Rapid Design and Production of Diverse Expression Vectors.

PubMed

Martella, Andrea; Matjusaitis, Mantas; Auxillos, Jamie; Pollard, Steven M; Cai, Yizhi

2017-07-21

Mammalian plasmid expression vectors are critical reagents underpinning many facets of research across biology, biomedical research, and the biotechnology industry. Traditional cloning methods often require laborious manual design and assembly of plasmids using tailored sequential cloning steps. This process can be protracted, complicated, expensive, and error-prone. New tools and strategies that facilitate the efficient design and production of bespoke vectors would help relieve a current bottleneck for researchers. To address this, we have developed an extensible mammalian modular assembly kit (EMMA). This enables rapid and efficient modular assembly of mammalian expression vectors in a one-tube, one-step golden-gate cloning reaction, using a standardized library of compatible genetic parts. The high modularity, flexibility, and extensibility of EMMA provide a simple method for the production of functionally diverse mammalian expression vectors. We demonstrate the value of this toolkit by constructing and validating a range of representative vectors, such as transient and stable expression vectors (transposon based vectors), targeting vectors, inducible systems, polycistronic expression cassettes, fusion proteins, and fluorescent reporters. The method also supports simple assembly combinatorial libraries and hierarchical assembly for production of larger multigenetic cargos. In summary, EMMA is compatible with automated production, and novel genetic parts can be easily incorporated, providing new opportunities for mammalian synthetic biology.

A Phrase-Based Matching Function.

ERIC Educational Resources Information Center

Galbiati, Giulia

1991-01-01

Describes the development of an information retrieval system designed for nonspecialist users that is based on the binary vector model. The syntactic structure of phrases used for indexing is examined, queries using an experimental collection of documents are described, and precision values are examined. (19 references) (LRW)

Meson effective mass in the isospin medium in hard-wall AdS/QCD model

NASA Astrophysics Data System (ADS)

Mamedov, Shahin

2016-02-01

We study a mass splitting of the light vector, axial-vector, and pseudoscalar mesons in the isospin medium in the framework of the hard-wall model. We write an effective mass definition for the interacting gauge fields and scalar field introduced in gauge field theory in the bulk of AdS space-time. Relying on holographic duality we obtain a formula for the effective mass of a boundary meson in terms of derivative operator over the extra bulk coordinate. The effective mass found in this way coincides with the one obtained from finding of poles of the two-point correlation function. In order to avoid introducing distinguished infrared boundaries in the quantization formula for the different mesons from the same isotriplet we introduce extra action terms at this boundary, which reduces distinguished values of this boundary to the same value. Profile function solutions and effective mass expressions were found for the in-medium ρ , a_1, and π mesons.

Correlation between polar values and vector analysis.

PubMed

Naeser, K; Behrens, J K

1997-01-01

To evaluate the possible correlation between polar value and vector analysis assessment of surgically induced astigmatism. Department of Ophthalmology, Aalborg Sygehus Syd, Denmark. The correlation between polar values and vector analysis was evaluated by simple mathematical and optical methods using accepted principles of trigonometry and first-order optics. Vector analysis and polar values report different aspects of surgically induced astigmatism. Vector analysis describes the total astigmatic change, characterized by both astigmatic magnitude and direction, while the polar value method produces a single, reduced figure that reports flattening or steepening in preselected directions, usually the plane of the surgical meridian. There is a simple Pythagorean correlation between vector analysis and two polar values separated by an arch of 45 degrees. The polar value calculated in the surgical meridian indicates the power or the efficacy of the surgical procedure. The polar value calculated in a plane inclined 45 degrees to the surgical meridian indicates the degree of cylinder rotation induced by surgery. These two polar values can be used to obtain other relevant data such as magnitude, direction, and sphere of an induced cylinder. Consistent use of these methods will enable surgeons to control and in many cases reduce preoperative astigmatism.

Stokes' theorem, gauge symmetry and the time-dependent Aharonov-Bohm effect

DOE Office of Scientific and Technical Information (OSTI.GOV)

Macdougall, James, E-mail: jbm34@mail.fresnostate.edu; Singleton, Douglas, E-mail: dougs@csufresno.edu

2014-04-15

Stokes' theorem is investigated in the context of the time-dependent Aharonov-Bohm effect—the two-slit quantum interference experiment with a time varying solenoid between the slits. The time varying solenoid produces an electric field which leads to an additional phase shift which is found to exactly cancel the time-dependent part of the usual magnetic Aharonov-Bohm phase shift. This electric field arises from a combination of a non-single valued scalar potential and/or a 3-vector potential. The gauge transformation which leads to the scalar and 3-vector potentials for the electric field is non-single valued. This feature is connected with the non-simply connected topology ofmore » the Aharonov-Bohm set-up. The non-single valued nature of the gauge transformation function has interesting consequences for the 4-dimensional Stokes' theorem for the time-dependent Aharonov-Bohm effect. An experimental test of these conclusions is proposed.« less

Search for heavy vector-like quarks coupling to light quarks in proton–proton collisions at s = 7   TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-05-01

This Letter presents a search for singly produced vector-like quarks, Q, coupling to light quarks, q. The search is sensitive to both charged current (CC) and neutral current (NC) processes, pp→Qq→Wqq' and pp→Qq→Zqq' with a leptonic decay of the vector gauge boson. In 1.04fb -1 of data taken in 2011 by the ATLAS experiment at a center-of-mass energy √s=7TeV, no evidence of such heavy vector-like quarks is observed above the expected Standard Model background. Limits on the heavy vector-like quark production cross section times branching ratio as a function of mass m Q are obtained. For a coupling κ qQ=v/mmore » Q, where v is the Higgs vacuum expectation value, 95% C.L. lower limits on the mass of a vector-like quark are set at 900 GeV and 760 GeV from CC and NC processes, respectively.« less

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

2013-12-15

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Code Samples Used for Complexity and Control

NASA Astrophysics Data System (ADS)

Ivancevic, Vladimir G.; Reid, Darryn J.

2015-11-01

The following sections are included: * MathematicaⓇ Code * Generic Chaotic Simulator * Vector Differential Operators * NLS Explorer * 2C++ Code * C++ Lambda Functions for Real Calculus * Accelerometer Data Processor * Simple Predictor-Corrector Integrator * Solving the BVP with the Shooting Method * Linear Hyperbolic PDE Solver * Linear Elliptic PDE Solver * Method of Lines for a Set of the NLS Equations * C# Code * Iterative Equation Solver * Simulated Annealing: A Function Minimum * Simple Nonlinear Dynamics * Nonlinear Pendulum Simulator * Lagrangian Dynamics Simulator * Complex-Valued Crowd Attractor Dynamics * Freeform Fortran Code * Lorenz Attractor Simulator * Complex Lorenz Attractor * Simple SGE Soliton * Complex Signal Presentation * Gaussian Wave Packet * Hermitian Matrices * Euclidean L2-Norm * Vector/Matrix Operations * Plain C-Code: Levenberg-Marquardt Optimizer * Free Basic Code: 2D Crowd Dynamics with 3000 Agents

Matrix multiplication operations using pair-wise load and splat operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eichenberger, Alexandre E.; Gschwind, Michael K.; Gunnels, John A.

Mechanisms for performing a matrix multiplication operation are provided. A vector load operation is performed to load a first vector operand of the matrix multiplication operation to a first target vector register. A pair-wise load and splat operation is performed to load a pair of scalar values of a second vector operand and replicate the pair of scalar values within a second target vector register. An operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the matrix multiplication operation. The partial product is accumulatedmore » with other partial products and a resulting accumulated partial product is stored. This operation may be repeated for a second pair of scalar values of the second vector operand.« less

Probability Distributions of Minkowski Distances between Discrete Random Variables.

ERIC Educational Resources Information Center

Schroger, Erich; And Others

1993-01-01

Minkowski distances are used to indicate similarity of two vectors in an N-dimensional space. How to compute the probability function, the expectation, and the variance for Minkowski distances and the special cases City-block distance and Euclidean distance. Critical values for tests of significance are presented in tables. (SLD)

Structuring Stokes correlation functions using vector-vortex beam

NASA Astrophysics Data System (ADS)

Kumar, Vijay; Anwar, Ali; Singh, R. P.

2018-01-01

Higher order statistical correlations of the optical vector speckle field, formed due to scattering of a vector-vortex beam, are explored. Here, we report on the experimental construction of the Stokes parameters covariance matrix, consisting of all possible spatial Stokes parameters correlation functions. We also propose and experimentally realize a new Stokes correlation functions called Stokes field auto correlation functions. It is observed that the Stokes correlation functions of the vector-vortex beam will be reflected in the respective Stokes correlation functions of the corresponding vector speckle field. The major advantage of proposing Stokes correlation functions is that the Stokes correlation function can be easily tuned by manipulating the polarization of vector-vortex beam used to generate vector speckle field and to get the phase information directly from the intensity measurements. Moreover, this approach leads to a complete experimental Stokes characterization of a broad range of random fields.

Grid generation on surfaces in 3 dimensions

NASA Technical Reports Server (NTRS)

Eiseman, Peter R.

1986-01-01

The development of a surface grid generation algorithm was initiated. The basic adaptive movement technique of mean-value-relaxation was extended from the viewpoint of a single coordinate grid over a surface described by a single scalar function to that of a surface more generally defined by vector functions and covered by a collection of smoothly connected grids. Within the multiconnected assemblage, the application of control was examined in several instances.

Calibration of Predictor Models Using Multiple Validation Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Practical auxiliary basis implementation of Rung 3.5 functionals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janesko, Benjamin G., E-mail: b.janesko@tcu.edu; Scalmani, Giovanni; Frisch, Michael J.

2014-07-21

Approximate exchange-correlation functionals for Kohn-Sham density functional theory often benefit from incorporating exact exchange. Exact exchange is constructed from the noninteracting reference system's nonlocal one-particle density matrix γ(r{sup -vector},r{sup -vector}′). Rung 3.5 functionals attempt to balance the strengths and limitations of exact exchange using a new ingredient, a projection of γ(r{sup -vector},r{sup -vector} ′) onto a semilocal model density matrix γ{sub SL}(ρ(r{sup -vector}),∇ρ(r{sup -vector}),r{sup -vector}−r{sup -vector} ′). γ{sub SL} depends on the electron density ρ(r{sup -vector}) at reference point r{sup -vector}, and is closely related to semilocal model exchange holes. We present a practical implementation of Rung 3.5 functionals, expandingmore » the r{sup -vector}−r{sup -vector} ′ dependence of γ{sub SL} in an auxiliary basis set. Energies and energy derivatives are obtained from 3D numerical integration as in standard semilocal functionals. We also present numerical tests of a range of properties, including molecular thermochemistry and kinetics, geometries and vibrational frequencies, and bandgaps and excitation energies. Rung 3.5 functionals typically provide accuracy intermediate between semilocal and hybrid approximations. Nonlocal potential contributions from γ{sub SL} yield interesting successes and failures for band structures and excitation energies. The results enable and motivate continued exploration of Rung 3.5 functional forms.« less

Combining Relevance Vector Machines and exponential regression for bearing residual life estimation

NASA Astrophysics Data System (ADS)

Di Maio, Francesco; Tsui, Kwok Leung; Zio, Enrico

2012-08-01

In this paper we present a new procedure for estimating the bearing Residual Useful Life (RUL) by combining data-driven and model-based techniques. Respectively, we resort to (i) Relevance Vector Machines (RVMs) for selecting a low number of significant basis functions, called Relevant Vectors (RVs), and (ii) exponential regression to compute and continuously update residual life estimations. The combination of these techniques is developed with reference to partially degraded thrust ball bearings and tested on real world vibration-based degradation data. On the case study considered, the proposed procedure outperforms other model-based methods, with the added value of an adequate representation of the uncertainty associated to the estimates of the quantification of the credibility of the results by the Prognostic Horizon (PH) metric.

Energy Band Gap Dependence of Valley Polarization of the Hexagonal Lattice

NASA Astrophysics Data System (ADS)

Ghalamkari, Kazu; Tatsumi, Yuki; Saito, Riichiro

2018-02-01

The origin of valley polarization of the hexagonal lattice is analytically discussed by tight binding method as a function of energy band gap. When the energy gap decreases to zero, the intensity of optical absorption becomes sharp as a function of k near the K (or K') point in the hexagonal Brillouin zone, while the peak intensity at the K (or K') point keeps constant with decreasing the energy gap. When the dipole vector as a function of k can have both real and imaginary parts that are perpendicular to each other in the k space, the valley polarization occurs. When the dipole vector has only real values by selecting a proper phase of wave functions, the valley polarization does not occur. The degree of the valley polarization may show a discrete change that can be relaxed to a continuous change of the degree of valley polarization when we consider the life time of photo-excited carrier.

Identifying Turbulent Structures through Topological Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, Peer-Timo; Gruber, Andrea; Bennett, Janine C.

2016-01-01

A new method of extracting vortical structures from a turbulent flow is proposed whereby topological segmentation of an indicator function scalar field is used to identify the regions of influence of the individual vortices. This addresses a long-standing challenge in vector field topological analysis: indicator functions commonly used produce a scalar field based on the local velocity vector field; reconstructing regions of influence for a particular structure requires selecting a threshold to define vortex extent. In practice, the same threshold is rarely meaningful throughout a given flow. By also considering the topology of the indicator field function, the characteristics ofmore » vortex strength and extent can be separated and the ambiguity in the choice of the threshold reduced. The proposed approach is able to identify several types of vortices observed in a jet in cross-flow configuration simultaneously where no single threshold value for a selection of common indicator functions appears able to identify all of these vortex types.« less

Nonparametric methods for drought severity estimation at ungauged sites

NASA Astrophysics Data System (ADS)

Sadri, S.; Burn, D. H.

2012-12-01

The objective in frequency analysis is, given extreme events such as drought severity or duration, to estimate the relationship between that event and the associated return periods at a catchment. Neural networks and other artificial intelligence approaches in function estimation and regression analysis are relatively new techniques in engineering, providing an attractive alternative to traditional statistical models. There are, however, few applications of neural networks and support vector machines in the area of severity quantile estimation for drought frequency analysis. In this paper, we compare three methods for this task: multiple linear regression, radial basis function neural networks, and least squares support vector regression (LS-SVR). The area selected for this study includes 32 catchments in the Canadian Prairies. From each catchment drought severities are extracted and fitted to a Pearson type III distribution, which act as observed values. For each method-duration pair, we use a jackknife algorithm to produce estimated values at each site. The results from these three approaches are compared and analyzed, and it is found that LS-SVR provides the best quantile estimates and extrapolating capacity.

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

NASA Astrophysics Data System (ADS)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

Limitations to mapping habitat-use areas in changing landscapes using the Mahalanobis distance statistic

USGS Publications Warehouse

Knick, Steven T.; Rotenberry, J.T.

1998-01-01

We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

Recognition and Classification of Road Condition on the Basis of Friction Force by Using a Mobile Robot

NASA Astrophysics Data System (ADS)

Watanabe, Tatsuhito; Katsura, Seiichiro

A person operating a mobile robot in a remote environment receives realistic visual feedback about the condition of the road on which the robot is moving. The categorization of the road condition is necessary to evaluate the conditions for safe and comfortable driving. For this purpose, the mobile robot should be capable of recognizing and classifying the condition of the road surfaces. This paper proposes a method for recognizing the type of road surfaces on the basis of the friction between the mobile robot and the road surfaces. This friction is estimated by a disturbance observer, and a support vector machine is used to classify the surfaces. The support vector machine identifies the type of the road surface using feature vector, which is determined using the arithmetic average and variance derived from the torque values. Further, these feature vectors are mapped onto a higher dimensional space by using a kernel function. The validity of the proposed method is confirmed by experimental results.

Index formulas for higher order Loewner vector fields

NASA Astrophysics Data System (ADS)

Broad, Steven

Let ∂ be the Cauchy-Riemann operator and f be a C real-valued function in a neighborhood of 0 in R in which ∂z¯nf≠0 for all z≠0. In such cases, ∂z¯nf is known as a Loewner vector field due to its connection with Loewner's conjecture that the index of such a vector field is bounded above by n. The n=2 case of Loewner's conjecture implies Carathéodory's conjecture that any C-immersion of S into R must have at least two umbilics. Recent work of F. Xavier produced a formula for computing the index of Loewner vector fields when n=2 using data about the Hessian of f. In this paper, we extend this result and establish an index formula for ∂z¯nf for all n⩾2. Structurally, our index formula provides a defect term, which contains geometric data extracted from Hessian-like objects associated with higher order derivatives of f.

Application of quasi-distributions for solving inverse problems of neutron and {gamma}-ray transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pogosbekyan, L.R.; Lysov, D.A.

The considered inverse problems deal with the calculation of the unknown values of nuclear installations by means of the known (goal) functionals of neutron/{gamma}-ray distributions. The example of these problems might be the calculation of the automatic control rods position as function of neutron sensors reading, or the calculation of experimentally-corrected values of cross-sections, isotopes concentration, fuel enrichment via the measured functional. The authors have developed the new method to solve inverse problem. It finds flux density as quasi-solution of the particles conservation linear system adjointed to equalities for functionals. The method is more effective compared to the one basedmore » on the classical perturbation theory. It is suitable for vectorization and it can be used successfully in optimization codes.« less

A Mathematical Motivation for Complex-Valued Convolutional Networks.

PubMed

Tygert, Mark; Bruna, Joan; Chintala, Soumith; LeCun, Yann; Piantino, Serkan; Szlam, Arthur

2016-05-01

A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing real-valued random vectors, complex-valued convnets can be viewed as data-driven multiscale windowed power spectra, data-driven multiscale windowed absolute spectra, data-driven multiwavelet absolute values, or (in their most general configuration) data-driven nonlinear multiwavelet packets. Indeed, complex-valued convnets can calculate multiscale windowed spectra when the convnet filters are windowed complex-valued exponentials. Standard real-valued convnets, using rectified linear units (ReLUs), sigmoidal (e.g., logistic or tanh) nonlinearities, or max pooling, for example, do not obviously exhibit the same exact correspondence with data-driven wavelets (whereas for complex-valued convnets, the correspondence is much more than just a vague analogy). Courtesy of the exact correspondence, the remarkably rich and rigorous body of mathematical analysis for wavelets applies directly to (complex-valued) convnets.

"Analytical" vector-functions I

NASA Astrophysics Data System (ADS)

Todorov, Vladimir Todorov

2017-12-01

In this note we try to give a new (or different) approach to the investigation of analytical vector functions. More precisely a notion of a power xn; n ∈ ℕ+ of a vector x ∈ ℝ3 is introduced which allows to define an "analytical" function f : ℝ3 → ℝ3. Let furthermore f (ξ )= ∑n =0 ∞ anξn be an analytical function of the real variable ξ. Here we replace the power ξn of the number ξ with the power of a vector x ∈ ℝ3 to obtain a vector "power series" f (x )= ∑n =0 ∞ anxn . We research some properties of the vector series as well as some applications of this idea. Note that an "analytical" vector function does not depend of any basis, which may be used in research into some problems in physics.

Vector-averaged gravity does not alter acetylcholine receptor single channel properties

NASA Technical Reports Server (NTRS)

Reitstetter, R.; Gruener, R.

1994-01-01

To examine the physiological sensitivity of membrane receptors to altered gravity, we examined the single channel properties of the acetylcholine receptor (AChR), in co-cultures of Xenopus myocytes and neurons, to vector-averaged gravity in the clinostat. This experimental paradigm produces an environment in which, from the cell's perspective, the gravitational vector is "nulled" by continuous averaging. In that respect, the clinostat simulates one aspect of space microgravity where the gravity force is greatly reduced. After clinorotation, the AChR channel mean open-time and conductance were statistically not different from control values but showed a rotation-dependent trend that suggests a process of cellular adaptation to clinorotation. These findings therefore suggest that the ACHR channel function may not be affected in the microgravity of space despite changes in the receptor's cellular organization.

Evaluation of modulation transfer function of optical lens system by support vector regression methodologies - A comparative study

NASA Astrophysics Data System (ADS)

Petković, Dalibor; Shamshirband, Shahaboddin; Saboohi, Hadi; Ang, Tan Fong; Anuar, Nor Badrul; Rahman, Zulkanain Abdul; Pavlović, Nenad T.

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict estimate MTF value of the actual optical system according to experimental tests. Instead of minimizing the observed training error, SVR_poly and SVR_rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR_rbf approach in compare to SVR_poly soft computing methodology.

Orthonormal vector polynomials in a unit circle, Part I: Basis set derived from gradients of Zernike polynomials.

PubMed

Zhao, Chunyu; Burge, James H

2007-12-24

Zernike polynomials provide a well known, orthogonal set of scalar functions over a circular domain, and are commonly used to represent wavefront phase or surface irregularity. A related set of orthogonal functions is given here which represent vector quantities, such as mapping distortion or wavefront gradient. These functions are generated from gradients of Zernike polynomials, made orthonormal using the Gram- Schmidt technique. This set provides a complete basis for representing vector fields that can be defined as a gradient of some scalar function. It is then efficient to transform from the coefficients of the vector functions to the scalar Zernike polynomials that represent the function whose gradient was fit. These new vector functions have immediate application for fitting data from a Shack-Hartmann wavefront sensor or for fitting mapping distortion for optical testing. A subsequent paper gives an additional set of vector functions consisting only of rotational terms with zero divergence. The two sets together provide a complete basis that can represent all vector distributions in a circular domain.

On the M-function and Borg-Marchenko theorems for vector-valued Sturm-Liouville equations

NASA Astrophysics Data System (ADS)

Andersson, E.

2003-12-01

We will consider a vector-valued Sturm-Liouville equation of the form R[U]≔-(PU')'+QU=λWU, x∈[0,b), with P-1, W, Q∈Lloc1([0,b))m×m being Hermitian and under some additional conditions on P-1 and W. We give an elementary deduction of the leading order term asymptotics for the Titchmarsh-Weyl M-function corresponding to this equation. In the special case of P=W=I, Q∈L1([0,∞))m×m and the Neumann boundary conditions at 0, we will also prove that M=(1/√-λ )(I+R)(I-R)-1, where R=limn→∞ Rn=∑n=1∞Qn, for recursively defined sequences {Rn} and {Qn}. If Q∈Lloc1([0,b))m×m, 0

Evaluation of the concentration and bioactivity of adenovirus vectors for gene therapy.

PubMed Central

Mittereder, N; March, K L; Trapnell, B C

1996-01-01

Development of adenovirus vectors as potential therapeutic agents for multiple applications of in vivo human gene therapy has resulted in numerous preclinical and clinical studies. However, lack of standardization of the methods for quantifying the physical concentration and functionally active fraction of virions in these studies has often made comparison between various studies difficult or impossible. This study was therefore carried out to define the variables for quantification of the concentration of adenovirus vectors. The methods for evaluation of total virion concentration included electron microscopy and optical absorbance. The methods for evaluation of the concentration of functional virions included detection of gene transfer (transgene transfer and expression) and the plaque assay on 293 cells. Enumeration of total virion concentration by optical absorbance was found to be a precise procedure, but accuracy was dependent on physical disruption of the virion to eliminate artifacts from light scattering and also on a correct value for the extinction coefficient. Both biological assays for enumerating functional virions were highly dependent on the assay conditions and in particular the time of virion adsorption and adsorption volume. Under optimal conditions, the bioactivity of the vector, defined as the fraction of total virions which leads to detected target cell infection, was determined to be 0.10 in the plaque assay and 0.29 in the gene transfer assay. This difference is most likely due to the fact that detection by gene transfer requires only measurement of levels of transgene expression in the infected cell whereas plaque formation is dependent on a series of biological events of much greater complexity. These results show that the exact conditions for determination of infectious virion concentration and bioactivity of recombinant adenovirus vectors are critical and must be standardized for comparability. These observations may be very useful in comparison of data from different preclinical and clinical studies and may also have important implications for how adenovirus vectors can optimally be used in human gene therapy. PMID:8892868

BJUT at TREC 2014 Temporal Summarization Track

DTIC Science & Technology

2014-11-01

information retrieval, indexing and relevancy rankings. In VSM, sentences and queries are represented as vectors: 1, 2, ,( , ,..., ) j j j t jd w w w...di = (w1, j , w2, j , · · · , wt, j ) (1) Each dimension corresponds to a separate term. If a t - m occurs in the sentence, its value in the vector is non...by the cost function Σi|I(Xi)− ∑ j WijI(Xi;Xj)|2 (5) Table 1: Experimental Result. EG C F Q0 Q1 AVG Q0 Q1 AVG Q0 Q1 AVG Topic 11 0.0504 0.0396 0.0358

Current Advances and Future Challenges in Adenoviral Vector Biology and Targeting

PubMed Central

Campos, Samuel K.; Barry, Michael A.

2008-01-01

Gene delivery vectors based on Adenoviral (Ad) vectors have enormous potential for the treatment of both hereditary and acquired disease. Detailed structural analysis of the Ad virion, combined with functional studies has broadened our knowledge of the structure/function relationships between Ad vectors and host cells/tissues and substantial achievement has been made towards a thorough understanding of the biology of Ad vectors. The widespread use of Ad vectors for clinical gene therapy is compromised by their inherent immunogenicity. The generation of safer and more effective Ad vectors, targeted to the site of disease, has therefore become a great ambition in the field of Ad vector development. This review provides a synopsis of the structure/function relationships between Ad vectors and host systems and summarizes the many innovative approaches towards achieving Ad vector targeting. PMID:17584037

Experimental and Theoretical Performance of a Particle Velocity Vector Sensor in a Hybrid Acoustic Beamformer

DTIC Science & Technology

2009-12-01

characterized first by the amplitude and phase relationship of their transfer functions relative to their co-located pressure microphone. The transfer...The Microflown acoustic particle velocity channels were characterized first by the amplitude and phase relationship of their transfer functions...k H k H k and  34Ĥ k . 3) The angular relationships of the velocity sensors to their respective MRAs were recorded and stored as the values of

Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study.

PubMed

Lima, Clodoaldo A M; Coelho, André L V

2011-10-01

We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely, Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). Copyright © 2011 Elsevier B.V. All rights reserved.

Monopole-antimonopole interaction potential

NASA Astrophysics Data System (ADS)

Saurabh, Ayush; Vachaspati, Tanmay

2017-11-01

We numerically study the interactions of twisted monopole-antimonopole pairs in the 't Hooft-Polyakov model for a range of values of the scalar to vector mass ratio. We also recover the sphaleron solution at maximum twist discovered by Taubes [Commun. Math. Phys. 86, 257 (1982), 10.1007/BF01206014] and map out its energy and size as functions of parameters.

Determination of key parameters of vector multifractal vector fields

NASA Astrophysics Data System (ADS)

Schertzer, D. J. M.; Tchiguirinskaia, I.

2017-12-01

For too long time, multifractal analyses and simulations have been restricted to scalar-valued fields (Schertzer and Tchiguirinskaia, 2017a,b). For instance, the wind velocity multifractality has been mostly analysed in terms of scalar structure functions and with the scalar energy flux. This restriction has had the unfortunate consequences that multifractals were applicable to their full extent in geophysics, whereas it has inspired them. Indeed a key question in geophysics is the complexity of the interactions between various fields or they components. Nevertheless, sophisticated methods have been developed to determine the key parameters of scalar valued fields. In this communication, we first present the vector extensions of the universal multifractal analysis techniques to multifractals whose generator belong to a Levy-Clifford algebra (Schertzer and Tchiguirinskaia, 2015). We point out further extensions noting the increased complexity. For instance, the (scalar) index of multifractality becomes a matrice. Schertzer, D. and Tchiguirinskaia, I. (2015) `Multifractal vector fields and stochastic Clifford algebra', Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(12), p. 123127. doi: 10.1063/1.4937364. Schertzer, D. and Tchiguirinskaia, I. (2017) `An Introduction to Multifractals and Scale Symmetry Groups', in Ghanbarian, B. and Hunt, A. (eds) Fractals: Concepts and Applications in Geosciences. CRC Press, p. (in press). Schertzer, D. and Tchiguirinskaia, I. (2017b) `Pandora Box of Multifractals: Barely Open ?', in Tsonis, A. A. (ed.) 30 Years of Nonlinear Dynamics in Geophysics. Berlin: Springer, p. (in press).

Feature extraction through parallel Probabilistic Principal Component Analysis for heart disease diagnosis

NASA Astrophysics Data System (ADS)

Shah, Syed Muhammad Saqlain; Batool, Safeera; Khan, Imran; Ashraf, Muhammad Usman; Abbas, Syed Hussnain; Hussain, Syed Adnan

2017-09-01

Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.

Detection of presence of chemical precursors

NASA Technical Reports Server (NTRS)

Li, Jing (Inventor); Meyyappan, Meyya (Inventor); Lu, Yijiang (Inventor)

2009-01-01

Methods and systems for determining if one or more target molecules are present in a gas, by exposing a functionalized carbon nanostructure (CNS) to the gas and measuring an electrical parameter value EPV(n) associated with each of N CNS sub-arrays. In a first embodiment, a most-probable concentration value C(opt) is estimated, and an error value, depending upon differences between the measured values EPV(n) and corresponding values EPV(n;C(opt)) is computed. If the error value is less than a first error threshold value, the system interprets this as indicating that the target molecule is present in a concentration C.apprxeq.C(opt). A second embodiment uses extensive statistical and vector space analysis to estimate target molecule concentration.

Genome content analysis yields new insights into the relationship between the human malaria parasite Plasmodium falciparum and its anopheline vectors.

PubMed

Oppenheim, Sara J; Rosenfeld, Jeffrey A; DeSalle, Rob

2017-02-27

The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach.

A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

PubMed

Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

2015-02-01

We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

A Note on a Sampling Theorem for Functions over GF(q)n Domain

NASA Astrophysics Data System (ADS)

Ukita, Yoshifumi; Saito, Tomohiko; Matsushima, Toshiyasu; Hirasawa, Shigeichi

In digital signal processing, the sampling theorem states that any real valued function ƒ can be reconstructed from a sequence of values of ƒ that are discretely sampled with a frequency at least twice as high as the maximum frequency of the spectrum of ƒ. This theorem can also be applied to functions over finite domain. Then, the range of frequencies of ƒ can be expressed in more detail by using a bounded set instead of the maximum frequency. A function whose range of frequencies is confined to a bounded set is referred to as bandlimited function. And a sampling theorem for bandlimited functions over Boolean domain has been obtained. Here, it is important to obtain a sampling theorem for bandlimited functions not only over Boolean domain (GF(q)n domain) but also over GF(q)n domain, where q is a prime power and GF(q) is Galois field of order q. For example, in experimental designs, although the model can be expressed as a linear combination of the Fourier basis functions and the levels of each factor can be represented by GF(q)n, the number of levels often take a value greater than two. However, the sampling theorem for bandlimited functions over GF(q)n domain has not been obtained. On the other hand, the sampling points are closely related to the codewords of a linear code. However, the relation between the parity check matrix of a linear code and any distinct error vectors has not been obtained, although it is necessary for understanding the meaning of the sampling theorem for bandlimited functions. In this paper, we generalize the sampling theorem for bandlimited functions over Boolean domain to a sampling theorem for bandlimited functions over GF(q)n domain. We also present a theorem for the relation between the parity check matrix of a linear code and any distinct error vectors. Lastly, we clarify the relation between the sampling theorem for functions over GF(q)n domain and linear codes.

Thermodynamic integration of the free energy along a reaction coordinate in Cartesian coordinates

NASA Astrophysics Data System (ADS)

den Otter, W. K.

2000-05-01

A generalized formulation of the thermodynamic integration (TI) method for calculating the free energy along a reaction coordinate is derived. Molecular dynamics simulations with a constrained reaction coordinate are used to sample conformations. These are then projected onto conformations with a higher value of the reaction coordinate by means of a vector field. The accompanying change in potential energy plus the divergence of the vector field constitute the derivative of the free energy. Any vector field meeting some simple requirements can be used as the basis of this TI expression. Two classes of vector fields are of particular interest here. The first recovers the conventional TI expression, with its cumbersome dependence on a full set of generalized coordinates. As the free energy is a function of the reaction coordinate only, it should in principle be possible to derive an expression depending exclusively on the definition of the reaction coordinate. This objective is met by the second class of vector fields to be discussed. The potential of mean constraint force (PMCF) method, after averaging over the unconstrained momenta, falls in this second class. The new method is illustrated by calculations on the isomerization of n-butane, and is compared with existing methods.

Flight-Determined Subsonic Longitudinal Stability and Control Derivatives of the F-18 High Angle of Attack Research Vehicle (HARV) with Thrust Vectoring

NASA Technical Reports Server (NTRS)

Iliff, Kenneth W.; Wang, Kon-Sheng Charles

1997-01-01

The subsonic longitudinal stability and control derivatives of the F-18 High Angle of Attack Research Vehicle (HARV) are extracted from dynamic flight data using a maximum likelihood parameter identification technique. The technique uses the linearized aircraft equations of motion in their continuous/discrete form and accounts for state and measurement noise as well as thrust-vectoring effects. State noise is used to model the uncommanded forcing function caused by unsteady aerodynamics over the aircraft, particularly at high angles of attack. Thrust vectoring was implemented using electrohydraulically-actuated nozzle postexit vanes and a specialized research flight control system. During maneuvers, a control system feature provided independent aerodynamic control surface inputs and independent thrust-vectoring vane inputs, thereby eliminating correlations between the aircraft states and controls. Substantial variations in control excitation and dynamic response were exhibited for maneuvers conducted at different angles of attack. Opposing vane interactions caused most thrust-vectoring inputs to experience some exhaust plume interference and thus reduced effectiveness. The estimated stability and control derivatives are plotted, and a discussion relates them to predicted values and maneuver quality.

System for Automated Calibration of Vector Modulators

NASA Technical Reports Server (NTRS)

Lux, James; Boas, Amy; Li, Samuel

2009-01-01

Vector modulators are used to impose baseband modulation on RF signals, but non-ideal behavior limits the overall performance. The non-ideal behavior of the vector modulator is compensated using data collected with the use of an automated test system driven by a LabVIEW program that systematically applies thousands of control-signal values to the device under test and collects RF measurement data. The technology innovation automates several steps in the process. First, an automated test system, using computer controlled digital-to-analog converters (DACs) and a computer-controlled vector network analyzer (VNA) systematically can apply different I and Q signals (which represent the complex number by which the RF signal is multiplied) to the vector modulator under test (VMUT), while measuring the RF performance specifically, gain and phase. The automated test system uses the LabVIEW software to control the test equipment, collect the data, and write it to a file. The input to the Lab - VIEW program is either user-input for systematic variation, or is provided in a file containing specific test values that should be fed to the VMUT. The output file contains both the control signals and the measured data. The second step is to post-process the file to determine the correction functions as needed. The result of the entire process is a tabular representation, which allows translation of a desired I/Q value to the required analog control signals to produce a particular RF behavior. In some applications, corrected performance is needed only for a limited range. If the vector modulator is being used as a phase shifter, there is only a need to correct I and Q values that represent points on a circle, not the entire plane. This innovation has been used to calibrate 2-GHz MMIC (monolithic microwave integrated circuit) vector modulators in the High EIRP Cluster Array project (EIRP is high effective isotropic radiated power). These calibrations were then used to create correction tables to allow the commanding of the phase shift in each of four channels used as a phased array for beam steering of a Ka-band (32-GHz) signal. The system also was the basis of a breadboard electronic beam steering system. In this breadboard, the goal was not to make systematic measurements of the properties of a vector modulator, but to drive the breadboard with a series of test patterns varying in phase and amplitude. This is essentially the same calibration process, but with the difference that the data collection process is oriented toward collecting breadboard performance, rather than the measurement of output from a network analyzer.

[Formula: see text]-convergence, complete convergence, and weak laws of large numbers for asymptotically negatively associated random vectors with values in [Formula: see text].

PubMed

Ko, Mi-Hwa

2018-01-01

In this paper, based on the Rosenthal-type inequality for asymptotically negatively associated random vectors with values in [Formula: see text], we establish results on [Formula: see text]-convergence and complete convergence of the maximums of partial sums are established. We also obtain weak laws of large numbers for coordinatewise asymptotically negatively associated random vectors with values in [Formula: see text].

Value at 2 of the L-function of an elliptic curve

NASA Astrophysics Data System (ADS)

Brunault, Francois

2006-02-01

We study the special value at 2 of L-functions of modular forms of weight 2 on congruence subgroups of the modular group. We prove an explicit version of Beilinson's theorem for the modular curve X_1(N). When N is prime, we deduce that the target space of Beilinson's regulator map is generated by the images of Milnor symbols associated to modular units of X_1(N). We also suggest a reformulation of Zagier's conjecture on L(E,2) for the jacobian J_1(N) of X_1(N), where E is an elliptic curve of conductor N. In this direction we define an analogue of the elliptic dilogarithm for any jacobian J : it is a function R_J from the complex points of J to a finite-dimensional vector space. In the case J=J_1(N), we establish a link between the aforementioned L-values and the function R_J evaluated at Q-rational points of the cuspidal subgroup of J.

Minimal supergravity models of inflation

NASA Astrophysics Data System (ADS)

Ferrara, Sergio; Kallosh, Renata; Linde, Andrei; Porrati, Massimo

2013-10-01

We present a superconformal master action for a class of supergravity models with one arbitrary function defining the Jordan frame. It leads to a gauge-invariant action for a real vector multiplet, which upon gauge fixing describes a massive vector multiplet, or to a dual formulation with a linear multiplet and a massive tensor field. In both cases the models have one real scalar, the inflaton, naturally suited for single-field inflation. Vectors and tensors required by supersymmetry to complement a single real scalar do not acquire vacuum expectation values during inflation, so there is no need to stabilize the extra scalars that are always present in the theories with chiral matter multiplets. The new class of models can describe any inflaton potential that vanishes at its minimum and grows monotonically away from the minimum. In this class of supergravity models, one can fit any desirable choice of inflationary parameters ns and r.

Effective Numerical Methods for Solving Elliptical Problems in Strengthened Sobolev Spaces

NASA Technical Reports Server (NTRS)

D'yakonov, Eugene G.

1996-01-01

Fourth-order elliptic boundary value problems in the plane can be reduced to operator equations in Hilbert spaces G that are certain subspaces of the Sobolev space W(sub 2)(exp 2)(Omega) is identical with G(sup (2)). Appearance of asymptotically optimal algorithms for Stokes type problems made it natural to focus on an approach that considers rot w is identical with (D(sub 2)w - D(sub 1)w) is identical with vector of u as a new unknown vector-function, which automatically satisfies the condition div vector of u = 0. In this work, we show that this approach can also be developed for an important class of problems from the theory of plates and shells with stiffeners. The main mathematical problem was to show that the well-known inf-sup condition (normal solvability of the divergence operator) holds for special Hilbert spaces. This result is also essential for certain hydrodynamics problems.

Permutation entropy with vector embedding delays

NASA Astrophysics Data System (ADS)

Little, Douglas J.; Kane, Deb M.

2017-12-01

Permutation entropy (PE) is a statistic used widely for the detection of structure within a time series. Embedding delay times at which the PE is reduced are characteristic timescales for which such structure exists. Here, a generalized scheme is investigated where embedding delays are represented by vectors rather than scalars, permitting PE to be calculated over a (D -1 ) -dimensional space, where D is the embedding dimension. This scheme is applied to numerically generated noise, sine wave and logistic map series, and experimental data sets taken from a vertical-cavity surface emitting laser exhibiting temporally localized pulse structures within the round-trip time of the laser cavity. Results are visualized as PE maps as a function of embedding delay, with low PE values indicating combinations of embedding delays where correlation structure is present. It is demonstrated that vector embedding delays enable identification of structure that is ambiguous or masked, when the embedding delay is constrained to scalar form.

A Bitvectors Library for PVS

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Miner, Paul S.; Srivas, Mandayam K.; Greve, Dave A.; Miller, Steven P.

1996-01-01

This paper describes a bitvectors library that has been developed for PVS. The library defines a bitvector as a function from a subrange of the integers into (0,1). The library provides functions that interpret a bitvector as a natural number, as a 2's complement number, as a vector of logical values and as a 2's complement fraction. The library provides a concatenation operator and an extractor. Shift, extend and rotate operations are also, defined. Fundamental properties of each of these operations have been proved in PVS.

Study of Equatorial Ionospheric irregularities and Mapping of Electron Density Profiles and Ionograms

DTIC Science & Technology

2012-03-09

equation is a product of a complex basis vector in Jackson and a linear combination of plane wave functions. We convert both the amplitudes and the...wave function arguments from complex scalars to complex vectors . This conversion allows us to separate the electric field vector and the imaginary...magnetic field vector , because exponentials of imaginary scalars convert vectors to imaginary vectors and vice versa, while ex- ponentials of imaginary

Solution of an optimal control lifting body entry problem by an improved method of perturbation functions

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.

1975-01-01

This paper presents a solution to a complex lifting reentry three-degree-of-freedom problem by using the calculus of variations to minimize the integral of the sum of the aerodynamics loads and heat rate input to the vehicle. The entry problem considered does not have state and/or control constraints along the trajectory. The calculus of variations method applied to this problem gives rise to a set of necessary conditions which are used to formulate a two point boundary value (TPBV) problem. This TPBV problem is then numerically solved by an improved method of perturbation functions (IMPF) using several starting co-state vectors. These vectors were chosen so that each one had a larger norm with respect to show how the envelope of convergence is significantly increased using this method and cases are presented to point this out.

Recent Selected Papers of Northwestern Polytechnical University in Two Parts, Part II.

DTIC Science & Technology

1981-08-28

OF CONTENTS Page Dual Properties of Elastic Structures 1 Matrix Analysis of Wings 76 On a Method for the Determination of Plane Stress Fracture...I= Ea]{(x, v,z) j l~i l’m mini The equation above means that the cisplacement function vector determines the strain function vector. (Assumption II...means that the distributed load function vector is determined by the stress function vector. In Section 1, there was an analysis of a three

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Semiflexible polymer dynamics with a bead-spring model

NASA Astrophysics Data System (ADS)

Barkema, Gerard T.; Panja, Debabrata; van Leeuwen, J. M. J.

2014-11-01

We study the dynamical properties of semiflexible polymers with a recently introduced bead-spring model. We focus on double-stranded DNA (dsDNA). The two parameters of the model, T* and ν, are chosen to match its experimental force-extension curve. In comparison to its groundstate value, the bead-spring Hamiltonian is approximated in the first order by the Hessian that is quadratic in the bead positions. The eigenmodes of the Hessian provide the longitudinal (stretching) and transverse (bending) eigenmodes of the polymer, and the corresponding eigenvalues match well with the established phenomenology of semiflexible polymers. At the Hessian approximation of the Hamiltonian, the polymer dynamics is linear. Using the longitudinal and transverse eigenmodes, for the linearized problem, we obtain analytical expressions of (i) the autocorrelation function of the end-to-end vector, (ii) the autocorrelation function of a bond (i.e. a spring, or a tangent) vector at the middle of the chain, and (iii) the mean-square displacement of a tagged bead in the middle of the chain, as the sum over the contributions from the modes—the so-called ‘mode sums’. We also perform simulations with the full dynamics of the model. The simulations yield numerical values of the correlations functions (i-iii) that agree very well with the analytical expressions for the linearized dynamics. This does not however mean that the nonlinearities are not present. In fact, we also study the mean-square displacement of the longitudinal component of the end-to-end vector that showcases strong nonlinear effects in the polymer dynamics, and we identify at least an effective t7/8 power-law regime in its time-dependence. Nevertheless, in comparison to the full mean-square displacement of the end-to-end vector the nonlinear effects remain small at all times—it is in this sense we state that our results demonstrate that the linearized dynamics suffices for dsDNA fragments that are shorter than or comparable to the persistence length. Our results are consistent with those of the wormlike chain (WLC) model, the commonly used descriptive tool of semiflexible polymers.

Smisc - A collection of miscellaneous functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Landon Sego, PNNL

2015-08-31

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAsmore » d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).« less

A Temperature Compensation Method for Piezo-Resistive Pressure Sensor Utilizing Chaotic Ions Motion Algorithm Optimized Hybrid Kernel LSSVM.

PubMed

Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam Sm, Jahangir

2016-10-14

A piezo-resistive pressure sensor is made of silicon, the nature of which is considerably influenced by ambient temperature. The effect of temperature should be eliminated during the working period in expectation of linear output. To deal with this issue, an approach consists of a hybrid kernel Least Squares Support Vector Machine (LSSVM) optimized by a chaotic ions motion algorithm presented. To achieve the learning and generalization for excellent performance, a hybrid kernel function, constructed by a local kernel as Radial Basis Function (RBF) kernel, and a global kernel as polynomial kernel is incorporated into the Least Squares Support Vector Machine. The chaotic ions motion algorithm is introduced to find the best hyper-parameters of the Least Squares Support Vector Machine. The temperature data from a calibration experiment is conducted to validate the proposed method. With attention on algorithm robustness and engineering applications, the compensation result shows the proposed scheme outperforms other compared methods on several performance measures as maximum absolute relative error, minimum absolute relative error mean and variance of the averaged value on fifty runs. Furthermore, the proposed temperature compensation approach lays a foundation for more extensive research.

Vibration responses of h-BN sheet to charge doping and external strain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Wei; Yang, Yu; Zheng, Fawei

2013-12-07

Based on density functional theory and density functional perturbation theory calculations, we systematically investigate the vibration responses of h-BN sheet to charge doping and external strains. It is found that under hole doping, the phonon frequencies of the ZO and TO branches at different wave vector q shift linearly with different slopes. Under electron doping, although the phonon frequencies shift irregularly, the shifting values are different at different phonon wave vectors. Interestingly, we find that external strain can restrain the irregular vibration responses of h-BN sheet to electron doping. The critical factor is revealed to be the relative position ofmore » the nearly free electron and boron p{sub z} states of h-BN sheet. Under external strains, the vibration responses of h-BN sheet are also found to be highly dependent on the phonon branches. Different vibration modes at different q points are revealed to be responsible for the vibration responses of h-BN sheet to charge doping and external strain. Our results point out a new way to detect the doping or strain status of h-BN sheet by measuring the vibration frequencies at different wave vector.« less

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

Optical Signal Processing.

DTIC Science & Technology

1983-11-30

be large if s is highly negative, which is the Poynting vector, the same singularity function can be case for TeO2 operated in the slow-shear mode...we give the values of the elastic coefficients for PbMoO 4 and TeO2 from which we calculate that s = -0.176 for PbMoO 4 and s = 0.274 for TeO 2. Our...lowest for TeO2 and highest for PbMoO 4; the rate for fused quartz is nearly halfway between these two values. The diffraction patterns produced by

Evaluation Method for Service Branding Using Word-of-Mouth Data

NASA Astrophysics Data System (ADS)

Shirahada, Kunio; Kosaka, Michitaka

Development and spread of internet technology contributes service firms to obtaining the high capability of brand information transmission as well as relative customer feedback data collection. In this paper, we propose a new evaluation method for service branding using firms and consumers data on the internet. Based on service marketing 7Ps (Product, Price, Place, Promotion, People, Physical evidence, Process) which are the key viewpoints for branding, we develop a brand evaluation system including coding methods for Word-of-Mouth (WoM) and corporate introductory information on the internet to identify both customer's service value recognition vector and firm's service value proposition vector. Our system quantitatively clarify both customer's service value recognition of the firm and firm's strength in service value proposition, thereby analyzing service brand communication gaps between firm and consumers. We applied this system to Japanese Ryokan hotel industry. Using six ryokan-hotels' data on Jyaran-net and Rakuten travel, we made totally 983 codes from WoM information and analyzed their service brand value according to three price based categories. As a result, we found that the characteristics of customers' service value recognition vector differ according to the price categories. In addition, the system clarified that there is a firm that has a different service value proposition vector from customers' recognition vector. This helps to analyze corporate service brand strategy and has a significance as a system technology supporting service management.

An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

2003-01-01

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

"Triplet" polycistronic vectors encoding Gata4, Mef2c, and Tbx5 enhances postinfarct ventricular functional improvement compared with singlet vectors.

PubMed

Mathison, Megumi; Singh, Vivek P; Gersch, Robert P; Ramirez, Maricela O; Cooney, Austin; Kaminsky, Stephen M; Chiuchiolo, Maria J; Nasser, Ahmed; Yang, Jianchang; Crystal, Ronald G; Rosengart, Todd K

2014-10-01

The in situ reprogramming of cardiac fibroblasts into induced cardiomyocytes by the administration of gene transfer vectors encoding Gata4 (G), Mef2c (M), and Tbx5 (T) has been shown to improve ventricular function in myocardial infarction models. The efficacy of this strategy could, however, be limited by the need for fibroblast targets to be infected 3 times--once by each of the 3 transgene vectors. We hypothesized that a polycistronic "triplet" vector encoding all 3 transgenes would enhance postinfarct ventricular function compared with use of "singlet" vectors. After validation of the polycistronic vector expression in vitro, adult male Fischer 344 rats (n=6) underwent coronary ligation with or without intramyocardial administration of an adenovirus encoding all 3 major vascular endothelial growth factor (VEGF) isoforms (AdVEGF-All6A positive), followed 3 weeks later by the administration to AdVEGF-All6A-positive treated rats of singlet lentivirus encoding G, M, or T (1×10(5) transducing units each) or the same total dose of a GMT "triplet" lentivirus vector. Western blots demonstrated that triplet and singlet vectors yielded equivalent GMT transgene expression, and fluorescence activated cell sorting demonstrated that triplet vectors were nearly twice as potent as singlet vectors in generating induced cardiomyocytes from cardiac fibroblasts. Echocardiography demonstrated that GMT triplet vectors were more effective than the 3 combined singlet vectors in enhancing ventricular function from postinfarct baselines (triplet, 37%±10%; singlet, 13%±7%; negative control, 9%±5%; P<.05). These data have confirmed that the in situ administration of G, M, and T induces postinfarct ventricular functional improvement and that GMT polycistronic vectors enhance the efficacy of this strategy. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Conditional Tests for Localizing Trait Genes

PubMed Central

Di, Yanming; Thompson, Elizabeth A.

2009-01-01

Background/Aims With pedigree data, genetic linkage can be detected using inheritance vector tests, which explore the discrepancy between the posterior distribution of the inheritance vectors given observed trait values and the prior distribution of the inheritance vectors. In this paper, we propose conditional inheritance vector tests for linkage localization. These conditional tests can also be used to detect additional linkage signals in the presence of previously detected causal genes. Methods For linkage localization, we propose to perform inheritance vector tests conditioning on the inheritance vectors at two positions bounding a test region. We can detect additional linkage signals by conducting a further conditional test in a region with no previously detected genes. We use randomized p values to extend the marginal and conditional tests when the inheritance vectors cannot be completely determined from genetic marker data. Results We conduct simulation studies to compare and contrast the marginal and the conditional tests and to demonstrate that randomized p values can capture both the significance and the uncertainty in the test results. Conclusions The simulation results demonstrate that the proposed conditional tests provide useful localization information, and with informative marker data, the uncertainty in randomized marginal and conditional test results is small. PMID:19439976

Characterization of Hadamard vector classes in terms of least deviations of their elements from vectors of finite degree

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radzievski, G V

2001-12-31

Let A be a linear operator with domain D(A) in a complex Banach space X. An element g element of D{sub {infinity}}(A):=intersection{sub j=1}{sup {infinity}}D(A{sup j}) is called a vector of degree at most {xi} (>0) relative to A if ||A{sup j}g||{<=}c(g){xi}{sup j}, j=0,1,.... The set of vectors of degree at most {xi} is denoted by G{sub {xi}}(A) and the least deviation of an element f of X from the set G{sub {xi}}(A) is denoted by E{sub {xi}}(f,A). For a fixed sequence of positive numbers ({psi}{sub j}){sub j=1}{sup {infinity}} consider a function {gamma}({xi}):=min{sub j=1,2,...}({xi}{psi}{sub j}){sup 1/j}. Conditions for the sequence ({psi}{submore » j}){sub j=1}{sup {infinity}} and the operator A are found that ensure the equality lim sup{sub j{yields}}{sub {infinity}}((||A{sup j}f||)/({psi}{sub j})){sup 1/j} = lim sup{sub {xi}}{sub {yields}}{sub {infinity}}{xi}/({gamma}(E{sub {xi}}(f,A){sup -1})) for f element of D{sub {infinity}}(A). If the quantity on the left-hand side of this formula is finite, then f belongs to the Hadamard class determined by the operator A and the sequence {l_brace}{psi}{sub j}{r_brace}{sub j=1}{sup {infinity}}. One consequence of the above formula is an expression in terms of E{sub {xi}}(f,A) for the radius of holomorphy of the vector-valued function F(zA)f, where f element of D{sub {infinity}}(A), and F(z):={sigma}{sub j=1}{sup {infinity}}z{sup j}/{psi}{sub j} is an entire function.« less

Singular value description of a digital radiographic detector: Theory and measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kyprianou, Iacovos S.; Badano, Aldo; Gallas, Brandon D.

The H operator represents the deterministic performance of any imaging system. For a linear, digital imaging system, this system operator can be written in terms of a matrix, H, that describes the deterministic response of the system to a set of point objects. A singular value decomposition of this matrix results in a set of orthogonal functions (singular vectors) that form the system basis. A linear combination of these vectors completely describes the transfer of objects through the linear system, where the respective singular values associated with each singular vector describe the magnitude with which that contribution to the objectmore » is transferred through the system. This paper is focused on the measurement, analysis, and interpretation of the H matrix for digital x-ray detectors. A key ingredient in the measurement of the H matrix is the detector response to a single x ray (or infinitestimal x-ray beam). The authors have developed a method to estimate the 2D detector shift-variant, asymmetric ray response function (RRF) from multiple measured line response functions (LRFs) using a modified edge technique. The RRF measurements cover a range of x-ray incident angles from 0 deg. (equivalent location at the detector center) to 30 deg. (equivalent location at the detector edge) for a standard radiographic or cone-beam CT geometric setup. To demonstrate the method, three beam qualities were tested using the inherent, Lu/Er, and Yb beam filtration. The authors show that measures using the LRF, derived from an edge measurement, underestimate the system's performance when compared with the H matrix derived using the RRF. Furthermore, the authors show that edge measurements must be performed at multiple directions in order to capture rotational asymmetries of the RRF. The authors interpret the results of the H matrix SVD and provide correlations with the familiar MTF methodology. Discussion is made about the benefits of the H matrix technique with regards to signal detection theory, and the characterization of shift-variant imaging systems.« less

Internal and external potential-field estimation from regional vector data at varying satellite altitude

NASA Astrophysics Data System (ADS)

Plattner, Alain; Simons, Frederik J.

2017-10-01

When modelling satellite data to recover a global planetary magnetic or gravitational potential field, the method of choice remains their analysis in terms of spherical harmonics. When only regional data are available, or when data quality varies strongly with geographic location, the inversion problem becomes severely ill-posed. In those cases, adopting explicitly local methods is to be preferred over adapting global ones (e.g. by regularization). Here, we develop the theory behind a procedure to invert for planetary potential fields from vector observations collected within a spatially bounded region at varying satellite altitude. Our method relies on the construction of spatiospectrally localized bases of functions that mitigate the noise amplification caused by downward continuation (from the satellite altitude to the source) while balancing the conflicting demands for spatial concentration and spectral limitation. The `altitude-cognizant' gradient vector Slepian functions (AC-GVSF) enjoy a noise tolerance under downward continuation that is much improved relative to the `classical' gradient vector Slepian functions (CL-GVSF), which do not factor satellite altitude into their construction. Furthermore, venturing beyond the realm of their first application, published in a preceding paper, in the present article we extend the theory to being able to handle both internal and external potential-field estimation. Solving simultaneously for internal and external fields under the limitation of regional data availability reduces internal-field artefacts introduced by downward-continuing unmodelled external fields, as we show with numerical examples. We explain our solution strategies on the basis of analytic expressions for the behaviour of the estimation bias and variance of models for which signal and noise are uncorrelated, (essentially) space- and band-limited, and spectrally (almost) white. The AC-GVSF are optimal linear combinations of vector spherical harmonics. Their construction is not altogether very computationally demanding when the concentration domains (the regions of spatial concentration) have circular symmetry, for example, on spherical caps or rings—even when the spherical-harmonic bandwidth is large. Data inversion proceeds by solving for the expansion coefficients of truncated function sequences, by least-squares analysis in a reduced-dimensional space. Hence, our method brings high-resolution regional potential-field modelling from incomplete and noisy vector-valued satellite data within reach of contemporary desktop machines.

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arrighi, Bill

2016-03-03

libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.

Increasing the computational efficient of digital cross correlation by a vectorization method

NASA Astrophysics Data System (ADS)

Chang, Ching-Yuan; Ma, Chien-Ching

2017-08-01

This study presents a vectorization method for use in MATLAB programming aimed at increasing the computational efficiency of digital cross correlation in sound and images, resulting in a speedup of 6.387 and 36.044 times compared with performance values obtained from looped expression. This work bridges the gap between matrix operations and loop iteration, preserving flexibility and efficiency in program testing. This paper uses numerical simulation to verify the speedup of the proposed vectorization method as well as experiments to measure the quantitative transient displacement response subjected to dynamic impact loading. The experiment involved the use of a high speed camera as well as a fiber optic system to measure the transient displacement in a cantilever beam under impact from a steel ball. Experimental measurement data obtained from the two methods are in excellent agreement in both the time and frequency domain, with discrepancies of only 0.68%. Numerical and experiment results demonstrate the efficacy of the proposed vectorization method with regard to computational speed in signal processing and high precision in the correlation algorithm. We also present the source code with which to build MATLAB-executable functions on Windows as well as Linux platforms, and provide a series of examples to demonstrate the application of the proposed vectorization method.

Ability of herpes simplex virus vectors to boost immune responses to DNA vectors and to protect against challenge by simian immunodeficiency virus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaur, Amitinder; Sanford, Hannah B.; Garry, Deirdre

2007-01-20

The immunogenicity and protective capacity of replication-defective herpes simplex virus (HSV) vector-based vaccines were examined in rhesus macaques. Three macaques were inoculated with recombinant HSV vectors expressing Gag, Env, and a Tat-Rev-Nef fusion protein of simian immunodeficiency virus (SIV). Three other macaques were primed with recombinant DNA vectors expressing Gag, Env, and a Pol-Tat-Nef-Vif fusion protein prior to boosting with the HSV vectors. Robust anti-Gag and anti-Env cellular responses were detected in all six macaques. Following intravenous challenge with wild-type, cloned SIV239, peak and 12-week plasma viremia levels were significantly lower in vaccinated compared to control macaques. Plasma SIV RNAmore » in vaccinated macaques was inversely correlated with anti-Rev ELISPOT responses on the day of challenge (P value < 0.05), anti-Tat ELISPOT responses at 2 weeks post challenge (P value < 0.05) and peak neutralizing antibody titers pre-challenge (P value 0.06). These findings support continued study of recombinant herpesviruses as a vaccine approach for AIDS.« less

Molecular dynamics simulation of a nanofluidic energy absorption system: effects of the chiral vector of carbon nanotubes.

PubMed

Ganjiani, Sayed Hossein; Hossein Nezhad, Alireza

2018-02-14

A Nanofluidic Energy Absorption System (NEAS) is a novel nanofluidic system with a small volume and weight. In this system, the input mechanical energy is converted to surface tension energy during liquid infiltration in the nanotube. The NEAS is made of a mixture of nanoporous material particles in a functional liquid. In this work, the effects of the chiral vector of a carbon nanotube (CNT) on the performance characteristics of the NEAS are investigated by using molecular dynamics simulation. For this purpose, six CNTs with different diameters for each type of armchair, zigzag and chiral, and several chiral CNTs with different chiral vectors (different values of indices (m,n)) are selected and studied. The results show that in the chiral CNTs, the contact angle shows the hydrophobicity of the CNT, and infiltration pressure is reduced by increasing the values of m and n (increasing the CNT diameter). Contact angle and infiltration pressure are decreased by almost 1.4% and 9% at all diameters, as the type of CNT is changed from chiral to zigzag and then to armchair. Absorbed energy density and efficiency are also decreased by increasing m and n and by changing the type of CNT from chiral to zigzag and then to armchair.

a Gsa-Svm Hybrid System for Classification of Binary Problems

NASA Astrophysics Data System (ADS)

Sarafrazi, Soroor; Nezamabadi-pour, Hossein; Barahman, Mojgan

2011-06-01

This paperhybridizesgravitational search algorithm (GSA) with support vector machine (SVM) and made a novel GSA-SVM hybrid system to improve the classification accuracy in binary problems. GSA is an optimization heuristic toolused to optimize the value of SVM kernel parameter (in this paper, radial basis function (RBF) is chosen as the kernel function). The experimental results show that this newapproach can achieve high classification accuracy and is comparable to or better than the particle swarm optimization (PSO)-SVM and genetic algorithm (GA)-SVM, which are two hybrid systems for classification.

A Versatile Transposon-Based Activation Tag Vector System for Functional Genomics in Cereals and Other Monocot Plants1[OA

PubMed Central

Qu, Shaohong; Desai, Aparna; Wing, Rod; Sundaresan, Venkatesan

2008-01-01

Transposon insertional mutagenesis is an effective alternative to T-DNA mutagenesis when transformation through tissue culture is inefficient as is the case for many crop species. When used as activation tags, transposons can be exploited to generate novel gain-of-function phenotypes without transformation and are of particular value in the study of polyploid plants where gene knockouts will not have phenotypes. We have developed an in cis-activation-tagging Ac-Ds transposon system in which a T-DNA vector carries a Dissociation (Ds) element containing 4× cauliflower mosaic virus enhancers along with the Activator (Ac) transposase gene. Stable Ds insertions were selected using green fluorescent protein and red fluorescent protein genes driven by promoters that are functional in maize (Zea mays) and rice (Oryza sativa). The system has been tested in rice, where 638 stable Ds insertions were selected from an initial set of 26 primary transformants. By analysis of 311 flanking sequences mapped to the rice genome, we could demonstrate the wide distribution of the elements over the rice chromosomes. Enhanced expression of rice genes adjacent to Ds insertions was detected in the insertion lines using semiquantitative reverse transcription-PCR method. The in cis-two-element vector system requires minimal number of primary transformants and eliminates the need for crossing, while the use of fluorescent markers instead of antibiotic or herbicide resistance increases the applicability to other plants and eliminates problems with escapes. Because Ac-Ds has been shown to transpose widely in the plant kingdom, the activation vector system developed in this study should be of utility more generally to other monocots. PMID:17993541

Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

NASA Astrophysics Data System (ADS)

Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

2014-03-01

A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

Effective Perron-Frobenius eigenvalue for a correlated random map

NASA Astrophysics Data System (ADS)

Pool, Roman R.; Cáceres, Manuel O.

2010-09-01

We investigate the evolution of random positive linear maps with various type of disorder by analytic perturbation and direct simulation. Our theoretical result indicates that the statistics of a random linear map can be successfully described for long time by the mean-value vector state. The growth rate can be characterized by an effective Perron-Frobenius eigenvalue that strongly depends on the type of correlation between the elements of the projection matrix. We apply this approach to an age-structured population dynamics model. We show that the asymptotic mean-value vector state characterizes the population growth rate when the age-structured model has random vital parameters. In this case our approach reveals the nontrivial dependence of the effective growth rate with cross correlations. The problem was reduced to the calculation of the smallest positive root of a secular polynomial, which can be obtained by perturbations in terms of Green’s function diagrammatic technique built with noncommutative cumulants for arbitrary n -point correlations.

Minimal entropy probability paths between genome families.

PubMed

Ahlbrandt, Calvin; Benson, Gary; Casey, William

2004-05-01

We develop a metric for probability distributions with applications to biological sequence analysis. Our distance metric is obtained by minimizing a functional defined on the class of paths over probability measures on N categories. The underlying mathematical theory is connected to a constrained problem in the calculus of variations. The solution presented is a numerical solution, which approximates the true solution in a set of cases called rich paths where none of the components of the path is zero. The functional to be minimized is motivated by entropy considerations, reflecting the idea that nature might efficiently carry out mutations of genome sequences in such a way that the increase in entropy involved in transformation is as small as possible. We characterize sequences by frequency profiles or probability vectors, in the case of DNA where N is 4 and the components of the probability vector are the frequency of occurrence of each of the bases A, C, G and T. Given two probability vectors a and b, we define a distance function based as the infimum of path integrals of the entropy function H( p) over all admissible paths p(t), 0 < or = t< or =1, with p(t) a probability vector such that p(0)=a and p(1)=b. If the probability paths p(t) are parameterized as y(s) in terms of arc length s and the optimal path is smooth with arc length L, then smooth and "rich" optimal probability paths may be numerically estimated by a hybrid method of iterating Newton's method on solutions of a two point boundary value problem, with unknown distance L between the abscissas, for the Euler-Lagrange equations resulting from a multiplier rule for the constrained optimization problem together with linear regression to improve the arc length estimate L. Matlab code for these numerical methods is provided which works only for "rich" optimal probability vectors. These methods motivate a definition of an elementary distance function which is easier and faster to calculate, works on non-rich vectors, does not involve variational theory and does not involve differential equations, but is a better approximation of the minimal entropy path distance than the distance //b-a//(2). We compute minimal entropy distance matrices for examples of DNA myostatin genes and amino-acid sequences across several species. Output tree dendograms for our minimal entropy metric are compared with dendograms based on BLAST and BLAST identity scores.

Principal fiber bundle description of number scaling for scalars and vectors: application to gauge theory

NASA Astrophysics Data System (ADS)

Benioff, Paul

2015-05-01

The purpose of this paper is to put the description of number scaling and its effects on physics and geometry on a firmer foundation, and to make it more understandable. A main point is that two different concepts, number and number value are combined in the usual representations of number structures. This is valid as long as just one structure of each number type is being considered. It is not valid when different structures of each number type are being considered. Elements of base sets of number structures, considered by themselves, have no meaning. They acquire meaning or value as elements of a number structure. Fiber bundles over a space or space time manifold, M, are described. The fiber consists of a collection of many real or complex number structures and vector space structures. The structures are parameterized by a real or complex scaling factor, s. A vector space at a fiber level, s, has, as scalars, real or complex number structures at the same level. Connections are described that relate scalar and vector space structures at both neighbor M locations and at neighbor scaling levels. Scalar and vector structure valued fields are described and covariant derivatives of these fields are obtained. Two complex vector fields, each with one real and one imaginary field, appear, with one complex field associated with positions in M and the other with position dependent scaling factors. A derivation of the covariant derivative for scalar and vector valued fields gives the same vector fields. The derivation shows that the complex vector field associated with scaling fiber levels is the gradient of a complex scalar field. Use of these results in gauge theory shows that the imaginary part of the vector field associated with M positions acts like the electromagnetic field. The physical relevance of the other three fields, if any, is not known.

Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

NASA Astrophysics Data System (ADS)

Patkin, M. L.; Rogachev, G. N.

2018-02-01

A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

Music Signal Processing Using Vector Product Neural Networks

NASA Astrophysics Data System (ADS)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

Equivalence of the O( n) vector ferromagnetic and antiferromagnetic models

NASA Astrophysics Data System (ADS)

Sousa, J. Ricardo de

The effective-field renormalization group (EFRG) approach is used to find the Néel temperature ( TN) of the O( n) vector model with antiferromagnetic (AF) interaction. The EFRG method is illustrated by employing approximations in which clusters with one ( N‧=1) and two ( N=2) spins are used. The critical temperature TN is obtained as a function of component ( n) and coordination ( z) numbers. For all values of n and z we show that TN= Tc, where Tc is the Curie temperature for the ferromagnetic (F) case. As a comparison, the results of the quantum Heisenberg model ( n=3) with F and AF interactions are also presented, and we find that TN> Tc, which is different from the classical result Tc= TN.

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-01-01

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method. PMID:26569241

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-11-10

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Probabilities and statistics for backscatter estimates obtained by a scatterometer

NASA Technical Reports Server (NTRS)

Pierson, Willard J., Jr.

1989-01-01

Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.

Understanding Singular Vectors

ERIC Educational Resources Information Center

James, David; Botteron, Cynthia

2013-01-01

matrix yields a surprisingly simple, heuristical approximation to its singular vectors. There are correspondingly good approximations to the singular values. Such rules of thumb provide an intuitive interpretation of the singular vectors that helps explain why the SVD is so…

Density-dependent host choice by disease vectors: epidemiological implications of the ideal free distribution.

PubMed

Basáñez, María-Gloria; Razali, Karina; Renz, Alfons; Kelly, David

2007-03-01

The proportion of vector blood meals taken on humans (the human blood index, h) appears as a squared term in classical expressions of the basic reproduction ratio (R(0)) for vector-borne infections. Consequently, R(0) varies non-linearly with h. Estimates of h, however, constitute mere snapshots of a parameter that is predicted, from evolutionary theory, to vary with vector and host abundance. We test this prediction using a population dynamics model of river blindness assuming that, before initiation of vector control or chemotherapy, recorded measures of vector density and human infection accurately represent endemic equilibrium. We obtain values of h that satisfy the condition that the effective reproduction ratio (R(e)) must equal 1 at equilibrium. Values of h thus obtained decrease with vector density, decrease with the vector:human ratio and make R(0) respond non-linearly rather than increase linearly with vector density. We conclude that if vectors are less able to obtain human blood meals as their density increases, antivectorial measures may not lead to proportional reductions in R(0) until very low vector levels are achieved. Density dependence in the contact rate of infectious diseases transmitted by insects may be an important non-linear process with implications for their epidemiology and control.

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

PubMed Central

Zhao, Henan; Bryant, Garnett W.; Griffin, Wesley; Terrill, Judith E.; Chen, Jian

2017-01-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. PMID:28113469

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields.

PubMed

Henan Zhao; Bryant, Garnett W; Griffin, Wesley; Terrill, Judith E; Jian Chen

2017-06-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

Transverse Momentum Distributions of Electron in Simulated QED Model

NASA Astrophysics Data System (ADS)

Kaur, Navdeep; Dahiya, Harleen

2018-05-01

In the present work, we have studied the transverse momentum distributions (TMDs) for the electron in simulated QED model. We have used the overlap representation of light-front wave functions where the spin-1/2 relativistic composite system consists of spin-1/2 fermion and spin-1 vector boson. The results have been obtained for T-even TMDs in transverse momentum plane for fixed value of longitudinal momentum fraction x.

Electromagnetic van Kampen waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ignatov, A. M., E-mail: aign@fpl.gpi.ru

2017-01-15

The theory of van Kampen waves in plasma with an arbitrary anisotropic distribution function is developed. The obtained solutions are explicitly expressed in terms of the permittivity tensor. There are three types of perturbations, one of which is characterized by the frequency dependence on the wave vector, while for the other two, the dispersion relation is lacking. Solutions to the conjugate equations allowing one to solve the initial value problem are analyzed.

Validation of a recombinant human bactericidal/permeability-increasing protein (hBPI) expression vector using murine mammary gland tumor cells and the early development of hBPI transgenic goat embryos.

PubMed

Gui, Tao; Liu, Xing; Tao, Jia; Chen, Jianwen; Li, Yunsheng; Zhang, Meiling; Wu, Ronghua; Zhang, Yuanliang; Peng, Kaisong; Liu, Ya; Zhang, Xiaorong; Zhang, Yunhai

2013-12-01

Human bactericidal/permeability-increasing protein (hBPI) is the only antibacterial peptide which acts against both gram-negative bacteria and neutralizes endotoxins in human polymorphonuclear neutrophils; therefore, hBPI is of great value in clinical applications. In the study, we constructed a hBPI expression vector (pBC1-Loxp-Neo-Loxp-hBPI) containing the full-length hBPI coding sequence which could be specifically expressed in the mammary gland. To validate the function of the vector, in vitro cultured C127 (mouse mammary Carcinoma Cells) were transfected with the vector, and the transgenic cell clones were selected to express hBPI by hormone induction. The mRNA and protein expression of hBPI showed that the constructed vector was effective and suitable for future application in producing mammary gland bioreactor. Then, female and male goat fibroblasts were transfected with the vector, and two male and two female transgenic clonal cell lines were obtained. Using the transgenic cell lines as nuclear donors for somatic cell nuclear transfer, the reconstructed goat embryos produced from all four clones could develop to blastocysts in vitro. In conclusion, we constructed and validated an efficient mammary gland-specific hBPI expression vector, pBC1-Loxp-Neo-Loxp-hBPI, and transgenic hBPI goat embryos were successfully produced, laying foundations for future production of recombinant hBPI in goat mammary gland. Copyright © 2013 Elsevier B.V. All rights reserved.

A mapping of an ensemble of mitochondrial sequences for various organisms into 3D space based on the word composition.

PubMed

Aita, Takuyo; Nishigaki, Koichi

2012-11-01

To visualize a bird's-eye view of an ensemble of mitochondrial genome sequences for various species, we recently developed a novel method of mapping a biological sequence ensemble into Three-Dimensional (3D) vector space. First, we represented a biological sequence of a species s by a word-composition vector x(s), where its length [absolute value]x(s)[absolute value] represents the sequence length, and its unit vector x(s)/[absolute value]x(s)[absolute value] represents the relative composition of the K-tuple words through the sequence and the size of the dimension, N=4(K), is the number of all possible words with the length of K. Second, we mapped the vector x(s) to the 3D position vector y(s), based on the two following simple principles: (1) [absolute value]y(s)[absolute value]=[absolute value]x(s)[absolute value] and (2) the angle between y(s) and y(t) maximally correlates with the angle between x(s) and x(t). The mitochondrial genome sequences for 311 species, including 177 Animalia, 85 Fungi and 49 Green plants, were mapped into 3D space by using K=7. The mapping was successful because the angles between vectors before and after the mapping highly correlated with each other (correlation coefficients were 0.92-0.97). Interestingly, the Animalia kingdom is distributed along a single arc belt (just like the Milky Way on a Celestial Globe), and the Fungi and Green plant kingdoms are distributed in a similar arc belt. These two arc belts intersect at their respective middle regions and form a cross structure just like a jet aircraft fuselage and its wings. This new mapping method will allow researchers to intuitively interpret the visual information presented in the maps in a highly effective manner. Copyright © 2012 Elsevier Inc. All rights reserved.

Analysis of ground-motion simulation big data

NASA Astrophysics Data System (ADS)

Maeda, T.; Fujiwara, H.

2016-12-01

We developed a parallel distributed processing system which applies a big data analysis to the large-scale ground motion simulation data. The system uses ground-motion index values and earthquake scenario parameters as input. We used peak ground velocity value and velocity response spectra as the ground-motion index. The ground-motion index values are calculated from our simulation data. We used simulated long-period ground motion waveforms at about 80,000 meshes calculated by a three dimensional finite difference method based on 369 earthquake scenarios of a great earthquake in the Nankai Trough. These scenarios were constructed by considering the uncertainty of source model parameters such as source area, rupture starting point, asperity location, rupture velocity, fmax and slip function. We used these parameters as the earthquake scenario parameter. The system firstly carries out the clustering of the earthquake scenario in each mesh by the k-means method. The number of clusters is determined in advance using a hierarchical clustering by the Ward's method. The scenario clustering results are converted to the 1-D feature vector. The dimension of the feature vector is the number of scenario combination. If two scenarios belong to the same cluster the component of the feature vector is 1, and otherwise the component is 0. The feature vector shows a `response' of mesh to the assumed earthquake scenario group. Next, the system performs the clustering of the mesh by k-means method using the feature vector of each mesh previously obtained. Here the number of clusters is arbitrarily given. The clustering of scenarios and meshes are performed by parallel distributed processing with Hadoop and Spark, respectively. In this study, we divided the meshes into 20 clusters. The meshes in each cluster are geometrically concentrated. Thus this system can extract regions, in which the meshes have similar `response', as clusters. For each cluster, it is possible to determine particular scenario parameters which characterize the cluster. In other word, by utilizing this system, we can obtain critical scenario parameters of the ground-motion simulation for each evaluation point objectively. This research was supported by CREST, JST.

A New Approach to Attitude Stability and Control for Low Airspeed Vehicles

NASA Technical Reports Server (NTRS)

Lim, K. B.; Shin, Y-Y.; Moerder, D. D.; Cooper, E. G.

2004-01-01

This paper describes an approach for controlling the attitude of statically unstable thrust-levitated vehicles in hover or slow translation. The large thrust vector that characterizes such vehicles can be modulated to provide control forces and moments to the airframe, but such modulation is accompanied by significant unsteady flow effects. These effects are difficult to model, and can compromise the practical value of thrust vectoring in closed-loop attitude stability, even if the thrust vectoring machinery has sufficient bandwidth for stabilization. The stabilization approach described in this paper is based on using internal angular momentum transfer devices for stability, augmented by thrust vectoring for trim and other "outer loop" control functions. The three main components of this approach are: (1) a z-body axis angular momentum bias enhances static attitude stability, reducing the amount of control activity needed for stabilization, (2) optionally, gimbaled reaction wheels provide high-bandwidth control torques for additional stabilization, or agility, and (3) the resulting strongly coupled system dynamics are controlled by a multivariable controller. A flight test vehicle is described, and nonlinear simulation results are provided that demonstrate the efficiency of the approach.

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

NASA Astrophysics Data System (ADS)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

Ex Vivo Adenoviral Vector Gene Delivery Results in Decreased Vector-associated Inflammation Pre- and Post–lung Transplantation in the Pig

PubMed Central

Yeung, Jonathan C; Wagnetz, Dirk; Cypel, Marcelo; Rubacha, Matthew; Koike, Terumoto; Chun, Yi-Min; Hu, Jim; Waddell, Thomas K; Hwang, David M; Liu, Mingyao; Keshavjee, Shaf

2012-01-01

Acellular normothermic ex vivo lung perfusion (EVLP) is a novel method of donor lung preservation for transplantation. As cellular metabolism is preserved during perfusion, it represents a potential platform for effective gene transduction in donor lungs. We hypothesized that vector-associated inflammation would be reduced during ex vivo delivery due to isolation from the host immune system response. We compared ex vivo with in vivo intratracheal delivery of an E1-, E3-deleted adenoviral vector encoding either green fluorescent protein (GFP) or interleukin-10 (IL-10) to porcine lungs. Twelve hours after delivery, the lung was transplanted and the post-transplant function assessed. We identified significant transgene expression by 12 hours in both in vivo and ex vivo delivered groups. Lung function remained excellent in all ex vivo groups after viral vector delivery; however, as expected, lung function decreased in the in vivo delivered adenovirus vector encoding GFP (AdGFP) group with corresponding increases in IL-1β levels. Transplanted lung function was excellent in the ex vivo transduced lungs and inferior lung function was seen in the in vivo group after transplantation. In summary, ex vivo delivery of adenoviral gene therapy to the donor lung is superior to in vivo delivery in that it leads to less vector-associated inflammation and provides superior post-transplant lung function. PMID:22453765

Structural features that predict real-value fluctuations of globular proteins

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-01-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real-value of residue fluctuations using the support vector regression. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson’s correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models is that the former predicts the real-value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. PMID:22328193

Automated image segmentation using support vector machines

NASA Astrophysics Data System (ADS)

Powell, Stephanie; Magnotta, Vincent A.; Andreasen, Nancy C.

2007-03-01

Neurodegenerative and neurodevelopmental diseases demonstrate problems associated with brain maturation and aging. Automated methods to delineate brain structures of interest are required to analyze large amounts of imaging data like that being collected in several on going multi-center studies. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures including the thalamus (0.88), caudate (0.85) and the putamen (0.81). In this work, apriori probability information was generated using Thirion's demons registration algorithm. The input vector consisted of apriori probability, spherical coordinates, and an iris of surrounding signal intensity values. We have applied the support vector machine (SVM) machine learning algorithm to automatically segment subcortical and cerebellar regions using the same input vector information. SVM architecture was derived from the ANN framework. Training was completed using a radial-basis function kernel with gamma equal to 5.5. Training was performed using 15,000 vectors collected from 15 training images in approximately 10 minutes. The resulting support vectors were applied to delineate 10 images not part of the training set. Relative overlap calculated for the subcortical structures was 0.87 for the thalamus, 0.84 for the caudate, 0.84 for the putamen, and 0.72 for the hippocampus. Relative overlap for the cerebellar lobes ranged from 0.76 to 0.86. The reliability of the SVM based algorithm was similar to the inter-rater reliability between manual raters and can be achieved without rater intervention.

Pinning, rotation, and metastability of BiFeO 3 cycloidal domains in a magnetic field

DOE PAGES

Fishman, Randy S.

2018-01-03

Earlier models for the room-temperature multiferroic BiFeO 3 implicitly assumed that a very strong anisotropy restricts the domain wave vectors q to the threefold-symmetric axis normal to the static polarization P. However, recent measurements demonstrate that the domain wave vectors q rotate within the hexagonal plane normal to P away from the magnetic field orientation m. In this paper, we show that the previously neglected threefold anisotropy K 3 restricts the wave vectors to lie along the threefold axis in zero field. Taking m to lie along a threefold axis, the domain with q parallel to m remains metastable belowmore » B c1≈7 T. Due to the pinning of domains by nonmagnetic impurities, the wave vectors of the other two domains start to rotate away from m above 5.6 T, when the component of the torque τ=M×B along P exceeds a threshold value τ pin. Since τ=0 when m⊥q, the wave vectors of those domains never become completely perpendicular to the magnetic field. Our results explain recent measurements of the critical field as a function of field orientation, small-angle neutron scattering measurements of the wave vectors, as well as spectroscopic measurements with m along a threefold axis. Finally, the model developed in this paper also explains how the three multiferroic domains of BiFeO 3 for a fixed P can be manipulated by a magnetic field.« less

Pinning, rotation, and metastability of BiFeO3 cycloidal domains in a magnetic field

NASA Astrophysics Data System (ADS)

Fishman, Randy S.

2018-01-01

Earlier models for the room-temperature multiferroic BiFeO3 implicitly assumed that a very strong anisotropy restricts the domain wave vectors q to the threefold-symmetric axis normal to the static polarization P . However, recent measurements demonstrate that the domain wave vectors q rotate within the hexagonal plane normal to P away from the magnetic field orientation m . We show that the previously neglected threefold anisotropy K3 restricts the wave vectors to lie along the threefold axis in zero field. Taking m to lie along a threefold axis, the domain with q parallel to m remains metastable below Bc 1≈7 T. Due to the pinning of domains by nonmagnetic impurities, the wave vectors of the other two domains start to rotate away from m above 5.6 T, when the component of the torque τ =M ×B along P exceeds a threshold value τpin. Since τ =0 when m ⊥q , the wave vectors of those domains never become completely perpendicular to the magnetic field. Our results explain recent measurements of the critical field as a function of field orientation, small-angle neutron scattering measurements of the wave vectors, as well as spectroscopic measurements with m along a threefold axis. The model developed in this paper also explains how the three multiferroic domains of BiFeO3 for a fixed P can be manipulated by a magnetic field.

Pinning, rotation, and metastability of BiFeO 3 cycloidal domains in a magnetic field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fishman, Randy S.

Earlier models for the room-temperature multiferroic BiFeO 3 implicitly assumed that a very strong anisotropy restricts the domain wave vectors q to the threefold-symmetric axis normal to the static polarization P. However, recent measurements demonstrate that the domain wave vectors q rotate within the hexagonal plane normal to P away from the magnetic field orientation m. In this paper, we show that the previously neglected threefold anisotropy K 3 restricts the wave vectors to lie along the threefold axis in zero field. Taking m to lie along a threefold axis, the domain with q parallel to m remains metastable belowmore » B c1≈7 T. Due to the pinning of domains by nonmagnetic impurities, the wave vectors of the other two domains start to rotate away from m above 5.6 T, when the component of the torque τ=M×B along P exceeds a threshold value τ pin. Since τ=0 when m⊥q, the wave vectors of those domains never become completely perpendicular to the magnetic field. Our results explain recent measurements of the critical field as a function of field orientation, small-angle neutron scattering measurements of the wave vectors, as well as spectroscopic measurements with m along a threefold axis. Finally, the model developed in this paper also explains how the three multiferroic domains of BiFeO 3 for a fixed P can be manipulated by a magnetic field.« less

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

PubMed

Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

2015-09-16

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

Functional polycarbonates and their self-assemblies as promising non-viral vectors.

PubMed

Seow, Wei Yang; Yang, Yi Yan

2009-10-01

Polycarbonates are promising biomaterials due to their biocompatibility, degradability and low toxicity. In this study, a series of COOH-functionalized polycarbonates was synthesized via an organocatalytic ring opening polymerization pathway under mild conditions. The polymers displayed a range of molecular weights (M(w): 3.1, 5.5 and 9.7 kDa) and were very narrowly distributed (polydispersity index: 1.07, 1.07 and 1.15 respectively). Aliphatic amines with different chain lengths (triethylenetetramine, tetraethylenepentamine or pentaethylenehexamine) were then conjugated onto the polycarbonate backbone using DIC/NHS chemistry. These amine-functionalized polycarbonates could form nanoparticles upon simple dissolution in water and had CMC values ranging from 22 to 45 mg/L. It was found that a longer amine chain resulted in greater buffering capacity, more positive zeta potential and smaller hydrodynamic size of the polymeric nanoparticles. Results from gel retardation assays indicated that the polymers were able to condense DNA. In-vitro studies further demonstrated that selected amine-functionalized polycarbonates could mediate efficient luciferase expression in HEK293, HepG2 and 4T1 cell lines at levels that were comparable, or even superior, to the polyethylenimine (PEI) standard. Importantly, minimal cytotoxicty was induced in the cells. These functional polycarbonates therefore have the potential to be a useful non-viral vector for gene therapy.

Method and system for efficiently searching an encoded vector index

DOEpatents

Bui, Thuan Quang; Egan, Randy Lynn; Kathmann, Kevin James

2001-09-04

Method and system aspects for efficiently searching an encoded vector index are provided. The aspects include the translation of a search query into a candidate bitmap, and the mapping of data from the candidate bitmap into a search result bitmap according to entry values in the encoded vector index. Further, the translation includes the setting of a bit in the candidate bitmap for each entry in a symbol table that corresponds to candidate of the search query. Also included in the mapping is the identification of a bit value in the candidate bitmap pointed to by an entry in an encoded vector.

On orthogonal expansions of the space of vector functions which are square-summable over a given domain and the vector analysis operators

NASA Technical Reports Server (NTRS)

Bykhovskiy, E. B.; Smirnov, N. V.

1983-01-01

The Hilbert space L2(omega) of vector functions is studied. A breakdown of L2(omega) into orthogonal subspaces is discussed and the properties of the operators for projection onto these subspaces are investigated from the standpoint of preserving the differential properties of the vectors being projected. Finally, the properties of the operators are examined.

Vector species richness increases haemorrhagic disease prevalence through functional diversity modulating the duration of seasonal transmission.

PubMed

Park, Andrew W; Cleveland, Christopher A; Dallas, Tad A; Corn, Joseph L

2016-06-01

Although many parasites are transmitted between hosts by a suite of arthropod vectors, the impact of vector biodiversity on parasite transmission is poorly understood. Positive relationships between host infection prevalence and vector species richness (SR) may operate through multiple mechanisms, including (i) increased vector abundance, (ii) a sampling effect in which species of high vectorial capacity are more likely to occur in species-rich communities, and (iii) functional diversity whereby communities comprised species with distinct phenologies may extend the duration of seasonal transmission. Teasing such mechanisms apart is impeded by a lack of appropriate data, yet could highlight a neglected role for functional diversity in parasite transmission. We used statistical modelling of extensive host, vector and microparasite data to test the hypothesis that functional diversity leading to longer seasonal transmission explained variable levels of disease in a wildlife population. We additionally developed a simple transmission model to guide our expectation of how an increased transmission season translates to infection prevalence. Our study demonstrates that vector SR is associated with increased levels of disease reporting, but not via increases in vector abundance or via a sampling effect. Rather, the relationship operates by extending the length of seasonal transmission, in line with theoretical predictions.

A simple method of equine limb force vector analysis and its potential applications.

PubMed

Hobbs, Sarah Jane; Robinson, Mark A; Clayton, Hilary M

2018-01-01

Ground reaction forces (GRF) measured during equine gait analysis are typically evaluated by analyzing discrete values obtained from continuous force-time data for the vertical, longitudinal and transverse GRF components. This paper describes a simple, temporo-spatial method of displaying and analyzing sagittal plane GRF vectors. In addition, the application of statistical parametric mapping (SPM) is introduced to analyse differences between contra-lateral fore and hindlimb force-time curves throughout the stance phase. The overall aim of the study was to demonstrate alternative methods of evaluating functional (a)symmetry within horses. GRF and kinematic data were collected from 10 horses trotting over a series of four force plates (120 Hz). The kinematic data were used to determine clean hoof contacts. The stance phase of each hoof was determined using a 50 N threshold. Vertical and longitudinal GRF for each stance phase were plotted both as force-time curves and as force vector diagrams in which vectors originating at the centre of pressure on the force plate were drawn at intervals of 8.3 ms for the duration of stance. Visual evaluation was facilitated by overlay of the vector diagrams for different limbs. Summary vectors representing the magnitude (VecMag) and direction (VecAng) of the mean force over the entire stance phase were superimposed on the force vector diagram. Typical measurements extracted from the force-time curves (peak forces, impulses) were compared with VecMag and VecAng using partial correlation (controlling for speed). Paired samples t -tests (left v. right diagonal pair comparison and high v. low vertical force diagonal pair comparison) were performed on discrete and vector variables using traditional methods and Hotelling's T 2 tests on normalized stance phase data using SPM. Evidence from traditional statistical tests suggested that VecMag is more influenced by the vertical force and impulse, whereas VecAng is more influenced by the longitudinal force and impulse. When used to evaluate mean data from the group of ten sound horses, SPM did not identify differences between the left and right contralateral limb pairs or between limb pairs classified according to directional asymmetry. When evaluating a single horse, three periods were identified during which differences in the forces between the left and right forelimbs exceeded the critical threshold ( p  < .01). Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave harmonious results and both methods identified the same inter-limb asymmetries. As alpha was more tightly controlled using SPM, significance was only found in the individual horse although T 2 plots followed the same trends as discrete analysis for the group. The techniques of force vector analysis and SPM hold promise for investigations of sidedness and asymmetry in horses.

Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

2017-12-01

Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

A complementation assay for in vivo protein structure/function analysis in Physcomitrella patens (Funariaceae)

DOE PAGES

Scavuzzo-Duggan, Tess R.; Chaves, Arielle M.; Roberts, Alison W.

2015-07-14

Here, a method for rapid in vivo functional analysis of engineered proteins was developed using Physcomitrella patens. A complementation assay was designed for testing structure/function relationships in cellulose synthase (CESA) proteins. The components of the assay include (1) construction of test vectors that drive expression of epitope-tagged PpCESA5 carrying engineered mutations, (2) transformation of a ppcesa5 knockout line that fails to produce gametophores with test and control vectors, (3) scoring the stable transformants for gametophore production, (4) statistical analysis comparing complementation rates for test vectors to positive and negative control vectors, and (5) analysis of transgenic protein expression by Westernmore » blotting. The assay distinguished mutations that generate fully functional, nonfunctional, and partially functional proteins. In conclusion, compared with existing methods for in vivo testing of protein function, this complementation assay provides a rapid method for investigating protein structure/function relationships in plants.« less

Mathematical Methods for Optical Physics and Engineering

NASA Astrophysics Data System (ADS)

Gbur, Gregory J.

2011-01-01

1. Vector algebra; 2. Vector calculus; 3. Vector calculus in curvilinear coordinate systems; 4. Matrices and linear algebra; 5. Advanced matrix techniques and tensors; 6. Distributions; 7. Infinite series; 8. Fourier series; 9. Complex analysis; 10. Advanced complex analysis; 11. Fourier transforms; 12. Other integral transforms; 13. Discrete transforms; 14. Ordinary differential equations; 15. Partial differential equations; 16. Bessel functions; 17. Legendre functions and spherical harmonics; 18. Orthogonal functions; 19. Green's functions; 20. The calculus of variations; 21. Asymptotic techniques; Appendices; References; Index.

Electrokinetic Control of Viscous Fingering

NASA Astrophysics Data System (ADS)

Mirzadeh, Mohammad; Bazant, Martin Z.

2017-10-01

We present a theory of the interfacial stability of two immiscible electrolytes under the coupled action of pressure gradients and electric fields in a Hele-Shaw cell or porous medium. Mathematically, our theory describes a phenomenon of "vector Laplacian growth," in which the interface moves in response to the gradient of a vector-valued potential function through a generalized mobility tensor. Physically, we extend the classical Saffman-Taylor problem to electrolytes by incorporating electrokinetic (EK) phenomena. A surprising prediction is that viscous fingering can be controlled by varying the injection ratio of electric current to flow rate. Beyond a critical injection ratio, stability depends only upon the relative direction of flow and current, regardless of the viscosity ratio. Possible applications include porous materials processing, electrically enhanced oil recovery, and EK remediation of contaminated soils.

IDA (Institute for Defense Analyses) GAMMA-Ray Laser Annual Summary Report (1986). Investigation of the Feasibility of Developing a Laser Using Nuclear Transitions

DTIC Science & Technology

1988-12-01

a computer simulation for a small value of r .................................... 25 Figure 5. A typical pulse shape for r = 8192...26 Figure 6. Pulse duration as function of r from the statistical simulations , assuming a spontaneous lifetime of 1 s...scaling factor from the statistical simulations ................. 29 Figure 10. Basic pulse characteristics and associated Bloch vector angles for the

Reducible boundary conditions in coupled channels

NASA Astrophysics Data System (ADS)

Pankrashkin, Konstantin

2005-10-01

We study Hamiltonians with point interactions in spaces of vector-valued functions. Using some information from the theory of quantum graphs, we describe a class of the operators which can be reduced to the direct sum of several one-dimensional problems. It shown that such a reduction is closely connected with the invariance under channel permutations. Examples are provided by some 'model' interactions, in particular, the so-called δ, δ' and the Kirchhoff couplings.

Abnormal neural activity as a potential biomarker for drug-naive first-episode adolescent-onset schizophrenia with coherence regional homogeneity and support vector machine analyses.

PubMed

Liu, Yi; Zhang, Yan; Lv, Luxian; Wu, Renrong; Zhao, Jingping; Guo, Wenbin

2018-02-01

Patients with adolescent-onset schizophrenia (AOS) hold the same but severe form of symptoms with adult-onset schizophrenia, and with worse outcome and poor treatment response to antipsychotics. Several dominant brain regions of schizophrenia patients show significantly abnormal structural and functional connectivity during resting-state scans. However, coherence regional homogeneity (Cohe-ReHo) in drug-naive first-episode patients with AOS remains unclear. A total of 48 drug-naive first-episode AOS outpatients and 31 healthy controls underwent resting-state functional magnetic resonance scans. Cohe-ReHo and support vector machine analyses were used to analyze the data. Compared with the healthy controls, the AOS group showed significantly decreased Cohe-ReHo values distributed over brain regions, including the left postcentral gyrus, left superior temporal gyrus, left paracentral lobule, right precentral gyrus, right inferior parietal lobule (IPL), right middle frontal gyrus, and bilateral precuneus. No region with increased Cohe-ReHo values was observed in the AOS group compared with healthy controls. In addition, the right IPL was correlated with fluency (r=-0.324, p=0.030). However, the correlation was not significant after the Bonferroni correction at p<0.0083 (0.05/6). A combination of the Cohe-ReHo values in the bilateral precuneus and right IPL discriminated the patients from controls with the sensitivity, specificity, and accuracy of 91.67%, 87.10%, and 89.87%, respectively. Our findings suggested that the AOS patients exhibited diminished Cohe-ReHo values in some regions within the DMN network and sensorimotor network. The abnormalities in particular brain regions (bilateral precuneus and right IPL) may serve as potential biomarkers for AOS. Copyright © 2017 Elsevier B.V. All rights reserved.

Deconvolution Methods for Multi-Detectors

DTIC Science & Technology

1989-08-30

in [7). We will say sometimes that the family of distributions jI,..,’m is strongly coprime. It might be useful to explain why is (4) called a...form g In the variable ?. given by n 3(11) g q(z~t,p):= 1 kz()(k k=1 Given a family of m entire holomorphic functions f n’*If m its zero set Z is defined...write g1 g jdk" Recall the k=l coefficients gi are holomorphic in both z and t. Let F be the vector valued holomorphic function F: - (f1 ’..’,f ) we

Gaussian statistics for palaeomagnetic vectors

USGS Publications Warehouse

Love, J.J.; Constable, C.G.

2003-01-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to formulate the inverse problem, and how to estimate the mean and variance of the magnetic vector field, even when the data consist of mixed combinations of directions and intensities. We examine palaeomagnetic secular-variation data from Hawaii and Re??union, and although these two sites are on almost opposite latitudes, we find significant differences in the mean vector and differences in the local vectorial variances, with the Hawaiian data being particularly anisotropic. These observations are inconsistent with a description of the mean field as being a simple geocentric axial dipole and with secular variation being statistically symmetrical with respect to reflection through the equatorial plane. Finally, our analysis of palaeomagnetic acquisition data from the 1960 Kilauea flow in Hawaii and the Holocene Xitle flow in Mexico, is consistent with the widely held suspicion that directional data are more accurate than intensity data.

Gaussian statistics for palaeomagnetic vectors

NASA Astrophysics Data System (ADS)

Love, J. J.; Constable, C. G.

2003-03-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimodal) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to formulate the inverse problem, and how to estimate the mean and variance of the magnetic vector field, even when the data consist of mixed combinations of directions and intensities. We examine palaeomagnetic secular-variation data from Hawaii and Réunion, and although these two sites are on almost opposite latitudes, we find significant differences in the mean vector and differences in the local vectorial variances, with the Hawaiian data being particularly anisotropic. These observations are inconsistent with a description of the mean field as being a simple geocentric axial dipole and with secular variation being statistically symmetrical with respect to reflection through the equatorial plane. Finally, our analysis of palaeomagnetic acquisition data from the 1960 Kilauea flow in Hawaii and the Holocene Xitle flow in Mexico, is consistent with the widely held suspicion that directional data are more accurate than intensity data.

Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state.

PubMed

Perendeci, Altinay; Arslan, Sever; Tanyolaç, Abdurrahman; Celebi, Serdar S

2009-10-01

A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a sugar factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5-10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.

Modification and identification of a vector for making a large phage antibody library.

PubMed

Zhang, Guo-min; Chen, Yü-ping; Guan, Yuan-zhi; Wang, Yan; An, Yun-qing

2007-11-20

The large phage antibody library is used to obtain high-affinity human antibody, and the Loxp/cre site-specific recombination system is a potential method for constructing a large phage antibody library. In the present study, a phage antibody library vector pDF was reconstructed to construct diabody more quickly and conveniently without injury to homologous recombination and the expression function of the vector and thus to integrate construction of the large phage antibody library with the preparation of diabodies. scFv was obtained by overlap polymerase chain reaction (PCR) amplification with the newly designed VL and VH extension primers. loxp511 was flanked by VL and VH and the endonuclease ACC III encoding sequences were introduced on both sides of loxp511. scFv was cloned into the vector pDF to obtain the vector pDscFv. The vector expression function was identified and the feasibility of diabody preparation was evaluated. A large phage antibody library was constructed in pDscFv. Several antigens were used to screen the antibody library and the quality of the antibody library was evaluated. The phage antibody library expression vector pDscFv was successfully constructed and confirmed to express functional scFv. The large phage antibody library constructed using this vector was of high diversity. Screening of the library on 6 antigens confirmed the generation of specific antibodies to these antigens. Two antibodies were subjected to enzymatic digestion and were prepared into diabody with functional expression. The reconstructed vector pDscFv retains its recombination capability and expression function and can be used to construct large phage antibody libraries. It can be used as a convenient and quick method for preparing diabodies after simple enzymatic digestion, which facilitates clinical trials and application of antibody therapy.

Functional characterization of adenoviral/retroviral chimeric vectors and their use for efficient screening of retroviral producer cell lines.

PubMed

Duisit, G; Salvetti, A; Moullier, P; Cosset, F L

1999-01-20

We have generated three different E1-deleted replication-defective adenoviral vectors expressing either Moloney murine leukemia virus (Mo-MuLV) Gag-Pol core particle proteins, gibbon ape leukemia virus (GALV) envelope glycoproteins, or an MuLV-derived retroviral vector genome encoding mCD2 antigen, a murine cell surface marker easily detectable by flow cytometry. Each of the three vectors was first characterized individually by infection of cells providing the complementary retroviral function(s) and able to induce the production of retroviral vectors with an efficiency similar to or higher than that of FLY stable retroviral packaging cells [Cosset, F.-L., Takeuchi, Y., Battini, J.-L., Weiss, R.A., and Collins, M.K.L., (1995). J. Virol. 69, 7430-7436]. In small-scale pilot experiments, TE671 cells simultaneously coinfected with the three adenoviral vectors efficiently released helper-free retroviral vectors in their supernatant, with titers greater than 10(6) infectious particles per milliliter by end-point titrations. Our results also indicated that in contrast to retroviral vector-packageable RNAs, the adenovirus-mediated overexpression of both Gag-Pol and Env packaging functions had limited impact on retroviral titers. The primary mechanism suspected is the premature intracellular cleavage of the Pr65gag precursor that we found in gag-pol-expressing cells, which in turn may impair the normal incorporation of high loads of functional Env. Last, the characterization of the adenoviral/retroviral chimeric vectors allowed the screening of various primate cells for retroviral production and we found that three hepatocyte-derived cell lines were highly efficient in the assembly and release of infectious retroviral particles.

PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin; Zhong, ShiSheng

2018-02-01

In this research, we propose a preference-guided optimisation algorithm for multi-criteria decision-making (MCDM) problems with interval-valued fuzzy preferences. The interval-valued fuzzy preferences are decomposed into a series of precise and evenly distributed preference-vectors (reference directions) regarding the objectives to be optimised on the basis of uniform design strategy firstly. Then the preference information is further incorporated into the preference-vectors based on the boundary intersection approach, meanwhile, the MCDM problem with interval-valued fuzzy preferences is reformulated into a series of single-objective optimisation sub-problems (each sub-problem corresponds to a decomposed preference-vector). Finally, a preference-guided optimisation algorithm based on MOEA/D (multi-objective evolutionary algorithm based on decomposition) is proposed to solve the sub-problems in a single run. The proposed algorithm incorporates the preference-vectors within the optimisation process for guiding the search procedure towards a more promising subset of the efficient solutions matching the interval-valued fuzzy preferences. In particular, lots of test instances and an engineering application are employed to validate the performance of the proposed algorithm, and the results demonstrate the effectiveness and feasibility of the algorithm.

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

TMV-Gate vectors: Gateway compatible tobacco mosaic virus based expression vectors for functional analysis of proteins

PubMed Central

Kagale, Sateesh; Uzuhashi, Shihomi; Wigness, Merek; Bender, Tricia; Yang, Wen; Borhan, M. Hossein; Rozwadowski, Kevin

2012-01-01

Plant viral expression vectors are advantageous for high-throughput functional characterization studies of genes due to their capability for rapid, high-level transient expression of proteins. We have constructed a series of tobacco mosaic virus (TMV) based vectors that are compatible with Gateway technology to enable rapid assembly of expression constructs and exploitation of ORFeome collections. In addition to the potential of producing recombinant protein at grams per kilogram FW of leaf tissue, these vectors facilitate either N- or C-terminal fusions to a broad series of epitope tag(s) and fluorescent proteins. We demonstrate the utility of these vectors in affinity purification, immunodetection and subcellular localisation studies. We also apply the vectors to characterize protein-protein interactions and demonstrate their utility in screening plant pathogen effectors. Given its broad utility in defining protein properties, this vector series will serve as a useful resource to expedite gene characterization efforts. PMID:23166857

[Teaching skills of functional assessment to medical students: why not playing games?].

PubMed

Huber, Philippe; Saber, Abdelmalek; Schnellmann, Yves; Gold, Gabriel

2012-11-07

Today, physicians take care of an aging population suffering from multiple chronic diseases and disabilities. Therefore, a good knowledge of functional assessment is required, and this topic should be addressed in the undergraduate medical curriculum. This article reports our experience with a seminar on functional assessment using an "aging game" as a pedagogic vector. This seminar is organized by geriatricians, occupational therapists and physical therapists. Medical students are exposed to situations where they experiment disabilities and try to elaborate compensatory strategies. Then, they reflect on a complex discharge project by analyzing a written clinical case. Finally, they are introduced to the use of validated functional assessment instruments. Evaluation indicated that this pedagogic approach is highly valued by students and fosters the acquisition of knowledge in functional assessment.

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model Descriptor Consistent Between Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-05-10

A major problem with cavitation in pumps and other hydraulic devices is that there is no effective method for detecting or predicting its inception. The traditional approach is to declare the pump in cavitation when the total head pressure drops by some arbitrary value (typically 3o/0) in response to a reduction in pump inlet pressure. However, the pump is already cavitating at this point. A method is needed in which cavitation events are captured as they occur and characterized by their process dynamics. The object of this research was to identify specific features of cavitation that could be used asmore » a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor was based on the physics of the phenomena, capturing the salient features of the process dynamics. An important element of this concept is the development and formulation of the extended process feature vector @) or model vector. Thk model-based descriptor encodes the specific information that describes the phenomena and its dynamics and is formulated as a data structure consisting of several elements. The first is a descriptive model abstracting the phenomena. The second is the parameter list associated with the functional model. The third is a figure of merit, a single number between [0,1] representing a confidence factor that the functional model and parameter list actually describes the observed data. Using this as a basis and applying it to the cavitation problem, any given location in a flow loop will have this data structure, differing in value but not content. The extended process feature vector is formulated as follows: E`> [ , {parameter Iist}, confidence factor]. (1) For this study, the model that characterized cavitation was a chirped-exponentially decaying sinusoid. Using the parameters defined by this model, the parameter list included frequency, decay, and chirp rate. Based on this, the process feature vector has the form: @=> [, {01 = a, ~= b, ~ = c}, cf = 0.80]. (2) In this experiment a reversible catastrophe was examined. The reason for this is that the same catastrophe could be repeated to ensure the statistical significance of the data.« less

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

A Weyl-Dirac cosmological model with DM and DE

NASA Astrophysics Data System (ADS)

Israelit, Mark

2011-03-01

In the Weyl-Dirac (W-D) framework a spatially closed cosmological model is considered. It is assumed that the space-time of the universe has a chaotic Weylian microstructure but is described on a large scale by Riemannian geometry. Locally fields of the Weyl connection vector act as creators of massive bosons having spin 1. It is suggested that these bosons, called weylons, provide most of the dark matter in the universe. At the beginning the universe is a spherically symmetric geometric entity without matter. Primary matter is created by Dirac’s gauge function very close to the beginning. In the early epoch, when the temperature of the universe achieves its maximum, chaotically oriented Weyl vector fields being localized in micro-cells create weylons. In the dust dominated period Dirac’s gauge function is giving rise to dark energy, the latter causing the cosmic acceleration at present. This oscillatory universe has an initial radius identical to the Plank length = 1.616 exp (-33) cm, at present the cosmic scale factor is 3.21 exp (28) cm, while its maximum value is 8.54 exp (28) cm. All forms of matter are created by geometrically based functions of the W-D theory.

Mayer control problem with probabilistic uncertainty on initial positions

NASA Astrophysics Data System (ADS)

Marigonda, Antonio; Quincampoix, Marc

2018-03-01

In this paper we introduce and study an optimal control problem in the Mayer's form in the space of probability measures on Rn endowed with the Wasserstein distance. Our aim is to study optimality conditions when the knowledge of the initial state and velocity is subject to some uncertainty, which are modeled by a probability measure on Rd and by a vector-valued measure on Rd, respectively. We provide a characterization of the value function of such a problem as unique solution of an Hamilton-Jacobi-Bellman equation in the space of measures in a suitable viscosity sense. Some applications to a pursuit-evasion game with uncertainty in the state space is also discussed, proving the existence of a value for the game.

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

Detection of Splice Sites Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Varadwaj, Pritish; Purohit, Neetesh; Arora, Bhumika

Automatic identification and annotation of exon and intron region of gene, from DNA sequences has been an important research area in field of computational biology. Several approaches viz. Hidden Markov Model (HMM), Artificial Intelligence (AI) based machine learning and Digital Signal Processing (DSP) techniques have extensively and independently been used by various researchers to cater this challenging task. In this work, we propose a Support Vector Machine based kernel learning approach for detection of splice sites (the exon-intron boundary) in a gene. Electron-Ion Interaction Potential (EIIP) values of nucleotides have been used for mapping character sequences to corresponding numeric sequences. Radial Basis Function (RBF) SVM kernel is trained using EIIP numeric sequences. Furthermore this was tested on test gene dataset for detection of splice site by window (of 12 residues) shifting. Optimum values of window size, various important parameters of SVM kernel have been optimized for a better accuracy. Receiver Operating Characteristic (ROC) curves have been utilized for displaying the sensitivity rate of the classifier and results showed 94.82% accuracy for splice site detection on test dataset.

[Evaluation of left ventricular diastolic function in canine acute myocardial ischemia using velocity vector imaging and quantitative tissue velocity imaging].

PubMed

Zhang, Chuan; Zha, Dao-Gang; DU, Rong-Sheng; Hu, Feng; Li, Sheng-Hui; Wu, Xiao-Yuan; Liu, Yi-Li

2009-07-01

To assess the value of velocity vector imaging (VVI) and quantitative tissue velocity imaging (QTVI) in assessing left ventricular diastolic function of the dogs with acute myocardial ischemia. Six healthy mongrel dogs were subjected to ligation of the left circumflex artery or left anterior descending artery to induce coronary artery stenosis of varying degrees. The mean peak diastolic velocity (Em) of the ventricular walls around the mitral annulus was recorded with VVI or QTVI in the coronary blood flow. The left ventricular end diastolic pressure (LVEDP) was measured with pigtail catheter in the left ventricle. As the coronary blood flow decreased, LVEDP was gradually increased, and Em measured by VVI or QTVI were also gradually decreased. A good linear correlation was shown between Em measured by VVI or QTVI and LVEDP (r=-0.834, P<0.001, and r=-0.68, P<0.001, respectively). A significant difference was observed in the correlation coefficient between VVI and QTVI (Z=2.625, P=0.0087). VVI and QTVI both provide good noninvasive means for measuring left ventricular diastolic function. VVI, a new echocardiographic modality without angular dependence, is better than QTVI in evaluating left ventricular diastolic function.

Artificial Potential Field Controllers for Robust Communications in a Network of Swarm Robots

DTIC Science & Technology

2005-05-18

vectors are less than 90◦ apart. Algorithm 1 The Algorithm for generating a feasible set of vectors P ← set of high priority vectors Csum ← [( LOS1 +R1...the 46 C program was finished reading and writing the values to the serial line it would delete the timing file. Only after the timing file had been... deleted would the base station write new values for the wheel velocities. The timing file kept both the Linux PC and the base station synchronized so

Polarization ellipse and Stokes parameters in geometric algebra.

PubMed

Santos, Adler G; Sugon, Quirino M; McNamara, Daniel J

2012-01-01

In this paper, we use geometric algebra to describe the polarization ellipse and Stokes parameters. We show that a solution to Maxwell's equation is a product of a complex basis vector in Jackson and a linear combination of plane wave functions. We convert both the amplitudes and the wave function arguments from complex scalars to complex vectors. This conversion allows us to separate the electric field vector and the imaginary magnetic field vector, because exponentials of imaginary scalars convert vectors to imaginary vectors and vice versa, while exponentials of imaginary vectors only rotate the vector or imaginary vector they are multiplied to. We convert this expression for polarized light into two other representations: the Cartesian representation and the rotated ellipse representation. We compute the conversion relations among the representation parameters and their corresponding Stokes parameters. And finally, we propose a set of geometric relations between the electric and magnetic fields that satisfy an equation similar to the Poincaré sphere equation.

Singular vectors for the WN algebras

NASA Astrophysics Data System (ADS)

Ridout, David; Siu, Steve; Wood, Simon

2018-03-01

In this paper, we use free field realisations of the A-type principal, or Casimir, WN algebras to derive explicit formulae for singular vectors in Fock modules. These singular vectors are constructed by applying screening operators to Fock module highest weight vectors. The action of the screening operators is then explicitly evaluated in terms of Jack symmetric functions and their skew analogues. The resulting formulae depend on sequences of pairs of integers that completely determine the Fock module as well as the Jack symmetric functions.

Detection of abnormal living patterns for elderly living alone using support vector data description.

PubMed

Shin, Jae Hyuk; Lee, Boreom; Park, Kwang Suk

2011-05-01

In this study, we developed an automated behavior analysis system using infrared (IR) motion sensors to assist the independent living of the elderly who live alone and to improve the efficiency of their healthcare. An IR motion-sensor-based activity-monitoring system was installed in the houses of the elderly subjects to collect motion signals and three different feature values, activity level, mobility level, and nonresponse interval (NRI). These factors were calculated from the measured motion signals. The support vector data description (SVDD) method was used to classify normal behavior patterns and to detect abnormal behavioral patterns based on the aforementioned three feature values. The simulation data and real data were used to verify the proposed method in the individual analysis. A robust scheme is presented in this paper for optimally selecting the values of different parameters especially that of the scale parameter of the Gaussian kernel function involving in the training of the SVDD window length, T of the circadian rhythmic approach with the aim of applying the SVDD to the daily behavior patterns calculated over 24 h. Accuracies by positive predictive value (PPV) were 95.8% and 90.5% for the simulation and real data, respectively. The results suggest that the monitoring system utilizing the IR motion sensors and abnormal-behavior-pattern detection with SVDD are effective methods for home healthcare of elderly people living alone.

Stable Local Volatility Calibration Using Kernel Splines

NASA Astrophysics Data System (ADS)

Coleman, Thomas F.; Li, Yuying; Wang, Cheng

2010-09-01

We propose an optimization formulation using L1 norm to ensure accuracy and stability in calibrating a local volatility function for option pricing. Using a regularization parameter, the proposed objective function balances the calibration accuracy with the model complexity. Motivated by the support vector machine learning, the unknown local volatility function is represented by a kernel function generating splines and the model complexity is controlled by minimizing the 1-norm of the kernel coefficient vector. In the context of the support vector regression for function estimation based on a finite set of observations, this corresponds to minimizing the number of support vectors for predictability. We illustrate the ability of the proposed approach to reconstruct the local volatility function in a synthetic market. In addition, based on S&P 500 market index option data, we demonstrate that the calibrated local volatility surface is simple and resembles the observed implied volatility surface in shape. Stability is illustrated by calibrating local volatility functions using market option data from different dates.

Large-Scale Parallel Simulations of Turbulent Combustion using Combined Dimension Reduction and Tabulation of Chemistry

DTIC Science & Technology

2012-05-22

tabulation of the reduced space is performed using the In Situ Adaptive Tabulation ( ISAT ) algorithm. In addition, we use x2f mpi – a Fortran library...for parallel vector-valued function evaluation (used with ISAT in this context) – to efficiently redistribute the chemistry workload among the...Constrained-Equilibrium (RCCE) method, and tabulation of the reduced space is performed using the In Situ Adaptive Tabulation ( ISAT ) algorithm. In addition

Dynamics of the EEG of human brain in the gradient magnetic fields of geological faults in different geographical and climatic zones

NASA Astrophysics Data System (ADS)

Pobachenko, S. V.; Sokolov, M. V.; Grigoriev, P. E.; Vasilieva, I. V.

2017-11-01

There are presented the results of experimental studies of the dynamics of indices of the functional state of a person located within the zones characterized by anomalous parameters of spatial distribution of magnetic field vector values. It is shown that these geophysical modifications have a pronounced effect on the dynamics of electrical activity indices of the human brain, regardless of geographic and climatic conditions.

What is a vector?

PubMed Central

Morgan, Eric René; Booth, Mark; Norman, Rachel; Mideo, Nicole; McCallum, Hamish; Fenton, Andy

2017-01-01

Many important and rapidly emerging pathogens of humans, livestock and wildlife are ‘vector-borne’. However, the term ‘vector’ has been applied to diverse agents in a broad range of epidemiological systems. In this perspective, we briefly review some common definitions, identify the strengths and weaknesses of each and consider the functional differences between vectors and other hosts from a range of ecological, evolutionary and public health perspectives. We then consider how the use of designations can afford insights into our understanding of epidemiological and evolutionary processes that are not otherwise apparent. We conclude that from a medical and veterinary perspective, a combination of the ‘haematophagous arthropod’ and ‘mobility’ definitions is most useful because it offers important insights into contact structure and control and emphasizes the opportunities for pathogen shifts among taxonomically similar species with similar feeding modes and internal environments. From a population dynamics and evolutionary perspective, we suggest that a combination of the ‘micropredator’ and ‘sequential’ definition is most appropriate because it captures the key aspects of transmission biology and fitness consequences for the pathogen and vector itself. However, we explicitly recognize that the value of a definition always depends on the research question under study. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289253

Pangloss revisited: a critique of the dilution effect and the biodiversity-buffers-disease paradigm.

PubMed

Randolph, S E; Dobson, A D M

2012-06-01

The twin concepts of zooprophylaxis and the dilution effect originated with vector-borne diseases (malaria), were driven forward by studies on Lyme borreliosis and have now developed into the mantra "biodiversity protects against disease". The basic idea is that by diluting the assemblage of transmission-competent hosts with non-competent hosts, the probability of vectors feeding on transmission-competent hosts is reduced and so the abundance of infected vectors is lowered. The same principle has recently been applied to other infectious disease systems--tick-borne, insect-borne, indirectly transmitted via intermediate hosts, directly transmitted. It is claimed that the presence of extra species of various sorts, acting through a variety of distinct mechanisms, causes the prevalence of infectious agents to decrease. Examination of the theoretical and empirical evidence for this hypothesis reveals that it applies only in certain circumstances even amongst tick-borne diseases, and even less often if considering the correct metric--abundance rather than prevalence of infected vectors. Whether dilution or amplification occurs depends more on specific community composition than on biodiversity per se. We warn against raising a straw man, an untenable argument easily dismantled and dismissed. The intrinsic value of protecting biodiversity and ecosystem function outweighs this questionable utilitarian justification.

Anisotropy and phonon modes from analysis of the dielectric function tensor and the inverse dielectric function tensor of monoclinic yttrium orthosilicate

NASA Astrophysics Data System (ADS)

Mock, A.; Korlacki, R.; Knight, S.; Schubert, M.

2018-04-01

We determine the frequency dependence of the four independent Cartesian tensor elements of the dielectric function for monoclinic symmetry Y2SiO5 using generalized spectroscopic ellipsometry from 40-1200 cm-1. Three different crystal cuts, each perpendicular to a principle axis, are investigated. We apply our recently described augmentation of lattice anharmonicity onto the eigendielectric displacement vector summation approach [A. Mock et al., Phys. Rev. B 95, 165202 (2017), 10.1103/PhysRevB.95.165202], and we present and demonstrate the application of an eigendielectric displacement loss vector summation approach with anharmonic broadening. We obtain an excellent match between all measured and model-calculated dielectric function tensor elements and all dielectric loss function tensor elements. We obtain 23 Au and 22 Bu symmetry long-wavelength active transverse and longitudinal optical mode parameters including their eigenvector orientation within the monoclinic lattice. We perform density functional theory calculations and obtain 23 Au symmetry and 22 Bu transverse and longitudinal optical mode parameters and their orientation within the monoclinic lattice. We compare our results from ellipsometry and density functional theory and find excellent agreement. We also determine the static and above reststrahlen spectral range dielectric tensor values and find a recently derived generalization of the Lyddane-Sachs-Teller relation for polar phonons in monoclinic symmetry materials satisfied [M. Schubert, Phys Rev. Lett. 117, 215502 (2016), 10.1103/PhysRevLett.117.215502].

Positivity of the universal pairing in 3 dimensions

NASA Astrophysics Data System (ADS)

Calegari, Danny; Freedman, Michael H.; Walker, Kevin

2010-01-01

Associated to a closed, oriented surface S is the complex vector space with basis the set of all compact, oriented 3 -manifolds which it bounds. Gluing along S defines a Hermitian pairing on this space with values in the complex vector space with basis all closed, oriented 3 -manifolds. The main result in this paper is that this pairing is positive, i.e. that the result of pairing a nonzero vector with itself is nonzero. This has bearing on the question of what kinds of topological information can be extracted in principle from unitary (2+1) -dimensional TQFTs. The proof involves the construction of a suitable complexity function c on all closed 3 -manifolds, satisfying a gluing axiom which we call the topological Cauchy-Schwarz inequality, namely that c(AB) le max(c(AA),c(BB)) for all A,B which bound S , with equality if and only if A=B . The complexity function c involves input from many aspects of 3 -manifold topology, and in the process of establishing its key properties we obtain a number of results of independent interest. For example, we show that when two finite-volume hyperbolic 3 -manifolds are glued along an incompressible acylindrical surface, the resulting hyperbolic 3 -manifold has minimal volume only when the gluing can be done along a totally geodesic surface; this generalizes a similar theorem for closed hyperbolic 3 -manifolds due to Agol-Storm-Thurston.

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

A simple method of equine limb force vector analysis and its potential applications

PubMed Central

Robinson, Mark A.; Clayton, Hilary M.

2018-01-01

Background Ground reaction forces (GRF) measured during equine gait analysis are typically evaluated by analyzing discrete values obtained from continuous force-time data for the vertical, longitudinal and transverse GRF components. This paper describes a simple, temporo-spatial method of displaying and analyzing sagittal plane GRF vectors. In addition, the application of statistical parametric mapping (SPM) is introduced to analyse differences between contra-lateral fore and hindlimb force-time curves throughout the stance phase. The overall aim of the study was to demonstrate alternative methods of evaluating functional (a)symmetry within horses. Methods GRF and kinematic data were collected from 10 horses trotting over a series of four force plates (120 Hz). The kinematic data were used to determine clean hoof contacts. The stance phase of each hoof was determined using a 50 N threshold. Vertical and longitudinal GRF for each stance phase were plotted both as force-time curves and as force vector diagrams in which vectors originating at the centre of pressure on the force plate were drawn at intervals of 8.3 ms for the duration of stance. Visual evaluation was facilitated by overlay of the vector diagrams for different limbs. Summary vectors representing the magnitude (VecMag) and direction (VecAng) of the mean force over the entire stance phase were superimposed on the force vector diagram. Typical measurements extracted from the force-time curves (peak forces, impulses) were compared with VecMag and VecAng using partial correlation (controlling for speed). Paired samples t-tests (left v. right diagonal pair comparison and high v. low vertical force diagonal pair comparison) were performed on discrete and vector variables using traditional methods and Hotelling’s T2 tests on normalized stance phase data using SPM. Results Evidence from traditional statistical tests suggested that VecMag is more influenced by the vertical force and impulse, whereas VecAng is more influenced by the longitudinal force and impulse. When used to evaluate mean data from the group of ten sound horses, SPM did not identify differences between the left and right contralateral limb pairs or between limb pairs classified according to directional asymmetry. When evaluating a single horse, three periods were identified during which differences in the forces between the left and right forelimbs exceeded the critical threshold (p < .01). Discussion Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave harmonious results and both methods identified the same inter-limb asymmetries. As alpha was more tightly controlled using SPM, significance was only found in the individual horse although T2 plots followed the same trends as discrete analysis for the group. Conclusions The techniques of force vector analysis and SPM hold promise for investigations of sidedness and asymmetry in horses. PMID:29492341

The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models

PubMed Central

Noid, W. G.; Liu, Pu; Wang, Yanting; Chu, Jhih-Wei; Ayton, Gary S.; Izvekov, Sergei; Andersen, Hans C.; Voth, Gregory A.

2008-01-01

The multiscale coarse-graining (MS-CG) method [S. Izvekov and G. A. Voth, J. Phys. Chem. B 109, 2469 (2005);J. Chem. Phys. 123, 134105 (2005)] employs a variational principle to determine an interaction potential for a CG model from simulations of an atomically detailed model of the same system. The companion paper proved that, if no restrictions regarding the form of the CG interaction potential are introduced and if the equilibrium distribution of the atomistic model has been adequately sampled, then the MS-CG variational principle determines the exact many-body potential of mean force (PMF) governing the equilibrium distribution of CG sites generated by the atomistic model. In practice, though, CG force fields are not completely flexible, but only include particular types of interactions between CG sites, e.g., nonbonded forces between pairs of sites. If the CG force field depends linearly on the force field parameters, then the vector valued functions that relate the CG forces to these parameters determine a set of basis vectors that span a vector subspace of CG force fields. The companion paper introduced a distance metric for the vector space of CG force fields and proved that the MS-CG variational principle determines the CG force force field that is within that vector subspace and that is closest to the force field determined by the many-body PMF. The present paper applies the MS-CG variational principle for parametrizing molecular CG force fields and derives a linear least squares problem for the parameter set determining the optimal approximation to this many-body PMF. Linear systems of equations for these CG force field parameters are derived and analyzed in terms of equilibrium structural correlation functions. Numerical calculations for a one-site CG model of methanol and a molecular CG model of the EMIM+∕NO3− ionic liquid are provided to illustrate the method. PMID:18601325

Anisotropic optical absorption induced by Rashba spin-orbit coupling in monolayer phosphorene

NASA Astrophysics Data System (ADS)

Li, Yuan; Li, Xin; Wan, Qi; Bai, R.; Wen, Z. C.

2018-04-01

We obtain the effective Hamiltonian of the phosphorene including the effect of Rashba spin-orbit coupling in the frame work of the low-energy theory. The spin-splitting energy bands show an anisotropy feature for the wave vectors along kx and ky directions, where kx orients to ΓX direction in the k space. We numerically study the optical absorption of the electrons for different wave vectors with Rashba spin-orbit coupling. We find that the spin-flip transition from the valence band to the conduction band induced by the circular polarized light closes to zero with increasing the x-component wave vector when ky equals to zero, while it can be significantly increased to a large value when ky gets a small value. When the wave vector varies along the ky direction, the spin-flip transition can also increase to a large value, however, which shows an anisotropy feature for the optical absorption. Especially, the spin-conserved transitions keep unchanged and have similar varying trends for different wave vectors. This phenomenon provides a novel route for the manipulation of the spin-dependent property of the fermions in the monolayer phosphorene.

Design type air engine Di Pietro

NASA Astrophysics Data System (ADS)

Zwierzchowski, Jaroslaw

The article presents a pneumatic engine constructed by Angelo Di Pietro. 3D solid models of pneumatic engine components were presented therein. A directional valve is a key element of the control system. The valve functions as a camshaft distributing air to particular engine chambers. The construction designed by Angelo Di Pietro is modern and innovative. A pneumatic engine requires low pressure to start rotary movement. With the use of CFD software, the fields of velocity vectors' distribution were determined. Moreover, the author determined the distribution of pressure values in engine inlet and outlet channels. CFD model studies on engine operation were conducted for chosen stages of operating cycles. On the basis of simulation tests that were conducted, the values of flow rates for the engine were determined. The distribution of pressure values made it possible to evaluate the torque value on the rotating shaft.

Multifractal vector fields and stochastic Clifford algebra.

PubMed

Schertzer, Daniel; Tchiguirinskaia, Ioulia

2015-12-01

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

Vector curvaton with varying kinetic function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dimopoulos, Konstantinos; Karciauskas, Mindaugas; Wagstaff, Jacques M.

2010-01-15

A new model realization of the vector curvaton paradigm is presented and analyzed. The model consists of a single massive Abelian vector field, with a Maxwell-type kinetic term. By assuming that the kinetic function and the mass of the vector field are appropriately varying during inflation, it is shown that a scale-invariant spectrum of superhorizon perturbations can be generated. These perturbations can contribute to the curvature perturbation of the Universe. If the vector field remains light at the end of inflation it is found that it can generate substantial statistical anisotropy in the spectrum and bispectrum of the curvature perturbation.more » In this case the non-Gaussianity in the curvature perturbation is predominantly anisotropic, which will be a testable prediction in the near future. If, on the other hand, the vector field is heavy at the end of inflation then it is demonstrated that particle production is approximately isotropic and the vector field alone can give rise to the curvature perturbation, without directly involving any fundamental scalar field. The parameter space for both possibilities is shown to be substantial. Finally, toy models are presented which show that the desired variation of the mass and kinetic function of the vector field can be realistically obtained, without unnatural tunings, in the context of supergravity or superstrings.« less

Direct model-based predictive control scheme without cost function for voltage source inverters with reduced common-mode voltage

NASA Astrophysics Data System (ADS)

Kim, Jae-Chang; Moon, Sung-Ki; Kwak, Sangshin

2018-04-01

This paper presents a direct model-based predictive control scheme for voltage source inverters (VSIs) with reduced common-mode voltages (CMVs). The developed method directly finds optimal vectors without using repetitive calculation of a cost function. To adjust output currents with the CMVs in the range of -Vdc/6 to +Vdc/6, the developed method uses voltage vectors, as finite control resources, excluding zero voltage vectors which produce the CMVs in the VSI within ±Vdc/2. In a model-based predictive control (MPC), not using zero voltage vectors increases the output current ripples and the current errors. To alleviate these problems, the developed method uses two non-zero voltage vectors in one sampling step. In addition, the voltage vectors scheduled to be used are directly selected at every sampling step once the developed method calculates the future reference voltage vector, saving the efforts of repeatedly calculating the cost function. And the two non-zero voltage vectors are optimally allocated to make the output current approach the reference current as close as possible. Thus, low CMV, rapid current-following capability and sufficient output current ripple performance are attained by the developed method. The results of a simulation and an experiment verify the effectiveness of the developed method.

Decays of the vector glueball

NASA Astrophysics Data System (ADS)

Giacosa, Francesco; Sammet, Julia; Janowski, Stanislaus

2017-06-01

We calculate two- and three-body decays of the (lightest) vector glueball into (pseudo)scalar, (axial-)vector, as well as pseudovector and excited vector mesons in the framework of a model of QCD. While absolute values of widths cannot be predicted because the corresponding coupling constants are unknown, some interesting branching ratios can be evaluated by setting the mass of the yet hypothetical vector glueball to 3.8 GeV as predicted by quenched lattice QCD. We find that the decay mode ω π π should be one of the largest (both through the decay chain O →b1π →ω π π and through the direct coupling O →ω π π ). Similarly, the (direct and indirect) decay into π K K*(892 ) is sizable. Moreover, the decays into ρ π and K*(892 )K are, although subleading, possible and could play a role in explaining the ρ π puzzle of the charmonium state ψ (2 S ) thanks to a (small) mixing with the vector glueball. The vector glueball can be directly formed at the ongoing BESIII experiment as well as at the future PANDA experiment at the FAIR facility. If the width is sufficiently small (≲100 MeV ) it should not escape future detection. It should be stressed that the employed model is based on some inputs and simplifying assumptions: the value of glueball mass (at present, the quenched lattice value is used), the lack of mixing of the glueball with other quarkonium states, and the use of few interaction terms. It then represents a first step toward the identification of the main decay channels of the vector glueball, but shall be improved when corresponding experimental candidates and/or new lattice results will be available.

Models for discrete-time self-similar vector processes with application to network traffic

NASA Astrophysics Data System (ADS)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN.

PubMed

Liu, Chang; Cheng, Gang; Chen, Xihui; Pang, Yusong

2018-05-11

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

PubMed Central

Cheng, Gang; Chen, Xihui

2018-01-01

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears. PMID:29751671

Effects of Faraday Rotation Observed in Filter Magnetograph Data

NASA Technical Reports Server (NTRS)

Hagyard, Mona J.; Adams, Mitzi L.; Smith, J. E.; West, Edward A.

1999-01-01

In this paper we analyze the effects of Faraday rotation on the azimuth of the transverse magnetic field from observations taken with the Marshall Space Flight Center's vector magnetograph for a simple sunspot observed on June 9, 1985. Vector magnetograms were obtained over the wavelength interval of 170 mA redward of line center of the Fe I 5250.22 A spectral line to 170 mA to the blue, in steps of 10 mA. These data were analyzed to produce the variation of the azimuth as a function of wavelength at each pixel over the field of vi ew of the sunspot. At selected locations in the sunspot, curves of the observed variation of azimuth with wavelength were compared with model calculations for the amount of Faraday rotation of the azimuth. From these comparisons we derived the amount of rotation as functions of bo th the magnitude and inclination of the sunspot's field and deduced the ranges of these field values for which Faraday rotation presents a significant problem in observations taken near the center of a spectral line.

Decomposition-aggregation stability analysis. [for large scale dynamic systems with application to spinning Skylab control system

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Weissenberger, S.; Cuk, S. M.

1973-01-01

This report presents the development and description of the decomposition aggregation approach to stability investigations of high dimension mathematical models of dynamic systems. The high dimension vector differential equation describing a large dynamic system is decomposed into a number of lower dimension vector differential equations which represent interconnected subsystems. Then a method is described by which the stability properties of each subsystem are aggregated into a single vector Liapunov function, representing the aggregate system model, consisting of subsystem Liapunov functions as components. A linear vector differential inequality is then formed in terms of the vector Liapunov function. The matrix of the model, which reflects the stability properties of the subsystems and the nature of their interconnections, is analyzed to conclude over-all system stability characteristics. The technique is applied in detail to investigate the stability characteristics of a dynamic model of a hypothetical spinning Skylab.

A Real-Time Phase Vector Display for EEG Monitoring

NASA Technical Reports Server (NTRS)

Finger, Herbert J.; Anliker, James E.; Rimmer, Tamara

1973-01-01

A real-time, computer-based, phase vector display system has been developed which will output a vector whose phase is equal to the delay between a trigger and the peak of a function which is quasi-coherent with respect to the trigger. The system also contains a sliding averager which enables the operator to average successive trials before calculating the phase vector. Data collection, averaging and display generation are performed on a LINC-8 computer. Output displays appear on several X-Y CRT display units and on a kymograph camera/oscilloscope unit which is used to generate photographs of time-varying phase vectors or contourograms of time-varying averages of input functions.

Method and system of filtering and recommending documents

DOEpatents

Patton, Robert M.; Potok, Thomas E.

2016-02-09

Disclosed is a method and system for discovering documents using a computer and providing a small set of the most relevant documents to the attention of a human observer. Using the method, the computer obtains a seed document from the user and generates a seed document vector using term frequency-inverse corpus frequency weighting. A keyword index for a plurality of source documents can be compared with the weighted terms of the seed document vector. The comparison is then filtered to reduce the number of documents, which define an initial subset of the source documents. Initial subset vectors are generated and compared to the seed document vector to obtain a similarity value for each comparison. Based on the similarity value, the method then recommends one or more of the source documents.

How representative is the 'Representative Value' of refraction provided by the Shin-Nippon NVision-K 5001 autorefractor?

PubMed

Tang, Wing Chun; Tang, Ying Yung; Lam, Carly S Y

2014-01-01

The aim of the study was to evaluate the level of agreement between the 'Representative Value' (RV) of refraction obtained from the Shin-Nippon NVision-K 5001 instrument with values calculated from individual measurement readings using standard algebraic methods. Cycloplegic autorefraction readings for 101 myopic children aged 8-13 years (10.9 ± 1.42 years) were obtained using the Shin-Nippon NVision-K 5001. Ten autorefractor measurements were taken for each eye. The spherical equivalent (SE), sphere (Sph) and cylindrical component (Cyl) power of each eye were calculated, firstly, by averaging the 10 repeated measurements (Mean SE, Mean Sph and Mean Cyl), and secondly, by the vector representation method (Vector SE, Vector Sph and Vector Cyl). These calculated values were then compared with those of RV (RV SE, RV Sph and RV Cyl) provided by the proprietary software of the NVision-K 5001 using one-way analysis of variance (anova). The agreement between the methods was also assessed. The SE of the subjects ranged from -5.37 to -0.62 D (mean ± SD, = -2.89 ± 1.01 D). The Mean SE was in exact agreement with the Vector SE. There were no significant differences between the RV readings and those calculated using non-vectorial or vectorial methods for any of the refractive powers (SE, p = 0.99; Sph, p = 0.93; Cyl, p = 0.24). The (mean ± SD) differences were: RV SE vs Mean SE (and also RV SE vs Vector SE) -0.01 ± 0.06 D; RV Sph vs Mean Sph, -0.01 ± 0.05 D; RV Sph vs Vector Sph, -0.04 ± 0.06 D; RV Cyl vs Mean Cyl, 0.01 ± 0.07 D; RV Cyl vs Vector Cyl, 0.06 ± 0.09 D. Ninety-eight percent of RV reading differed from their non-vectorial or vectorial counterparts by less than 0.25 D. The RV values showed good agreement to the results calculated using conventional methods. Although the formula used to calculate RV by the NVision-K 5001 autorefractor is proprietary, our results provide validation for the use of RV measurements in clinical practice and vision science research. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

Working with and Visualizing Big Data Efficiently with Python for the DARPA XDATA Program

DTIC Science & Technology

2017-08-01

same function to be used with scalar inputs, input arrays of the same shape, or even input arrays of dimensionality in some cases. Most of the math ... math operations on values ● Split-apply-combine: similar to group-by operations in databases ● Join: combine two datasets using common columns 4.3.3...Numba - Continue to increase SIMD performance with support for fast math flags and improved support for AVX, Intel’s large vector

Crystallographic Topology 2: Overview and Work in Progress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, C.K.

1999-08-01

This overview describes an application of contemporary geometric topology and stochastic process concepts to structural crystallography. In this application, crystallographic groups become orbifolds, crystal structures become Morse functions on orbifolds, and vibrating atoms in a crystal become vector valued Gaussian measures with the Radon-Nikodym property. Intended crystallographic benefits include new methods for visualization of space groups and crystal structures, analysis of the thermal motion patterns seen in ORTEP drawings, and a classification scheme for crystal structures based on their Heegaard splitting properties.

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

Turner, A. J.; Jacob, D. J.

2015-06-30

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-01-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-06-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Induced Monoculture in Axelrod Model with Clever Mass Media

NASA Astrophysics Data System (ADS)

Rodríguez, Arezky H.; Del Castillo-Mussot, M.; Vázquez, G. J.

A new model is proposed, in the context of Axelrod's model for the study of cultural dissemination, to include an external vector field (VF) which describes the effects of mass media on social systems. The VF acts over the whole system and it is characterized by two parameters: a nonnull overlap with each agent in the society and a confidence value of its information. Beyond a threshold value of the confidence, there is induced monocultural globalization of the system lined up with the VF. Below this value, the multicultural states are unstable and certain homogenization of the system is obtained in opposite line up according to that we have called negative publicity effect. Three regimes of behavior for the spread process of the VF information as a function of time are reported.

Shape functions for velocity interpolation in general hexahedral cells

USGS Publications Warehouse

Naff, R.L.; Russell, T.F.; Wilson, J.D.

2002-01-01

Numerical methods for grids with irregular cells require discrete shape functions to approximate the distribution of quantities across cells. For control-volume mixed finite-element (CVMFE) methods, vector shape functions approximate velocities and vector test functions enforce a discrete form of Darcy's law. In this paper, a new vector shape function is developed for use with irregular, hexahedral cells (trilinear images of cubes). It interpolates velocities and fluxes quadratically, because as shown here, the usual Piola-transformed shape functions, which interpolate linearly, cannot match uniform flow on general hexahedral cells. Truncation-error estimates for the shape function are demonstrated. CVMFE simulations of uniform and non-uniform flow with irregular meshes show first- and second-order convergence of fluxes in the L2 norm in the presence and absence of singularities, respectively.

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

Segmentation of discrete vector fields.

PubMed

Li, Hongyu; Chen, Wenbin; Shen, I-Fan

2006-01-01

In this paper, we propose an approach for 2D discrete vector field segmentation based on the Green function and normalized cut. The method is inspired by discrete Hodge Decomposition such that a discrete vector field can be broken down into three simpler components, namely, curl-free, divergence-free, and harmonic components. We show that the Green Function Method (GFM) can be used to approximate the curl-free and the divergence-free components to achieve our goal of the vector field segmentation. The final segmentation curves that represent the boundaries of the influence region of singularities are obtained from the optimal vector field segmentations. These curves are composed of piecewise smooth contours or streamlines. Our method is applicable to both linear and nonlinear discrete vector fields. Experiments show that the segmentations obtained using our approach essentially agree with human perceptual judgement.

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Reconstruction of the domain orientation distribution function of polycrystalline PZT ceramics using vector piezoresponse force microscopy.

PubMed

Kratzer, Markus; Lasnik, Michael; Röhrig, Sören; Teichert, Christian; Deluca, Marco

2018-01-11

Lead zirconate titanate (PZT) is one of the prominent materials used in polycrystalline piezoelectric devices. Since the ferroelectric domain orientation is the most important parameter affecting the electromechanical performance, analyzing the domain orientation distribution is of great importance for the development and understanding of improved piezoceramic devices. Here, vector piezoresponse force microscopy (vector-PFM) has been applied in order to reconstruct the ferroelectric domain orientation distribution function of polished sections of device-ready polycrystalline lead zirconate titanate (PZT) material. A measurement procedure and a computer program based on the software Mathematica have been developed to automatically evaluate the vector-PFM data for reconstructing the domain orientation function. The method is tested on differently in-plane and out-of-plane poled PZT samples, and the results reveal the expected domain patterns and allow determination of the polarization orientation distribution function at high accuracy.

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE PAGES

None, None

2016-11-21

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Polarization locked vector solitons and axis instability in optical fiber.

PubMed

Cundiff, Steven T.; Collings, Brandon C.; Bergman, Keren

2000-09-01

We experimentally observe polarization-locked vector solitons in optical fiber. Polarization locked-vector solitons use nonlinearity to preserve their polarization state despite the presence of birefringence. To achieve conditions where the delicate balance between nonlinearity and birefringence can survive, we studied the polarization evolution of the pulses circulating in a laser constructed entirely of optical fiber. We observe two distinct states with fixed polarization. This first state occurs for very small values birefringence and is elliptically polarized. We measure the relative phase between orthogonal components along the two principal axes to be +/-pi/2. The relative amplitude varies linearly with the magnitude of the birefringence. This state is a polarization locked vector soliton. The second, linearly polarized, state occurs for larger values of birefringence. The second state is due to the fast axis instability. We provide complete characterization of these states, and present a physical explanation of both of these states and the stability of the polarization locked vector solitons. (c) 2000 American Institute of Physics.

Polarization locked vector solitons and axis instability in optical fiber

NASA Astrophysics Data System (ADS)

Cundiff, Steven T.; Collings, Brandon C.; Bergman, Keren

2000-09-01

We experimentally observe polarization-locked vector solitons in optical fiber. Polarization locked-vector solitons use nonlinearity to preserve their polarization state despite the presence of birefringence. To achieve conditions where the delicate balance between nonlinearity and birefringence can survive, we studied the polarization evolution of the pulses circulating in a laser constructed entirely of optical fiber. We observe two distinct states with fixed polarization. This first state occurs for very small values birefringence and is elliptically polarized. We measure the relative phase between orthogonal components along the two principal axes to be ±π/2. The relative amplitude varies linearly with the magnitude of the birefringence. This state is a polarization locked vector soliton. The second, linearly polarized, state occurs for larger values of birefringence. The second state is due to the fast axis instability. We provide complete characterization of these states, and present a physical explanation of both of these states and the stability of the polarization locked vector solitons.

Electric fields and vector potentials of thin cylindrical antennas

NASA Astrophysics Data System (ADS)

King, Ronold W. P.

1990-09-01

The vector potential and electric field generated by the current in a center-driven or parasitic dipole antenna that extends from z = -h to z = h are investigated for each of the several components of the current. These include sin k(h - absolute value of z), sin k (absolute value of z) - sin kh, cos kz - cos kh, and cos kz/2 - cos kh/2. Of special interest are the interactions among the variously spaced elements in parallel nonstaggered arrays. These depend on the mutual vector potentials. It is shown that at a radial distance rho approximately = h and in the range z = -h to h, the vector potentials due to all four components become alike and have an approximately plane-wave form. Simple approximate formulas for the electric fields and vector potentials generated by each of the four distributions are derived and compared with the exact results. The application of the new formulas to large arrays is discussed.

Use of insecticide-treated house screens to reduce infestations of dengue virus vectors, Mexico.

PubMed

Manrique-Saide, Pablo; Che-Mendoza, Azael; Barrera-Perez, Mario; Guillermo-May, Guillermo; Herrera-Bojorquez, Josue; Dzul-Manzanilla, Felipe; Gutierrez-Castro, Cipriano; Lenhart, Audrey; Vazquez-Prokopec, Gonzalo; Sommerfeld, Johannes; McCall, Philip J; Kroeger, Axel; Arredondo-Jimenez, Juan I

2015-02-01

Dengue prevention efforts rely on control of virus vectors. We investigated use of insecticide-treated screens permanently affixed to windows and doors in Mexico and found that the screens significantly reduced infestations of Aedes aegypti mosquitoes in treated houses. Our findings demonstrate the value of this method for dengue virus vector control.

Simple cloning strategy using GFPuv gene as positive/negative indicator.

PubMed

Miura, Hiromi; Inoko, Hidetoshi; Inoue, Ituro; Tanaka, Masafumi; Sato, Masahiro; Ohtsuka, Masato

2011-09-15

Because construction of expression vectors is the first requisite in the functional analysis of genes, development of simple cloning systems is a major requirement during the postgenomic era. In the current study, we developed cloning vectors for gain- or loss-of-function studies by using the GFPuv gene as a positive/negative indicator of cloning. These vectors allow us to easily detect correct clones and obtain expression vectors from a simple procedure by means of the combined use of the GFPuv gene and a type IIS restriction enzyme. Copyright © 2011 Elsevier Inc. All rights reserved.

Observation of Polarization-Locked Vector Solitons in an Optical Fiber

NASA Astrophysics Data System (ADS)

Cundiff, S. T.; Collings, B. C.; Akhmediev, N. N.; Soto-Crespo, J. M.; Bergman, K.; Knox, W. H.

1999-05-01

We observe polarization-locked vector solitons in a mode-locked fiber laser. Temporal vector solitons have components along both birefringent axes. Despite different phase velocities due to linear birefringence, the relative phase of the components is locked at +/-π/2. The value of +/-π/2 and component magnitudes agree with a simple analysis of the Kerr nonlinearity. These fragile phase-locked vector solitons have been the subject of much theoretical conjecture, but have previously eluded experimental observation.

Taser X26 discharges in swine: ventricular rhythm capture is dependent on discharge vector.

PubMed

Valentino, Daniel J; Walter, Robert J; Dennis, Andrew J; Margeta, Bosko; Starr, Frederic; Nagy, Kimberly K; Bokhari, Faran; Wiley, Dorion E; Joseph, Kimberly T; Roberts, Roxanne R

2008-12-01

Data from our previous studies indicate that Taser X26 stun devices can acutely alter cardiac function in swine. We hypothesized that most transcardiac discharge vectors would capture ventricular rhythm, but that other vectors, not traversing the heart, would fail to capture the ventricular rhythm. Using an Institutional Animal Care and Use Committee (IACUC) approved protocol, four Yorkshire pigs (25-36 kg) were anesthetized, paralyzed with succinylcholine (2 mg/kg), and then exposed to 10 second discharges from a police-issue Taser X26. For most discharges, the barbed darts were pushed manually into the skin to their full depth (12 mm) and were arranged in either transcardiac (such that a straight line connecting the darts would cross the region of the heart) or non-transcardiac vectors. A total of 11 different vectors and 22 discharge conditions were studied. For each vector, by simply rotating the cartridge 180-degrees in the gun, the primary current-emitting dart was changed and the direction of current flow during the discharge was reversed without physically moving the darts. Echocardiography and electrocardiograms (ECGs) were performed before, during, and after all discharges. p values < 0.05 were considered significant. ECGs were unreadable during the discharges because of electrical interference, but echocardiography images clearly demonstrated that ventricular rhythm was captured immediately in 52.5% (31 of 59) of the discharges on the ventral surface of the animal. In each of these cases, capture of the ventricular rhythm with rapid ventricular contractions consistent with ventricular tachycardia (VT) or flutter was seen throughout the discharge. A total of 27 discharges were administered with transcardiac vectors and ventricular capture occurred in 23 of these discharges (85.2% capture rate). A total of 32 non-transcardiac discharges were administered ventrally and capture was seen in only eight of these (25% capture rate). Ventricular fibrillation (VF) was seen with two vectors, both of which were transcardiac. In the remaining animals, VT occurred postdischarge until sinus rhythm was regained spontaneously. For most transcardiac vectors, Taser X26 caused immediate ventricular rhythm capture. This usually reverted spontaneously to sinus rhythm but potentially fatal VF was seen with two vectors. For some non-transcardiac vectors, capture was also seen but with a significantly (p < 0.0001) decreased incidence.

Metal-induced gap states in ferroelectric capacitors and its relationship with complex band structures

NASA Astrophysics Data System (ADS)

Junquera, Javier; Aguado-Puente, Pablo

2013-03-01

At metal-isulator interfaces, the metallic wave functions with an energy eigenvalue within the band gap decay exponentially inside the dielectric (metal-induced gap states, MIGS). These MIGS can be actually regarded as Bloch functions with an associated complex wave vector. Usually only real values of the wave vectors are discussed in text books, since infinite periodicity is assumed and, in that situation, wave functions growing exponentially in any direction would not be physically valid. However, localized wave functions with an exponential decay are indeed perfectly valid solution of the Schrodinger equation in the presence of defects, surfaces or interfaces. For this reason, properties of MIGS have been typically discussed in terms of the complex band structure of bulk materials. The probable dependence on the interface particulars has been rarely taken into account explicitly due to the difficulties to include them into the model or simulations. We aim to characterize from first-principles simulations the MIGS in realistic ferroelectric capacitors and their connection with the complex band structure of the ferroelectric material. We emphasize the influence of the real interface beyond the complex band structure of bulk materials. Financial support provided by MICINN Grant FIS2009-12721-C04-02, and by the European Union Grant No. CP-FP 228989-2 ``OxIDes''. Computer resources provided by the RES.

Polarization radiation in the planetary atmosphere delimited by a heterogeneous diffusely reflecting surface

NASA Technical Reports Server (NTRS)

Strelkov, S. A.; Sushkevich, T. A.

1983-01-01

Spatial frequency characteristics (SFC) and the scattering functions were studied in the two cases of a uniform horizontal layer with absolutely black bottom, and an isolated layer. The mathematical model for these examples describes the horizontal heterogeneities in a light field with regard to radiation polarization in a three dimensional planar atmosphere, delimited by a heterogeneous surface with diffuse reflection. The perturbation method was used to obtain vector transfer equations which correspond to the linear and nonlinear systems of polarization radiation transfer. The boundary value tasks for the vector transfer equation that is a parametric set and one dimensional are satisfied by the SFC of the nonlinear system, and are expressed through the SFC of linear approximation. As a consequence of the developed theory, formulas were obtained for analytical calculation of albedo in solving the task of dissemination of polarization radiation in the planetary atmosphere with uniform Lambert bottom.

Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

NASA Technical Reports Server (NTRS)

Saha, Bhaskar; Goebel, kai

2007-01-01

Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

Energy and maximum norm estimates for nonlinear conservation laws

NASA Technical Reports Server (NTRS)

Olsson, Pelle; Oliger, Joseph

1994-01-01

We have devised a technique that makes it possible to obtain energy estimates for initial-boundary value problems for nonlinear conservation laws. The two major tools to achieve the energy estimates are a certain splitting of the flux vector derivative f(u)(sub x), and a structural hypothesis, referred to as a cone condition, on the flux vector f(u). These hypotheses are fulfilled for many equations that occur in practice, such as the Euler equations of gas dynamics. It should be noted that the energy estimates are obtained without any assumptions on the gradient of the solution u. The results extend to weak solutions that are obtained as point wise limits of vanishing viscosity solutions. As a byproduct we obtain explicit expressions for the entropy function and the entropy flux of symmetrizable systems of conservation laws. Under certain circumstances the proposed technique can be applied repeatedly so as to yield estimates in the maximum norm.

Ghost instabilities of cosmological models with vector fields nonminimally coupled to the curvature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Himmetoglu, Burak; Peloso, Marco; Contaldi, Carlo R.

2009-12-15

We prove that many cosmological models characterized by vectors nonminimally coupled to the curvature (such as the Turner-Widrow mechanism for the production of magnetic fields during inflation, and models of vector inflation or vector curvaton) contain ghosts. The ghosts are associated with the longitudinal vector polarization present in these models and are found from studying the sign of the eigenvalues of the kinetic matrix for the physical perturbations. Ghosts introduce two main problems: (1) they make the theories ill defined at the quantum level in the high energy/subhorizon regime (and create serious problems for finding a well-behaved UV completion), andmore » (2) they create an instability already at the linearized level. This happens because the eigenvalue corresponding to the ghost crosses zero during the cosmological evolution. At this point the linearized equations for the perturbations become singular (we show that this happens for all the models mentioned above). We explicitly solve the equations in the simplest cases of a vector without a vacuum expectation value in a Friedmann-Robertson-Walker geometry, and of a vector with a vacuum expectation value plus a cosmological constant, and we show that indeed the solutions of the linearized equations diverge when these equations become singular.« less

The Adenovirus Genome Contributes to the Structural Stability of the Virion

PubMed Central

Saha, Bratati; Wong, Carmen M.; Parks, Robin J.

2014-01-01

Adenovirus (Ad) vectors are currently the most commonly used platform for therapeutic gene delivery in human gene therapy clinical trials. Although these vectors are effective, many researchers seek to further improve the safety and efficacy of Ad-based vectors through detailed characterization of basic Ad biology relevant to its function as a vector system. Most Ad vectors are deleted of key, or all, viral protein coding sequences, which functions to not only prevent virus replication but also increase the cloning capacity of the vector for foreign DNA. However, radical modifications to the genome size significantly decreases virion stability, suggesting that the virus genome plays a role in maintaining the physical stability of the Ad virion. Indeed, a similar relationship between genome size and virion stability has been noted for many viruses. This review discusses the impact of the genome size on Ad virion stability and emphasizes the need to consider this aspect of virus biology in Ad-based vector design. PMID:25254384

Numerically stable formulas for a particle-based explicit exponential integrator

NASA Astrophysics Data System (ADS)

Nadukandi, Prashanth

2015-05-01

Numerically stable formulas are presented for the closed-form analytical solution of the X-IVAS scheme in 3D. This scheme is a state-of-the-art particle-based explicit exponential integrator developed for the particle finite element method. Algebraically, this scheme involves two steps: (1) the solution of tangent curves for piecewise linear vector fields defined on simplicial meshes and (2) the solution of line integrals of piecewise linear vector-valued functions along these tangent curves. Hence, the stable formulas presented here have general applicability, e.g. exact integration of trajectories in particle-based (Lagrangian-type) methods, flow visualization and computer graphics. The Newton form of the polynomial interpolation definition is used to express exponential functions of matrices which appear in the analytical solution of the X-IVAS scheme. The divided difference coefficients in these expressions are defined in a piecewise manner, i.e. in a prescribed neighbourhood of removable singularities their series approximations are computed. An optimal series approximation of divided differences is presented which plays a critical role in this methodology. At least ten significant decimal digits in the formula computations are guaranteed to be exact using double-precision floating-point arithmetic. The worst case scenarios occur in the neighbourhood of removable singularities found in fourth-order divided differences of the exponential function.

Monte-Carlo Method Application for Precising Meteor Velocity from TV Observations

NASA Astrophysics Data System (ADS)

Kozak, P.

2014-12-01

Monte-Carlo method (method of statistical trials) as an application for meteor observations processing was developed in author's Ph.D. thesis in 2005 and first used in his works in 2008. The idea of using the method consists in that if we generate random values of input data - equatorial coordinates of the meteor head in a sequence of TV frames - in accordance with their statistical distributions we get a possibility to plot the probability density distributions for all its kinematical parameters, and to obtain their mean values and dispersions. At that the theoretical possibility appears to precise the most important parameter - geocentric velocity of a meteor - which has the highest influence onto precision of meteor heliocentric orbit elements calculation. In classical approach the velocity vector was calculated in two stages: first we calculate the vector direction as a vector multiplication of vectors of poles of meteor trajectory big circles, calculated from two observational points. Then we calculated the absolute value of velocity independently from each observational point selecting any of them from some reasons as a final parameter. In the given method we propose to obtain a statistical distribution of velocity absolute value as an intersection of two distributions corresponding to velocity values obtained from different points. We suppose that such an approach has to substantially increase the precision of meteor velocity calculation and remove any subjective inaccuracies.

Cone-Specific Promoters for Gene Therapy of Achromatopsia and Other Retinal Diseases

PubMed Central

Ye, Guo-Jie; Budzynski, Ewa; Sonnentag, Peter; Nork, T. Michael; Sheibani, Nader; Gurel, Zafer; Boye, Sanford L.; Peterson, James J.; Boye, Shannon E.; Hauswirth, William W.; Chulay, Jeffrey D.

2016-01-01

Adeno-associated viral (AAV) vectors containing cone-specific promoters have rescued cone photoreceptor function in mouse and dog models of achromatopsia, but cone-specific promoters have not been optimized for use in primates. Using AAV vectors administered by subretinal injection, we evaluated a series of promoters based on the human L-opsin promoter, or a chimeric human cone transducin promoter, for their ability to drive gene expression of green fluorescent protein (GFP) in mice and nonhuman primates. Each of these promoters directed high-level GFP expression in mouse photoreceptors. In primates, subretinal injection of an AAV-GFP vector containing a 1.7-kb L-opsin promoter (PR1.7) achieved strong and specific GFP expression in all cone photoreceptors and was more efficient than a vector containing the 2.1-kb L-opsin promoter that was used in AAV vectors that rescued cone function in mouse and dog models of achromatopsia. A chimeric cone transducin promoter that directed strong GFP expression in mouse and dog cone photoreceptors was unable to drive GFP expression in primate cones. An AAV vector expressing a human CNGB3 gene driven by the PR1.7 promoter rescued cone function in the mouse model of achromatopsia. These results have informed the design of an AAV vector for treatment of patients with achromatopsia. PMID:26603570

Alpharetroviral Vector-mediated Gene Therapy for X-CGD: Functional Correction and Lack of Aberrant Splicing

PubMed Central

Kaufmann, Kerstin B.; Brendel, Christian; Suerth, Julia D.; Mueller-Kuller, Uta; Chen-Wichmann, Linping; Schwäble, Joachim; Pahujani, Shweta; Kunkel, Hana; Schambach, Axel; Baum, Christopher; Grez, Manuel

2013-01-01

Comparative integrome analysis has revealed that the most neutral integration pattern among retroviruses is attributed to alpharetroviruses. We chose X-linked chronic granulomatous disease (X-CGD) as model to evaluate the potential of self-inactivating (SIN) alpharetroviral vectors for gene therapy of monogenic diseases. Therefore, we combined the alpharetroviral vector backbone with the elongation factor-1α short promoter, both considered to possess a low genotoxic profile, to drive transgene (gp91phox) expression. Following efficient transduction transgene expression was sustained and provided functional correction of the CGD phenotype in a cell line model at low vector copy number. Further analysis in a murine X-CGD transplantation model revealed gene-marking of bone marrow cells and oxidase positive granulocytes in peripheral blood. Transduction of human X-CGD CD34+ cells provided functional correction up to wild-type levels and long-term expression upon transplantation into a humanized mouse model. In contrast to lentiviral vectors, no aberrantly spliced transcripts containing cellular exons fused to alpharetroviral sequences were found in transduced cells, implying that the safety profile of alpharetroviral vectors may extend beyond their neutral integration profile. Taken together, this highlights the potential of this SIN alpharetroviral system as a platform for new candidate vectors for future gene therapy of hematopoietic disorders. PMID:23207695

Cone-Specific Promoters for Gene Therapy of Achromatopsia and Other Retinal Diseases.

PubMed

Ye, Guo-Jie; Budzynski, Ewa; Sonnentag, Peter; Nork, T Michael; Sheibani, Nader; Gurel, Zafer; Boye, Sanford L; Peterson, James J; Boye, Shannon E; Hauswirth, William W; Chulay, Jeffrey D

2016-01-01

Adeno-associated viral (AAV) vectors containing cone-specific promoters have rescued cone photoreceptor function in mouse and dog models of achromatopsia, but cone-specific promoters have not been optimized for use in primates. Using AAV vectors administered by subretinal injection, we evaluated a series of promoters based on the human L-opsin promoter, or a chimeric human cone transducin promoter, for their ability to drive gene expression of green fluorescent protein (GFP) in mice and nonhuman primates. Each of these promoters directed high-level GFP expression in mouse photoreceptors. In primates, subretinal injection of an AAV-GFP vector containing a 1.7-kb L-opsin promoter (PR1.7) achieved strong and specific GFP expression in all cone photoreceptors and was more efficient than a vector containing the 2.1-kb L-opsin promoter that was used in AAV vectors that rescued cone function in mouse and dog models of achromatopsia. A chimeric cone transducin promoter that directed strong GFP expression in mouse and dog cone photoreceptors was unable to drive GFP expression in primate cones. An AAV vector expressing a human CNGB3 gene driven by the PR1.7 promoter rescued cone function in the mouse model of achromatopsia. These results have informed the design of an AAV vector for treatment of patients with achromatopsia.

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation

PubMed Central

Zhang, Rui; Zhu, Shiping; Zhou, Qin

2016-01-01

Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models. PMID:27775660

An ESS maximum principle for matrix games.

PubMed

Vincent, T L; Cressman, R

2000-11-01

Previous work has demonstrated that for games defined by differential or difference equations with a continuum of strategies, there exists a G-function, related to individual fitness, that must take on a maximum with respect to a virtual variable v whenever v is one of the vectors in the coalition of vectors which make up the evolutionarily stable strategy (ESS). This result, called the ESS maximum principle, is quite useful in determining candidates for an ESS. This principle is reformulated here, so that it may be conveniently applied to matrix games. In particular, we define a matrix game to be one in which fitness is expressed in terms of strategy frequencies and a matrix of expected payoffs. It is shown that the G-function in the matrix game setting must again take on a maximum value at all the strategies which make up the ESS coalition vector. The reformulated maximum principle is applicable to both bilinear and nonlinear matrix games. One advantage in employing this principle to solve the traditional bilinear matrix game is that the same G-function is used to find both pure and mixed strategy solutions by simply specifying an appropriate strategy space. Furthermore we show how the theory may be used to solve matrix games which are not in the usual bilinear form. We examine in detail two nonlinear matrix games: the game between relatives and the sex ratio game. In both of these games an ESS solution is determined. These examples not only illustrate the usefulness of this approach to finding solutions to an expanded class of matrix games, but aids in understanding the nature of the ESS as well.

A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier.

PubMed

Zhou, Shenghan; Qian, Silin; Chang, Wenbing; Xiao, Yiyong; Cheng, Yang

2018-06-14

Timely and accurate state detection and fault diagnosis of rolling element bearings are very critical to ensuring the reliability of rotating machinery. This paper proposes a novel method of rolling bearing fault diagnosis based on a combination of ensemble empirical mode decomposition (EEMD), weighted permutation entropy (WPE) and an improved support vector machine (SVM) ensemble classifier. A hybrid voting (HV) strategy that combines SVM-based classifiers and cloud similarity measurement (CSM) was employed to improve the classification accuracy. First, the WPE value of the bearing vibration signal was calculated to detect the fault. Secondly, if a bearing fault occurred, the vibration signal was decomposed into a set of intrinsic mode functions (IMFs) by EEMD. The WPE values of the first several IMFs were calculated to form the fault feature vectors. Then, the SVM ensemble classifier was composed of binary SVM and the HV strategy to identify the bearing multi-fault types. Finally, the proposed model was fully evaluated by experiments and comparative studies. The results demonstrate that the proposed method can effectively detect bearing faults and maintain a high accuracy rate of fault recognition when a small number of training samples are available.

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE)

PubMed Central

Boker, Steven M.; Brick, Timothy R.; Pritikin, Joshua N.; Wang, Yang; von Oertzen, Timo; Brown, Donald; Lach, John; Estabrook, Ryne; Hunter, Michael D.; Maes, Hermine H.; Neale, Michael C.

2015-01-01

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE) is a novel paradigm for research in the behavioral, social, and health sciences. The MIDDLE approach is based on the seemingly-impossible idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. MIDDLE rests on the assumption that participant data should belong to, be controlled by, and remain in the possession of the participants themselves. Distributed likelihood estimation refers to fitting statistical models by sending an objective function and vector of parameters to each participants’ personal device (e.g., smartphone, tablet, computer), where the likelihood of that individual’s data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from responding participants and chooses new vectors of parameters until the model converges. A MIDDLE study provides significantly greater privacy for participants, automatic management of opt-in and opt-out consent, lower cost for the researcher and funding institute, and faster determination of results. Furthermore, if a participant opts into several studies simultaneously and opts into data sharing, these studies automatically have access to individual-level longitudinal data linked across all studies. PMID:26717128

Determination of aberration center of Ronchigram for automated aberration correctors in scanning transmission electron microscopy.

PubMed

Sannomiya, Takumi; Sawada, Hidetaka; Nakamichi, Tomohiro; Hosokawa, Fumio; Nakamura, Yoshio; Tanishiro, Yasumasa; Takayanagi, Kunio

2013-12-01

A generic method to determine the aberration center is established, which can be utilized for aberration calculation and axis alignment for aberration corrected electron microscopes. In this method, decentering induced secondary aberrations from inherent primary aberrations are minimized to find the appropriate axis center. The fitness function to find the optimal decentering vector for the axis was defined as a sum of decentering induced secondary aberrations with properly distributed weight values according to the aberration order. Since the appropriate decentering vector is determined from the aberration values calculated at an arbitrary center axis, only one aberration measurement is in principle required to find the center, resulting in /very fast center search. This approach was tested for the Ronchigram based aberration calculation method for aberration corrected scanning transmission electron microscopy. Both in simulation and in experiments, the center search was confirmed to work well although the convergence to find the best axis becomes slower with larger primary aberrations. Such aberration center determination is expected to fully automatize the aberration correction procedures, which used to require pre-alignment of experienced users. This approach is also applicable to automated aperture positioning. Copyright © 2013 Elsevier B.V. All rights reserved.

Decision support system for diabetic retinopathy using discrete wavelet transform.

PubMed

Noronha, K; Acharya, U R; Nayak, K P; Kamath, S; Bhandary, S V

2013-03-01

Prolonged duration of the diabetes may affect the tiny blood vessels of the retina causing diabetic retinopathy. Routine eye screening of patients with diabetes helps to detect diabetic retinopathy at the early stage. It is very laborious and time-consuming for the doctors to go through many fundus images continuously. Therefore, decision support system for diabetic retinopathy detection can reduce the burden of the ophthalmologists. In this work, we have used discrete wavelet transform and support vector machine classifier for automated detection of normal and diabetic retinopathy classes. The wavelet-based decomposition was performed up to the second level, and eight energy features were extracted. Two energy features from the approximation coefficients of two levels and six energy values from the details in three orientations (horizontal, vertical and diagonal) were evaluated. These features were fed to the support vector machine classifier with various kernel functions (linear, radial basis function, polynomial of orders 2 and 3) to evaluate the highest classification accuracy. We obtained the highest average classification accuracy, sensitivity and specificity of more than 99% with support vector machine classifier (polynomial kernel of order 3) using three discrete wavelet transform features. We have also proposed an integrated index called Diabetic Retinopathy Risk Index using clinically significant wavelet energy features to identify normal and diabetic retinopathy classes using just one number. We believe that this (Diabetic Retinopathy Risk Index) can be used as an adjunct tool by the doctors during the eye screening to cross-check their diagnosis.

Properties of Longitudinal Electromagnetic Oscillations in Metals and Their Excitation at Planar and Spherical Surfaces.

PubMed

Datsyuk, Vitaly V; Pavlyniuk, Oleg R

2017-12-01

The common definition of the spatially dispersive permittivity is revised. The response of the degenerate electron gas on an electric field satisfying the vector Helmholtz equation is found with a solution to the Boltzmann equation. The calculated longitudinal dielectric function coincides with that obtained by Klimontovich and Silin in 1952 and Lindhard in 1954. However, it depends on the square of the wavenumber, a parameter of the vector Helmholtz equation, but not the wave vector of a plane electromagnetic wave. This new concept simplifies simulation of the nonlocal effects, for example, with a generalized Lorents-Mie theory, since no Fourier transforms should be made. The Fresnel coefficients are generalized allowing for excitation of the longitudinal electromagnetic waves. To verify the theory, the extinction spectra for silver and gold nanometer-sized spheres are calculated. For these particles, the generalized Lorents-Mie theory gives the blue shift and broadening of the plasmon resonance which are in excellent agreement with experimental data. In addition, the nonlocal theory explains vanishing of the plasmon resonance observed for gold spheres with diameters less than or equal to 2 nm. The calculations using the Klimontovich-Silin-Lindhard and hydrodynamic dielectric functions for silver are found to give close results at photon energies from 3 to 4 eV. We show that the absolute values of the wavenumbers of the longitudinal waves in solids are much higher than those of the transverse waves.

Properties of Longitudinal Electromagnetic Oscillations in Metals and Their Excitation at Planar and Spherical Surfaces

NASA Astrophysics Data System (ADS)

Datsyuk, Vitaly V.; Pavlyniuk, Oleg R.

2017-08-01

The common definition of the spatially dispersive permittivity is revised. The response of the degenerate electron gas on an electric field satisfying the vector Helmholtz equation is found with a solution to the Boltzmann equation. The calculated longitudinal dielectric function coincides with that obtained by Klimontovich and Silin in 1952 and Lindhard in 1954. However, it depends on the square of the wavenumber, a parameter of the vector Helmholtz equation, but not the wave vector of a plane electromagnetic wave. This new concept simplifies simulation of the nonlocal effects, for example, with a generalized Lorents-Mie theory, since no Fourier transforms should be made. The Fresnel coefficients are generalized allowing for excitation of the longitudinal electromagnetic waves. To verify the theory, the extinction spectra for silver and gold nanometer-sized spheres are calculated. For these particles, the generalized Lorents-Mie theory gives the blue shift and broadening of the plasmon resonance which are in excellent agreement with experimental data. In addition, the nonlocal theory explains vanishing of the plasmon resonance observed for gold spheres with diameters less than or equal to 2 nm. The calculations using the Klimontovich-Silin-Lindhard and hydrodynamic dielectric functions for silver are found to give close results at photon energies from 3 to 4 eV. We show that the absolute values of the wavenumbers of the longitudinal waves in solids are much higher than those of the transverse waves.

Why do people move? Enhancing human mobility prediction using local functions based on public records and SNS data.

PubMed

Kim, Jungmin; Park, Juyong; Lee, Wonjae

2018-01-01

The quality of life for people in urban regions can be improved by predicting urban human mobility and adjusting urban planning accordingly. In this study, we compared several possible variables to verify whether a gravity model (a human mobility prediction model borrowed from Newtonian mechanics) worked as well in inner-city regions as it did in intra-city regions. We reviewed the resident population, the number of employees, and the number of SNS posts as variables for generating mass values for an urban traffic gravity model. We also compared the straight-line distance, travel distance, and the impact of time as possible distance values. We defined the functions of urban regions on the basis of public records and SNS data to reflect the diverse social factors in urban regions. In this process, we conducted a dimension reduction method for the public record data and used a machine learning-based clustering algorithm for the SNS data. In doing so, we found that functional distance could be defined as the Euclidean distance between social function vectors in urban regions. Finally, we examined whether the functional distance was a variable that had a significant impact on urban human mobility.

Aviation Trainer Technology Test Plan. Volume II. Software Development

DTIC Science & Technology

1991-11-25

feild values in new node *Ieg>X=x newg->X = Y newg->Len =len; newg->Help =help; newg->Ignore = ignore; newg->Format = format; newg->Validation - NULL;I... vector : North long varVFE; /* F-16A velocity vector : East long varVFU; /* F-16A velocity vector : Up */ long varH; /* plane heading */ long varC; /* plane...31\\\\ETH523.sys" parmsdr.args=getds(); parmsdr.non7=OxOO; /*save interrupt vector for future restoration */ cSavvecso; rc=getdso; rc=cInitParameters

Term frequency - function of document frequency: a new term weighting scheme for enterprise information retrieval

NASA Astrophysics Data System (ADS)

Zhang, Hui; Wang, Deqing; Wu, Wenjun; Hu, Hongping

2012-11-01

In today's business environment, enterprises are increasingly under pressure to process the vast amount of data produced everyday within enterprises. One method is to focus on the business intelligence (BI) applications and increasing the commercial added-value through such business analytics activities. Term weighting scheme, which has been used to convert the documents as vectors in the term space, is a vital task in enterprise Information Retrieval (IR), text categorisation, text analytics, etc. When determining term weight in a document, the traditional TF-IDF scheme sets weight value for the term considering only its occurrence frequency within the document and in the entire set of documents, which leads to some meaningful terms that cannot get the appropriate weight. In this article, we propose a new term weighting scheme called Term Frequency - Function of Document Frequency (TF-FDF) to address this issue. Instead of using monotonically decreasing function such as Inverse Document Frequency, FDF presents a convex function that dynamically adjusts weights according to the significance of the words in a document set. This function can be manually tuned based on the distribution of the most meaningful words which semantically represent the document set. Our experiments show that the TF-FDF can achieve higher value of Normalised Discounted Cumulative Gain in IR than that of TF-IDF and its variants, and improving the accuracy of relevance ranking of the IR results.

Numerical solution of 2D-vector tomography problem using the method of approximate inverse

DOE Office of Scientific and Technical Information (OSTI.GOV)

Svetov, Ivan; Maltseva, Svetlana; Polyakova, Anna

2016-08-10

We propose a numerical solution of reconstruction problem of a two-dimensional vector field in a unit disk from the known values of the longitudinal and transverse ray transforms. The algorithm is based on the method of approximate inverse. Numerical simulations confirm that the proposed method yields good results of reconstruction of vector fields.

Pentatomoids as vectors of plant pathogens

USDA-ARS?s Scientific Manuscript database

Vector-borne pathogens can be categorized functionally according to the degree of symbiosis that they acquire with their respective vectors. Three modes of transmission have been broadly described: non-persistent, semi-persistent, and persistent. Originally compiled specifically for viruses transm...

Chroma Shift and Gamut Shape: Going Beyond Average Color Fidelity and Gamut Area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Royer, Michael P.; Houser, Kevin W.; David, Aurelien

Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes key components that go beyond the two high-level average values, Fidelity Index (IES Rf) and Gamut Index (IES Rg). This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. We illustrate why and how the Color Vector Graphic and Local Chroma Shift values capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IESmore » Rg), but that is pertinent to more completely quantifying color rendition, and to understanding human evaluations of color quality in the built environment. We also present alternatives for quantifying the Color Vector Graphic and Local Chroma Shift values, which can inform the development of future measures.« less

Acoustic communication in insect disease vectors

PubMed Central

Vigoder, Felipe de Mello; Ritchie, Michael Gordon; Gibson, Gabriella; Peixoto, Alexandre Afranio

2013-01-01

Acoustic signalling has been extensively studied in insect species, which has led to a better understanding of sexual communication, sexual selection and modes of speciation. The significance of acoustic signals for a blood-sucking insect was first reported in the XIX century by Christopher Johnston, studying the hearing organs of mosquitoes, but has received relatively little attention in other disease vectors until recently. Acoustic signals are often associated with mating behaviour and sexual selection and changes in signalling can lead to rapid evolutionary divergence and may ultimately contribute to the process of speciation. Songs can also have implications for the success of novel methods of disease control such as determining the mating competitiveness of modified insects used for mass-release control programs. Species-specific sound “signatures” may help identify incipient species within species complexes that may be of epidemiological significance, e.g. of higher vectorial capacity, thereby enabling the application of more focussed control measures to optimise the reduction of pathogen transmission. Although the study of acoustic communication in insect vectors has been relatively limited, this review of research demonstrates their value as models for understanding both the functional and evolutionary significance of acoustic communication in insects. PMID:24473800

Enduring high-efficiency in vivo transfection of neurons with non-viral magnetoparticles in the rat visual cortex for optogenetic applications.

PubMed

Soto-Sánchez, Cristina; Martínez-Navarrete, Gema; Humphreys, Lawrence; Puras, Gustavo; Zarate, Jon; Pedraz, José Luis; Fernández, Eduardo

2015-05-01

This work demonstrates the successful long-term transfection in vivo of a DNA plasmid vector in rat visual cortex neurons using the magnetofection technique. The transfection rates reached values of up to 97% of the neurons after 30days, comparable to those achieved by viral vectors. Immunohistochemical treatment with anti-EGFP antibodies enhanced the detection of the EYFP-channelrhodopsin expression throughout the dendritic trees and cell bodies. These results show that magnetic nanoparticles offer highly efficient and enduring in vivo high-rate transfection in identified neurons of an adult mammalian brain and suggest that the magnetotechnique facilitates the introduction of large functional genetic material like channelrhodopsin with safe non-viral vectors using minimally invasive approaches. Gene therapy may be one of the treatment modalities for neurological diseases in the future. The use of viral transfection remains a concern due to restrictions to the size limit of the genetic material able to be packed, as well as safety issues. In this work, the authors evaluated magnetoplexes as an alternative vehicle. The results showed very promising data in that these nanoparticles could offer high transfection efficiency. Copyright © 2015 Elsevier Inc. All rights reserved.

A complete set of two-dimensional harmonic vortices on a spherical surface

NASA Astrophysics Data System (ADS)

Esparza, Christian; Rendón, Pablo Luis; Ley Koo, Eugenio

2018-03-01

The solutions of the Euler equations on a spherical surface are constructed, starting from a vector velocity potential A in the radial direction and with a two-dimensional spherical harmonic variation of order m and well-defined parity under \\varphi \\mapsto -\\varphi . The solutions are well-behaved on the entire surface and continuous at the position of a parallel circle θ ={θ }0, where the vorticity is shown to be harmonically distributed. The velocity field is evaluated as the curl of the vector potential: it is shown that the velocity is divergenceless and distributed on the spherical surface. Its polar components at the parallel circle are shown to be continuous, confirming its divergenceless nature, while its azimuthal components are discontinuous at the circle, and their discontinuity is a measure of the vorticity in the radial direction. A closed form for the velocity field lines is also obtained in terms of fixed values of the scalar harmonic function associated with the vector potential. Additionally, the connections of the solutions on a spherical surface with their circular, elliptic and bipolar counterparts on the equatorial plane are implemented via stereographic projections.

Contrasting Effects of Human, Canine, and Hybrid Adenovirus Vectors on the Phenotypical and Functional Maturation of Human Dendritic Cells: Implications for Clinical Efficacy▿

PubMed Central

Perreau, Matthieu; Mennechet, Franck; Serratrice, Nicolas; Glasgow, Joel N.; Curiel, David T.; Wodrich, Harald; Kremer, Eric J.

2007-01-01

Antipathogen immune responses create a balance between immunity, tolerance, and immune evasion. However, during gene therapy most viral vectors are delivered in substantial doses and are incapable of expressing gene products that reduce the host's ability to detect transduced cells. Gene transfer efficacy is also modified by the in vivo transduction of dendritic cells (DC), which notably increases the immunogenicity of virions and vector-encoded genes. In this study, we evaluated parameters that are relevant to the use of canine adenovirus serotype 2 (CAV-2) vectors in the clinical setting by assaying their effect on human monocyte-derived DC (hMoDC). We compared CAV-2 to human adenovirus (HAd) vectors containing the wild-type virion, functional deletions in the penton base RGD motif, and the CAV-2 fiber knob. In contrast to the HAd type 5 (HAd5)-based vectors, CAV-2 poorly transduced hMoDC, provoked minimal upregulation of major histocompatibility complex class I/II and costimulatory molecules (CD40, CD80, and CD86), and induced negligible morphological changes indicative of DC maturation. Functional maturation assay results (e.g., reduced antigen uptake; tumor necrosis factor alpha, interleukin-1β [IL-1β], gamma interferon [IFN-γ], IL-10, IL-12, and IFN-α/β secretion; and stimulation of heterologous T-cell proliferation) were also significantly lower for CAV-2. Our data suggested that this was due, in part, to the use of an alternative receptor and a block in vesicular escape. Additionally, HAd5 vector-induced hMoDC maturation was independent of the aforementioned cytokines. Paradoxically, an HAd5/CAV-2 hybrid vector induced the greatest phenotypical and functional maturation of hMoDC. Our data suggest that CAV-2 and the HAd5/CAV-2 vector may be the antithesis of Adenoviridae immunogenicity and that each may have specific clinical advantages. PMID:17229706

Micrometeoroid/space debris effects on materials

NASA Technical Reports Server (NTRS)

Zwiener, James M.; Finckenor, Miria M.

1993-01-01

The Long Duration Exposure Facility (LDEF) micrometeoroid/space debris impact data has been reduced in terms that are convenient for evaluating the overall quantitative effect on material properties. Impact crater flux has been evaluated as a function of angle from velocity vector and as a function of crater size. This data is combined with spall data from flight and ground testing to calculate effective solar absorption and emittance values versus time. Results indicate that the surface damage from micrometeoroid/space debris does not significantly affect the overall surface optical thermal physical properties. Of course the local damage around impact craters radically alter optical properties. Damage to composites and solar cells on an overall basis was minimal.

Asymptotics of the evolution semigroup associated with a scalar field in the presence of a non-linear electromagnetic field

NASA Astrophysics Data System (ADS)

Albeverio, Sergio; Tamura, Hiroshi

2018-04-01

We consider a model describing the coupling of a vector-valued and a scalar homogeneous Markovian random field over R4, interpreted as expressing the interaction between a charged scalar quantum field coupled with a nonlinear quantized electromagnetic field. Expectations of functionals of the random fields are expressed by Brownian bridges. Using this, together with Feynman-Kac-Itô type formulae and estimates on the small time and large time behaviour of Brownian functionals, we prove asymptotic upper and lower bounds on the kernel of the transition semigroup for our model. The upper bound gives faster than exponential decay for large distances of the corresponding resolvent (propagator).

Green’s Functions for a Theoretical Model of an Aperture Fed Stacked-Patch Microstrip Antenna

DTIC Science & Technology

1989-12-01

44 4 - 1 Normalized values of D bk3b on the real axis for (a) f = 4 GHz, bib = 1.6 mm, b2b = 4.8 mm, Flb = 5 o’ 2b = 2.5 Eo’ 3b = Co, P’lb = 2b...dielectric la. bIb Thickness of dielectric lb. b2b Total thickness of dielectrics lb and 2b. Cli Observer cell on the aperture, i is an index variable...interface 3b (patch 2). Sfj Source current cell on the feedline. tb Thickness of dielectric layer 2b ( b2b - bib). T lj Vector rooftop basis function

A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

PubMed

Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

2008-04-01

Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

USSR and Eastern Europe Scientific Abstracts- Physics - Number 45

DTIC Science & Technology

1978-10-02

compound, a function of the angle between the electrical vector of the ’ light wave and the optical c-axis of the crystal. Heterodiodes have first...of naturally radioactive U, Th and K in a 1-liter sample. USSR A VECTOR MESON IN A QUANTUM ELECTROMAGNETIC FIELD Moscow TEORETICHESKAYA I...arbitrary spin in a classical plane electromagnetic field are used to find the exact wave function of a vector meson in the quantum field of a linearly

Cre-lox Univector acceptor vectors for functional screening in protoplasts: analysis of Arabidopsis donor cDNAs encoding ABSCISIC ACID INSENSITIVE1-Like protein phosphatases

PubMed Central

Jia, Fan; Gampala, Srinivas S.L.; Mittal, Amandeep; Luo, Qingjun; Rock, Christopher D.

2009-01-01

The 14,200 available full length Arabidopsis thaliana cDNAs in the Universal Plasmid System (UPS) donor vector pUNI51 should be applied broadly and efficiently to leverage a “functional map-space” of homologous plant genes. We have engineered Cre-lox UPS host acceptor vectors (pCR701- 705) with N-terminal epitope tags in frame with the loxH site and downstream from the maize Ubiquitin promoter for use in transient protoplast expression assays and particle bombardment transformation of monocots. As an example of the utility of these vectors, we recombined them with several Arabidopsis cDNAs encoding Ser/Thr protein phosphatase type 2C (PP2Cs) known from genetic studies or predicted by hierarchical clustering meta-analysis to be involved in ABA and stress responses. Our functional results in Zea mays mesophyll protoplasts on ABA-inducible expression effects on the Late Embryogenesis Abundant promoter ProEm:GUS reporter were consistent with predictions and resulted in identification of novel activities of some PP2Cs. Deployment of these vectors can facilitate functional genomics and proteomics and identification of novel gene activities. PMID:19499346

Adenovirus vector expressing keratinocyte growth factor using CAG promoter impairs pulmonary function of mice with elastase-induced emphysema.

PubMed

Oki, Hiroshi; Yazawa, Takuya; Baba, Yasuko; Kanegae, Yumi; Sato, Hanako; Sakamoto, Seiko; Goto, Takahisa; Saito, Izumu; Kurahashi, Kiyoyasu

2017-07-01

Pulmonary emphysema impairs quality of life and increases mortality. It has previously been shown that administration of adenovirus vector expressing murine keratinocyte growth factor (KGF) before elastase instillation prevents pulmonary emphysema in mice. We therefore hypothesized that therapeutic administration of KGF would restore damage to lungs caused by elastase instillation and thus improve pulmonary function in an animal model. KGF expressing adenovirus vector, which prevented bleomycin-induced pulmonary fibrosis in a previous study, was constructed. Adenovirus vector (1.0 × 10 9 plaque-forming units) was administered intratracheally one week after administration of elastase into mouse lungs. One week after administration of KGF-vector, exercise tolerance testing and blood gas analysis were performed, after which the lungs were removed under deep anesthesia. KGF-positive pneumocytes were more numerous, surfactant protein secretion in the airspace greater and mean linear intercept of lungs shorter in animals that had received KGF than in control animals. Unexpectedly, however, arterial blood oxygenation was worse in the KGF group and maximum running speed, an indicator of exercise capacity, had not improved after KGF in mice with elastase-induced emphysema, indicating that KGF-expressing adenovirus vector impaired pulmonary function in these mice. Notably, vector lacking KGF-expression unit did not induce such impairment, implying that the KGF expression unit itself may cause the damage to alveolar cells. Possible involvement of the CAG promoter used for KGF expression in impairing pulmonary function is discussed. © 2017 The Societies and John Wiley & Sons Australia, Ltd.

From micro-correlations to macro-correlations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

2016-11-15

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’smore » “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.« less

An alternative design for a sparse distributed memory

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1989-01-01

A new design for a Sparse Distributed Memory, called the selected-coordinate design, is described. As in the original design, there are a large number of memory locations, each of which may be activated by many different addresses (binary vectors) in a very large address space. Each memory location is defined by specifying ten selected coordinates (bit positions in the address vectors) and a set of corresponding assigned values, consisting of one bit for each selected coordinate. A memory location is activated by an address if, for all ten of the locations's selected coordinates, the corresponding bits in the address vector match the respective assigned value bits, regardless of the other bits in the address vector. Some comparative memory capacity and signal-to-noise ratio estimates for the both the new and original designs are given. A few possible hardware embodiments of the new design are described.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moyotl, A.; Rosado, A.; Tavares-Velasco, G.

The magnetic dipole moment and the electric dipole moment of leptons are calculated under the assumption of lepton flavor violation (LFV) induced by spin-1 unparticles with both vector and axial-vector couplings to leptons, including a CP-violating phase. The experimental limits on the muon magnetic dipole moment and LFV process, such as the decay l{sub i}{sup -}{yields}l{sub j}{sup -}l{sub k}{sup -}l{sub k}{sup +}, are then used to constrain the LFV couplings for particular values of the unparticle operator dimension d{sub U} and the unparticle scale {Lambda}{sub U}, assuming that LFV transitions between the tau and muon leptons are dominant. It ismore » found that the current experimental constraints favor a scenario with dominance of the vector couplings over the axial-vector couplings. We also obtain estimates for the electric dipole moments of the electron and the muon, which are well below the experimental values.« less

A Preliminary Study to Forecast Japanese Encephalitis Vector Abundance in Paddy Growing Area, with the Aid of Radar Satellite Images.

PubMed

Raju, K Hari Kishan; Sabesan, Shanmugavelu; Rajavel, Aladu Ramakrishnan; Subramanian, Swaminathan; Natarajan, Ramalingam; Thenmozhi, Velayutham; Tyagi, Brij Kishore; Jambulingam, Purushothaman

2016-02-01

Vector mosquitoes of Japanese encephalitis (JE) breed mostly in rice fields, and human cases occur scattered over extended rural rice-growing areas. From this, one may surmise an ecological connection with the irrigation facilities and paddy cultivation. Furthermore, it has been hypothesized that a particular stage of paddy growth is a premonitory sign that can lead to a markedly increased population of the vector mosquitoes. The present study aimed to forecast the vector abundance by monitoring the paddy growth using remote sensing and geographical information systems. The abundance of the JE vector Culex tritaeniorhynchus peaked when the paddy crop was at its heading stage and dipped when the crop reached the maturing stage. A significant positive correlation was observed between paddy growth and adult density (r = 0.73, p < 0.008). The sigma naught values (σ0) derived from satellite images of paddy fields ranged from -18.3 (during transplantation stage) to approximately -10 (during the noncultivation period). A significant positive correlation was observed between σ0 and paddy growth stages (r = 0.87, p < 0.05) and adult vector density (r = 0.74, p = 0.04). The σ0 value observed during the vegetative and flowering stages of paddy growth ranged from -17.6 to -17.16, at which period the vector density started building up. This could be the spectral signature that denotes the "risk," following which a high vector abundance is expected during heading stage of the paddy.

A Computationally Efficient Filter for Reducing Shot Noise in Low S/N Data

PubMed Central

Okada, Mami; Ishikawa, Tomoe; Ikegaya, Yuji

2016-01-01

Functional multineuron calcium imaging (fMCI) provides a useful experimental platform to simultaneously capture the spatiotemporal patterns of neuronal activity from a large cell population in situ. However, fMCI often suffers from low signal-to-noise ratios (S/N). The main factor that causes the low S/N is shot noise that arises from photon detectors. Here, we propose a new denoising procedure, termed the Okada filter, which is designed to reduce shot noise under low S/N conditions, such as fMCI. The core idea of the Okada filter is to replace the fluorescence intensity value of a given frame time with the average of two values at the preceding and following frames unless the focused value is the median among these three values. This process is iterated serially throughout a time-series vector. In fMCI data of hippocampal neurons, the Okada filter rapidly reduces background noise and significantly improves the S/N. The Okada filter is also applicable for reducing shot noise in electrophysiological data and photographs. Finally, the Okada filter can be described using a single continuous differentiable equation based on the logistic function and is thus mathematically tractable. PMID:27304217

Technical note: An approach to derive breeding goals from the preferences of decision makers.

PubMed

Alfonso, L

2016-11-01

This paper deals with the use of the Choquet integral to identify breeding objectives and construct an aggregate genotype. The Choquet integral can be interpreted as an extension of the aggregate genotype based on profit equations, substituting the vector of economic weights by a monotone function, called capacity, which allows the aggregation of traits based, for instance, on the preferences of decision makers. It allows the aggregation of traits with or without economic value, taking into account not only the importance of the breeding value of each trait but also the interaction among them. Two examples have been worked out for pig and dairy cattle breeding scenarios to illustrate its application. It is shown that the expression of stakeholders' or decision makers' preferences, as a single ranking of animals or groups of animals, could be sufficient to extract information to derive breeding objectives. It is also shown that coalitions among traits can be identified to evaluate whether a linear additive function, equivalent of the Hazel aggregate genotype where economic values are replaced by Shapley values, could be adequate to define the net merit of breeding animals.

Vector matter waves in two-component Bose-Einstein condensates with spatially modulated nonlinearities

NASA Astrophysics Data System (ADS)

Xu, Si-Liu; He, Jun-Rong; Xue, Li; Belić, Milivoj R.

2018-02-01

We demonstrate three-dimensional (3D) vector solitary waves in the coupled (3 + 1)-D nonlinear Gross-Pitaevskii equations with variable nonlinearity coefficients. The analysis is carried out in spherical coordinates, providing novel localized solutions that depend on three modal numbers, l, m, and n. Using the similarity transformation (ST) method in 3D, vector solitary waves are built with the help of a combination of harmonic and trapping potentials, including multipole solutions and necklace rings. In general, the solutions found are stable for low values of the modal numbers; for values larger than 2, the solutions are found to be unstable. Variable nonlinearity allows the utilization of soliton management methods.

Development of a new vector using Soybean yellow common mosaic virus for gene function study or heterologous protein expression in soybeans.

PubMed

Lim, Seungmo; Nam, Moon; Kim, Kil Hyun; Lee, Su-Heon; Moon, Jung-Kyung; Lim, Hyoun-Sub; Choung, Myoung-Gun; Kim, Sang-Mok; Moon, Jae Sun

2016-02-01

A new vector using Soybean yellow common mosaic virus (SYCMV) was constructed for gene function study or heterologous protein expression in soybeans. The in vitro transcript with a 5' cap analog m7GpppG from an SYCMV full-length infectious vector driven by a T7 promoter infected soybeans (pSYCMVT7-full). The symptoms observed in the soybeans infected with either the sap from SYCMV-infected leaves or pSYCMVT7-full were indistinguishable, suggesting that the vector exhibits equivalent biological activity as the virus itself. To utilize the vector further, a DNA-based vector driven by the Cauliflower mosaic virus (CaMV) 35S promoter was constructed. The complete sequence of the SYCMV genome was inserted into a binary vector flanked by a CaMV 35S promoter at the 5' terminus of the SYCMV genome and a cis-cleaving ribozyme sequence followed by a nopaline synthase terminator at the 3' terminus of the SYCMV genome (pSYCMV-full). The SYCMV-derived vector was tested for use as a virus-induced gene silencing (VIGS) vector for the functional analysis of soybean genes. VIGS constructs containing either a fragment of the Phytoene desaturase (PDS) gene (pSYCMV-PDS1) or a fragment of the small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (RbcS) gene (pSYCMV-RbcS2) were constructed. Plants infiltrated with each vector using the Agrobacterium-mediated inoculation method exhibited distinct symptoms, such as photo-bleaching in plants infiltrated with pSYCMV-PDS1 and yellow or pale green coloring in plants infiltrated with pSYCMV-RbcS2. In addition, down-regulation of the transcripts of the two target genes was confirmed via northern blot analysis. Particle bombardment and direct plasmid DNA rubbing were also confirmed as alternative inoculation methods. To determine if the SYCMV vector can be used for the expression of heterologous proteins in soybean plants, the vector encoding amino acids 135-160 of VP1 of Foot-and-mouth disease virus (FMDV) serotype O1 Campos (O1C) was constructed (pSYCMV-FMDV). Plants infiltrated with pSYCMV-FMDV were only detected via western blotting using the O1C antibody. Based on these results, we propose that the SYCMV-derived vector can be used for gene function study or expression of useful heterologous proteins in soybeans. Copyright © 2015 Elsevier B.V. All rights reserved.

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Fisher statistics for analysis of diffusion tensor directional information.

PubMed

Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

2012-04-30

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of neuroanatomical features to tractography clustering.

PubMed

Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

2013-09-01

Diffusion tensor imaging allows unprecedented insight into brain neural connectivity in vivo by allowing reconstruction of neuronal tracts via captured patterns of water diffusion in white matter microstructures. However, tractography algorithms often output hundreds of thousands of fibers, rendering subsequent data analysis intractable. As a remedy, fiber clustering techniques are able to group fibers into dozens of bundles and thus facilitate analyses. Most existing fiber clustering methods rely on geometrical information of fibers, by viewing them as curves in 3D Euclidean space. The important neuroanatomical aspect of fibers, however, is ignored. In this article, the neuroanatomical information of each fiber is encapsulated in the associativity vector, which functions as the unique "fingerprint" of the fiber. Specifically, each entry in the associativity vector describes the relationship between the fiber and a certain anatomical ROI in a fuzzy manner. The value of the entry approaches 1 if the fiber is spatially related to the ROI at high confidence; on the contrary, the value drops closer to 0. The confidence of the ROI is calculated by diffusing the ROI according to the underlying fibers from tractography. In particular, we have adopted the fast marching method for simulation of ROI diffusion. Using the associativity vectors of fibers, we further model fibers as observations sampled from multivariate Gaussian mixtures in the feature space. To group all fibers into relevant major bundles, an expectation-maximization clustering approach is employed. Experimental results indicate that our method results in anatomically meaningful bundles that are highly consistent across subjects. Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.

Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses.

PubMed

Ye, Jun

2015-03-01

In pattern recognition and medical diagnosis, similarity measure is an important mathematical tool. To overcome some disadvantages of existing cosine similarity measures of simplified neutrosophic sets (SNSs) in vector space, this paper proposed improved cosine similarity measures of SNSs based on cosine function, including single valued neutrosophic cosine similarity measures and interval neutrosophic cosine similarity measures. Then, weighted cosine similarity measures of SNSs were introduced by taking into account the importance of each element. Further, a medical diagnosis method using the improved cosine similarity measures was proposed to solve medical diagnosis problems with simplified neutrosophic information. The improved cosine similarity measures between SNSs were introduced based on cosine function. Then, we compared the improved cosine similarity measures of SNSs with existing cosine similarity measures of SNSs by numerical examples to demonstrate their effectiveness and rationality for overcoming some shortcomings of existing cosine similarity measures of SNSs in some cases. In the medical diagnosis method, we can find a proper diagnosis by the cosine similarity measures between the symptoms and considered diseases which are represented by SNSs. Then, the medical diagnosis method based on the improved cosine similarity measures was applied to two medical diagnosis problems to show the applications and effectiveness of the proposed method. Two numerical examples all demonstrated that the improved cosine similarity measures of SNSs based on the cosine function can overcome the shortcomings of the existing cosine similarity measures between two vectors in some cases. By two medical diagnoses problems, the medical diagnoses using various similarity measures of SNSs indicated the identical diagnosis results and demonstrated the effectiveness and rationality of the diagnosis method proposed in this paper. The improved cosine measures of SNSs based on cosine function can overcome some drawbacks of existing cosine similarity measures of SNSs in vector space, and then their diagnosis method is very suitable for handling the medical diagnosis problems with simplified neutrosophic information and demonstrates the effectiveness and rationality of medical diagnoses. Copyright © 2014 Elsevier B.V. All rights reserved.

Viral vector-based tools advance knowledge of basal ganglia anatomy and physiology.

PubMed

Sizemore, Rachel J; Seeger-Armbruster, Sonja; Hughes, Stephanie M; Parr-Brownlie, Louise C

2016-04-01

Viral vectors were originally developed to deliver genes into host cells for therapeutic potential. However, viral vector use in neuroscience research has increased because they enhance interpretation of the anatomy and physiology of brain circuits compared with conventional tract tracing or electrical stimulation techniques. Viral vectors enable neuronal or glial subpopulations to be labeled or stimulated, which can be spatially restricted to a single target nucleus or pathway. Here we review the use of viral vectors to examine the structure and function of motor and limbic basal ganglia (BG) networks in normal and pathological states. We outline the use of viral vectors, particularly lentivirus and adeno-associated virus, in circuit tracing, optogenetic stimulation, and designer drug stimulation experiments. Key studies that have used viral vectors to trace and image pathways and connectivity at gross or ultrastructural levels are reviewed. We explain how optogenetic stimulation and designer drugs used to modulate a distinct pathway and neuronal subpopulation have enhanced our mechanistic understanding of BG function in health and pathophysiology in disease. Finally, we outline how viral vector technology may be applied to neurological and psychiatric conditions to offer new treatments with enhanced outcomes for patients. Copyright © 2016 the American Physiological Society.

Gene silencing in Escherichia coli using antisense RNAs expressed from doxycycline-inducible vectors.

PubMed

Nakashima, N; Tamura, T

2013-06-01

Here, we report on the construction of doxycycline (tetracycline analogue)-inducible vectors that express antisense RNAs in Escherichia coli. Using these vectors, the expression of genes of interest can be silenced conditionally. The expression of antisense RNAs from the vectors was more tightly regulated than the previously constructed isopropyl-β-D-galactopyranoside-inducible vectors. Furthermore, expression levels of antisense RNAs were enhanced by combining the doxycycline-inducible promoter with the T7 promoter-T7 RNA polymerase system; the T7 RNA polymerase gene, under control of the doxycycline-inducible promoter, was integrated into the lacZ locus of the genome without leaving any antibiotic marker. These vectors are useful for investigating gene functions or altering cell phenotypes for biotechnological and industrial applications. A gene silencing method using antisense RNAs in Escherichia coli is described, which facilitates the investigation of bacterial gene function. In particular, the method is suitable for comprehensive analyses or phenotypic analyses of genes essential for growth. Here, we describe expansion of vector variations for expressing antisense RNAs, allowing choice of a vector appropriate for the target genes or experimental purpose. © 2013 The Society for Applied Microbiology.

Viral vector-based tools advance knowledge of basal ganglia anatomy and physiology

PubMed Central

Sizemore, Rachel J.; Seeger-Armbruster, Sonja; Hughes, Stephanie M.

2016-01-01

Viral vectors were originally developed to deliver genes into host cells for therapeutic potential. However, viral vector use in neuroscience research has increased because they enhance interpretation of the anatomy and physiology of brain circuits compared with conventional tract tracing or electrical stimulation techniques. Viral vectors enable neuronal or glial subpopulations to be labeled or stimulated, which can be spatially restricted to a single target nucleus or pathway. Here we review the use of viral vectors to examine the structure and function of motor and limbic basal ganglia (BG) networks in normal and pathological states. We outline the use of viral vectors, particularly lentivirus and adeno-associated virus, in circuit tracing, optogenetic stimulation, and designer drug stimulation experiments. Key studies that have used viral vectors to trace and image pathways and connectivity at gross or ultrastructural levels are reviewed. We explain how optogenetic stimulation and designer drugs used to modulate a distinct pathway and neuronal subpopulation have enhanced our mechanistic understanding of BG function in health and pathophysiology in disease. Finally, we outline how viral vector technology may be applied to neurological and psychiatric conditions to offer new treatments with enhanced outcomes for patients. PMID:26888111

Floating point only SIMD instruction set architecture including compare, select, Boolean, and alignment operations

DOEpatents

Gschwind, Michael K [Chappaqua, NY

2011-03-01

Mechanisms for implementing a floating point only single instruction multiple data instruction set architecture are provided. A processor is provided that comprises an issue unit, an execution unit coupled to the issue unit, and a vector register file coupled to the execution unit. The execution unit has logic that implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA). The floating point vector registers of the vector register file store both scalar and floating point values as vectors having a plurality of vector elements. The processor may be part of a data processing system.

Chemical composition, toxicity and non-target effects of Pinus kesiya essential oil: An eco-friendly and novel larvicide against malaria, dengue and lymphatic filariasis mosquito vectors.

PubMed

Govindarajan, Marimuthu; Rajeswary, Mohan; Benelli, Giovanni

2016-07-01

Mosquitoes (Diptera: Culicidae) are vectors of important parasites and pathogens causing death, poverty and social disability worldwide, with special reference to tropical and subtropical countries. The overuse of synthetic insecticides to control mosquito vectors lead to resistance, adverse environmental effects and high operational costs. Therefore, the development of eco-friendly control tools is an important public health challenge. In this study, the mosquito larvicidal activity of Pinus kesiya leaf essential oil (EO) was evaluated against the malaria vector Anopheles stephensi, the dengue vector Aedes aegypti and the lymphatic filariasis vector Culex quinquefasciatus. The chemical composition of the EO was analyzed by gas chromatography-mass spectroscopy. GC-MS revealed that the P. kesiya EO contained 18 compounds. Major constituents were α-pinene, β-pinene, myrcene and germacrene D. In acute toxicity assays, the EO showed significant toxicity against early third-stage larvae of An. stephensi, Ae. aegypti and Cx. quinquefasciatus, with LC50 values of 52, 57, and 62µg/ml, respectively. Notably, the EO was safer towards several aquatic non-target organisms Anisops bouvieri, Diplonychus indicus and Gambusia affinis, with LC50 values ranging from 4135 to 8390µg/ml. Overall, this research adds basic knowledge to develop newer and safer natural larvicides from Pinaceae plants against malaria, dengue and filariasis mosquito vectors. Copyright © 2016 Elsevier Inc. All rights reserved.

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

A graph-based approach to inequality assessment

NASA Astrophysics Data System (ADS)

Palestini, Arsen; Pignataro, Giuseppe

2016-08-01

In a population consisting of heterogeneous types, whose income factors are indicated by nonnegative vectors, policies aggregating different factors can be represented by coalitions in a cooperative game, whose characteristic function is a multi-factor inequality index. When it is not possible to form all coalitions, the feasible ones can be indicated by a graph. We redefine Shapley and Banzhaf values on graph games to deduce some properties involving the degrees of the graph vertices and marginal contributions to overall inequality. An example is finally provided based on a modified multi-factor Atkinson index.

Vector autoregressive models: A Gini approach

NASA Astrophysics Data System (ADS)

Mussard, Stéphane; Ndiaye, Oumar Hamady

2018-02-01

In this paper, it is proven that the usual VAR models may be performed in the Gini sense, that is, on a ℓ1 metric space. The Gini regression is robust to outliers. As a consequence, when data are contaminated by extreme values, we show that semi-parametric VAR-Gini regressions may be used to obtain robust estimators. The inference about the estimators is made with the ℓ1 norm. Also, impulse response functions and Gini decompositions for prevision errors are introduced. Finally, Granger's causality tests are properly derived based on U-statistics.

Vector dissimilarity and clustering.

PubMed

Lefkovitch, L P

1991-04-01

Based on the description of objects by m attributes, an m-element vector dissimilarity function is defined that, unlike scalar functions, retains the distinction among attributes. This function, which satisfies the conditions for a metric, allows the definition of betweenness, which can then be used for clustering. Applications to the subset-generation phase of conditional clustering and to nearest-neighbor-type algorithms are described.

LINEARIZATION OF EMPIRICAL RHEOLOGICAL DATA FOR USE IN COMPOSITION CONTROL OF MULTICOMPONENT FOODSTUFFS.

PubMed

Drake, Birger; Nádai, Béla

1970-03-01

An empirical measure of viscosity, which is often far from being a linear function of composition, was used together with refractive index to build up a function which bears a linear relationship to the composition of tomato paste-water-sucrose mixtures. The new function can be used directly for rapid composition control by linear vector-vector transformation.

Aeromagnetic gradient compensation method for helicopter based on ɛ-support vector regression algorithm

NASA Astrophysics Data System (ADS)

Wu, Peilin; Zhang, Qunying; Fei, Chunjiao; Fang, Guangyou

2017-04-01

Aeromagnetic gradients are typically measured by optically pumped magnetometers mounted on an aircraft. Any aircraft, particularly helicopters, produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is essential, and least square (LS) is the conventional method used for reducing interference levels. However, the LSs approach to solving the aeromagnetic interference model has a few difficulties, one of which is in handling multicollinearity. Therefore, we propose an aeromagnetic gradient compensation method, specifically targeted for helicopter use but applicable on any airborne platform, which is based on the ɛ-support vector regression algorithm. The structural risk minimization criterion intrinsic to the method avoids multicollinearity altogether. Local aeromagnetic anomalies can be retained, and platform-generated fields are suppressed simultaneously by constructing an appropriate loss function and kernel function. The method was tested using an unmanned helicopter and obtained improvement ratios of 12.7 and 3.5 in the vertical and horizontal gradient data, respectively. Both of these values are probably better than those that would have been obtained from the conventional method applied to the same data, had it been possible to do so in a suitable comparative context. The validity of the proposed method is demonstrated by the experimental result.

Lovelock vacua with a recurrent null vector field

NASA Astrophysics Data System (ADS)

Ortaggio, Marcello

2018-02-01

Vacuum solutions of Lovelock gravity in the presence of a recurrent null vector field (a subset of Kundt spacetimes) are studied. We first discuss the general field equations, which constrain both the base space and the profile functions. While choosing a "generic" base space puts stronger constraints on the profile, in special cases there also exist solutions containing arbitrary functions (at least for certain values of the coupling constants). These and other properties (such as the p p - waves subclass and the overlap with VSI, CSI and universal spacetimes) are subsequently analyzed in more detail in lower dimensions n =5 , 6 as well as for particular choices of the base manifold. The obtained solutions describe various classes of nonexpanding gravitational waves propagating, e.g., in Nariai-like backgrounds M2×Σn -2. An Appendix contains some results about general (i.e., not necessarily Kundt) Lovelock vacua of Riemann type III/N and of Weyl and traceless-Ricci type III/N. For example, it is pointed out that for theories admitting a triply degenerate maximally symmetric vacuum, all the (reduced) field equations are satisfied identically, giving rise to large classes of exact solutions.

Generalized decompositions of dynamic systems and vector Lyapunov functions

NASA Astrophysics Data System (ADS)

Ikeda, M.; Siljak, D. D.

1981-10-01

The notion of decomposition is generalized to provide more freedom in constructing vector Lyapunov functions for stability analysis of nonlinear dynamic systems. A generalized decomposition is defined as a disjoint decomposition of a system which is obtained by expanding the state-space of a given system. An inclusion principle is formulated for the solutions of the expansion to include the solutions of the original system, so that stability of the expansion implies stability of the original system. Stability of the expansion can then be established by standard disjoint decompositions and vector Lyapunov functions. The applicability of the new approach is demonstrated using the Lotka-Volterra equations.

Method for Household Refrigerators Efficiency Increasing

NASA Astrophysics Data System (ADS)

Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.

2017-11-01

The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.

A vector autopilot system. [aircraft attitude determination with three-axis magnetometer

NASA Technical Reports Server (NTRS)

Pietila, R.; Dunn, W. R., Jr.

1976-01-01

Current technology has evolved low cost, highly reliable solid state vector magnetometers with excellent angular resolution. This paper discusses the role of a three-axis magnetometer as a new instrument for aircraft attitude determination. Using flight data acquired by an instrumented aircraft, attitude is calculated using the earth's magnetic field vector and compared to measured attitudes. The magnetic field alone is not adequate to resolve all attitude variations and the need for a second reference angle or vector is discussed. A system combining the functions of heading determination and attitude measurement is presented to show that both functions can be implemented with essentially the same component count required to measure heading alone. It is concluded that with the correlation achieved in calculated and measured attitude there is a potential application of vector magnetometry in attitude measurement systems.

The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2011-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

Poynting vector measurements of electromagnetic ion cyclotron waves in the plasmasphere

NASA Technical Reports Server (NTRS)

Labelle, J.; Treumann, R. A.

1992-01-01

Results are presented from an analysis of the June 6, 1985 Pc 2 measurements for which E, B, and delta-N were all analyzed. The event occurred in the duskside overlap region between the plasmaspheric bulge and the ion ring current. Results of the Poynting vector analysis of the R and L mode components show both of them to be characterized by northward Poynting vector, indicating energy flux away from the equator. The value of the Poynting vector was found to be about 3 microW/sq m.

Comparison of scoliosis measurements based on three-dimensional vertebra vectors and conventional two-dimensional measurements: advantages in evaluation of prognosis and surgical results.

PubMed

Illés, Tamás; Somoskeöy, Szabolcs

2013-06-01

A new concept of vertebra vectors based on spinal three-dimensional (3D) reconstructions of images from the EOS system, a new low-dose X-ray imaging device, was recently proposed to facilitate interpretation of EOS 3D data, especially with regard to horizontal plane images. This retrospective study was aimed at the evaluation of the spinal layout visualized by EOS 3D and vertebra vectors before and after surgical correction, the comparison of scoliotic spine measurement values based on 3D vertebra vectors with measurements using conventional two-dimensional (2D) methods, and an evaluation of horizontal plane vector parameters for their relationship with the magnitude of scoliotic deformity. 95 patients with adolescent idiopathic scoliosis operated according to the Cotrel-Dubousset principle were subjected to EOS X-ray examinations pre- and postoperatively, followed by 3D reconstructions and generation of vertebra vectors in a calibrated coordinate system to calculate vector coordinates and parameters, as published earlier. Differences in values of conventional 2D Cobb methods and methods based on vertebra vectors were evaluated by means comparison T test and relationship of corresponding parameters was analysed by bivariate correlation. Relationship of horizontal plane vector parameters with the magnitude of scoliotic deformities and results of surgical correction were analysed by Pearson correlation and linear regression. In comparison to manual 2D methods, a very close relationship was detectable in vertebra vector-based curvature data for coronal curves (preop r 0.950, postop r 0.935) and thoracic kyphosis (preop r 0.893, postop r 0.896), while the found small difference in L1-L5 lordosis values (preop r 0.763, postop r 0.809) was shown to be strongly related to the magnitude of corresponding L5 wedge. The correlation analysis results revealed strong correlation between the magnitude of scoliosis and the lateral translation of apical vertebra in horizontal plane. The horizontal plane coordinates of the terminal and initial points of apical vertebra vectors represent this (r 0.701; r 0.667). Less strong correlation was detected in the axial rotation of apical vertebras and the magnitudes of the frontal curves (r 0.459). Vertebra vectors provide a key opportunity to visualize spinal deformities in all three planes simultaneously. Measurement methods based on vertebral vectors proved to be just as accurate and reliable as conventional measurement methods for coronal and sagittal plane parameters. In addition, the horizontal plane display of the curves can be studied using the same vertebra vectors. Based on the vertebra vectors data, during the surgical treatment of spinal deformities, the diminution of the lateral translation of the vertebras seems to be more important in the results of the surgical correction than the correction of the axial rotation.

An Improved Brome mosaic virus Silencing Vector: Greater Insert Stability and More Extensive VIGS1[OPEN

PubMed Central

2018-01-01

Virus-induced gene silencing (VIGS) is used extensively for gene function studies in plants. VIGS is inexpensive and rapid compared with silencing conducted through stable transformation, but many virus-silencing vectors, especially in grasses, induce only transient silencing phenotypes. A major reason for transient phenotypes is the instability of the foreign gene fragment (insert) in the vector during VIGS. Here, we report the development of a Brome mosaic virus (BMV)-based vector that better maintains inserts through modification of the original BMV vector RNA sequence. Modification of the BMV RNA3 sequence yielded a vector, BMVCP5, that better maintained phytoene desaturase and heat shock protein70-1 (HSP70-1) inserts in Nicotiana benthamiana and maize (Zea mays). Longer maintenance of inserts was correlated with greater target gene silencing and more extensive visible silencing phenotypes displaying greater tissue penetration and involving more leaves. The modified vector accumulated similarly to the original vector in N. benthamiana after agroinfiltration, thus maintaining a high titer of virus in this intermediate host used to produce virus inoculum for grass hosts. For HSP70, silencing one family member led to a large increase in the expression of another family member, an increase likely related to the target gene knockdown and not a general effect of virus infection. The cause of the increased insert stability in the modified vector is discussed in relationship to its recombination and accumulation potential. The modified vector will improve functional genomic studies in grasses, and the conceptual methods used to improve the vector may be applied to other VIGS vectors. PMID:29127260

Robust support vector regression networks for function approximation with outliers.

PubMed

Chuang, Chen-Chia; Su, Shun-Feng; Jeng, Jin-Tsong; Hsiao, Chih-Ching

2002-01-01

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.

A Quantitative Method to Identify Lithology Beneath Cover

NASA Astrophysics Data System (ADS)

Gettings, M. E.

2008-12-01

Geophysical terranes (map areas of similar potential field data response) can be used in the estimation of geological map units beneath cover (bedrock, alluvium, or tectonic block). Potential field data over nearby bedrock terranes defines "candidate terranes". Geophysical anomaly dimensions, shapes, amplitudes, trends/structural grain, and fractal measures yield a vector of measures characterizing the terrane. To compare candidate terranes fields with those for covered areas, the effect of depth of cover must be taken into account. Gravity anomaly data yields depth estimates by which the aeromagnetic data of candidate terranes are then upward continued. Comparison of characteristics of the upward continued fields from the candidate terranes to those of covered areas rank the candidates. Because of signal loss in upward continuation and overlap of physical properties, the vectors of measures for the candidate terranes are usually not unique. Possibility theory offers a relatively objective and robust method that can be used to rank terrane types that includes uncertainty. The strategy is to prepare membership functions for each measure of each candidate terrane and the covered area, based on observed values and degree of knowledge, and then form the fuzzy-logical combination of these to estimate the possibility and its uncertainty for each candidate terrane. Membership functions include uncertainty by the degree of membership for various possibility values. With no other information, uncertainty is based on information content from survey specifications and geologic features dimensions. Geologic data can also be included, such as structural trends, proximity, and tectonic history. Little knowledge implies wide membership functions; perfect knowledge, a delta function. This and the combination rules in fuzzy logic yield a robust estimation method. An uncertain membership function of a characteristic contributes much less to the possibility than a precise one. The final result for each covered area is a ranked possibility function for each candidate terrane as the underlying bedrock of the covered area that honors the aeromagnetic field and the geologic constraints that have been included. An example of the application of this method is presented for an area in south central Arizona.

A transposase strategy for creating libraries of circularly permuted proteins.

PubMed

Mehta, Manan M; Liu, Shirley; Silberg, Jonathan J

2012-05-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions.

A transposase strategy for creating libraries of circularly permuted proteins

PubMed Central

Mehta, Manan M.; Liu, Shirley; Silberg, Jonathan J.

2012-01-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions. PMID:22319214

Lefschetz thimbles in fermionic effective models with repulsive vector-field

NASA Astrophysics Data System (ADS)

Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira

2018-06-01

We discuss two problems in complexified auxiliary fields in fermionic effective models, the auxiliary sign problem associated with the repulsive vector-field and the choice of the cut for the scalar field appearing from the logarithmic function. In the fermionic effective models with attractive scalar and repulsive vector-type interaction, the auxiliary scalar and vector fields appear in the path integral after the bosonization of fermion bilinears. When we make the path integral well-defined by the Wick rotation of the vector field, the oscillating Boltzmann weight appears in the partition function. This "auxiliary" sign problem can be solved by using the Lefschetz-thimble path-integral method, where the integration path is constructed in the complex plane. Another serious obstacle in the numerical construction of Lefschetz thimbles is caused by singular points and cuts induced by multivalued functions of the complexified scalar field in the momentum integration. We propose a new prescription which fixes gradient flow trajectories on the same Riemann sheet in the flow evolution by performing the momentum integration in the complex domain.

Delivery and evaluation of recombinant adeno-associated viral vectors in the equine distal extremity for the treatment of laminitis.

PubMed

Mason, J B; Gurda, B L; Van Wettere, A; Engiles, J B; Wilson, J M; Richardson, D W

2017-01-01

Our long-term aim is to develop a gene therapy approach for the prevention of laminitis in the contralateral foot of horses with major musculoskeletal injuries and non-weightbearing lameness. The goal of this study was to develop a practical method to efficiently deliver therapeutic proteins deep within the equine foot. Randomised in vivo experiment. We used recombinant adeno-associated viral vectors (rAAVs) to deliver marker genes using regional limb perfusion through the palmar digital artery of the horse. Vector serotypes rAAV2/1, 2/8 and 2/9 all successfully transduced equine foot tissues and displayed similar levels and patterns of transduction. The regional distribution of transduction within the foot decreased with decreasing vector dose. The highest transduction values were seen in the sole and coronary regions and the lowest transduction values were detected in the dorsal hoof-wall region. The use of a surfactant-enriched vector diluent increased regional distribution of the vector and improved the transduction in the hoof-wall region. The hoof-wall region of the foot, which exhibited the lowest levels of transduction using saline as the vector diluent, displayed a dramatic increase in transduction when surfactant was included in the vector diluent (9- to 81-fold increase). In transduced tissues, no significant difference was observed between promoters (chicken β-actin vs. cytomegalovirus) for gene expression. All horses tested for vector-neutralising antibodies were positive for serotype-specific neutralising antibodies to rAAV2/5. The current experiments demonstrate that transgenes can be successfully delivered to the equine distal extremity using rAAV vectors and that serotypes 2/8, 2/9 and 2/1 can successfully transduce tissues of the equine foot. When the vector was diluted with surfactant-containing saline, the level of transduction increased dramatically. The increased level of transduction due to the addition of surfactant also improved the distribution pattern of transduction. © 2015 EVJ Ltd.

Geographical distribution of reference value of aging people's left ventricular end systolic diameter based on the support vector regression.

PubMed

Han, Xiao; Ge, Miao; Dong, Jie; Xue, Ranying; Wang, Zixuan; He, Jinwei

2014-09-01

The aim of this paper is to analyze the geographical distribution of reference value of aging people's left ventricular end systolic diameter (LVDs), and to provide a scientific basis for clinical examination. The study is focus on the relationship between reference value of left ventricular end systolic diameter of aging people and 14 geographical factors, selecting 2495 samples of left ventricular end systolic diameter (LVDs) of aging people in 71 units of China, in which including 1620 men and 875 women. By using the Moran's I index to make sure the relationship between the reference values and spatial geographical factors, extracting 5 geographical factors which have significant correlation with left ventricular end systolic diameter for building the support vector regression, detecting by the method of paired sample t test to make sure the consistency between predicted and measured values, finally, makes the distribution map through the disjunctive kriging interpolation method and fits the three-dimensional trend of normal reference value. It is found that the correlation between the extracted geographical factors and the reference value of left ventricular end systolic diameter is quite significant, the 5 indexes respectively are latitude, annual mean air temperature, annual mean relative humidity, annual precipitation amount, annual range of air temperature, the predicted values and the observed ones are in good conformity, there is no significant difference at 95% degree of confidence. The overall trend of predicted values increases from west to east, increases first and then decreases from north to south. If geographical values are obtained in one region, the reference value of left ventricular end systolic diameter of aging people in this region can be obtained by using the support vector regression model. It could be more scientific to formulate the different distributions on the basis of synthesizing the physiological and the geographical factors. -Use Moran's index to analyze the spatial correlation. -Choose support vector machine to build model that overcome complexity of variables. -Test normal distribution of predicted data to guarantee the interpolation results. -Through trend analysis to explain the changes of reference value clearly. Copyright © 2014 Elsevier Inc. All rights reserved.

Analytic calculation of finite-population reproductive numbers for direct- and vector-transmitted diseases with homogeneous mixing.

PubMed

Keegan, Lindsay; Dushoff, Jonathan

2014-05-01

The basic reproductive number, R0, provides a foundation for evaluating how various factors affect the incidence of infectious diseases. Recently, it has been suggested that, particularly for vector-transmitted diseases, R0 should be modified to account for the effects of finite host population within a single disease transmission generation. Here, we use a transmission factor approach to calculate such "finite-population reproductive numbers," under the assumption of homogeneous mixing, for both vector-borne and directly transmitted diseases. In the case of vector-borne diseases, we estimate finite-population reproductive numbers for both host-to-host and vector-to-vector generations, assuming that the vector population is effectively infinite. We find simple, interpretable formulas for all three of these quantities. In the direct case, we find that finite-population reproductive numbers diverge from R0 before R0 reaches half of the population size. In the vector-transmitted case, we find that the host-to-host number diverges at even lower values of R0, while the vector-to-vector number diverges very little over realistic parameter ranges.

Preparation for a first-in-man lentivirus trial in patients with cystic fibrosis

PubMed Central

Alton, Eric W F W; Beekman, Jeffery M; Boyd, A Christopher; Brand, June; Carlon, Marianne S; Connolly, Mary M; Chan, Mario; Conlon, Sinead; Davidson, Heather E; Davies, Jane C; Davies, Lee A; Dekkers, Johanna F; Doherty, Ann; Gea-Sorli, Sabrina; Gill, Deborah R; Griesenbach, Uta; Hasegawa, Mamoru; Higgins, Tracy E; Hironaka, Takashi; Hyndman, Laura; McLachlan, Gerry; Inoue, Makoto; Hyde, Stephen C; Innes, J Alastair; Maher, Toby M; Moran, Caroline; Meng, Cuixiang; Paul-Smith, Michael C; Pringle, Ian A; Pytel, Kamila M; Rodriguez-Martinez, Andrea; Schmidt, Alexander C; Stevenson, Barbara J; Sumner-Jones, Stephanie G; Toshner, Richard; Tsugumine, Shu; Wasowicz, Marguerite W; Zhu, Jie

2017-01-01

We have recently shown that non-viral gene therapy can stabilise the decline of lung function in patients with cystic fibrosis (CF). However, the effect was modest, and more potent gene transfer agents are still required. Fuson protein (F)/Hemagglutinin/Neuraminidase protein (HN)-pseudotyped lentiviral vectors are more efficient for lung gene transfer than non-viral vectors in preclinical models. In preparation for a first-in-man CF trial using the lentiviral vector, we have undertaken key translational preclinical studies. Regulatory-compliant vectors carrying a range of promoter/enhancer elements were assessed in mice and human air–liquid interface (ALI) cultures to select the lead candidate; cystic fibrosis transmembrane conductance receptor (CFTR) expression and function were assessed in CF models using this lead candidate vector. Toxicity was assessed and ‘benchmarked’ against the leading non-viral formulation recently used in a Phase IIb clinical trial. Integration site profiles were mapped and transduction efficiency determined to inform clinical trial dose-ranging. The impact of pre-existing and acquired immunity against the vector and vector stability in several clinically relevant delivery devices was assessed. A hybrid promoter hybrid cytosine guanine dinucleotide (CpG)- free CMV enhancer/elongation factor 1 alpha promoter (hCEF) consisting of the elongation factor 1α promoter and the cytomegalovirus enhancer was most efficacious in both murine lungs and human ALI cultures (both at least 2-log orders above background). The efficacy (at least 14% of airway cells transduced), toxicity and integration site profile supports further progression towards clinical trial and pre-existing and acquired immune responses do not interfere with vector efficacy. The lead rSIV.F/HN candidate expresses functional CFTR and the vector retains 90–100% transduction efficiency in clinically relevant delivery devices. The data support the progression of the F/HN-pseudotyped lentiviral vector into a first-in-man CF trial in 2017. PMID:27852956

Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hualan; Price, Morgan N.; Waters, Robert Jordan

Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach for discovering the functions of bacterial genes. However, the development of a suitable TnSeq strategy for a given bacterium can be costly and time-consuming. To meet this challenge, we describe a part-based strategy for constructing libraries of hundreds of transposon delivery vectors, which we term “magic pools.” Within a magic pool, each transposon vector has a different combination of upstream sequences (promoters and ribosome binding sites) and antibiotic resistance markers as well as a random DNA barcode sequence, which allows the tracking of each vector during mutagenesis experiments. Tomore » identify an efficient vector for a given bacterium, we mutagenize it with a magic pool and sequence the resulting insertions; we then use this efficient vector to generate a large mutant library. We used the magic pool strategy to construct transposon mutant libraries in five genera of bacteria, including three genera of the phylumBacteroidetes. IMPORTANCEMolecular genetics is indispensable for interrogating the physiology of bacteria. However, the development of a functional genetic system for any given bacterium can be time-consuming. Here, we present a streamlined approach for identifying an effective transposon mutagenesis system for a new bacterium. Our strategy first involves the construction of hundreds of different transposon vector variants, which we term a “magic pool.” The efficacy of each vector in a magic pool is monitored in parallel using a unique DNA barcode that is introduced into each vector design. Using archived DNA “parts,” we next reassemble an effective vector for making a whole-genome transposon mutant library that is suitable for large-scale interrogation of gene function using competitive growth assays. Here, we demonstrate the utility of the magic pool system to make mutant libraries in five genera of bacteria.« less

Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

DOE PAGES

Liu, Hualan; Price, Morgan N.; Waters, Robert Jordan; ...

2018-01-16

Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach for discovering the functions of bacterial genes. However, the development of a suitable TnSeq strategy for a given bacterium can be costly and time-consuming. To meet this challenge, we describe a part-based strategy for constructing libraries of hundreds of transposon delivery vectors, which we term “magic pools.” Within a magic pool, each transposon vector has a different combination of upstream sequences (promoters and ribosome binding sites) and antibiotic resistance markers as well as a random DNA barcode sequence, which allows the tracking of each vector during mutagenesis experiments. Tomore » identify an efficient vector for a given bacterium, we mutagenize it with a magic pool and sequence the resulting insertions; we then use this efficient vector to generate a large mutant library. We used the magic pool strategy to construct transposon mutant libraries in five genera of bacteria, including three genera of the phylumBacteroidetes. IMPORTANCEMolecular genetics is indispensable for interrogating the physiology of bacteria. However, the development of a functional genetic system for any given bacterium can be time-consuming. Here, we present a streamlined approach for identifying an effective transposon mutagenesis system for a new bacterium. Our strategy first involves the construction of hundreds of different transposon vector variants, which we term a “magic pool.” The efficacy of each vector in a magic pool is monitored in parallel using a unique DNA barcode that is introduced into each vector design. Using archived DNA “parts,” we next reassemble an effective vector for making a whole-genome transposon mutant library that is suitable for large-scale interrogation of gene function using competitive growth assays. Here, we demonstrate the utility of the magic pool system to make mutant libraries in five genera of bacteria.« less

A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

NASA Astrophysics Data System (ADS)

Porwal, A.; Carranza, J.; Hale, M.

2004-12-01

A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

Statistical Theory of the Ideal MHD Geodynamo

NASA Technical Reports Server (NTRS)

Shebalin, J. V.

2012-01-01

A statistical theory of geodynamo action is developed, using a mathematical model of the geodynamo as a rotating outer core containing an ideal (i.e., no dissipation), incompressible, turbulent, convecting magnetofluid. On the concentric inner and outer spherical bounding surfaces the normal components of the velocity, magnetic field, vorticity and electric current are zero, as is the temperature fluctuation. This allows the use of a set of Galerkin expansion functions that are common to both velocity and magnetic field, as well as vorticity, current and the temperature fluctuation. The resulting dynamical system, based on the Boussinesq form of the magnetohydrodynamic (MHD) equations, represents MHD turbulence in a spherical domain. These basic equations (minus the temperature equation) and boundary conditions have been used previously in numerical simulations of forced, decaying MHD turbulence inside a sphere [1,2]. Here, the ideal case is studied through statistical analysis and leads to a prediction that an ideal coherent structure will be found in the form of a large-scale quasistationary magnetic field that results from broken ergodicity, an effect that has been previously studied both analytically and numerically for homogeneous MHD turbulence [3,4]. The axial dipole component becomes prominent when there is a relatively large magnetic helicity (proportional to the global correlation of magnetic vector potential and magnetic field) and a stationary, nonzero cross helicity (proportional to the global correlation of velocity and magnetic field). The expected angle of the dipole moment vector with respect to the rotation axis is found to decrease to a minimum as the average cross helicity increases for a fixed value of magnetic helicity and then to increase again when average cross helicity approaches its maximum possible value. Only a relatively small value of cross helicity is needed to produce a dipole moment vector that is aligned at approx.10deg with the rotation axis.

Kny Coupling Constants and Form Factors from the Chiral Bag Model

NASA Astrophysics Data System (ADS)

Jeong, M. T.; Cheon, Il-T.

2000-09-01

The form factors and coupling constants for KNΛ and KNΣ interactions have been calculated in the framework of the Chiral Bag Model with vector mesons. Taking into account vector meson (ρ, ω, K*) field effects, we find -3.88 ≤ gKNΛ ≤ -3.67 and 1.15 ≤ gKNΣ ≤ 1.24, where the quark-meson coupling constants are determined by fitting the renormalized, πNN coupling constant, [gπNN(0)]2/4π = 14.3. It is shown that vector mesons make significant contributions to the coupling constants gKNΛ and gKNΣ. Our values are existing within the experimental limits compared to the phenomenological values extracted from the kaon photo production experiments.

Fuzzy scalar and vector median filters based on fuzzy distances.

PubMed

Chatzis, V; Pitas, I

1999-01-01

In this paper, the fuzzy scalar median (FSM) is proposed, defined by using ordering of fuzzy numbers based on fuzzy minimum and maximum operations defined by using the extension principle. Alternatively, the FSM is defined from the minimization of a fuzzy distance measure, and the equivalence of the two definitions is proven. Then, the fuzzy vector median (FVM) is proposed as an extension of vector median, based on a novel distance definition of fuzzy vectors, which satisfy the property of angle decomposition. By defining properly the fuzziness of a value, the combination of the basic properties of the classical scalar and vector median (VM) filter with other desirable characteristics can be succeeded.

[Identification of varieties of cashmere by Vis/NIR spectroscopy technology based on PCA-SVM].

PubMed

Wu, Gui-Fang; He, Yong

2009-06-01

One mixed algorithm was presented to discriminate cashmere varieties with principal component analysis (PCA) and support vector machine (SVM). Cashmere fiber has such characteristics as threadlike, softness, glossiness and high tensile strength. The quality characters and economic value of each breed of cashmere are very different. In order to safeguard the consumer's rights and guarantee the quality of cashmere product, quickly, efficiently and correctly identifying cashmere has significant meaning to the production and transaction of cashmere material. The present research adopts Vis/NIRS spectroscopy diffuse techniques to collect the spectral data of cashmere. The near infrared fingerprint of cashmere was acquired by principal component analysis (PCA), and support vector machine (SVM) methods were used to further identify the cashmere material. The result of PCA indicated that the score map made by the scores of PC1, PC2 and PC3 was used, and 10 principal components (PCs) were selected as the input of support vector machine (SVM) based on the reliabilities of PCs of 99.99%. One hundred cashmere samples were used for calibration and the remaining 75 cashmere samples were used for validation. A one-against-all multi-class SVM model was built, the capabilities of SVM with different kernel function were comparatively analyzed, and the result showed that SVM possessing with the Gaussian kernel function has the best identification capabilities with the accuracy of 100%. This research indicated that the data mining method of PCA-SVM has a good identification effect, and can work as a new method for rapid identification of cashmere material varieties.

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Absorptive corrections for vector mesons: matching to complex mass scheme and longitudinal corrections

NASA Astrophysics Data System (ADS)

Jiménez Pérez, L. A.; Toledo Sánchez, G.

2017-12-01

Unstable spin-1 particles are properly described by including absorptive corrections to the electromagnetic vertex and propagator, without breaking the electromagnetic gauge invariance. We show that the modified propagator can be set in a complex mass form, provided the mass and width parameters, which are properly defined at the pole, are replaced by energy dependent functions fulfilling the same requirements at the pole. We exemplify the case for the {K}* (892) vector meson, and find that the mass function deviates around 2 MeV from the Kπ threshold to the pole, and that the width function exhibits a different behavior compared to the uncorrected energy dependent width. Considering the {τ }-\\to {K}{{S}}{π }-{ν }τ decay as dominated by the {K}* (892) and {K}{\\prime * }(1410) vectors and one scalar particle, we exhibit the role of the transversal and longitudinal corrections to the vector propagator by obtaining the modified vector and scalar form factors. The modified vector form factor is found to be the same as in the complex mass form, while the scalar form factor receives a modification from the longitudinal correction to the vector propagator. A fit to the experimental Kπ spectrum shows that the phase induced by the presence of this new contribution in the scalar sector improves the description of the experimental data in the troublesome region around 0.7 GeV. Besides that, the correction to the scalar form factor is found to be negligible.

Closed-form integrator for the quaternion (euler angle) kinematics equations

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A. (Inventor)

2000-01-01

The invention is embodied in a method of integrating kinematics equations for updating a set of vehicle attitude angles of a vehicle using 3-dimensional angular velocities of the vehicle, which includes computing an integrating factor matrix from quantities corresponding to the 3-dimensional angular velocities, computing a total integrated angular rate from the quantities corresponding to a 3-dimensional angular velocities, computing a state transition matrix as a sum of (a) a first complementary function of the total integrated angular rate and (b) the integrating factor matrix multiplied by a second complementary function of the total integrated angular rate, and updating the set of vehicle attitude angles using the state transition matrix. Preferably, the method further includes computing a quanternion vector from the quantities corresponding to the 3-dimensional angular velocities, in which case the updating of the set of vehicle attitude angles using the state transition matrix is carried out by (a) updating the quanternion vector by multiplying the quanternion vector by the state transition matrix to produce an updated quanternion vector and (b) computing an updated set of vehicle attitude angles from the updated quanternion vector. The first and second trigonometric functions are complementary, such as a sine and a cosine. The quantities corresponding to the 3-dimensional angular velocities include respective averages of the 3-dimensional angular velocities over plural time frames. The updating of the quanternion vector preserves the norm of the vector, whereby the updated set of vehicle attitude angles are virtually error-free.

Receptor-mediated gene transfer vectors: progress towards genetic pharmaceuticals.

PubMed

Molas, M; Gómez-Valadés, A G; Vidal-Alabró, A; Miguel-Turu, M; Bermudez, J; Bartrons, R; Perales, J C

2003-10-01

Although specific delivery to tissues and unique cell types in vivo has been demonstrated for many non-viral vectors, current methods are still inadequate for human applications, mainly because of limitations on their efficiencies. All the steps required for an efficient receptor-mediated gene transfer process may in principle be exploited to enhance targeted gene delivery. These steps are: DNA/vector binding, internalization, subcellular trafficking, vesicular escape, nuclear import, and unpacking either for transcription or other functions (i.e., antisense, RNA interference, etc.). The large variety of vector designs that are currently available, usually aimed at improving the efficiency of these steps, has complicated the evaluation of data obtained from specific derivatives of such vectors. The importance of the structure of the final vector and the consequences of design decisions at specific steps on the overall efficiency of the vector will be discussed in detail. We emphasize in this review that stability in serum and thus, proper bioavailability of vectors to their specific receptors may be the single greatest limiting factor on the overall gene transfer efficiency in vivo. We discuss current approaches to overcome the intrinsic instability of synthetic vectors in the blood. In this regard, a summary of the structural features of the vectors obtained from current protocols will be presented and their functional characteristics evaluated. Dissecting information on molecular conjugates obtained by such methodologies, when carefully evaluated, should provide important guidelines for the creation of effective, targeted and safe DNA therapeutics.

The simulation on diode-clamped five-level converters common-mode voltage suppression with zero-vector PWM strategy

NASA Astrophysics Data System (ADS)

Zhang, Yonggao; Gao, Yanli; Long, Lizhong

2012-04-01

More and more researchers have great concern on the issue of Common-mode voltage (CMV) in high voltage large power converter. A novel common-mode voltage suppression scheme based on zero-vector PWM strategy (ZVPWM) is present in this paper. Taking a diode-clamped five-level converter as example, the principle of zero vector PWM common-mode voltage (ZCMVPWM) suppression method is studied in detail. ZCMVPWM suppression strategy is including four important parts, which are locating the sector of reference voltage vector, locating the small triangular sub-sector of reference voltage vector, reference vector synthesis, and calculating the operating time of vector. The principles of four important pars are illustrated in detail and the corresponding MATLAB models are established. System simulation and experimental results are provided. It gives some consultation value for the development and research of multi-level converters.

Vector and Axial-Vector Correlators in AN Instanton-Like Quark Model

NASA Astrophysics Data System (ADS)

Dorokhov, Alexander E.

The behavior of the vector Adler function at spacelike momenta is studied in the framework of a covariant chiral quark model with instanton-like quark-quark interaction. This function describes the transition between the high energy asymptotically free region of almost massless current quarks to the low energy hadronized regime with massive constituent quarks. The model reproduces the Adler function and V-A correlator extracted from the ALEPH and OPAL data on hadronic τ lepton decays, transformed into the Euclidean domain via dispersion relations. The leading order contribution from hadronic part of the photon vacuum polarization to the anomalous magnetic moment of the muon, aμ hvp(1), is estimated.

Improved Saturated Hydraulic Conductivity Pedotransfer Functions Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Araya, S. N.; Ghezzehei, T. A.

2017-12-01

Saturated hydraulic conductivity (Ks) is one of the fundamental hydraulic properties of soils. Its measurement, however, is cumbersome and instead pedotransfer functions (PTFs) are often used to estimate it. Despite a lot of progress over the years, generic PTFs that estimate hydraulic conductivity generally don't have a good performance. We develop significantly improved PTFs by applying state of the art machine learning techniques coupled with high-performance computing on a large database of over 20,000 soils—USKSAT and the Florida Soil Characterization databases. We compared the performance of four machine learning algorithms (k-nearest neighbors, gradient boosted model, support vector machine, and relevance vector machine) and evaluated the relative importance of several soil properties in explaining Ks. An attempt is also made to better account for soil structural properties; we evaluated the importance of variables derived from transformations of soil water retention characteristics and other soil properties. The gradient boosted models gave the best performance with root mean square errors less than 0.7 and mean errors in the order of 0.01 on a log scale of Ks [cm/h]. The effective particle size, D10, was found to be the single most important predictor. Other important predictors included percent clay, bulk density, organic carbon percent, coefficient of uniformity and values derived from water retention characteristics. Model performances were consistently better for Ks values greater than 10 cm/h. This study maximizes the extraction of information from a large database to develop generic machine learning based PTFs to estimate Ks. The study also evaluates the importance of various soil properties and their transformations in explaining Ks.

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

A component compensation method for magnetic interferential field

NASA Astrophysics Data System (ADS)

Zhang, Qi; Wan, Chengbiao; Pan, Mengchun; Liu, Zhongyan; Sun, Xiaoyong

2017-04-01

A new component searching with scalar restriction method (CSSRM) is proposed for magnetometer to compensate magnetic interferential field caused by ferromagnetic material of platform and improve measurement performance. In CSSRM, the objection function for parameter estimation is to minimize magnetic field (components and magnitude) difference between its measurement value and reference value. Two scalar compensation method is compared with CSSRM and the simulation results indicate that CSSRM can estimate all interferential parameters and external magnetic field vector with high accuracy. The magnetic field magnitude and components, compensated with CSSRM, coincide with true value very well. Experiment is carried out for a tri-axial fluxgate magnetometer, mounted in a measurement system with inertial sensors together. After compensation, error standard deviation of both magnetic field components and magnitude are reduced from more than thousands nT to less than 20 nT. It suggests that CSSRM provides an effective way to improve performance of magnetic interferential field compensation.

Higher-dimensional Wannier functions of multiparameter Hamiltonians

NASA Astrophysics Data System (ADS)

Hanke, Jan-Philipp; Freimuth, Frank; Blügel, Stefan; Mokrousov, Yuriy

2015-05-01

When using Wannier functions to study the electronic structure of multiparameter Hamiltonians H(k ,λ ) carrying a dependence on crystal momentum k and an additional periodic parameter λ , one usually constructs several sets of Wannier functions for a set of values of λ . We present the concept of higher-dimensional Wannier functions (HDWFs), which provide a minimal and accurate description of the electronic structure of multiparameter Hamiltonians based on a single set of HDWFs. The obstacle of nonorthogonality of Bloch functions at different λ is overcome by introducing an auxiliary real space, which is reciprocal to the parameter λ . We derive a generalized interpolation scheme and emphasize the essential conceptual and computational simplifications in using the formalism, for instance, in the evaluation of linear response coefficients. We further implement the necessary machinery to construct HDWFs from ab initio within the full potential linearized augmented plane-wave method (FLAPW). We apply our implementation to accurately interpolate the Hamiltonian of a one-dimensional magnetic chain of Mn atoms in two important cases of λ : (i) the spin-spiral vector q and (ii) the direction of the ferromagnetic magnetization m ̂. Using the generalized interpolation of the energy, we extract the corresponding values of magnetocrystalline anisotropy energy, Heisenberg exchange constants, and spin stiffness, which compare very well with the values obtained from direct first principles calculations. For toy models we demonstrate that the method of HDWFs can also be used in applications such as the virtual crystal approximation, ferroelectric polarization, and spin torques.

Which nanowire couples better electrically to a metal contact: Armchair or zigzag nanotube?

NASA Technical Reports Server (NTRS)

Anantram, M. P.; Biegel, Bryan (Technical Monitor)

2001-01-01

The fundamental question of how chirality affects tile electronic coupling of a nanotube to metal contacts is important for tile application of nanotubes as nanowires. We show that metallic-zigzag nanotubes are superior to armchair nanotubes as nanowires, by modeling the metal-nanotube interface. More specifically, we show that as a function of coupling strength, the total electron transmission of armchair nanotubes increases and tends to be pinned close to unity for a metal with Fermi wave vector close to that of gold. In contrast, the transmission probability of zigzag nanotubes increases to the maximum possible value of two. The origin of these effects lies in the details of the wave function, which is explained.

Nucleon form factors from quenched lattice QCD with domain wall fermions

NASA Astrophysics Data System (ADS)

Sasaki, Shoichi; Yamazaki, Takeshi

2008-07-01

We present a quenched lattice calculation of the weak nucleon form factors: vector [FV(q2)], induced tensor [FT(q2)], axial vector [FA(q2)] and induced pseudoscalar [FP(q2)] form factors. Our simulations are performed on three different lattice sizes L3×T=243×32, 163×32, and 123×32 with a lattice cutoff of a-1≈1.3GeV and light quark masses down to about 1/4 the strange quark mass (mπ≈390MeV) using a combination of the DBW2 gauge action and domain wall fermions. The physical volume of our largest lattice is about (3.6fm)3, where the finite volume effects on form factors become negligible and the lower momentum transfers (q2≈0.1GeV2) are accessible. The q2 dependences of form factors in the low q2 region are examined. It is found that the vector, induced tensor, and axial-vector form factors are well described by the dipole form, while the induced pseudoscalar form factor is consistent with pion-pole dominance. We obtain the ratio of axial to vector coupling gA/gV=FA(0)/FV(0)=1.219(38) and the pseudoscalar coupling gP=mμFP(0.88mμ2)=8.15(54), where the errors are statistical errors only. These values agree with experimental values from neutron β decay and muon capture on the proton. However, the root mean-squared radii of the vector, induced tensor, and axial vector underestimate the known experimental values by about 20%. We also calculate the pseudoscalar nucleon matrix element in order to verify the axial Ward-Takahashi identity in terms of the nucleon matrix elements, which may be called as the generalized Goldberger-Treiman relation.

Stokes polarimetry using analysis of the nonlinear voltage-retardance relationship for liquid-crystal variable retarders

DOE Office of Scientific and Technical Information (OSTI.GOV)

López-Téllez, J. M., E-mail: jmlopez@comunidad.unam.mx; Bruce, N. C.

2014-03-15

We present a method for using liquid-crystal variable retarders (LCVR’s) with continually varying voltage to measure the Stokes vector of a light beam. The LCVR's are usually employed with fixed retardance values due to the nonlinear voltage-retardance behavior that they show. The nonlinear voltage-retardance relationship is first measured and then a linear fit of the known retardance terms to the detected signal is performed. We use known waveplates (half-wave and quarter-wave) as devices to provide controlled polarization states to the Stokes polarimeter and we use the measured Stokes parameters as functions of the orientation of the axes of the waveplatesmore » as an indication of the quality of the polarimeter. Results are compared to a Fourier analysis method that does not take into account the nonlinear voltage-retardance relationship and also to a Fourier analysis method that uses experimental voltage values to give a linear retardance function with time. Also, we present results of simulations for comparison.« less

An Improved Brome mosaic virus Silencing Vector: Greater Insert Stability and More Extensive VIGS.

PubMed

Ding, Xin Shun; Mannas, Stephen W; Bishop, Bethany A; Rao, Xiaolan; Lecoultre, Mitchell; Kwon, Soonil; Nelson, Richard S

2018-01-01

Virus-induced gene silencing (VIGS) is used extensively for gene function studies in plants. VIGS is inexpensive and rapid compared with silencing conducted through stable transformation, but many virus-silencing vectors, especially in grasses, induce only transient silencing phenotypes. A major reason for transient phenotypes is the instability of the foreign gene fragment (insert) in the vector during VIGS. Here, we report the development of a Brome mosaic virus (BMV)-based vector that better maintains inserts through modification of the original BMV vector RNA sequence. Modification of the BMV RNA3 sequence yielded a vector, BMVCP5, that better maintained phytoene desaturase and heat shock protein70-1 ( HSP70-1 ) inserts in Nicotiana benthamiana and maize ( Zea mays ). Longer maintenance of inserts was correlated with greater target gene silencing and more extensive visible silencing phenotypes displaying greater tissue penetration and involving more leaves. The modified vector accumulated similarly to the original vector in N. benthamiana after agroinfiltration, thus maintaining a high titer of virus in this intermediate host used to produce virus inoculum for grass hosts. For HSP70 , silencing one family member led to a large increase in the expression of another family member, an increase likely related to the target gene knockdown and not a general effect of virus infection. The cause of the increased insert stability in the modified vector is discussed in relationship to its recombination and accumulation potential. The modified vector will improve functional genomic studies in grasses, and the conceptual methods used to improve the vector may be applied to other VIGS vectors. © 2018 American Society of Plant Biologists. All Rights Reserved.

Optical implementation of inner product neural associative memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor)

1995-01-01

An optical implementation of an inner-product neural associative memory is realized with a first spatial light modulator for entering an initial two-dimensional N-tuple vector and for entering a thresholded output vector image after each iteration until convergence is reached, and a second spatial light modulator for entering M weighted vectors of inner-product scalars multiplied with each of the M stored vectors, where the inner-product scalars are produced by multiplication of the initial input vector in the first iterative cycle (and thresholded vectors in subsequent iterative cycles) with each of the M stored vectors, and the weighted vectors are produced by multiplication of the scalars with corresponding ones of the stored vectors. A Hughes liquid crystal light valve is used for the dual function of summing the weighted vectors and thresholding the sum vector. The thresholded vector is then entered through the first spatial light modulator for reiteration of the process cycle until convergence is reached.

Quantization of Electromagnetic Fields in Cavities

NASA Technical Reports Server (NTRS)

Kakazu, Kiyotaka; Oshiro, Kazunori

1996-01-01

A quantization procedure for the electromagnetic field in a rectangular cavity with perfect conductor walls is presented, where a decomposition formula of the field plays an essential role. All vector mode functions are obtained by using the decomposition. After expanding the field in terms of the vector mode functions, we get the quantized electromagnetic Hamiltonian.

Amiloride-enhanced gene transfection of octa-arginine functionalized calcium phosphate nanoparticles.

PubMed

Vanegas Sáenz, Juan Ramón; Tenkumo, Taichi; Kamano, Yuya; Egusa, Hiroshi; Sasaki, Keiichi

2017-01-01

Nanoparticles represent promising gene delivery systems in biomedicine to facilitate prolonged gene expression with low toxicity compared to viral vectors. Specifically, nanoparticles of calcium phosphate (nCaP), the main inorganic component of human bone, exhibit high biocompatibility and good biodegradability and have been reported to have high affinity for protein or DNA, having thus been used as gene transfer vectors. On the other hand, Octa-arginine (R8), which has a high permeability to cell membrane, has been reported to improve intracellular delivery systems. Here, we present an optimized method for nCaP-mediated gene delivery using an octa-arginine (R8)-functionalized nCaP vector containing a marker or functional gene construct. nCaP particle size was between 220-580 nm in diameter and all R8-functionalized nCaPs carried a positive charge. R8 concentration significantly improved nCaP transfection efficiency with high cell compatibility in human mesenchymal stem cells (hMSC) and human osteoblasts (hOB) in particular, suggesting nCaPs as a good option for non-viral vector gene delivery. Furthermore, pre-treatment with different endocytosis inhibitors identified that the endocytic pathway differed among cell lines and functionalized nanoparticles, with amiloride increasing transfection efficiency of R8-functionalized nCaPs in hMSC and hOB.

Adenovirus Vectors Target Several Cell Subtypes of Mammalian Inner Ear In Vivo

PubMed Central

Li, Wenyan; Shen, Jun

2016-01-01

Mammalian inner ear harbors diverse cell types that are essential for hearing and balance. Adenovirus is one of the major vectors to deliver genes into the inner ear for functional studies and hair cell regeneration. To identify adenovirus vectors that target specific cell subtypes in the inner ear, we studied three adenovirus vectors, carrying a reporter gene encoding green fluorescent protein (GFP) from two vendors or with a genome editing gene Cre recombinase (Cre), by injection into postnatal days 0 (P0) and 4 (P4) mouse cochlea through scala media by cochleostomy in vivo. We found three adenovirus vectors transduced mouse inner ear cells with different specificities and expression levels, depending on the type of adenoviral vectors and the age of mice. The most frequently targeted region was the cochlear sensory epithelium, including auditory hair cells and supporting cells. Adenovirus with GFP transduced utricular supporting cells as well. This study shows that adenovirus vectors are capable of efficiently and specifically transducing different cell types in the mammalian inner ear and provides useful tools to study inner ear gene function and to evaluate gene therapy to treat hearing loss and vestibular dysfunction. PMID:28116172

Near-Wall Velocity Field Measurements of a Very Low Momentum Flux Transverse Jet

DTIC Science & Technology

2014-06-01

nozzle was used to generate olive oil droplets approximately 1 μm in diameter with approximately 20 particles per 32 x 32 px interrogation region...pair, two for each window size, 64 x 64 px and 32 x 32 px. Vectors with cross-correlation peak ratios Q < 1.7 were eliminated and replaced with a... vector whose value was interpolated by using values of its nearest neighbors. III. Results and Discussion A total of five momentum flux ratios were

Why do people move? Enhancing human mobility prediction using local functions based on public records and SNS data

PubMed Central

Park, Juyong

2018-01-01

The quality of life for people in urban regions can be improved by predicting urban human mobility and adjusting urban planning accordingly. In this study, we compared several possible variables to verify whether a gravity model (a human mobility prediction model borrowed from Newtonian mechanics) worked as well in inner-city regions as it did in intra-city regions. We reviewed the resident population, the number of employees, and the number of SNS posts as variables for generating mass values for an urban traffic gravity model. We also compared the straight-line distance, travel distance, and the impact of time as possible distance values. We defined the functions of urban regions on the basis of public records and SNS data to reflect the diverse social factors in urban regions. In this process, we conducted a dimension reduction method for the public record data and used a machine learning-based clustering algorithm for the SNS data. In doing so, we found that functional distance could be defined as the Euclidean distance between social function vectors in urban regions. Finally, we examined whether the functional distance was a variable that had a significant impact on urban human mobility. PMID:29432440

MATHEMATICAL ROUTINES FOR ENGINEERS AND SCIENTISTS

NASA Technical Reports Server (NTRS)

Kantak, A. V.

1994-01-01

The purpose of this package is to provide the scientific and engineering community with a library of programs useful for performing routine mathematical manipulations. This collection of programs will enable scientists to concentrate on their work without having to write their own routines for solving common problems, thus saving considerable amounts of time. This package contains sixteen subroutines. Each is separately documented with descriptions of the invoking subroutine call, its required parameters, and a sample test program. The functions available include: maxima, minima, and sort of vectors; factorials; random number generator (uniform or Gaussian distribution); complimentary error function; fast Fourier Transformation; Simpson's Rule integration; matrix determinate and inversion; Bessel function (J Bessel function for any order, and modified Bessel function for zero order); roots of a polynomial; roots of non-linear equation; and the solution of first order ordinary differential equations using Hamming's predictor-corrector method. There is also a subroutine for using a dot matrix printer to plot a given set of y values for a uniformly increasing x value. This package is written in FORTRAN 77 (Super Soft Small System FORTRAN compiler) for batch execution and has been implemented on the IBM PC computer series under MS-DOS with a central memory requirement of approximately 28K of 8 bit bytes for all subroutines. This program was developed in 1986.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

Larvicidal activity of Morinda citrifolia L. (Noni) (Family: Rubiaceae) leaf extract against Anopheles stephensi, Culex quinquefasciatus, and Aedes aegypti.

PubMed

Kovendan, Kalimuthu; Murugan, Kadarkarai; Shanthakumar, Shanmugam Perumal; Vincent, Savariar; Hwang, Jiang-Shiou

2012-10-01

Morinda citrifolia leaf extract was tested for larvicidal activity against three medically important mosquito vectors such as malarial vector Anopheles stephensi, dengue vector Aedes aegypti, and filarial vector Culex quinquefasciatus. The plant material was shade dried at room temperature and powdered coarsely. From the leaf, 1-kg powder was macerated with 3.0 L of hexane, chloroform, acetone, methanol, and water sequentially for a period of 72 h each and filtered. The yield of extracts was hexane (13.56 g), chloroform (15.21 g), acetone (12.85 g), methanol (14.76 g), and water (12.92 g), respectively. The extracts were concentrated at reduced temperature on a rotary vacuum evaporator and stored at a temperature of 4°C. The M. citrifolia leaf extract at 200, 300, 400, 500, and 600 ppm caused a significant mortality of three mosquito species. Hexane, chloroform, acetone, and water caused moderate considerable mortality; however, the highest larval mortality was methanolic extract, observed in three mosquito vectors. The larval mortality was observed after 24-h exposure. No mortality was observed in the control. The third larvae of Anopheles stephensi had values of LC(50) = 345.10, 324.26, 299.97, 261.96, and 284.59 ppm and LC(90) = 653.00, 626.58, 571.89, 505.06, and 549.51 ppm, respectively. The Aedes aegypti had values of LC(50) = 361.75, 343.22, 315.40, 277.92, and 306.98 ppm and LC(90) = 687.39, 659.02, 611.35, 568.18, and 613.25 ppm, respectively. The Culex quinquefasciatus had values of LC(50) = 382.96, 369.85, 344.34, 330.42, and 324.64 ppm and LC(90) = 726.18, 706.57, 669.28, 619.63, and 644.47 ppm, respectively. The results of the leaf extract of M. citrifolia are promising as good larvicidal activity against the mosquito vector Anopheles stephensi, Aedes aegypti, and Culex quinquefasciatus. This is a new eco-friendly approach for the control of vector control programs. Therefore, this study provides first report on the larvicidal activities against three species of mosquito vectors of this plant extracts from India.

Quasi-local action of curl-less vector potential on vortex dynamics in superconductors

NASA Astrophysics Data System (ADS)

Gulian, Armen M.; Nikoghosyan, Vahan R.; Gulian, Ellen D.; Melkonyan, Gurgen G.

2018-04-01

Studies of the Abrikosov vortex motion in superconductors based on time-dependent Ginzburg-Landau equations reveal an opportunity to detect the values of the Aharonov-Bohm type curl-less vector potentials without closed-loop electron trajectories encompassing the magnetic flux.

Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).

PubMed

Poil, S-S; Bollmann, S; Ghisleni, C; O'Gorman, R L; Klaver, P; Ball, J; Eich-Höchli, D; Brandeis, D; Michels, L

2014-08-01

Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification. This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value. ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers. Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood. Spectral biomarkers may have both diagnostic and prognostic value. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Transformation to equivalent dimensions—a new methodology to study earthquake clustering

NASA Astrophysics Data System (ADS)

Lasocki, Stanislaw

2014-05-01

A seismic event is represented by a point in a parameter space, quantified by the vector of parameter values. Studies of earthquake clustering involve considering distances between such points in multidimensional spaces. However, the metrics of earthquake parameters are different, hence the metric in a multidimensional parameter space cannot be readily defined. The present paper proposes a solution of this metric problem based on a concept of probabilistic equivalence of earthquake parameters. Under this concept the lengths of parameter intervals are equivalent if the probability for earthquakes to take values from either interval is the same. Earthquake clustering is studied in an equivalent rather than the original dimensions space, where the equivalent dimension (ED) of a parameter is its cumulative distribution function. All transformed parameters are of linear scale in [0, 1] interval and the distance between earthquakes represented by vectors in any ED space is Euclidean. The unknown, in general, cumulative distributions of earthquake parameters are estimated from earthquake catalogues by means of the model-free non-parametric kernel estimation method. Potential of the transformation to EDs is illustrated by two examples of use: to find hierarchically closest neighbours in time-space and to assess temporal variations of earthquake clustering in a specific 4-D phase space.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Surveillance of hemodialysis vascular access with ultrasound vector flow imaging

NASA Astrophysics Data System (ADS)

Brandt, Andreas H.; Olesen, Jacob B.; Hansen, Kristoffer L.; Rix, Marianne; Jensen, Jørgen A.; Nielsen, Michael B.

2015-03-01

The aim of this study was prospectively to monitor the volume flow in patients with arteriovenous fistula (AVF) with the angle independent ultrasound technique Vector Flow Imaging (VFI). Volume flow values were compared with Ultrasound dilution technique (UDT). Hemodialysis patients need a well-functioning vascular access with as few complications as possible and preferred vascular access is an AVF. Dysfunction due to stenosis is a common complication, and regular monitoring of volume flow is recommended to preserve AVF patency. UDT is considered the gold standard for volume flow surveillance, but VFI has proven to be more precise, when performing single repeated instantaneous measurements. Three patients with AVF were monitored with UDT and VFI monthly for five months. A commercial ultrasound scanner with a 9 MHz linear array transducer with integrated VFI was used to obtain data. UDT values were obtained with Transonic HD03 Flow-QC Hemodialysis Monitor. Three independent measurements at each scan session were obtained with UDT and VFI each month. Average deviation of volume flow between UDT and VFI was 25.7 % (Cl: 16.7% to 34.7%) (p= 0.73). The standard deviation for all patients, calculated from the mean variance of each individual scan sessions, was 199.8 ml/min for UDT and 47.6 ml/min for VFI (p = 0.002). VFI volume flow values were not significantly different from the corresponding estimates obtained using UDT, and VFI measurements were more precise than UDT. The study indicates that VFI can be used for surveillance of volume flow.

Fast software-based volume rendering using multimedia instructions on PC platforms and its application to virtual endoscopy

NASA Astrophysics Data System (ADS)

Mori, Kensaku; Suenaga, Yasuhito; Toriwaki, Jun-ichiro

2003-05-01

This paper describes a software-based fast volume rendering (VolR) method on a PC platform by using multimedia instructions, such as SIMD instructions, which are currently available in PCs' CPUs. This method achieves fast rendering speed through highly optimizing software rather than an improved rendering algorithm. In volume rendering using a ray casting method, the system requires fast execution of the following processes: (a) interpolation of voxel or color values at sample points, (b) computation of normal vectors (gray-level gradient vectors), (c) calculation of shaded values obtained by dot-products of normal vectors and light source direction vectors, (d) memory access to a huge area, and (e) efficient ray skipping at translucent regions. The proposed software implements these fundamental processes in volume rending by using special instruction sets for multimedia processing. The proposed software can generate virtual endoscopic images of a 3-D volume of 512x512x489 voxel size by volume rendering with perspective projection, specular reflection, and on-the-fly normal vector computation on a conventional PC without any special hardware at thirteen frames per second. Semi-translucent display is also possible.

The O(3P) and N(4S) density measurement at 225 km by ultraviolet absorption and fluorescence in the Apollo-Soyuz test project

NASA Technical Reports Server (NTRS)

Kaufman, F.; Rawling, W. T.; Donahue, T. M.; Anderson, J. G.; Hudson, R. D.

1976-01-01

The densities of O(3P) and N(4S) at 225 km were determined during the Apollo Soyuz Test Project by a resonance absorption/fluorescence technique in which OI and NI line radiation produced and collimated on board the Apollo was reflected from the Soyuz back to the Apollo for spectral analysis. The two spacecraft maneuvered so that a range of observation angles of plus or minus 15 deg with respect to the normal to the orbital velocity vector was scanned. The measurements were made at night on two consecutive orbits at spacecraft separations of 150 and 500 m. The resulting relative counting rates as function of observation angle were compared to calculated values to determine the oxygen value. This value agrees with mass spectrometric measurements made under similar conditions. The nitrogen value is in good agreement with other measurements and suggests a smaller diurnal variation than is predicted by present models.

Quantity, Revisited: An Object-Oriented Reusable Class

NASA Technical Reports Server (NTRS)

Funston, Monica Gayle; Gerstle, Walter; Panthaki, Malcolm

1998-01-01

"Quantity", a prototype implementation of an object-oriented class, was developed for two reasons: to help engineers and scientists manipulate the many types of quantities encountered during routine analysis, and to create a reusable software component to for large domain-specific applications. From being used as a stand-alone application to being incorporated into an existing computational mechanics toolkit, "Quantity" appears to be a useful and powerful object. "Quantity" has been designed to maintain the full engineering meaning of values with respect to units and coordinate systems. A value is a scalar, vector, tensor, or matrix, each of which is composed of Value Components, each of which may be an integer, floating point number, fuzzy number, etc., and its associated physical unit. Operations such as coordinate transformation and arithmetic operations are handled by member functions of "Quantity". The prototype has successfully tested such characteristics as maintaining a numeric value, an associated unit, and an annotation. In this paper we further explore the design of "Quantity", with particular attention to coordinate systems.

Nutrition Status Parameters and Hydration Status by Bioelectrical Impedance Vector Analysis Were Associated With Lung Function Impairment in Children and Adolescents With Cystic Fibrosis.

PubMed

Hauschild, Daniela Barbieri; Barbosa, Eliana; Moreira, Emilia Addison Machado; Ludwig Neto, Norberto; Platt, Vanessa Borges; Piacentini Filho, Eduardo; Wazlawik, Elisabeth; Moreno, Yara Maria Franco

2016-06-01

(1) To compare nutrition and hydration status between a group of children/adolescents with cystic fibrosis (CFG; n = 46; median age, 8.5 years) and a control group without cystic fibrosis (CG). (2) To examine the association of nutrition and hydration status with lung function in the CFG. A cross-sectional study. Nutrition screening, anthropometric parameters, and bioelectrical impedance analysis (BIA) were assessed. The z scores for body mass index for age, height for age, mid upper arm circumference, triceps and subscapular skinfold thickness, mid upper arm muscle area, resistance/height, and reactance/height were calculated. Bioelectrical impedance vector analysis was conducted. Forced expiratory volume in 1 second <80% was considered lung function impairment. An adjusted logistic regression was applied (P < .05). In the CFG, lung function impairment was observed in 51.1%. All anthropometric parameters were lower, and the mean z-resistance/height and z-reactance/height were higher in the CFG (P < .05) compared with the CG. In the CFG, 43% were severely/mildly dehydrated, while none were in the CG (P = .007). In the CFG, there was an association between high nutrition risk-via nutrition screening (odds ratio [OR], 22.28; P < .05), lower values of anthropometric parameters, higher z-resistance/height (OR, 2.23; P < .05) and z-reactance/height (OR, 1.81; P < .05), and dehydration (OR, 4.94; P < .05)-and lung function impairment. The CFG exhibited a compromised nutrition status assessed by anthropometric and BIA parameters. Nutrition screening, anthropometric and BIA parameters, and hydration status were associated with lung function. © 2016 American Society for Parenteral and Enteral Nutrition.

Modeling the human body shape in bioimpedance vector measurements.

PubMed

Kim, Chul-Hyun; Park, Jae-Hyeon; Kim, Hyeoijin; Chung, Sochung; Park, Seung-Hun

2010-01-01

Human body shape, called somatotype, has described physique of humans in health and sports applications, relating anthropometric measurements to fatness, muscularity and linearity in a structured way. Here we propose a new method based on bioelectric impedance vector analysis (BIVA) of R/H and Xc/H to represent the cross-sectional area and the body cell mass in a given surface area (m(2)) respectively. Data from six gymnasts, ten dancers, and five fashion models, groups whose physiques and BMI ranges were distinct from one another, were measured for somatotype and BIVA. The models had highest values of the R/H and gymnasts the lowest. Xc/H was lower in models than in the dancers and gymnasts (p < 0.05). Phase angle was lowest in the models and highest in gymnasts significantly (p < 0.05). Pattern analysis from BIVA corresponded to the calculated anthropometric somatotype supporting the hypothesis that BIA's resistance (R) and reactance (Xc) are meaningful discriminates of body size and function which relate to physique in a purposive way.

Long time, large scale properties of the noisy driven-diffusion equation

NASA Astrophysics Data System (ADS)

Prakash, J. Ravi; Bouchaud, J. P.; Edwards, S. F.

1994-07-01

We study the driven-diffusion equation, describing the dynamics of density fluctuations delta-rho(x-vector, t) in powders or traffic flows. We have performed quite detailed numerical simulations of this equation in one dimension, focusing in particular on the scaling behavior of the correlation function (delta-rho(x-vector, t)delta-rho(0, 0)). One of our motivations was to assess the validity of various theoretical approaches, such as Renormalization Group and different self consistent truncation schemes, to these nonlinear dynamical equations. Although all of them are seen to predict correctly the scaling exponents, only one of them (where the non-exponential nature of the relaxation is taken into account) is able to reproduce satisfactorily the value of the numerical prefactors. Several other interesting issues, such as the noise spectrum of the output current, or the statistics of distance between jams (showing a transition between a `laminar' regime for small noise to a `jammed' regime for higher noise) are also investigated.

Breast Cancer Detection with Reduced Feature Set.

PubMed

Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydin

2015-01-01

This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%-40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bemporad, G.A.; Rubin, H.

This manuscript concerns the onset of thermohaline convection in a solar pond subject to field conditions as well as a small scale laboratory test section simulating the solar pond performance. The onset of thermohaline convection is analyzed in this study by means of a linear stability analysis in which the flow field perturbations are expended in sets of complete orthonormal functions satisfying the boundary conditions of the flow field. The linear stability analysis is first performed with regard to an advanced solar pond (ASP) subject to field conditions in which thermohaline convection develops in planes perpendicular to the unperturbed flowmore » velocity vector. In the laboratory simulator of the ASP the width and depth are of the same order of magnitude. In this case it is found that the side walls delay the onset of convection in planes perpendicular to the unperturbed flow velocity vector. The presence of the side walls may cause the planes parallel to the flow velocity to be the most susceptible to the development on all three spatial variables, are predicted. They may develop in planes parallel or perpendicular to the unperturbed velocity vector according to the value of the Reynolds number of the unperturbed flow and the ratio between the width and depth of the ASP simulator.« less

Laws of trigonometry on SU(3)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aslaksen, H.

1988-01-01

In this paper we will study triangles in SU(3). The orbit space of congruence classes of triangles in SU(3) has dimension 8. Each corner is made up of a pair of tangent vectors (X,Y), and we consider the 8 functions trX{sup 2}, i trX{sup 3}, trY{sup 2}, i trY{sup 3}, trXY, i trY{sup 2}Y, i trXY{sup 2}, trX{sup 2}Y{sup 2} which are invariant under the full isometry group of SU(3). We show that these 8 corner invariants determine the isometry class of the triangle. We give relations (laws of trigonometry) between the invariants at the different corners, enabling us tomore » determine the invariants at the remaining corners, including the values of the remaining side and angles, if we know one set of corner invariants. The invariants that only depend on one tangent vector we will call side invariants, while those that depend on two tangent vectors will be called angular invariants. For each triangle we then have 6 side invariants and 12 angular invariants. Hence we need 18 {minus} 8 = 10 laws of trigonometry. The basic tool for deriving these laws is a formula expressing tr(exp X exp Y) in terms of the corner invariants.« less

Two generalizations of Kohonen clustering

NASA Technical Reports Server (NTRS)

Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.

1993-01-01

The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.

Detection of surface cracking in steel pipes based on vibration data using a multi-class support vector machine classifier

NASA Astrophysics Data System (ADS)

Mustapha, S.; Braytee, A.; Ye, L.

2017-04-01

In this study, we focused at the development and verification of a robust framework for surface crack detection in steel pipes using measured vibration responses; with the presence of multiple progressive damage occurring in different locations within the structure. Feature selection, dimensionality reduction, and multi-class support vector machine were established for this purpose. Nine damage cases, at different locations, orientations and length, were introduced into the pipe structure. The pipe was impacted 300 times using an impact hammer, after each damage case, the vibration data were collected using 3 PZT wafers which were installed on the outer surface of the pipe. At first, damage sensitive features were extracted using the frequency response function approach followed by recursive feature elimination for dimensionality reduction. Then, a multi-class support vector machine learning algorithm was employed to train the data and generate a statistical model. Once the model is established, decision values and distances from the hyper-plane were generated for the new collected data using the trained model. This process was repeated on the data collected from each sensor. Overall, using a single sensor for training and testing led to a very high accuracy reaching 98% in the assessment of the 9 damage cases used in this study.

Video data compression using artificial neural network differential vector quantization

NASA Technical Reports Server (NTRS)

Krishnamurthy, Ashok K.; Bibyk, Steven B.; Ahalt, Stanley C.

1991-01-01

An artificial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Differential Vector Quantization is used to preserve edge features, and a new adaptive algorithm, known as Frequency-Sensitive Competitive Learning, is used to develop the vector quantizer codebook. To develop real time performance, a custom Very Large Scale Integration Application Specific Integrated Circuit (VLSI ASIC) is being developed to realize the associative memory functions needed in the vector quantization algorithm. By using vector quantization, the need for Huffman coding can be eliminated, resulting in superior performance against channel bit errors than methods that use variable length codes.

GPU Accelerated Vector Median Filter

NASA Technical Reports Server (NTRS)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, H; Li, H; Gordon, J

Purpose: To investigate radiotherapy outcomes by incorporating 4DCT-based physiological and tumor elasticity functions for lung cancer patients. Methods: 4DCT images were acquired from 28 lung SBRT patients before radiation treatment. Deformable image registration (DIR) was performed from the end-inhale to the end-exhale using a B-Spline-based algorithm (Elastix, an open source software package). The resultant displacement vector fields (DVFs) were used to calculate a relative Jacobian function (RV) for each patient. The computed functions in the lung and tumor regions represent lung ventilation and tumor elasticity properties, respectively. The 28 patients were divided into two groups: 16 with two-year tumor localmore » control (LC) and 12 with local failure (LF). The ventilation and elasticity related RV functions were calculated for each of these patients. Results: The LF patients have larger RV values than the LC patients. The mean RV value in the lung region was 1.15 (±0.67) for the LF patients, higher than 1.06 (±0.59) for the LC patients. In the tumor region, the elasticity-related RV values are 1.2 (±0.97) and 0.86 (±0.64) for the LF and LC patients, respectively. Among the 16 LC patients, 3 have the mean RV values greater than 1.0 in the tumors. These tumors were located near the diaphragm, where the displacements are relatively large.. RV functions calculated in the tumor were better correlated with treatment outcomes than those calculated in the lung. Conclusion: The ventilation and elasticity-related RV functions in the lung and tumor regions were calculated from 4DCT image and the resultant values showed differences between the LC and LF patients. Further investigation of the impact of the displacements on the computed RV is warranted. Results suggest that the RV images might be useful for evaluation of treatment outcome for lung cancer patients.« less

Measurements of wind vectors, eddy momentum transports, and energy conversions in Jupiter's atmosphere from Voyager 1 images

NASA Astrophysics Data System (ADS)

Beebe, R. F.; Ingersoll, A. P.; Hunt, G. E.; Mitchell, J. L.; Muller, J.-P.

1980-01-01

Voyager 1 narrow-angle images were used to obtain displacements of features down to 100 to 200 km in size over intervals of 10 hours. A global map of velocity vectors and longitudinally averaged zonal wind vectors as functions of the latitude, is presented and discussed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge upmore » the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.« less

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier.

PubMed

Huang, Nantian; Chen, Huaijin; Cai, Guowei; Fang, Lihua; Wang, Yuqiang

2016-11-10

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF₆ HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods.

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Variational Mode Decomposition and Multi-Layer Classifier

PubMed Central

Huang, Nantian; Chen, Huaijin; Cai, Guowei; Fang, Lihua; Wang, Yuqiang

2016-01-01

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF6 HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods. PMID:27834902

15N backbone dynamics of the S-peptide from ribonuclease A in its free and S-protein bound forms: toward a site-specific analysis of entropy changes upon folding.

PubMed Central

Alexandrescu, A. T.; Rathgeb-Szabo, K.; Rumpel, K.; Jahnke, W.; Schulthess, T.; Kammerer, R. A.

1998-01-01

Backbone 15N relaxation parameters (R1, R2, 1H-15N NOE) have been measured for a 22-residue recombinant variant of the S-peptide in its free and S-protein bound forms. NMR relaxation data were analyzed using the "model-free" approach (Lipari & Szabo, 1982). Order parameters obtained from "model-free" simulations were used to calculate 1H-15N bond vector entropies using a recently described method (Yang & Kay, 1996), in which the form of the probability density function for bond vector fluctuations is derived from a diffusion-in-a-cone motional model. The average change in 1H-15N bond vector entropies for residues T3-S15, which become ordered upon binding of the S-peptide to the S-protein, is -12.6+/-1.4 J/mol.residue.K. 15N relaxation data suggest a gradient of decreasing entropy values moving from the termini toward the center of the free peptide. The difference between the entropies of the terminal and central residues is about -12 J/mol residue K, a value comparable to that of the average entropy change per residue upon complex formation. Similar entropy gradients are evident in NMR relaxation studies of other denatured proteins. Taken together, these observations suggest denatured proteins may contain entropic contributions from non-local interactions. Consequently, calculations that model the entropy of a residue in a denatured protein as that of a residue in a di- or tri-peptide, might over-estimate the magnitude of entropy changes upon folding. PMID:9521116

High-frequency homogenization for travelling waves in periodic media.

PubMed

Harutyunyan, Davit; Milton, Graeme W; Craster, Richard V

2016-07-01

We consider high-frequency homogenization in periodic media for travelling waves of several different equations: the wave equation for scalar-valued waves such as acoustics; the wave equation for vector-valued waves such as electromagnetism and elasticity; and a system that encompasses the Schrödinger equation. This homogenization applies when the wavelength is of the order of the size of the medium periodicity cell. The travelling wave is assumed to be the sum of two waves: a modulated Bloch carrier wave having crystal wavevector [Formula: see text] and frequency ω 1 plus a modulated Bloch carrier wave having crystal wavevector [Formula: see text] and frequency ω 2 . We derive effective equations for the modulating functions, and then prove that there is no coupling in the effective equations between the two different waves both in the scalar and the system cases. To be precise, we prove that there is no coupling unless ω 1 = ω 2 and [Formula: see text] where Λ =(λ 1 λ 2 …λ d ) is the periodicity cell of the medium and for any two vectors [Formula: see text] the product a ⊙ b is defined to be the vector ( a 1 b 1 , a 2 b 2 ,…, a d b d ). This last condition forces the carrier waves to be equivalent Bloch waves meaning that the coupling constants in the system of effective equations vanish. We use two-scale analysis and some new weak-convergence type lemmas. The analysis is not at the same level of rigour as that of Allaire and co-workers who use two-scale convergence theory to treat the problem, but has the advantage of simplicity which will allow it to be easily extended to the case where there is degeneracy of the Bloch eigenvalue.

Irregular-Mesh Terrain Analysis and Incident Solar Radiation for Continuous Hydrologic Modeling in Mountain Watersheds

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Ogden, F. L.; Alvarez, L. V.

2016-12-01

This research work presents a methodology for estimating terrain slope degree, aspect (slope orientation) and total incoming solar radiation from Triangular Irregular Network (TIN) terrain models. The algorithm accounts for self shading and cast shadows, sky view fractions for diffuse radiation, remote albedo and atmospheric backscattering, by using a vectorial approach within a topocentric coordinate system and establishing geometric relations between groups of TIN elements and the sun position. A normal vector to the surface of each TIN element describes slope and aspect while spherical trigonometry allows computingunit vector defining the position of the sun at each hour and day of the year. Thus, a dot product determines the radiation flux at each TIN element. Cast shadows are computed by scanning the projection of groups of TIN elements in the direction of the closest perpendicular plane to the sun vector only in the visible horizon range. Sky view fractions are computed by a simplified scanning algorithm from the highest to the lowest triangles along prescribed directions and visible distances, useful to determine diffuse radiation. Finally, remotealbedo is computed from the sky view fraction complementary functions for prescribed albedo values of the surrounding terrain only for significant angles above the horizon. The sensitivity of the different radiative components is tested a in a moutainuous watershed in Wyoming, to seasonal changes in weather and surrounding albedo (snow). This methodology represents an improvement on the current algorithms to compute terrain and radiation values on triangular-based models in an accurate and efficient manner. All terrain-related features (e.g. slope, aspect, sky view fraction) can be pre-computed and stored for easy access for a subsequent, progressive-in-time, numerical simulation.

Correction of the enzymatic and functional deficits in a model of Pompe disease using adeno-associated virus vectors.

PubMed

Fraites, Thomas J; Schleissing, Mary R; Shanely, R Andrew; Walter, Glenn A; Cloutier, Denise A; Zolotukhin, Irene; Pauly, Daniel F; Raben, Nina; Plotz, Paul H; Powers, Scott K; Kessler, Paul D; Byrne, Barry J

2002-05-01

Pompe disease is a lysosomal storage disease caused by the absence of acid alpha-1,4 glucosidase (GAA). The pathophysiology of Pompe disease includes generalized myopathy of both cardiac and skeletal muscle. We sought to use recombinant adeno-associated virus (rAAV) vectors to deliver functional GAA genes in vitro and in vivo. Myotubes and fibroblasts from Pompe patients were transduced in vitro with rAAV2-GAA. At 14 days postinfection, GAA activities were at least fourfold higher than in their respective untransduced controls, with a 10-fold increase observed in GAA-deficient myotubes. BALB/c and Gaa(-/-) mice were also treated with rAAV vectors. Persistent expression of vector-derived human GAA was observed in BALB/c mice up to 6 months after treatment. In Gaa(-/-) mice, intramuscular and intramyocardial delivery of rAAV2-Gaa (carrying the mouse Gaa cDNA) resulted in near-normal enzyme activities. Skeletal muscle contractility was partially restored in the soleus muscles of treated Gaa(-/-) mice, indicating the potential for vector-mediated restoration of both enzymatic activity and muscle function. Furthermore, intramuscular treatment with a recombinant AAV serotype 1 vector (rAAV1-Gaa) led to nearly eight times normal enzymatic activity in Gaa(-/-) mice, with concomitant glycogen clearance as assessed in vitro and by proton magnetic resonance spectroscopy.

Gene Delivery to Adipose Tissue Using Transcriptionally Targeted rAAV8 Vectors

PubMed Central

Uhrig-Schmidt, Silke; Geiger, Matthias; Luippold, Gerd; Birk, Gerald; Mennerich, Detlev; Neubauer, Heike; Grimm, Dirk; Wolfrum, Christian; Kreuz, Sebastian

2014-01-01

In recent years, the increasing prevalence of obesity and obesity-related co-morbidities fostered intensive research in the field of adipose tissue biology. To further unravel molecular mechanisms of adipose tissue function, genetic tools enabling functional studies in vitro and in vivo are essential. While the use of transgenic animals is well established, attempts using viral and non-viral vectors to genetically modify adipocytes in vivo are rare. Therefore, we here characterized recombinant Adeno-associated virus (rAAV) vectors regarding their potency as gene transfer vehicles for adipose tissue. Our results demonstrate that a single dose of systemically applied rAAV8-CMV-eGFP can give rise to remarkable transgene expression in murine adipose tissues. Upon transcriptional targeting of the rAAV8 vector to adipocytes using a 2.2 kb fragment of the murine adiponectin (mAP2.2) promoter, eGFP expression was significantly decreased in off-target tissues while efficient transduction was maintained in subcutaneous and visceral fat depots. Moreover, rAAV8-mAP2.2-mediated expression of perilipin A – a lipid-droplet-associated protein – resulted in significant changes in metabolic parameters only three weeks post vector administration. Taken together, our findings indicate that rAAV vector technology is applicable as a flexible tool to genetically modify adipocytes for functional proof-of-concept studies and the assessment of putative therapeutic targets in vivo. PMID:25551639

The Eccentric Behavior of Nearly Frozen Orbits

NASA Technical Reports Server (NTRS)

Sweetser, Theodore H.; Vincent, Mark A.

2013-01-01

Frozen orbits are orbits which have only short-period changes in their mean eccentricity and argument of periapse, so that they basically keep a fixed orientation within their plane of motion. Nearly frozen orbits are those whose eccentricity and argument of periapse have values close to those of a frozen orbit. We call them "nearly" frozen because their eccentricity vector (a vector whose polar coordinates are eccentricity and argument of periapse) will stay within a bounded distance from the frozen orbit eccentricity vector, circulating around it over time. For highly inclined orbits around the Earth, this distance is effectively constant over time. Furthermore, frozen orbit eccentricity values are low enough that these orbits are essentially eccentric (i.e., off center) circles, so that nearly frozen orbits around Earth are bounded above and below by frozen orbits.

Mosquitocidal Effect of Glycosmis pentaphylla Leaf Extracts against Three Mosquito Species (Diptera: Culicidae)

PubMed Central

Ramkumar, Govindaraju; Karthi, Sengodan; Muthusamy, Ranganathan; Suganya, Ponnusamy; Natarajan, Devarajan; Kweka, Eliningaya J.; Shivakumar, Muthugounder S.

2016-01-01

Background The resistance status of malaria vectors to different classes of insecticides used for public health has raised concern for vector control programmes. Alternative compounds to supplement the existing tools are important to be searched to overcome the existing resistance and persistence of pesticides in vectors and the environment respectively. The mosquitocidal effects of Glycosmis pentaphylla using different solvents of acetone, methanol, chloroform and ethyl acetate extracts against three medically important mosquito vectors was conducted. Methods Glycosmis pentaphylla plant leaves were collected from Kolli Hills, India. The WHO test procedures for larval and adult bioassays were used to evaluate extracts against mosquito vectors, and the chemical composition of extracts identified using GC-MS analysis. Results The larvicidal and adulticidal activity of G. pentaphylla plant extracts clearly impacted the three species of major mosquitoes vectors. Acetone extracts had the highest larvicidal effect against An. stephensi, Cx. quinquefasciatus and Ae. aegypti with the LC50 and LC90 values of 0.0004, 138.54; 0.2669, 73.7413 and 0.0585, 303.746 mg/ml, respectively. The LC50 and LC90 adulticide values of G. pentaphylla leaf extracts in acetone, methanol, chloroform and ethyl acetate, solvents were as follows for Cx. quinquefasciatus, An. stephensi and Ae. Aegypti: 2.957, 5.458, 2.708, and 4.777, 3.449, 6.676 mg/ml respectively. The chemical composition of G. pentaphylla leaf extract has been found in 20 active compounds. Conclusions The plant leaf extracts of G. pentaphylla bioactive molecules which are effective and can be developed as an eco-friendly approach for larvicides and adulticidal mosquitoes vector control. Detailed identification and characterization of mosquitocidal effect of individual bioactive molecules ingredient may result into biodegradable effective tools for the control of mosquito vectors. PMID:27391146

Mosquitocidal Effect of Glycosmis pentaphylla Leaf Extracts against Three Mosquito Species (Diptera: Culicidae).

PubMed

Ramkumar, Govindaraju; Karthi, Sengodan; Muthusamy, Ranganathan; Suganya, Ponnusamy; Natarajan, Devarajan; Kweka, Eliningaya J; Shivakumar, Muthugounder S

2016-01-01

The resistance status of malaria vectors to different classes of insecticides used for public health has raised concern for vector control programmes. Alternative compounds to supplement the existing tools are important to be searched to overcome the existing resistance and persistence of pesticides in vectors and the environment respectively. The mosquitocidal effects of Glycosmis pentaphylla using different solvents of acetone, methanol, chloroform and ethyl acetate extracts against three medically important mosquito vectors was conducted. Glycosmis pentaphylla plant leaves were collected from Kolli Hills, India. The WHO test procedures for larval and adult bioassays were used to evaluate extracts against mosquito vectors, and the chemical composition of extracts identified using GC-MS analysis. The larvicidal and adulticidal activity of G. pentaphylla plant extracts clearly impacted the three species of major mosquitoes vectors. Acetone extracts had the highest larvicidal effect against An. stephensi, Cx. quinquefasciatus and Ae. aegypti with the LC50 and LC90 values of 0.0004, 138.54; 0.2669, 73.7413 and 0.0585, 303.746 mg/ml, respectively. The LC50 and LC90 adulticide values of G. pentaphylla leaf extracts in acetone, methanol, chloroform and ethyl acetate, solvents were as follows for Cx. quinquefasciatus, An. stephensi and Ae. Aegypti: 2.957, 5.458, 2.708, and 4.777, 3.449, 6.676 mg/ml respectively. The chemical composition of G. pentaphylla leaf extract has been found in 20 active compounds. The plant leaf extracts of G. pentaphylla bioactive molecules which are effective and can be developed as an eco-friendly approach for larvicides and adulticidal mosquitoes vector control. Detailed identification and characterization of mosquitocidal effect of individual bioactive molecules ingredient may result into biodegradable effective tools for the control of mosquito vectors.

Virus induced gene silencing (VIGS) for functional analysis of wheat genes involved in Zymoseptoria tritici susceptibility and resistance.

PubMed

Lee, Wing-Sham; Rudd, Jason J; Kanyuka, Kostya

2015-06-01

Virus-induced gene silencing (VIGS) has emerged as a powerful reverse genetic technology in plants supplementary to stable transgenic RNAi and, in certain species, as a viable alternative approach for gene functional analysis. The RNA virus Barley stripe mosaic virus (BSMV) was developed as a VIGS vector in the early 2000s and since then it has been used to study the function of wheat genes. Several variants of BSMV vectors are available, with some requiring in vitro transcription of infectious viral RNA, while others rely on in planta production of viral RNA from DNA-based vectors delivered to plant cells either by particle bombardment or Agrobacterium tumefaciens. We adapted the latest generation of binary BSMV VIGS vectors for the identification and study of wheat genes of interest involved in interactions with Zymoseptoria tritici and here present detailed and the most up-to-date protocols. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Renninger's Gedankenexperiment, the collapse of the wave function in a rigid quantum metamaterial and the reality of the quantum state vector.

PubMed

Savel'ev, Sergey E; Zagoskin, Alexandre M

2018-06-25

A popular interpretation of the "collapse" of the wave function is as being the result of a local interaction ("measurement") of the quantum system with a macroscopic system ("detector"), with the ensuing loss of phase coherence between macroscopically distinct components of its quantum state vector. Nevetheless as early as in 1953 Renninger suggested a Gedankenexperiment, in which the collapse is triggered by non-observation of one of two mutually exclusive outcomes of the measurement, i.e., in the absence of interaction of the quantum system with the detector. This provided a powerful argument in favour of "physical reality" of (nonlocal) quantum state vector. In this paper we consider a possible version of Renninger's experiment using the light propagation through a birefringent quantum metamaterial. Its realization would provide a clear visualization of a wave function collapse produced by a "non-measurement", and make the concept of a physically real quantum state vector more acceptable.

Quantized Vector Potential and the Photon Wave-function

NASA Astrophysics Data System (ADS)

Meis, C.; Dahoo, P. R.

2017-12-01

The vector potential function {\\overrightarrow{α }}kλ (\\overrightarrow{r},t) for a k-mode and λ-polarization photon, with the quantized amplitude α 0k (ω k ) = ξω k , satisfies the classical wave propagation equation as well as the Schrodinger’s equation with the relativistic massless Hamiltonian \\mathop{H}\\limits∼ =-i\\hslash c\\overrightarrow{\

Amplitude-phase characteristics of electromagnetic fields diffracted by a hole in a thin film with realistic optical properties

NASA Astrophysics Data System (ADS)

Dorofeyev, Illarion

2009-03-01

Characteristics of a quasi-spherical wave front of an electromagnetic field diffracted by a subwavelength hole in a thin film with real optical properties are studied. Related diffraction problem is solved in general by use of the scalar and vector Green's theorems and related Green's function of a boundary-value problem. Local phase deviations of a diffracted wave front from an ideal spherical front are calculated. Diffracted patterns are calculated for the coherent incident fields in case of holes array in a screen of perfect conductivity.

Universal portfolios generated by the Bregman divergence

NASA Astrophysics Data System (ADS)

Tan, Choon Peng; Kuang, Kee Seng

2017-04-01

The Bregman divergence of two probability vectors is a stronger form of the f-divergence introduced by Csiszar. Two versions of the Bregman universal portfolio are presented by exploiting the mean-value theorem. The explicit form of the Bregman universal portfolio generated by a function of a convex polynomial is derived and studied empirically. This portfolio can be regarded as another generalized of the well-known Helmbold portfolio. By running the portfolios on selected stock-price data sets from the local stock exchange, it is shown that it is possible to increase the wealth of the investor by using the portfolios in investment.

An iterative solver for the 3D Helmholtz equation

NASA Astrophysics Data System (ADS)

Belonosov, Mikhail; Dmitriev, Maxim; Kostin, Victor; Neklyudov, Dmitry; Tcheverda, Vladimir

2017-09-01

We develop a frequency-domain iterative solver for numerical simulation of acoustic waves in 3D heterogeneous media. It is based on the application of a unique preconditioner to the Helmholtz equation that ensures convergence for Krylov subspace iteration methods. Effective inversion of the preconditioner involves the Fast Fourier Transform (FFT) and numerical solution of a series of boundary value problems for ordinary differential equations. Matrix-by-vector multiplication for iterative inversion of the preconditioned matrix involves inversion of the preconditioner and pointwise multiplication of grid functions. Our solver has been verified by benchmarking against exact solutions and a time-domain solver.

Genome scaffolding and annotation for the pathogen vector Ixodes ricinus by ultra-long single molecule sequencing.

PubMed

Cramaro, Wibke J; Hunewald, Oliver E; Bell-Sakyi, Lesley; Muller, Claude P

2017-02-08

Global warming and other ecological changes have facilitated the expansion of Ixodes ricinus tick populations. Ixodes ricinus is the most important carrier of vector-borne pathogens in Europe, transmitting viruses, protozoa and bacteria, in particular Borrelia burgdorferi (sensu lato), the causative agent of Lyme borreliosis, the most prevalent vector-borne disease in humans in the Northern hemisphere. To faster control this disease vector, a better understanding of the I. ricinus tick is necessary. To facilitate such studies, we recently published the first reference genome of this highly prevalent pathogen vector. Here, we further extend these studies by scaffolding and annotating the first reference genome by using ultra-long sequencing reads from third generation single molecule sequencing. In addition, we present the first genome size estimation for I. ricinus ticks and the embryo-derived cell line IRE/CTVM19. 235,953 contigs were integrated into 204,904 scaffolds, extending the currently known genome lengths by more than 30% from 393 to 516 Mb and the N50 contig value by 87% from 1643 bp to a N50 scaffold value of 3067 bp. In addition, 25,263 sequences were annotated by comparison to the tick's North American relative Ixodes scapularis. After (conserved) hypothetical proteins, zinc finger proteins, secreted proteins and P450 coding proteins were the most prevalent protein categories annotated. Interestingly, more than 50% of the amino acid sequences matching the homology threshold had 95-100% identity to the corresponding I. scapularis gene models. The sequence information was complemented by the first genome size estimation for this species. Flow cytometry-based genome size analysis revealed a haploid genome size of 2.65Gb for I. ricinus ticks and 3.80 Gb for the cell line. We present a first draft sequence map of the I. ricinus genome based on a PacBio-Illumina assembly. The I. ricinus genome was shown to be 26% (500 Mb) larger than the genome of its American relative I. scapularis. Based on the genome size of 2.65 Gb we estimated that we covered about 67% of the non-repetitive sequences. Genome annotation will facilitate screening for specific molecular pathways in I. ricinus cells and provides an overview of characteristics and functions.

Color deconvolution. Optimizing handling of 3D unitary optical density vectors with polar coordinates.

PubMed

Bigras, Gilbert

2012-06-01

Color deconvolution relies on determination of unitary optical density vectors (OD(3D)) derived from pure constituent stains initially defined as intensity vectors in RGB space. OD(3D) can be defined in polar coordinates (phi, theta, radius); always being equal to one, radius can be ignored. Easier handling of unitary optical density 2D vectors (OD(2D)) is shown. OD(2D) pure stains used in anatomical pathology were assessed as centroid values (phi, theta) with a measure of variance: inertia based on arc lengths between centroid value and sampled points. These variables were plotted on a stereographic projection plane. In order to assess pure stains OD(2D), different methods of sampling RGB pixels were tested and compared: (2) direct sampling of nuclei from preparations using (a) composite H&E and (b) hematoxylin only and (2) for any pure stain RGB image, different associated 8-bit masks (saturation, brightness and RGB average) were used for sampling and compared. Behaviors of phi, theta and inertia were obtained by moving threshold in 8-bit mask histograms. Phi and theta stability were tested against variable light intensity during image acquisition and by using 2 different image acquisition systems. The more saturated RGB pixels are, the more stable phi, theta and inertia values are obtained. Different commercial hematoxylins have distinct OD(2D) characteristics. UltraView DAB stain shows high inertia and is angularly closer to usual counterstains than ultraView Red stain, which also has a lower inertia. Superior accuracy is expected from the latter stain. Phi and theta OD(2D) values are sensitive to light intensity variation, to the used imaging system and to the used objectives. An ImageJ plugin was designed to plot and interactively modify OD(2D) values with instant update of color deconvolution allowing heuristic segmentation. Utilization of polar OD(2D) eases statistical characterization of OD(3D) vectors: conditions of optimal sampling were demonstrated and various factors influencing OD(2D) stability were explored. Stereographic projection plane allows intuitive visualization of OD(3D) vectors as well as heuristic vectorial modification. All findings are not restricted to anatomical pathology but can be applied to bright field microscopy and subtractive color applications in general.

Spin-lattice relaxation-rate anomaly at structural phase transitions

NASA Astrophysics Data System (ADS)

Levanyuk, A. P.; Minyukov, S. A.; Etrillard, J.; Toudic, B.

1997-12-01

The theory of spin-lattice relaxation (SLR)-rate anomaly at structural phase transitions proposed about 30 years ago is reconsidered taking into account that knowledge about the relevant lattice response functions has changed considerably. We use both the results of previous authors and perform original calculations of the response functions when it is necessary. We consider displacive systems and use the perturbation theory to treat the lattice anharmonicities in a broad temperature region whenever possible. Some comments about the order-disorder systems are made as well. The possibility of linear coupling of the order parameter and the resonance frequency is always assumed. It is found that in the symmetrical phase the anomaly is due to the one-phonon processes, the anomalous part being proportional to either (T-Tc)-1 or (T-Tc)-1/2 depending on some condition on the soft-mode dispersion. In both cases the value of the SLR rate at the boundary of applicabity of the theory (close to the phase transition) is estimated to be 102-103 times more than the typical value of the SLR rate in an ideal crystal. An essential specific feature of the nonsymmetrical phase is appearance of third-order anharmonicities that are well known to lead to a low-frequency dispersion of the order-parameter damping constant. We have found that this constant exhibits, in addition, a strong wave-vector dispersion, so that the damping constant determing the SLR rate is quite different from that at zero wave vector. In the case of two-component order parameter the damping constant for the component with nonzero equilibrium value is different from that for the other component, the difference is of the same order of magnitude as the damping constants themselves. In the case of the incommensurate phase a part of the mentioned third-order anharmonicity is responsible for longitudinal-transversal interaction that is well known to influence the static longitudinal response function. We calculate as well the dynamic response function to find that for the SLR calculations the imaginary part is of main importance. Due to this interaction the longitudinal SLR rate acquires a dependence on the Larmor frequency. This dependence is however, fairly weak: a logarithmic one. The implications of the obtained results for interpretation of the experimental data on SLR in incommensurate phase are discussed as well.

What does not kill them makes them stronger: larval environment and infectious dose alter mosquito potential to transmit filarial worms.

PubMed

Breaux, Jennifer A; Schumacher, Molly K; Juliano, Steven A

2014-07-07

For organisms with complex life cycles, larval environments can modify adult phenotypes. For mosquitoes and other vectors, when physiological impacts of stressors acting on larvae carry over into the adult stage they may interact with infectious dose of a vector-borne pathogen, producing a range of phenotypes for vector potential. Investigation of impacts of a common source of stress, larval crowding and intraspecific competition, on adult vector interactions with pathogens may increase our understanding of the dynamics of pathogen transmission by mosquito vectors. Using Aedes aegypti and the nematode parasite Brugia pahangi, we demonstrate dose dependency of fitness effects of B. pahangi infection on the mosquito, as well as interactions between competitive stress among larvae and infectious dose for resulting adults that affect the physiological and functional ability of mosquitoes to act as vectors. Contrary to results from studies on mosquito-arbovirus interactions, our results suggest that adults from crowded larvae may limit infection better than do adults from uncrowded controls, and that mosquitoes from high-quality larval environments are more physiologically and functionally capable vectors of B. pahangi. Our results provide another example of how the larval environment can have profound effects on vector potential of resulting adults. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Simplified method for the screening of technological maturity of red grape and total phenolic compounds of red grape skin: application of the characteristic vector method to near-infrared spectra.

PubMed

Nogales-Bueno, Julio; Ayala, Fernando; Hernández-Hierro, José Miguel; Rodríguez-Pulido, Francisco José; Echávarri, José Federico; Heredia, Francisco José

2015-05-06

Characteristic vector analysis has been applied to near-infrared spectra to extract the main spectral information from hyperspectral images. For this purpose, 3, 6, 9, and 12 characteristic vectors have been used to reconstruct the spectra, and root-mean-square errors (RMSEs) have been calculated to measure the differences between characteristic vector reconstructed spectra (CVRS) and hyperspectral imaging spectra (HIS). RMSE values obtained were 0.0049, 0.0018, 0.0012, and 0.0012 [log(1/R) units] for spectra allocated into the validation set, for 3, 6, 9, and 12 characteristic vectors, respectively. After that, calibration models have been developed and validated using the different groups of CVRS to predict skin total phenolic concentration, sugar concentration, titratable acidity, and pH by modified partial least-squares (MPLS) regression. The obtained results have been compared to those previously obtained from HIS. The models developed from the CVRS reconstructed from 12 characteristic vectors present similar values of coefficients of determination (RSQ) and standard errors of prediction (SEP) than the models developed from HIS. RSQ and SEP were 0.84 and 1.13 mg g(-1) of skin grape (expressed as gallic acid equivalents), 0.93 and 2.26 °Brix, 0.97 and 3.87 g L(-1) (expressed as tartaric acid equivalents), and 0.91 and 0.14 for skin total phenolic concentration, sugar concentration, titratable acidity, and pH, respectively, for the models developed from the CVRS reconstructed from 12 characteristic vectors.

Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendices; Index.

Student Solution Manual for Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendix.

Distribution pattern of public transport passenger in Yogyakarta, Indonesia

NASA Astrophysics Data System (ADS)

Narendra, Alfa; Malkhamah, Siti; Sopha, Bertha Maya

2018-03-01

The arrival and departure distribution pattern of Trans Jogja bus passenger is one of the fundamental model for simulation. The purpose of this paper is to build models of passengers flows. This research used passengers data from January to May 2014. There is no policy that change the operation system affecting the nature of this pattern nowadays. The roads, buses, land uses, schedule, and people are relatively still the same. The data then categorized based on the direction, days, and location. Moreover, each category was fitted into some well-known discrete distributions. Those distributions are compared based on its AIC value and BIC. The chosen distribution model has the smallest AIC and BIC value and the negative binomial distribution found has the smallest AIC and BIC value. Probability mass function (PMF) plots of those models were compared to draw generic model from each categorical negative binomial distribution models. The value of accepted generic negative binomial distribution is 0.7064 and 1.4504 of mu. The minimum and maximum passenger vector value of distribution are is 0 and 41.

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2012-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine

NASA Astrophysics Data System (ADS)

Liu, Fei; He, Yong

2008-02-01

Visible and near infrared (Vis/NIR) transmission spectroscopy and chemometric methods were utilized to predict the pH values of cola beverages. Five varieties of cola were prepared and 225 samples (45 samples for each variety) were selected for the calibration set, while 75 samples (15 samples for each variety) for the validation set. The smoothing way of Savitzky-Golay and standard normal variate (SNV) followed by first-derivative were used as the pre-processing methods. Partial least squares (PLS) analysis was employed to extract the principal components (PCs) which were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. Then LS-SVM with radial basis function (RBF) kernel function and a two-step grid search technique were applied to build the regression model with a comparison of PLS regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias were 0.961, 0.040 and 0.012 for PLS, while 0.975, 0.031 and 4.697x10 -3 for LS-SVM, respectively. Both methods obtained a satisfying precision. The results indicated that Vis/NIR spectroscopy combined with chemometric methods could be applied as an alternative way for the prediction of pH of cola beverages.

A Non-Parametric Approach for the Activation Detection of Block Design fMRI Simulated Data Using Self-Organizing Maps and Support Vector Machine.

PubMed

Bahrami, Sheyda; Shamsi, Mousa

2017-01-01

Functional magnetic resonance imaging (fMRI) is a popular method to probe the functional organization of the brain using hemodynamic responses. In this method, volume images of the entire brain are obtained with a very good spatial resolution and low temporal resolution. However, they always suffer from high dimensionality in the face of classification algorithms. In this work, we combine a support vector machine (SVM) with a self-organizing map (SOM) for having a feature-based classification by using SVM. Then, a linear kernel SVM is used for detecting the active areas. Here, we use SOM for feature extracting and labeling the datasets. SOM has two major advances: (i) it reduces dimension of data sets for having less computational complexity and (ii) it is useful for identifying brain regions with small onset differences in hemodynamic responses. Our non-parametric model is compared with parametric and non-parametric methods. We use simulated fMRI data sets and block design inputs in this paper and consider the contrast to noise ratio (CNR) value equal to 0.6 for simulated datasets. fMRI simulated dataset has contrast 1-4% in active areas. The accuracy of our proposed method is 93.63% and the error rate is 6.37%.

Navier-Stokes dynamics on a differential one-form

NASA Astrophysics Data System (ADS)

Story, Troy L.

2006-11-01

After transforming the Navier-Stokes dynamic equation into a characteristic differential one-form on an odd-dimensional differentiable manifold, exterior calculus is used to construct a pair of differential equations and tangent vector(vortex vector) characteristic of Hamiltonian geometry. A solution to the Navier-Stokes dynamic equation is then obtained by solving this pair of equations for the position x^k and the conjugate to the position bk as functions of time. The solution bk is shown to be divergence-free by contracting the differential 3-form corresponding to the divergence of the gradient of the velocity with a triple of tangent vectors, implying constraints on two of the tangent vectors for the system. Analysis of the solution bk shows it is bounded since it remains finite as | x^k | ->,, and is physically reasonable since the square of the gradient of the principal function is bounded. By contracting the characteristic differential one-form with the vortex vector, the Lagrangian is obtained.

Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

DTIC Science & Technology

2017-02-01

note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based...this technical note are widely used and may have an important role when computing the distance and similarity of large datasets and when considering high...throughput processes. In this technical note, a number of different measures implemented in both MAT- LAB and Python as functions are used to

Remote sensing of phytoplankton chlorophyll-a concentration by use of ridge function fields.

PubMed

Pelletier, Bruno; Frouin, Robert

2006-02-01

A methodology is presented for retrieving phytoplankton chlorophyll-a concentration from space. The data to be inverted, namely, vectors of top-of-atmosphere reflectance in the solar spectrum, are treated as explanatory variables conditioned by angular geometry. This approach leads to a continuum of inverse problems, i.e., a collection of similar inverse problems continuously indexed by the angular variables. The resolution of the continuum of inverse problems is studied from the least-squares viewpoint and yields a solution expressed as a function field over the set of permitted values for the angular variables, i.e., a map defined on that set and valued in a subspace of a function space. The function fields of interest, for reasons of approximation theory, are those valued in nested sequences of subspaces, such as ridge function approximation spaces, the union of which is dense. Ridge function fields constructed on synthetic yet realistic data for case I waters handle well situations of both weakly and strongly absorbing aerosols, and they are robust to noise, showing improvement in accuracy compared with classic inversion techniques. The methodology is applied to actual imagery from the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS); noise in the data are taken into account. The chlorophyll-a concentration obtained with the function field methodology differs from that obtained by use of the standard SeaWiFS algorithm by 15.7% on average. The results empirically validate the underlying hypothesis that the inversion is solved in a least-squares sense. They also show that large levels of noise can be managed if the noise distribution is known or estimated.

Optical implementation of systolic array processing

NASA Technical Reports Server (NTRS)

Caulfield, H. J.; Rhodes, W. T.; Foster, M. J.; Horvitz, S.

1981-01-01

Algorithms for matrix vector multiplication are implemented using acousto-optic cells for multiplication and input data transfer and using charge coupled devices detector arrays for accumulation and output of the results. No two dimensional matrix mask is required; matrix changes are implemented electronically. A system for multiplying a 50 component nonnegative real vector by a 50 by 50 nonnegative real matrix is described. Modifications for bipolar real and complex valued processing are possible, as are extensions to matrix-matrix multiplication and multiplication of a vector by multiple matrices.

Amiloride-enhanced gene transfection of octa-arginine functionalized calcium phosphate nanoparticles

PubMed Central

Tenkumo, Taichi; Kamano, Yuya; Egusa, Hiroshi; Sasaki, Keiichi

2017-01-01

Nanoparticles represent promising gene delivery systems in biomedicine to facilitate prolonged gene expression with low toxicity compared to viral vectors. Specifically, nanoparticles of calcium phosphate (nCaP), the main inorganic component of human bone, exhibit high biocompatibility and good biodegradability and have been reported to have high affinity for protein or DNA, having thus been used as gene transfer vectors. On the other hand, Octa-arginine (R8), which has a high permeability to cell membrane, has been reported to improve intracellular delivery systems. Here, we present an optimized method for nCaP-mediated gene delivery using an octa-arginine (R8)-functionalized nCaP vector containing a marker or functional gene construct. nCaP particle size was between 220–580 nm in diameter and all R8-functionalized nCaPs carried a positive charge. R8 concentration significantly improved nCaP transfection efficiency with high cell compatibility in human mesenchymal stem cells (hMSC) and human osteoblasts (hOB) in particular, suggesting nCaPs as a good option for non-viral vector gene delivery. Furthermore, pre-treatment with different endocytosis inhibitors identified that the endocytic pathway differed among cell lines and functionalized nanoparticles, with amiloride increasing transfection efficiency of R8-functionalized nCaPs in hMSC and hOB. PMID:29145481

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Breaking the polar-nonpolar division in solvation free energy prediction.

PubMed

Wang, Bao; Wang, Chengzhang; Wu, Kedi; Wei, Guo-Wei

2018-02-05

Implicit solvent models divide solvation free energies into polar and nonpolar additive contributions, whereas polar and nonpolar interactions are inseparable and nonadditive. We present a feature functional theory (FFT) framework to break this ad hoc division. The essential ideas of FFT are as follows: (i) representability assumption: there exists a microscopic feature vector that can uniquely characterize and distinguish one molecule from another; (ii) feature-function relationship assumption: the macroscopic features, including solvation free energy, of a molecule is a functional of microscopic feature vectors; and (iii) similarity assumption: molecules with similar microscopic features have similar macroscopic properties, such as solvation free energies. Based on these assumptions, solvation free energy prediction is carried out in the following protocol. First, we construct a molecular microscopic feature vector that is efficient in characterizing the solvation process using quantum mechanics and Poisson-Boltzmann theory. Microscopic feature vectors are combined with macroscopic features, that is, physical observable, to form extended feature vectors. Additionally, we partition a solvation dataset into queries according to molecular compositions. Moreover, for each target molecule, we adopt a machine learning algorithm for its nearest neighbor search, based on the selected microscopic feature vectors. Finally, from the extended feature vectors of obtained nearest neighbors, we construct a functional of solvation free energy, which is employed to predict the solvation free energy of the target molecule. The proposed FFT model has been extensively validated via a large dataset of 668 molecules. The leave-one-out test gives an optimal root-mean-square error (RMSE) of 1.05 kcal/mol. FFT predictions of SAMPL0, SAMPL1, SAMPL2, SAMPL3, and SAMPL4 challenge sets deliver the RMSEs of 0.61, 1.86, 1.64, 0.86, and 1.14 kcal/mol, respectively. Using a test set of 94 molecules and its associated training set, the present approach was carefully compared with a classic solvation model based on weighted solvent accessible surface area. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The combined geodetic network adjusted on the reference ellipsoid - a comparison of three functional models for GNSS observations

NASA Astrophysics Data System (ADS)

Kadaj, Roman

2016-12-01

The adjustment problem of the so-called combined (hybrid, integrated) network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length) on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients). While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional model of the GNSS observations.

Fast support vector data descriptions for novelty detection.

PubMed

Liu, Yi-Hung; Liu, Yan-Chen; Chen, Yen-Jen

2010-08-01

Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems. However, the decision function of SVDD is expressed in terms of the kernel expansion, which results in a run-time complexity linear in the number of support vectors. For applications where fast real-time response is needed, how to speed up the decision function is crucial. This paper aims at dealing with the issue of reducing the testing time complexity of SVDD. A method called fast SVDD (F-SVDD) is proposed. Unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms, the proposed F-SVDD directly finds the preimage of a feature vector, and then uses a simple relationship between this feature vector and the SVDD sphere center to re-express the center with a single vector. The decision function of F-SVDD contains only one kernel term, and thus the decision boundary of F-SVDD is only spherical in the original space. Hence, the run-time complexity of the F-SVDD decision function is no longer linear in the support vectors, but is a constant, no matter how large the training set size is. In this paper, we also propose a novel direct preimage-finding method, which is noniterative and involves no free parameters. The unique preimage can be obtained in real time by the proposed direct method without taking trial-and-error. For demonstration, several real-world data sets and a large-scale data set, the extended MIT face data set, are used in experiments. In addition, a practical industry example regarding liquid crystal display micro-defect inspection is also used to compare the applicability of SVDD and our proposed F-SVDD when faced with mass data input. The results are very encouraging.

Rotation invariants of vector fields from orthogonal moments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Bo; Kostková, Jitka; Flusser, Jan

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

Yang, Bo; Kostková, Jitka; Flusser, Jan; ...

2017-09-11

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

A path model for Whittaker vectors

NASA Astrophysics Data System (ADS)

Di Francesco, Philippe; Kedem, Rinat; Turmunkh, Bolor

2017-06-01

In this paper we construct weighted path models to compute Whittaker vectors in the completion of Verma modules, as well as Whittaker functions of fundamental type, for all finite-dimensional simple Lie algebras, affine Lie algebras, and the quantum algebra U_q(slr+1) . This leads to series expressions for the Whittaker functions. We show how this construction leads directly to the quantum Toda equations satisfied by these functions, and to the q-difference equations in the quantum case. We investigate the critical limit of affine Whittaker functions computed in this way.

Dengue Fever Occurrence and Vector Detection by Larval Survey, Ovitrap and MosquiTRAP: A Space-Time Clusters Analysis

PubMed Central

de Melo, Diogo Portella Ornelas; Scherrer, Luciano Rios; Eiras, Álvaro Eduardo

2012-01-01

The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools. PMID:22848729

Linear Transformation Method for Multinuclide Decay Calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding Yuan

2010-12-29

A linear transformation method for generic multinuclide decay calculations is presented together with its properties and implications. The method takes advantage of the linear form of the decay solution N(t) = F(t)N{sub 0}, where N(t) is a column vector that represents the numbers of atoms of the radioactive nuclides in the decay chain, N{sub 0} is the initial value vector of N(t), and F(t) is a lower triangular matrix whose time-dependent elements are independent of the initial values of the system.

Attitude determination using vector observations: A fast optimal matrix algorithm

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1993-01-01

The attitude matrix minimizing Wahba's loss function is computed directly by a method that is competitive with the fastest known algorithm for finding this optimal estimate. The method also provides an estimate of the attitude error covariance matrix. Analysis of the special case of two vector observations identifies those cases for which the TRIAD or algebraic method minimizes Wahba's loss function.

Spin eigen-states of Dirac equation for quasi-two-dimensional electrons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eremko, Alexander, E-mail: eremko@bitp.kiev.ua; Brizhik, Larissa, E-mail: brizhik@bitp.kiev.ua; Loktev, Vadim, E-mail: vloktev@bitp.kiev.ua

Dirac equation for electrons in a potential created by quantum well is solved and the three sets of the eigen-functions are obtained. In each set the wavefunction is at the same time the eigen-function of one of the three spin operators, which do not commute with each other, but do commute with the Dirac Hamiltonian. This means that the eigen-functions of Dirac equation describe three independent spin eigen-states. The energy spectrum of electrons confined by the rectangular quantum well is calculated for each of these spin states at the values of energies relevant for solid state physics. It is shownmore » that the standard Rashba spin splitting takes place in one of such states only. In another one, 2D electron subbands remain spin degenerate, and for the third one the spin splitting is anisotropic for different directions of 2D wave vector.« less

Vector-Free and Transgene-Free Human iPS Cells Differentiate into Functional Neurons and Enhance Functional Recovery after Ischemic Stroke in Mice

PubMed Central

Mohamad, Osama; Faulkner, Ben; Chen, Dongdong; Yu, Shan Ping; Wei, Ling

2013-01-01

Stroke is a leading cause of human death and disability in the adult population in the United States and around the world. While stroke treatment is limited, stem cell transplantation has emerged as a promising regenerative therapy to replace or repair damaged tissues and enhance functional recovery after stroke. Recently, the creation of induced pluripotent stem (iPS) cells through reprogramming of somatic cells has revolutionized cell therapy by providing an unlimited source of autologous cells for transplantation. In addition, the creation of vector-free and transgene-free human iPS (hiPS) cells provides a new generation of stem cells with a reduced risk of tumor formation that was associated with the random integration of viral vectors seen with previous techniques. However, the potential use of these cells in the treatment of ischemic stroke has not been explored. In the present investigation, we examined the neuronal differentiation of vector-free and transgene-free hiPS cells and the transplantation of hiPS cell-derived neural progenitor cells (hiPS-NPCs) in an ischemic stroke model in mice. Vector-free hiPS cells were maintained in feeder-free and serum-free conditions and differentiated into functional neurons in vitro using a newly developed differentiation protocol. Twenty eight days after transplantation in stroke mice, hiPS-NPCs showed mature neuronal markers in vivo. No tumor formation was seen up to 12 months after transplantation. Transplantation of hiPS-NPCs restored neurovascular coupling, increased trophic support and promoted behavioral recovery after stroke. These data suggest that using vector-free and transgene-free hiPS cells in stem cell therapy are safe and efficacious in enhancing recovery after focal ischemic stroke in mice. PMID:23717557

Rapid production of functionalized recombinant proteins: marrying ligation independent cloning and in vitro protein ligation.

PubMed

Kushnir, Susanna; Marsac, Yoann; Breitling, Reinhard; Granovsky, Igor; Brok-Volchanskaya, Vera; Goody, Roger S; Becker, Christian F W; Alexandrov, Kirill

2006-01-01

Functional genomics and proteomics have been very active fields since the sequencing of several genomes was completed. To assign a physiological role to the newly discovered coding genes with unknown function, new generic methods for protein production, purification, and targeted functionalization are needed. This work presents a new vector, pCYSLIC, that allows rapid generation of Escherichia coli expression constructs via ligation-independent cloning (LIC). The vector is designed to facilitate protein purification by either Ni-NTA or GSH affinity chromatography. Subsequent proteolytic removal of affinity tags liberates an N-terminal cysteine residue that is then used for covalent modification of the target protein with different biophysical probes via protein ligation. The described system has been tested on 36 mammalian Rab GTPases, and it was demonstrated that recombinant GTPases produced with pCYSLIC could be efficiently modified with fluorescein or biotin in vitro. Finally, LIC was compared with the recently developed In-Fusion cloning method, and it was demonstrated that In-Fusion provides superior flexibility in choice of expression vector. By the application of In-Fusion cloning Cys-Rab6A GTPase with an N-terminal cysteine residue was generated employing unmodified pET30a vector and TVMV protease.

A novel packaging system for the generation of helper-free oncolytic MVM vector stocks.

PubMed

Brandenburger, A; Russell, S

1996-10-01

MVM-based autonomous parvoviral vectors have been shown to target the expression of heterologous genes in neoplastic cells and are therefore of interest for cancer gene therapy. The traditional method for production of parvoviral vectors requires the cotransfection of vector and helper plasmids into MVM-permissive cell lines, but recombination between the cotransfected plasmids invariably gives rise to vector stocks that are heavily contaminated with wild-type MVM. Therefore, to minimise recombination between the vector and helper genomes we have utilised a cell line in which the MVM helper functions are expressed inducibly from a modified MVM genome that is stably integrated into the host cell chromosome. Using this MVM packaging cell line, we could reproducibly generate MVM vector stocks that contained no detectable helper virus.

Probing Low-Mass Vector Bosons with Parity Nonconservation and Nuclear Anapole Moment Measurements in Atoms and Molecules

NASA Astrophysics Data System (ADS)

Dzuba, V. A.; Flambaum, V. V.; Stadnik, Y. V.

2017-12-01

In the presence of P -violating interactions, the exchange of vector bosons between electrons and nucleons induces parity-nonconserving (PNC) effects in atoms and molecules, while the exchange of vector bosons between nucleons induces anapole moments of nuclei. We perform calculations of such vector-mediated PNC effects in Cs, Ba+ , Yb, Tl, Fr, and Ra+ using the same relativistic many-body approaches as in earlier calculations of standard-model PNC effects, but with the long-range operator of the weak interaction. We calculate nuclear anapole moments due to vector-boson exchange using a simple nuclear model. From measured and predicted (within the standard model) values for the PNC amplitudes in Cs, Yb, and Tl, as well as the nuclear anapole moment of 133Cs, we constrain the P -violating vector-pseudovector nucleon-electron and nucleon-proton interactions mediated by a generic vector boson of arbitrary mass. Our limits improve on existing bounds from other experiments by many orders of magnitude over a very large range of vector-boson masses.

The Minkowski sum of a zonotope and the Voronoi polytope of the root lattice E{sub 7}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grishukhin, Vyacheslav P

2012-11-30

We show that the Minkowski sum P{sub V}(E{sub 7})+Z(U) of the Voronoi polytope P{sub V}(E{sub 7}) of the root lattice E{sub 7} and the zonotope Z(U) is a 7-dimensional parallelohedron if and only if the set U consists of minimal vectors of the dual lattice E{sub 7}{sup *} up to scalar multiplication, and U does not contain forbidden sets. The minimal vectors of E{sub 7} are the vectors r of the classical root system E{sub 7}. If the r{sup 2}-norm of the roots is set equal to 2, then the scalar products of minimal vectors from the dual lattice onlymore » take the values {+-}1/2. A set of minimal vectors is referred to as forbidden if it consists of six vectors, and the directions of some of these vectors can be changed so as to obtain a set of six vectors with all the pairwise scalar products equal to 1/2. Bibliography: 11 titles.« less

Modified Vaccinia Virus Ankara: History, Value in Basic Research, and Current Perspectives for Vaccine Development.

PubMed

Volz, A; Sutter, G

2017-01-01

Safety tested Modified Vaccinia virus Ankara (MVA) is licensed as third-generation vaccine against smallpox and serves as a potent vector system for development of new candidate vaccines against infectious diseases and cancer. Historically, MVA was developed by serial tissue culture passage in primary chicken cells of vaccinia virus strain Ankara, and clinically used to avoid the undesirable side effects of conventional smallpox vaccination. Adapted to growth in avian cells MVA lost the ability to replicate in mammalian hosts and lacks many of the genes orthopoxviruses use to conquer their host (cell) environment. As a biologically well-characterized mutant virus, MVA facilitates fundamental research to elucidate the functions of poxvirus host-interaction factors. As extremely safe viral vectors MVA vaccines have been found immunogenic and protective in various preclinical infection models. Multiple recombinant MVA currently undergo clinical testing for vaccination against human immunodeficiency viruses, Mycobacterium tuberculosis or Plasmodium falciparum. The versatility of the MVA vector vaccine platform is readily demonstrated by the swift development of experimental vaccines for immunization against emerging infections such as the Middle East Respiratory Syndrome. Recent advances include promising results from the clinical testing of recombinant MVA-producing antigens of highly pathogenic avian influenza virus H5N1 or Ebola virus. This review summarizes our current knowledge about MVA as a unique strain of vaccinia virus, and discusses the prospects of exploiting this virus as research tool in poxvirus biology or as safe viral vector vaccine to challenge existing and future bottlenecks in vaccinology. © 2017 Elsevier Inc. All rights reserved.

Current and future resources for functional metagenomics

PubMed Central

Lam, Kathy N.; Cheng, Jiujun; Engel, Katja; Neufeld, Josh D.; Charles, Trevor C.

2015-01-01

Functional metagenomics is a powerful experimental approach for studying gene function, starting from the extracted DNA of mixed microbial populations. A functional approach relies on the construction and screening of metagenomic libraries—physical libraries that contain DNA cloned from environmental metagenomes. The information obtained from functional metagenomics can help in future annotations of gene function and serve as a complement to sequence-based metagenomics. In this Perspective, we begin by summarizing the technical challenges of constructing metagenomic libraries and emphasize their value as resources. We then discuss libraries constructed using the popular cloning vector, pCC1FOS, and highlight the strengths and shortcomings of this system, alongside possible strategies to maximize existing pCC1FOS-based libraries by screening in diverse hosts. Finally, we discuss the known bias of libraries constructed from human gut and marine water samples, present results that suggest bias may also occur for soil libraries, and consider factors that bias metagenomic libraries in general. We anticipate that discussion of current resources and limitations will advance tools and technologies for functional metagenomics research. PMID:26579102

Current and future resources for functional metagenomics.

PubMed

Lam, Kathy N; Cheng, Jiujun; Engel, Katja; Neufeld, Josh D; Charles, Trevor C

2015-01-01

Functional metagenomics is a powerful experimental approach for studying gene function, starting from the extracted DNA of mixed microbial populations. A functional approach relies on the construction and screening of metagenomic libraries-physical libraries that contain DNA cloned from environmental metagenomes. The information obtained from functional metagenomics can help in future annotations of gene function and serve as a complement to sequence-based metagenomics. In this Perspective, we begin by summarizing the technical challenges of constructing metagenomic libraries and emphasize their value as resources. We then discuss libraries constructed using the popular cloning vector, pCC1FOS, and highlight the strengths and shortcomings of this system, alongside possible strategies to maximize existing pCC1FOS-based libraries by screening in diverse hosts. Finally, we discuss the known bias of libraries constructed from human gut and marine water samples, present results that suggest bias may also occur for soil libraries, and consider factors that bias metagenomic libraries in general. We anticipate that discussion of current resources and limitations will advance tools and technologies for functional metagenomics research.

Prediction on sunspot activity based on fuzzy information granulation and support vector machine

NASA Astrophysics Data System (ADS)

Peng, Lingling; Yan, Haisheng; Yang, Zhigang

2018-04-01

In order to analyze the range of sunspots, a combined prediction method of forecasting the fluctuation range of sunspots based on fuzzy information granulation (FIG) and support vector machine (SVM) was put forward. Firstly, employing the FIG to granulate sample data and extract va)alid information of each window, namely the minimum value, the general average value and the maximum value of each window. Secondly, forecasting model is built respectively with SVM and then cross method is used to optimize these parameters. Finally, the fluctuation range of sunspots is forecasted with the optimized SVM model. Case study demonstrates that the model have high accuracy and can effectively predict the fluctuation of sunspots.

Can different quantum state vectors correspond to the same physical state? An experimental test

NASA Astrophysics Data System (ADS)

Nigg, Daniel; Monz, Thomas; Schindler, Philipp; Martinez, Esteban A.; Hennrich, Markus; Blatt, Rainer; Pusey, Matthew F.; Rudolph, Terry; Barrett, Jonathan

2016-01-01

A century after the development of quantum theory, the interpretation of a quantum state is still discussed. If a physicist claims to have produced a system with a particular quantum state vector, does this represent directly a physical property of the system, or is the state vector merely a summary of the physicist’s information about the system? Assume that a state vector corresponds to a probability distribution over possible values of an unknown physical or ‘ontic’ state. Then, a recent no-go theorem shows that distinct state vectors with overlapping distributions lead to predictions different from quantum theory. We report an experimental test of these predictions using trapped ions. Within experimental error, the results confirm quantum theory. We analyse which kinds of models are ruled out.

An experimental investigation of thrust vectoring two-dimensional convergent-divergent nozzles installed in a twin-engine fighter model at high angles of attack

NASA Technical Reports Server (NTRS)

Capone, Francis J.; Mason, Mary L.; Leavitt, Laurence D.

1990-01-01

An investigation was conducted in the Langley 16-Foot Transonic Tunnel to determine thrust vectoring capability of subscale 2-D convergent-divergent exhaust nozzles installed on a twin engine general research fighter model. Pitch thrust vectoring was accomplished by downward rotation of nozzle upper and lower flaps. The effects of nozzle sidewall cutback were studied for both unvectored and pitch vectored nozzles. A single cutback sidewall was employed for yaw thrust vectoring. This investigation was conducted at Mach numbers ranging from 0 to 1.20 and at angles of attack from -2 to 35 deg. High pressure air was used to simulate jet exhaust and provide values of nozzle pressure ratio up to 9.

Spin Manipulating Vector and Tensor Polarized Deuterons Stored in COSY

NASA Astrophysics Data System (ADS)

Morozov, Vassili; Krisch, Alan; Leonova, Maria; Raymond, Richard; Sivers, Dennis; Wong, Victor; Yonehara, Katsuya; Bechstedt, Ulf; Gebel, Ralf; Lehrach, Andreas; Lorentz, Bernd; Maier, Rudolf; Schnase, Alexander; Stockhorst, Hans; Eversheim, Dieter; Hinterberger, Frank; Rohdjess, Heiko; Ulbrich, Kay

2004-05-01

We recently studied spin flipping and spin manipulation of a simultaneously vector and tensor polarized deuteron beam stored in the COSY Cooler Synchrotron at 1.85 GeV/c. Using the EDDA detector we calibrated vector and tensor analyzing powers, which were earlier unknown at this energy; thus, we were able to obtain the absolute values for both the vector and tensor polarizations. We manipulated the deuteron's polarization using a new water-cooled ferrite rf dipole, by adiabatically sweeping its frequency through an rf-induced spin resonance. We first experimentally determined the resonance's frequency and then varied the dipole's frequency range and frequency ramp time. This allowed us to maximize the vector polarization spin-flip efficiency to about 97 ± 1%. We also studied the interesting tensor polarization manipulation in considerable detail.

Expansion of Tabulated Scattering Matrices in Generalized Spherical Functions

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Yang, Ping

2016-01-01

An efficient way to solve the vector radiative transfer equation for plane-parallel turbid media is to Fourier-decompose it in azimuth. This methodology is typically based on the analytical computation of the Fourier components of the phase matrix and is predicated on the knowledge of the coefficients appearing in the expansion of the normalized scattering matrix in generalized spherical functions. Quite often the expansion coefficients have to be determined from tabulated values of the scattering matrix obtained from measurements or calculated by solving the Maxwell equations. In such cases one needs an efficient and accurate computer procedure converting a tabulated scattering matrix into the corresponding set of expansion coefficients. This short communication summarizes the theoretical basis of this procedure and serves as the user guide to a simple public-domain FORTRAN program.

Heat asymptotics for nonminimal Laplace type operators and application to noncommutative tori

NASA Astrophysics Data System (ADS)

Iochum, B.; Masson, T.

2018-07-01

Let P be a Laplace type operator acting on a smooth hermitean vector bundle V of fiber CN over a compact Riemannian manifold given locally by P = - [gμν u(x) ∂μ∂ν +vν(x) ∂ν + w(x) ] where u ,vν , w are MN(C) -valued functions with u(x) positive and invertible. For any a ∈ Γ(End(V)) , we consider the asymptotics Tr(ae-tP) ∼ t↓0+ ∑r=0∞ ar(a , P) t (r - d) / 2 where the coefficients ar(a , P) can be written as an integral of the functions ar(a , P) (x) = tr [ a(x) Rr(x) ] . The computation of R2 is performed opening the opportunity to calculate the modular scalar curvature for noncommutative tori.

Complex mode indication function and its applications to spatial domain parameter estimation

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

This paper introduces the concept of the Complex Mode Indication Function (CMIF) and its application in spatial domain parameter estimation. The concept of CMIF is developed by performing singular value decomposition (SVD) of the Frequency Response Function (FRF) matrix at each spectral line. The CMIF is defined as the eigenvalues, which are the square of the singular values, solved from the normal matrix formed from the FRF matrix, [ H( jω)] H[ H( jω)], at each spectral line. The CMIF appears to be a simple and efficient method for identifying the modes of the complex system. The CMIF identifies modes by showing the physical magnitude of each mode and the damped natural frequency for each root. Since multiple reference data is applied in CMIF, repeated roots can be detected. The CMIF also gives global modal parameters, such as damped natural frequencies, mode shapes and modal participation vectors. Since CMIF works in the spatial domain, uneven frequency spacing data such as data from spatial sine testing can be used. A second-stage procedure for accurate damped natural frequency and damping estimation as well as mode shape scaling is also discussed in this paper.

The possibilities of improvement in the sensitivity of cancer fluorescence diagnostics by computer image processing

NASA Astrophysics Data System (ADS)

Ledwon, Aleksandra; Bieda, Robert; Kawczyk-Krupka, Aleksandra; Polanski, Andrzej; Wojciechowski, Konrad; Latos, Wojciech; Sieron-Stoltny, Karolina; Sieron, Aleksander

2008-02-01

Background: Fluorescence diagnostics uses the ability of tissues to fluoresce after exposition to a specific wavelength of light. The change in fluorescence between normal and progression to cancer allows to see early cancer and precancerous lesions often missed by white light. Aim: To improve by computer image processing the sensitivity of fluorescence images obtained during examination of skin, oral cavity, vulva and cervix lesions, during endoscopy, cystoscopy and bronchoscopy using Xillix ONCOLIFE. Methods: Function of image f(x,y):R2 --> R 3 was transformed from original color space RGB to space in which vector of 46 values refers to every point labeled by defined xy-coordinates- f(x,y):R2 --> R 46. By means of Fisher discriminator vector of attributes of concrete point analalyzed in the image was reduced according to two defined classes defined as pathologic areas (foreground) and healthy areas (background). As a result the highest four fisher's coefficients allowing the greatest separation between points of pathologic (foreground) and healthy (background) areas were chosen. In this way new function f(x,y):R2 --> R 4 was created in which point x,y corresponds with vector Y, H, a*, c II. In the second step using Gaussian Mixtures and Expectation-Maximisation appropriate classificator was constructed. This classificator enables determination of probability that the selected pixel of analyzed image is a pathologically changed point (foreground) or healthy one (background). Obtained map of probability distribution was presented by means of pseudocolors. Results: Image processing techniques improve the sensitivity, quality and sharpness of original fluorescence images. Conclusion: Computer image processing enables better visualization of suspected areas examined by means of fluorescence diagnostics.

On the Runge-Lenz-Pauli vector operator as an aid to the calculation of atomic processes in laboratory and astrophysical plasmas

NASA Astrophysics Data System (ADS)

Hey, J. D.

2015-09-01

On the basis of the original definition and analysis of the vector operator by Pauli (1926 Z. Phys. 36 336-63), and further developments by Flamand (1966 J. Math. Phys. 7 1924-31), and by Becker and Bleuler (1976 Z. Naturforsch. 31a 517-23), we consider the action of the operator on both spherical polar and parabolic basis state wave functions, both with and without direct use of Pauli’s identity (Valent 2003 Am. J. Phys. 71 171-75). Comparison of the results, with the aid of two earlier papers (Hey 2006 J. Phys. B: At. Mol. Opt. Phys. 39 2641-64, Hey 2007 J. Phys. B: At. Mol. Opt. Phys. 40 4077-96), yields a convenient ladder technique in the form of a recurrence relation for calculating the transformation coefficients between the two sets of basis states, without explicit use of generalized hypergeometric functions. This result is therefore very useful for application to Stark effect and impact broadening calculations applied to high-n radio recombination lines from tenuous space plasmas. We also demonstrate the versatility of the Runge-Lenz-Pauli vector operator as a means of obtaining recurrence relations between expectation values of successive powers of quantum mechanical operators, by using it to provide, as an example, a derivation of the Kramers-Pasternack relation. It is suggested that this operator, whose potential use in Stark- and Zeeman-effect calculations for magnetically confined fusion edge plasmas (Rosato, Marandet and Stamm 2014 J. Phys. B: At. Mol. Opt. Phys. 47 105702) and tenuous space plasmas ( H II regions) has not been fully explored and exploited, may yet be found to yield a number of valuable results for applications to plasma diagnostic techniques based upon rate calculations of atomic processes.

Decoding the individual finger movements from single-trial functional magnetic resonance imaging recordings of human brain activity.

PubMed

Shen, Guohua; Zhang, Jing; Wang, Mengxing; Lei, Du; Yang, Guang; Zhang, Shanmin; Du, Xiaoxia

2014-06-01

Multivariate pattern classification analysis (MVPA) has been applied to functional magnetic resonance imaging (fMRI) data to decode brain states from spatially distributed activation patterns. Decoding upper limb movements from non-invasively recorded human brain activation is crucial for implementing a brain-machine interface that directly harnesses an individual's thoughts to control external devices or computers. The aim of this study was to decode the individual finger movements from fMRI single-trial data. Thirteen healthy human subjects participated in a visually cued delayed finger movement task, and only one slight button press was performed in each trial. Using MVPA, the decoding accuracy (DA) was computed separately for the different motor-related regions of interest. For the construction of feature vectors, the feature vectors from two successive volumes in the image series for a trial were concatenated. With these spatial-temporal feature vectors, we obtained a 63.1% average DA (84.7% for the best subject) for the contralateral primary somatosensory cortex and a 46.0% average DA (71.0% for the best subject) for the contralateral primary motor cortex; both of these values were significantly above the chance level (20%). In addition, we implemented searchlight MVPA to search for informative regions in an unbiased manner across the whole brain. Furthermore, by applying searchlight MVPA to each volume of a trial, we visually demonstrated the information for decoding, both spatially and temporally. The results suggest that the non-invasive fMRI technique may provide informative features for decoding individual finger movements and the potential of developing an fMRI-based brain-machine interface for finger movement. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Use of Multi-class Empirical Orthogonal Function for Identification of Hydrogeological Parameters and Spatiotemporal Pattern of Multiple Recharges in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Yeh, W. W. G.; Hsieh, I. H.

2017-12-01

This study develops an innovative calibration method for regional groundwater modeling by using multi-class empirical orthogonal functions (EOFs). The developed method is an iterative approach. Prior to carrying out the iterative procedures, the groundwater storage hydrographs associated with the observation wells are calculated. The combined multi-class EOF amplitudes and EOF expansion coefficients of the storage hydrographs are then used to compute the initial gauss of the temporal and spatial pattern of multiple recharges. The initial guess of the hydrogeological parameters are also assigned according to in-situ pumping experiment. The recharges include net rainfall recharge and boundary recharge, and the hydrogeological parameters are riverbed leakage conductivity, horizontal hydraulic conductivity, vertical hydraulic conductivity, storage coefficient, and specific yield. The first step of the iterative algorithm is to conduct the numerical model (i.e. MODFLOW) by the initial guess / adjusted values of the recharges and parameters. Second, in order to determine the best EOF combination of the error storage hydrographs for determining the correction vectors, the objective function is devised as minimizing the root mean square error (RMSE) of the simulated storage hydrographs. The error storage hydrograph are the differences between the storage hydrographs computed from observed and simulated groundwater level fluctuations. Third, adjust the values of recharges and parameters and repeat the iterative procedures until the stopping criterion is reached. The established methodology was applied to the groundwater system of Ming-Chu Basin, Taiwan. The study period is from January 1st to December 2ed in 2012. Results showed that the optimal EOF combination for the multiple recharges and hydrogeological parameters can decrease the RMSE of the simulated storage hydrographs dramatically within three calibration iterations. It represents that the iterative approach that using EOF techniques can capture the groundwater flow tendency and detects the correction vector of the simulated error sources. Hence, the established EOF-based methodology can effectively and accurately identify the multiple recharges and hydrogeological parameters.

Minimizing distortion and internal forces in truss structures by simulated annealing

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.

1989-01-01

Inaccuracies in the length of members and the diameters of joints of large truss reflector backup structures may produce unacceptable levels of surface distortion and member forces. However, if the member lengths and joint diameters can be measured accurately it is possible to configure the members and joints so that root-mean-square (rms) surface error and/or rms member forces is minimized. Following Greene and Haftka (1989) it is assumed that the force vector f is linearly proportional to the member length errors e(sub M) of dimension NMEMB (the number of members) and joint errors e(sub J) of dimension NJOINT (the number of joints), and that the best-fit displacement vector d is a linear function of f. Let NNODES denote the number of positions on the surface of the truss where error influences are measured. The solution of the problem is discussed. To classify, this problem was compared to a similar combinatorial optimization problem. In particular, when only the member length errors are considered, minimizing d(sup 2)(sub rms) is equivalent to the quadratic assignment problem. The quadratic assignment problem is a well known NP-complete problem in operations research literature. Hence minimizing d(sup 2)(sub rms) is is also an NP-complete problem. The focus of the research is the development of a simulated annealing algorithm to reduce d(sup 2)(sub rms). The plausibility of this technique is its recent success on a variety of NP-complete combinatorial optimization problems including the quadratic assignment problem. A physical analogy for simulated annealing is the way liquids freeze and crystallize. All computational experiments were done on a MicroVAX. The two interchange heuristic is very fast but produces widely varying results. The two and three interchange heuristic provides less variability in the final objective function values but runs much more slowly. Simulated annealing produced the best objective function values for every starting configuration and was faster than the two and three interchange heuristic.

Generalized hamming networks and applications.

PubMed

Koutroumbas, Konstantinos; Kalouptsidis, Nicholas

2005-09-01

In this paper the classical Hamming network is generalized in various ways. First, for the Hamming maxnet, a generalized model is proposed, which covers under its umbrella most of the existing versions of the Hamming Maxnet. The network dynamics are time varying while the commonly used ramp function may be replaced by a much more general non-linear function. Also, the weight parameters of the network are time varying. A detailed convergence analysis is provided. A bound on the number of iterations required for convergence is derived and its distribution functions are given for the cases where the initial values of the nodes of the Hamming maxnet stem from the uniform and the peak distributions. Stabilization mechanisms aiming to prevent the node(s) with the maximum initial value diverging to infinity or decaying to zero are described. Simulations demonstrate the advantages of the proposed extension. Also, a rough comparison between the proposed generalized scheme as well as the original Hamming maxnet and its variants is carried out in terms of the time required for convergence, in hardware implementations. Finally, the other two parts of the Hamming network, namely the competitors generating module and the decoding module, are briefly considered in the framework of various applications such as classification/clustering, vector quantization and function optimization.

Mathematical modeling of Chikungunya fever control

NASA Astrophysics Data System (ADS)

Hincapié-Palacio, Doracelly; Ospina, Juan

2015-05-01

Chikungunya fever is a global concern due to the occurrence of large outbreaks, the presence of persistent arthropathy and its rapid expansion throughout various continents. Globalization and climate change have contributed to the expansion of the geographical areas where mosquitoes Aedes aegypti and Aedes albopictus (Stegomyia) remain. It is necessary to improve the techniques of vector control in the presence of large outbreaks in The American Region. We derive measures of disease control, using a mathematical model of mosquito-human interaction, by means of three scenarios: a) a single vector b) two vectors, c) two vectors and human and non-human reservoirs. The basic reproductive number and critical control measures were deduced by using computer algebra with Maple (Maplesoft Inc, Ontario Canada). Control measures were simulated with parameter values obtained from published data. According to the number of households in high risk areas, the goals of effective vector control to reduce the likelihood of mosquito-human transmission would be established. Besides the two vectors, if presence of other non-human reservoirs were reported, the monthly target of effective elimination of the vector would be approximately double compared to the presence of a single vector. The model shows the need to periodically evaluate the effectiveness of vector control measures.

AAVPG: A vigilant vector where transgene expression is induced by p53

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bajgelman, Marcio C.; Medrano, Ruan F.V.; Carvalho, Anna Carolina P.V.

2013-12-15

Using p53 to drive transgene expression from viral vectors may provide on demand expression in response to physiologic stress, such as hypoxia or DNA damage. Here we introduce AAVPG, an adeno-associated viral (AAV) vector where a p53-responsive promoter, termed PG, is used to control transgene expression. In vitro assays show that expression from the AAVPG-luc vector was induced specifically in the presence of functional p53 (1038±202 fold increase, p<0.001). The AAVPG-luc vector was an effective biosensor of p53 activation in response to hypoxia (4.48±0.6 fold increase in the presence of 250 µM CoCl{sub 2}, p<0.001) and biomechanical stress (2.53±0.4 foldmore » increase with stretching, p<0.05). In vivo, the vigilant nature of the AAVPG-luc vector was revealed after treatment of tumor-bearing mice with doxorubicin (pre-treatment, 3.4×10{sup 5}±0.43×10{sup 5} photons/s; post-treatment, 6.6×10{sup 5}±2.1×10{sup 5} photons/s, p<0.05). These results indicate that the AAVPG vector is an interesting option for detecting p53 activity both in vitro and in vivo. - Highlights: • AAV vector where transgene expression is controlled by the tumor suppressor p53. • The new vector, AAVPG, shown to function as a biosensor of p53 activity, in vitro and in vivo. • The p53 activity monitored by the AAVPG vector is relevant to cancer and other diseases. • AAVPG reporter gene expression was activated upon DNA damage, hypoxia and mechanical stress.« less

Removing Ambiguities In Remotely Sensed Winds

NASA Technical Reports Server (NTRS)

Shaffer, Scott J.; Dunbar, Roy S.; Hsiao, Shuchi V.; Long, David G.

1991-01-01

Algorithm removes ambiguities in choices of candidate ocean-surface wind vectors estimated from measurements of radar backscatter from ocean waves. Increases accuracies of estimates of winds without requiring new instrumentation. Incorporates vector-median filtering function.

Numerical flux formulas for the Euler and Navier-Stokes equations. 2: Progress in flux-vector splitting

NASA Technical Reports Server (NTRS)

Coirier, William J.; Vanleer, Bram

1991-01-01

The accuracy of various numerical flux functions for the inviscid fluxes when used for Navier-Stokes computations is studied. The flux functions are benchmarked for solutions of the viscous, hypersonic flow past a 10 degree cone at zero angle of attack using first order, upwind spatial differencing. The Harten-Lax/Roe flux is found to give a good boundary layer representation, although its robustness is an issue. Some hybrid flux formulas, where the concepts of flux-vector and flux-difference splitting are combined, are shown to give unsatisfactory pressure distributions; there is still room for improvement. Investigations of low diffusion, pure flux-vector splittings indicate that a pure flux-vector splitting can be developed that eliminates spurious diffusion across the boundary layer. The resulting first-order scheme is marginally stable and not monotone.

Cationic liposome/DNA complexes: from structure to interactions with cellular membranes.

PubMed

Caracciolo, Giulio; Amenitsch, Heinz

2012-10-01

Gene-based therapeutic approaches are based upon the concept that, if a disease is caused by a mutation in a gene, then adding back the wild-type gene should restore regular function and attenuate the disease phenotype. To deliver the gene of interest, both viral and nonviral vectors are used. Viruses are efficient, but their application is impeded by detrimental side-effects. Among nonviral vectors, cationic liposomes are the most promising candidates for gene delivery. They form stable complexes with polyanionic DNA (lipoplexes). Despite several advantages over viral vectors, the transfection efficiency (TE) of lipoplexes is too low compared with those of engineered viral vectors. This is due to lack of knowledge about the interactions between complexes and cellular components. Rational design of efficient lipoplexes therefore requires deeper comprehension of the interactions between the vector and the DNA as well as the cellular pathways and mechanisms involved. The importance of the lipoplex structure in biological function is revealed in the application of synchrotron small-angle X-ray scattering in combination with functional TE measurements. According to current understanding, the structure of lipoplexes can change upon interaction with cellular membranes and such changes affect the delivery efficiency. Recently, a correlation between the mechanism of gene release from complexes, the structure, and the physical and chemical parameters of the complexes has been established. Studies aimed at correlating structure and activity of lipoplexes are reviewed herein. This is a fundamental step towards rational design of highly efficient lipid gene vectors.

A Foxtail mosaic virus Vector for Virus-Induced Gene Silencing in Maize.

PubMed

Mei, Yu; Zhang, Chunquan; Kernodle, Bliss M; Hill, John H; Whitham, Steven A

2016-06-01

Plant viruses have been widely used as vectors for foreign gene expression and virus-induced gene silencing (VIGS). A limited number of viruses have been developed into viral vectors for the purposes of gene expression or VIGS in monocotyledonous plants, and among these, the tripartite viruses Brome mosaic virus and Cucumber mosaic virus have been shown to induce VIGS in maize (Zea mays). We describe here a new DNA-based VIGS system derived from Foxtail mosaic virus (FoMV), a monopartite virus that is able to establish systemic infection and silencing of endogenous maize genes homologous to gene fragments inserted into the FoMV genome. To demonstrate VIGS applications of this FoMV vector system, four genes, phytoene desaturase (functions in carotenoid biosynthesis), lesion mimic22 (encodes a key enzyme of the porphyrin pathway), iojap (functions in plastid development), and brown midrib3 (caffeic acid O-methyltransferase), were silenced and characterized in the sweet corn line Golden × Bantam. Furthermore, we demonstrate that the FoMV infectious clone establishes systemic infection in maize inbred lines, sorghum (Sorghum bicolor), and green foxtail (Setaria viridis), indicating the potential wide applications of this viral vector system for functional genomics studies in maize and other monocots. © 2016 American Society of Plant Biologists. All Rights Reserved.

A Foxtail mosaic virus Vector for Virus-Induced Gene Silencing in Maize1[OPEN

PubMed Central

Mei, Yu; Kernodle, Bliss M.; Hill, John H.

2016-01-01

Plant viruses have been widely used as vectors for foreign gene expression and virus-induced gene silencing (VIGS). A limited number of viruses have been developed into viral vectors for the purposes of gene expression or VIGS in monocotyledonous plants, and among these, the tripartite viruses Brome mosaic virus and Cucumber mosaic virus have been shown to induce VIGS in maize (Zea mays). We describe here a new DNA-based VIGS system derived from Foxtail mosaic virus (FoMV), a monopartite virus that is able to establish systemic infection and silencing of endogenous maize genes homologous to gene fragments inserted into the FoMV genome. To demonstrate VIGS applications of this FoMV vector system, four genes, phytoene desaturase (functions in carotenoid biosynthesis), lesion mimic22 (encodes a key enzyme of the porphyrin pathway), iojap (functions in plastid development), and brown midrib3 (caffeic acid O-methyltransferase), were silenced and characterized in the sweet corn line Golden × Bantam. Furthermore, we demonstrate that the FoMV infectious clone establishes systemic infection in maize inbred lines, sorghum (Sorghum bicolor), and green foxtail (Setaria viridis), indicating the potential wide applications of this viral vector system for functional genomics studies in maize and other monocots. PMID:27208311

Poly-functional and long-lasting anticancer immune response elicited by a safe attenuated Pseudomonas aeruginosa vector for antigens delivery

PubMed Central

Chauchet, Xavier; Hannani, Dalil; Djebali, Sophia; Laurin, David; Polack, Benoit; Marvel, Jacqueline; Buffat, Laurent; Toussaint, Bertrand; Le Gouëllec, Audrey

2016-01-01

Live-attenuated bacterial vectors for antigens delivery have aroused growing interest in the field of cancer immunotherapy. Their potency to stimulate innate immunity and to promote intracellular antigen delivery into antigen-presenting cells could be exploited to elicit a strong and specific cellular immune response against tumor cells. We previously described genetically-modified and attenuated Pseudomonas aeruginosa vectors able to deliver in vivo protein antigens into antigen-presenting cells, through Type 3 secretion system of the bacteria. Using this approach, we managed to protect immunized mice against aggressive B16 melanoma development in both a prophylactic and therapeutic setting. In this study, we further investigated the antigen-specific CD8+ T cell response, in terms of phenotypic and functional aspects, obtained after immunizations with a killed but metabolically active P. aeruginosa attenuated vector. We demonstrated that P. aeruginosa vaccine induces a highly functional pool of antigen-specific CD8+ T cell able to infiltrate the tumor. Furthermore, multiple immunizations allowed the development of a long-lasting immune response, represented by a pool of predominantly effector memory cells which protected mice against late tumor challenge. Overall, killed but metabolically active P. aeruginosa vector is a safe and promising approach for active and specific antitumor immunotherapy. PMID:28035332

The hopf algebra of vector fields on complex quantum groups

NASA Astrophysics Data System (ADS)

Drabant, Bernhard; Jurčo, Branislav; Schlieker, Michael; Weich, Wolfgang; Zumino, Bruno

1992-10-01

We derive the equivalence of the complex quantum enveloping algebra and the algebra of complex quantum vector fields for the Lie algebra types A n , B n , C n , and D n by factorizing the vector fields uniquely into a triangular and a unitary part and identifying them with the corresponding elements of the algebra of regular functionals.

Hájek-Rényi inequality for m-asymptotically almost negatively associated random vectors in Hilbert space and applications.

PubMed

Ko, Mi-Hwa

2018-01-01

In this paper, we obtain the Hájek-Rényi inequality and, as an application, we study the strong law of large numbers for H -valued m -asymptotically almost negatively associated random vectors with mixing coefficients [Formula: see text] such that [Formula: see text].

Construction of siRNA/miRNA expression vectors based on a one-step PCR process

PubMed Central

Xu, Jun; Zeng, Jie Qiong; Wan, Gang; Hu, Gui Bin; Yan, Hong; Ma, Li Xin

2009-01-01

Background RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems. Results Here we report an ingenious method to solve traditional problems associated with construction of siRNA/miRNA expression vectors. We synthesized shorter primers (< 50 nucleotides) to generate a linear expression structure by PCR. The PCR products were directly transformed into chemically competent E. coli and converted to functional vectors in vivo via homologous recombination. The positive clones could be easily screened under UV light. Using this method we successfully constructed over 500 functional siRNA/miRNA expression vectors. Sequencing of the vectors confirmed a high accuracy rate. Conclusion This novel, convenient, low-cost and highly efficient approach may be useful for high-throughput assays of RNAi libraries. PMID:19490634

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

Can carbon nanotube fibers achieve the ultimate conductivity?—Coupled-mode analysis for electron transport through the carbon nanotube contact

NASA Astrophysics Data System (ADS)

Xu, Fangbo; Sadrzadeh, Arta; Xu, Zhiping; Yakobson, Boris I.

2013-08-01

Recent measurements of carbon nanotube (CNT) fibers electrical conductivity still show the values lower than that of individual CNTs, by about one magnitude order. The imperfections of manufacturing process and constituent components are described as culprits. What if every segment is made perfect? In this work, we study the quantum conductance through the parallel junction of flawless armchair CNTs using tight-binding method in conjunction with non-equilibrium Green's function approach. Short-range oscillations within the long-range oscillations as well as decaying envelopes are all observed in the computed Fermi-level (low bias) conductance as a function of contact length, L. The propagation of CNTs' Bloch waves is cast in the coupled-mode formalism and helps to reveal the quantum interference nature of various behaviors of conductance. Our analysis shows that the Bloch waves at the Fermi-level propagate through a parallel junction without reflection only at an optimal value of contact length. For quite a long junction, however, the conductance at the Fermi level diminishes due to the perturbation of periodic potential field of close-packed CNTs. Thus, a macroscopic fiber, containing an infinite number of junctions, forms a filter that permits passage of electrons with specific wave vectors, and these wave vectors are determined by the collection of all the junction lengths. We also argue that the energy gap introduced by long junctions can be overcome by small voltage (˜0.04 V) across the whole fiber. Overall, developing long individual all-armchair metallic CNTs serves as a promising way to the manufacture of high-conductivity fibers.

The Bartonella quintana Extracytoplasmic Function Sigma Factor RpoE Has a Role in Bacterial Adaptation to the Arthropod Vector Environment

PubMed Central

Abromaitis, Stephanie

2013-01-01

Bartonella quintana is a vector-borne bacterial pathogen that causes fatal disease in humans. During the infectious cycle, B. quintana transitions from the hemin-restricted human bloodstream to the hemin-rich body louse vector. Because extracytoplasmic function (ECF) sigma factors often regulate adaptation to environmental changes, we hypothesized that a previously unstudied B. quintana ECF sigma factor, RpoE, is involved in the transition from the human host to the body louse vector. The genomic context of B. quintana rpoE identified it as a member of the ECF15 family of sigma factors found only in alphaproteobacteria. ECF15 sigma factors are believed to be the master regulators of the general stress response in alphaproteobacteria. In this study, we examined the B. quintana RpoE response to two stressors that are encountered in the body louse vector environment, a decreased temperature and an increased hemin concentration. We determined that the expression of rpoE is significantly upregulated at the body louse (28°C) versus the human host (37°C) temperature. rpoE expression also was upregulated when B. quintana was exposed to high hemin concentrations. In vitro and in vivo analyses demonstrated that RpoE function is regulated by a mechanism involving the anti-sigma factor NepR and the response regulator PhyR. The ΔrpoE ΔnepR mutant strain of B. quintana established that RpoE-mediated transcription is important in mediating the tolerance of B. quintana to high hemin concentrations. We present the first analysis of an ECF15 sigma factor in a vector-borne human pathogen and conclude that RpoE has a role in the adaptation of B. quintana to the hemin-rich arthropod vector environment. PMID:23564167

An efficient viral vector for functional genomic studies of Prunus fruit trees and its induced resistance to Plum pox virus via silencing of a host factor gene.

PubMed

Cui, Hongguang; Wang, Aiming

2017-03-01

RNA silencing is a powerful technology for molecular characterization of gene functions in plants. A commonly used approach to the induction of RNA silencing is through genetic transformation. A potent alternative is to use a modified viral vector for virus-induced gene silencing (VIGS) to degrade RNA molecules sharing similar nucleotide sequence. Unfortunately, genomic studies in many allogamous woody perennials such as peach are severely hindered because they have a long juvenile period and are recalcitrant to genetic transformation. Here, we report the development of a viral vector derived from Prunus necrotic ringspot virus (PNRSV), a widespread fruit tree virus that is endemic in all Prunus fruit production countries and regions in the world. We show that the modified PNRSV vector, harbouring the sense-orientated target gene sequence of 100-200 bp in length in genomic RNA3, could efficiently trigger the silencing of a transgene or an endogenous gene in the model plant Nicotiana benthamiana. We further demonstrate that the PNRSV-based vector could be manipulated to silence endogenous genes in peach such as eukaryotic translation initiation factor 4E isoform (eIF(iso)4E), a host factor of many potyviruses including Plum pox virus (PPV). Moreover, the eIF(iso)4E-knocked down peach plants were resistant to PPV. This work opens a potential avenue for the control of virus diseases in perennial trees via viral vector-mediated silencing of host factors, and the PNRSV vector may serve as a powerful molecular tool for functional genomic studies of Prunus fruit trees. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

[Discrimination of varieties of borneol using terahertz spectra based on principal component analysis and support vector machine].

PubMed

Li, Wu; Hu, Bing; Wang, Ming-wei

2014-12-01

In the present paper, the terahertz time-domain spectroscopy (THz-TDS) identification model of borneol based on principal component analysis (PCA) and support vector machine (SVM) was established. As one Chinese common agent, borneol needs a rapid, simple and accurate detection and identification method for its different source and being easily confused in the pharmaceutical and trade links. In order to assure the quality of borneol product and guard the consumer's right, quickly, efficiently and correctly identifying borneol has significant meaning to the production and transaction of borneol. Terahertz time-domain spectroscopy is a new spectroscopy approach to characterize material using terahertz pulse. The absorption terahertz spectra of blumea camphor, borneol camphor and synthetic borneol were measured in the range of 0.2 to 2 THz with the transmission THz-TDS. The PCA scores of 2D plots (PC1 X PC2) and 3D plots (PC1 X PC2 X PC3) of three kinds of borneol samples were obtained through PCA analysis, and both of them have good clustering effect on the 3 different kinds of borneol. The value matrix of the first 10 principal components (PCs) was used to replace the original spectrum data, and the 60 samples of the three kinds of borneol were trained and then the unknown 60 samples were identified. Four kinds of support vector machine model of different kernel functions were set up in this way. Results show that the accuracy of identification and classification of SVM RBF kernel function for three kinds of borneol is 100%, and we selected the SVM with the radial basis kernel function to establish the borneol identification model, in addition, in the noisy case, the classification accuracy rates of four SVM kernel function are above 85%, and this indicates that SVM has strong generalization ability. This study shows that PCA with SVM method of borneol terahertz spectroscopy has good classification and identification effects, and provides a new method for species identification of borneol in Chinese medicine.

Balanced multiwavelets with interpolatory property.

PubMed

Li, Baobin; Peng, Lizhong

2011-05-01

Balanced multiwavelets with interpolatory property are discussed in this paper. This kind of multiwavelets can have a sampling property like Shannon's sampling theorem. It has been shown that the corresponding matrix-valued refinable mask has special structure, and an orthogonal multifilter bank {H(z),G(z)} can be reduced to a scalar valued conjugate quadrature filter (CQF) a(z) . But it does not mean that any scalar CQF can form a "good" multifilter bank which can generate a vector-valued refinable function with some degree of smoothness. In the context of balanced multiwavelets, we give the definition of transferring balance order, which a scalar CQF a(z) satisfies, to guarantee that the multiwavelet Ψ generated is balanced. On the basis of the parametrization of a scalar CQF with any length and conditions of transferring balance order, parametrization of multifilter banks which can generate interpolatory multiwavelet and interpolatory scaling function, is gotten. Moreover, some balanced interpolatory multiwavelets have been constructed. Interpolatory analysis-ready multiwavelets (armlets) are also discussed in this paper. It is known that conditions of armlets are easy to validate, compared with balanced multiwavelets. But it will be present that if the corresponding scaling function Φ is interpolatory, the multiwavelet Ψ is balanced of order n if and only if it is an armlet of order n. Finally, the application of balanced multiwavelets with interpolatory property in image processing is also discussed.

Diagnostic nanoparticle targeting of the EGF-receptor in complex biological conditions using single-domain antibodies.

PubMed

Zarschler, K; Prapainop, K; Mahon, E; Rocks, L; Bramini, M; Kelly, P M; Stephan, H; Dawson, K A

2014-06-07

For effective localization of functionalized nanoparticles at diseased tissues such as solid tumours or metastases through biorecognition, appropriate targeting vectors directed against selected tumour biomarkers are a key prerequisite. The diversity of such vector molecules ranges from proteins, including antibodies and fragments thereof, through aptamers and glycans to short peptides and small molecules. Here, we analyse the specific nanoparticle targeting capabilities of two previously suggested peptides (D4 and GE11) and a small camelid single-domain antibody (sdAb), representing potential recognition agents for the epidermal growth factor receptor (EGFR). We investigate specificity by way of receptor RNA silencing techniques and look at increasing complexity in vitro by introducing increasing concentrations of human or bovine serum. Peptides D4 and GE11 proved problematic to employ and conjugation resulted in non-receptor specific uptake into cells. Our results show that sdAb-functionalized particles can effectively target the EGFR, even in more complex bovine and human serum conditions where targeting specificity is largely conserved for increasing serum concentration. In human serum however, an inhibition of overall nanoparticle uptake is observed with increasing protein concentration. For highly affine targeting ligands such as sdAbs, targeting a receptor such as EGFR with low serum competitor abundance, receptor recognition function can still be partially realised in complex conditions. Here, we stress the value of evaluating the targeting efficiency of nanoparticle constructs in realistic biological milieu, prior to more extensive in vivo studies.

Linear Tidal Vestige Found in the WM Sheet

NASA Astrophysics Data System (ADS)

Lee, Jounghun; Kim, Suk; Rey, Soo-Chang

2018-06-01

We present a vestige of the linear tidal influence on the spin orientations of the constituent galaxies of the WM sheet discovered in the vicinity of the Virgo Cluster and the Local Void. The WM sheet is chosen as an optimal target since it has a rectangular parallelepiped-like shape whose three sides are in parallel with the supergalactic Cartesian axes. Determining three probability density functions of the absolute values of the supergalactic Cartesian components of the spin vectors of the WM sheet galaxies, we investigate their alignments with the principal directions of the surrounding large-scale tidal field. When the WM sheet galaxies located in the central region within the distance of 2 h ‑1 Mpc are excluded, the spin vectors of the remaining WM sheet galaxies are found to be weakly aligned, strongly aligned, and strongly anti-aligned with the minor, intermediate, and major principal directions of the surrounding large-scale tidal field, respectively. To examine whether or not the origin of the observed alignment tendency from the WM sheet is the linear tidal effect, we infer the eigenvalues of the linear tidal tensor from the axial ratios of the WM sheet with the help of the Zeldovich approximation and conduct a full analytic evaluation of the prediction of the linear tidal torque model for the three probability density functions. A detailed comparison between the analytical and the observational results reveals a good quantitative agreement not only in the behaviors but also in the amplitudes of the three probability density functions.

Vector-valued Lizorkin-Triebel spaces and sharp trace theory for functions in Sobolev spaces with mixed \\pmb{L_p}-norm for parabolic problems

NASA Astrophysics Data System (ADS)

Weidemaier, P.

2005-06-01

The trace problem on the hypersurface y_n=0 is investigated for a function u=u(y,t) \\in L_q(0,T;W_{\\underline p}^{\\underline m}(\\mathbb R_+^n)) with \\partial_t u \\in L_q(0,T; L_{\\underline p}(\\mathbb R_+^n)), that is, Sobolev spaces with mixed Lebesgue norm L_{\\underline p,q}(\\mathbb R^n_+\\times(0,T))=L_q(0,T;L_{\\underline p}(\\mathbb R_+^n)) are considered; here \\underline p=(p_1,\\dots,p_n) is a vector and \\mathbb R^n_+=\\mathbb R^{n-1} \\times (0,\\infty). Such function spaces are useful in the context of parabolic equations. They allow, in particular, different exponents of summability in space and time. It is shown that the sharp regularity of the trace in the time variable is characterized by the Lizorkin-Triebel space F_{q,p_n}^{1-1/(p_nm_n)}(0,T;L_{\\widetilde{\\underline p}}(\\mathbb R^{n-1})), \\underline p=(\\widetilde{\\underline p},p_n). A similar result is established for first order spatial derivatives of u. These results allow one to determine the exact spaces for the data in the inhomogeneous Dirichlet and Neumann problems for parabolic equations of the second order if the solution is in the space L_q(0,T; W_p^2(\\Omega)) \\cap W_q^1(0,T;L_p(\\Omega)) with p \\le q.

Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression.

PubMed

Ibitoye, Morufu Olusola; Hamzaid, Nur Azah; Abdul Wahab, Ahmad Khairi; Hasnan, Nazirah; Olatunji, Sunday Olusanya; Davis, Glen M

2016-07-19

The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70%) and testing (30%) subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R²) between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE) of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation.

Facile fabrication of eco-friendly nano-mosquitocides: Biophysical characterization and effectiveness on neglected tropical mosquito vectors.

PubMed

Govindarajan, Marimuthu; Hoti, S L; Benelli, Giovanni

2016-12-01

Mosquito (Diptera: Culicidae) vectors are solely responsible for transmitting important diseases such as malaria, dengue, chikungunya, Japanese encephalitis, lymphatic filariasis and Zika virus. Eco-friendly control tools of Culicidae vectors are a priority. In this study, we proposed a facile fabrication process of poly-disperse and stable silver nanoparticles (Ag NPs) using a cheap leaf extract of Ichnocarpus frutescens (Apocyanaceae). Bio-reduced Ag NPs were characterized by UV-vis spectrophotometry, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The acute toxicity of I. frutescens leaf extract and green-synthesized Ag NPs was evaluated against larvae of the malaria vector Anopheles subpictus, the dengue vector Aedes albopictus and the Japanese encephalitis vector Culex tritaeniorhynchus. Compared to the leaf aqueous extract, Ag NPs showed higher toxicity against A. subpictus, A. albopictus, and C. tritaeniorhynchus with LC 50 values of 14.22, 15.84 and 17.26μg/mL, respectively. Ag NPs were found safer to non-target mosquito predators Anisops bouvieri, Diplonychus indicus and Gambusia affinis, with LC 50 values ranging from 636.61 to 2098.61μg/mL. Overall, this research firstly shed light on the mosquitocidal potential of I. frutescens, a potential bio-resource for rapid, cheap and effective synthesis of poly-disperse and highly stable silver nanocrystals. Copyright © 2016 Elsevier Inc. All rights reserved.

Unsymmetric Lanczos model reduction and linear state function observer for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1991-01-01

This report summarizes part of the research work accomplished during the second year of a two-year grant. The research, entitled 'Application of Lanczos Vectors to Control Design of Flexible Structures' concerns various ways to use Lanczos vectors and Krylov vectors to obtain reduced-order mathematical models for use in the dynamic response analyses and in control design studies. This report presents a one-sided, unsymmetric block Lanczos algorithm for model reduction of structural dynamics systems with unsymmetric damping matrix, and a control design procedure based on the theory of linear state function observers to design low-order controllers for flexible structures.

Design and construction of functional AAV vectors.

PubMed

Gray, John T; Zolotukhin, Serge

2011-01-01

Using the basic principles of molecular biology and laboratory techniques presented in this chapter, researchers should be able to create a wide variety of AAV vectors for both clinical and basic research applications. Basic vector design concepts are covered for both protein coding gene expression and small non-coding RNA gene expression cassettes. AAV plasmid vector backbones (available via AddGene) are described, along with critical sequence details for a variety of modular expression components that can be inserted as needed for specific applications. Protocols are provided for assembling the various DNA components into AAV vector plasmids in Escherichia coli, as well as for transferring these vector sequences into baculovirus genomes for large-scale production of AAV in the insect cell production system.

Evaluation of larvicidal activity of Acalypha alnifolia Klein ex Willd. (Euphorbiaceae) leaf extract against the malarial vector, Anopheles stephensi, dengue vector, Aedes aegypti and Bancroftian filariasis vector, Culex quinquefasciatus (Diptera: Culicidae).

PubMed

Kovendan, Kalimuthu; Murugan, Kadarkarai; Vincent, Savariar

2012-02-01

The leaf extract of Acalypha alnifolia with different solvents - hexane, chloroform, ethyl acetate, acetone and methanol - were tested for larvicidal activity against three important mosquitoes such as malarial vector, Anopheles stephensi, dengue vector, Aedes aegypti and Bancroftian filariasis vector, Culex quinquefasciatus. The medicinal plants were collected from the area around Kallar Hills near the Western Ghats, Coimbatore, India. A. alnifolia plant was washed with tap water and shade dried at room temperature. The dried leaves were powdered mechanically using commercial electrical stainless steel blender. The powder 800 g of the leaf material was extract with 2.5 litre of various each organic solvents such as hexane, chloroform, ethyl acetate, acetone, methanol for 8 h using Soxhlet apparatus, and filtered. The crude plant extracts were evaporated to dryness in a rotary vacuum evaporator. The yield of extracts was hexane (8.64 g), chloroform (10.74 g), ethyl acetate (9.14 g), acetone (10.02 g), and methanol (11.43 g). One gram of the each plant residue was dissolved separately in 100 ml of acetone (stock solution) from which different concentrations, i.e., 50, 150, 250, 350 and 450 ppm, was prepared. The hexane, chloroform, ethyl acetate, acetone was moderate considerable mortality; however, the highest larval mortality was methanolic extract observed in three mosquito vectors. The larval mortality was observed after 24 h exposure. No mortality was observed in the control. The early fourth-instar larvae of A. stephensi had values of LC(50) = 197.37, 178.75, 164.34, 149.90 and 125.73 ppm and LC(90) = 477.60, 459.21, 435.07, 416.20 and 395.50 ppm, respectively. The A. aegypti had values of LC(50) = 202.15, 182.58, 160.35, 146.07 and 128.55 ppm and LC(90) = 476.57, 460.83, 440.78, 415.38 and 381.67 ppm, respectively. The C. quinquefasciatus had values of LC(50) = 198.79, 172.48, 151.06, 140.69 and 127.98 ppm and LC(90) = 458.73, 430.66, 418.78, 408.83 and 386.26 ppm, respectively. The results of the leaf extract of A. alnifloia are promising as good larvicidal activity against the mosquito vector, A. stephensi, A. aegypti, C. quinquefasciatus. Therefore, this study provides first report on the larvicidal activities against three species of mosquito vectors of this plant extracts from Southern India.

Coherent states for the relativistic harmonic oscillator

NASA Technical Reports Server (NTRS)

Aldaya, Victor; Guerrero, J.

1995-01-01

Recently we have obtained, on the basis of a group approach to quantization, a Bargmann-Fock-like realization of the Relativistic Harmonic Oscillator as well as a generalized Bargmann transform relating fock wave functions and a set of relativistic Hermite polynomials. Nevertheless, the relativistic creation and annihilation operators satisfy typical relativistic commutation relations of the Lie product (vector-z, vector-z(sup dagger)) approximately equals Energy (an SL(2,R) algebra). Here we find higher-order polarization operators on the SL(2,R) group, providing canonical creation and annihilation operators satisfying the Lie product (vector-a, vector-a(sup dagger)) = identity vector 1, the eigenstates of which are 'true' coherent states.

Flux vector splitting of the inviscid equations with application to finite difference methods

NASA Technical Reports Server (NTRS)

Steger, J. L.; Warming, R. F.

1979-01-01

The conservation-law form of the inviscid gasdynamic equations has the remarkable property that the nonlinear flux vectors are homogeneous functions of degree one. This property readily permits the splitting of flux vectors into subvectors by similarity transformations so that each subvector has associated with it a specified eigenvalue spectrum. As a consequence of flux vector splitting, new explicit and implicit dissipative finite-difference schemes are developed for first-order hyperbolic systems of equations. Appropriate one-sided spatial differences for each split flux vector are used throughout the computational field even if the flow is locally subsonic. The results of some preliminary numerical computations are included.

BPS/CFT Correspondence III: Gauge Origami Partition Function and qq-Characters

NASA Astrophysics Data System (ADS)

Nekrasov, Nikita

2018-03-01

We study generalized gauge theories engineered by taking the low energy limit of the Dp branes wrapping {X × {T}^{p-3}}, with X a possibly singular surface in a Calabi-Yau fourfold Z. For toric Z and X the partition function can be computed by localization, making it a statistical mechanical model, called the gauge origami. The random variables are the ensembles of Young diagrams. The building block of the gauge origami is associated with a tetrahedron, whose edges are colored by vector spaces. We show the properly normalized partition function is an entire function of the Coulomb moduli, for generic values of the {Ω} -background parameters. The orbifold version of the theory defines the qq-character operators, with and without the surface defects. The analytic properties are the consequence of a relative compactness of the moduli spaces M({ěc n}, k) of crossed and spiked instantons, demonstrated in "BPS/CFT correspondence II: instantons at crossroads, moduli and compactness theorem".

Treatment for meibomian gland dysfunction and dry eye symptoms with a single-dose vectored thermal pulsation: a review.

PubMed

Blackie, Caroline A; Carlson, Alan N; Korb, Donald R

2015-07-01

Meibomian gland dysfunction (MGD) is understood to be a highly prevalent, chronic progressive disease and the leading cause of dry eye. All available published peer-reviewed results of the novel vectored thermal pulsation therapy for patients with MGD are investigated. The PubMed and meeting abstract search revealed a total of 31 peer-reviewed reports on vectored thermal pulsation therapy at the time of the search (eight manuscripts and 23 meeting abstracts). All manuscripts evidence a significant increase in meibomian gland function (∼3×) and symptom improvement post a single 12-min treatment. Additional reported objective measures such as osmolarity, tear break-up time, or lipid layer thickness also increased as a result of the therapy; however, not all findings were statistically significant. The randomized controlled studies evidence sustained gland function and symptom relief lasting out to 12 months. The uncontrolled case series evidence significantly longer duration of effect. A single 12 minute vectored thermal pulsation treatment allows for reducing dry eye symptoms, improving meibomian gland function and other correlates of the ocular surface health.

A cost-function approach to rival penalized competitive learning (RPCL).

PubMed

Ma, Jinwen; Wang, Taijun

2006-08-01

Rival penalized competitive learning (RPCL) has been shown to be a useful tool for clustering on a set of sample data in which the number of clusters is unknown. However, the RPCL algorithm was proposed heuristically and is still in lack of a mathematical theory to describe its convergence behavior. In order to solve the convergence problem, we investigate it via a cost-function approach. By theoretical analysis, we prove that a general form of RPCL, called distance-sensitive RPCL (DSRPCL), is associated with the minimization of a cost function on the weight vectors of a competitive learning network. As a DSRPCL process decreases the cost to a local minimum, a number of weight vectors eventually fall into a hypersphere surrounding the sample data, while the other weight vectors diverge to infinity. Moreover, it is shown by the theoretical analysis and simulation experiments that if the cost reduces into the global minimum, a correct number of weight vectors is automatically selected and located around the centers of the actual clusters, respectively. Finally, we apply the DSRPCL algorithms to unsupervised color image segmentation and classification of the wine data.

The optical analogy for vector fields

NASA Technical Reports Server (NTRS)

Parker, E. N. (Editor)

1991-01-01

This paper develops the optical analogy for a general vector field. The optical analogy allows the examination of certain aspects of a vector field that are not otherwise readily accessible. In particular, in the cases of a stationary Eulerian flow v of an ideal fluid and a magnetostatic field B, the vectors v and B have surface loci in common with their curls. The intrinsic discontinuities around local maxima in absolute values of v and B take the form of vortex sheets and current sheets, respectively, the former playing a fundamental role in the development of hydrodyamic turbulence and the latter playing a major role in heating the X-ray coronas of stars and galaxies.

Vertical amplitude phase structure of a low-frequency acoustic field in shallow water

NASA Astrophysics Data System (ADS)

Kuznetsov, G. N.; Lebedev, O. V.; Stepanov, A. N.

2016-11-01

We obtain in integral and analytic form the relations for calculating the amplitude and phase characteristics of an interference structure of orthogonal projections of the oscillation velocity vector in shallow water. For different frequencies and receiver depths, we numerically study the source depth dependences of the effective phase velocities of an equivalent plane wave, the orthogonal projections of the sound pressure phase gradient, and the projections of the oscillation velocity vector. We establish that at low frequencies in zones of interference maxima, independently of source depth, weakly varying effective phase velocity values are observed, which exceed the sound velocity in water by 5-12%. We show that the angles of arrival of the equivalent plane wave and the oscillation velocity vector in the general case differ; however, they virtually coincide in the zone of the interference maximum of the sound pressure under the condition that the horizontal projections of the oscillation velocity appreciably exceed the value of the vertical projection. We give recommendations on using the sound field characteristics in zones with maximum values for solving rangefinding and signal-detection problems.

Edge smoothing for real-time simulation of a polygon face object system as viewed by a moving observer

NASA Technical Reports Server (NTRS)

Lotz, Robert W. (Inventor); Westerman, David J. (Inventor)

1980-01-01

The visual system within an aircraft flight simulation system receives flight data and terrain data which is formated into a buffer memory. The image data is forwarded to an image processor which translates the image data into face vertex vectors Vf, defining the position relationship between the vertices of each terrain object and the aircraft. The image processor then rotates, clips, and projects the image data into two-dimensional display vectors (Vd). A display generator receives the Vd faces, and other image data to provide analog inputs to CRT devices which provide the window displays for the simulated aircraft. The video signal to the CRT devices passes through an edge smoothing device which prolongs the rise time (and fall time) of the video data inversely as the slope of the edge being smoothed. An operational amplifier within the edge smoothing device has a plurality of independently selectable feedback capacitors each having a different value. The values of the capacitors form a series which doubles as a power of two. Each feedback capacitor has a fast switch responsive to the corresponding bit of a digital binary control word for selecting (1) or not selecting (0) that capacitor. The control word is determined by the slope of each edge. The resulting actual feedback capacitance for each edge is the sum of all the selected capacitors and is directly proportional to the value of the binary control word. The output rise time (or fall time) is a function of the feedback capacitance, and is controlled by the slope through the binary control word.

Analysis of the upper massif of the craniofacial with the radial method – practical use

PubMed Central

Lepich, Tomasz; Dąbek, Józefa; Stompel, Daniel; Gielecki, Jerzy S.

2011-01-01

Introduction The analysis of the upper massif of the craniofacial (UMC) is widely used in many fields of science. The aim of the study was to create a high resolution computer system based on a digital information record and on vector graphics, that could enable dimension measuring and evaluation of craniofacial shape using the radial method. Material and methods The study was carried out on 184 skulls, in a good state of preservation, from the early middle ages. The examined skulls were fixed into Molisson's craniostat in the author's own modification. They were directed in space towards the Frankfurt plane and photographed in frontal norm with a digital camera. The parameters describing the plane and dimensional structure of the UMC and orbits were obtained thanks to the computer analysis of the function recordings picturing the craniofacial structures and using software combining raster graphics with vector graphics. Results It was compared mean values of both orbits separately for male and female groups. In female skulls the comparison of the left and right side did not show statistically significant differences. In male group, higher values were observed for the right side. Only the circularity index presented higher values for the left side. Conclusions Computer graphics with the software used for analysing digital pictures of UMC and orbits increase the precision of measurements as well as the calculation possibilities. Recognition of the face in the post mortem examination is crucial for those working on identification in anthropology and criminology laboratories. PMID:22291834

Larvicidal and repellent potential of Zingiber nimmonii (J. Graham) Dalzell (Zingiberaceae) essential oil: an eco-friendly tool against malaria, dengue, and lymphatic filariasis mosquito vectors?

PubMed

Govindarajan, Marimuthu; Rajeswary, Mohan; Arivoli, Subramanian; Tennyson, Samuel; Benelli, Giovanni

2016-05-01

Mosquitoes (Diptera: Culicidae) are important vectors of terms of public health relevance, especially in tropical and sub-tropical regions. The continuous and indiscriminate use of conventional pesticides for the control of mosquito vectors has resulted in the development of resistance and negative impacts on non-target organisms and the environment. Therefore, there is a need for development of effective mosquito control tools. In this study, the larvicidal and repellent activity of Zingiber nimmonii rhizome essential oil (EO) was evaluated against the malaria vector Anopheles stephensi, the dengue vector Aedes aegypti, and the lymphatic filariasis vector Culex quinquefasciatus. The chemical composition of the EO was analyzed by gas chromatography-mass spectroscopy (GC-MS). GC-MS revealed that the Z. nimmonii EO contained at least 33 compounds. Major constituents were myrcene, β-caryophyllene, α-humulene, and α-cadinol. In acute toxicity assays, the EO showed significant toxicity against early third-stage larvae of An. stephensi, Ae. aegypti, and Cx. quinquefasciatus, with LC50 values of 41.19, 44.46, and 48.26 μg/ml, respectively. Repellency bioassays at 1.0, 2.0, and 5.0 mg/cm(2) of Z. nimmonii EO gave 100 % protection up to 120, 150, and 180 min. against An. stephensi, followed by Ae. aegypti (90, 120, and 150 min) and Cx. quinquefasciatus (60, 90, and 120 min). Furthermore, the EO was safer towards two non-target aquatic organisms, Diplonychus indicus and Gambusia affinis, with LC50 values of 3241.53 and 9250.12 μg/ml, respectively. Overall, this research adds basic knowledge to develop newer and safer natural larvicides and repellent from Zingiberaceae plants against malaria, dengue, and filariasis mosquito vectors.

Bluetongue Disease Risk Assessment Based on Observed and Projected Culicoides obsoletus spp. Vector Densities

PubMed Central

Brugger, Katharina; Rubel, Franz

2013-01-01

Bluetongue is an arboviral disease of ruminants causing significant economic losses. Our risk assessment is based on the epidemiological key parameter, the basic reproduction number. It is defined as the number of secondary cases caused by one primary case in a fully susceptible host population, in which values greater than one indicate the possibility, i.e., the risk, for a major disease outbreak. In the course of the Bluetongue virus serotype 8 (BTV-8) outbreak in Europe in 2006 we developed such a risk assessment for the University of Veterinary Medicine Vienna, Austria. Basic reproduction numbers were calculated using a well-known formula for vector-borne diseases considering the population densities of hosts (cattle and small ruminants) and vectors (biting midges of the Culicoides obsoletus spp.) as well as temperature dependent rates. The latter comprise the biting and mortality rate of midges as well as the reciprocal of the extrinsic incubation period. Most important, but generally unknown, is the spatio-temporal distribution of the vector density. Therefore, we established a continuously operating daily monitoring to quantify the seasonal cycle of the vector population by a statistical model. We used cross-correlation maps and Poisson regression to describe vector densities by environmental temperature and precipitation. Our results comprise time series of observed and simulated Culicoides obsoletus spp. counts as well as basic reproduction numbers for the period 2009–2011. For a spatio-temporal risk assessment we projected our results from the location of Vienna to the entire region of Austria. We compiled both daily maps of vector densities and the basic reproduction numbers, respectively. Basic reproduction numbers above one were generally found between June and August except in the mountainous regions of the Alps. The highest values coincide with the locations of confirmed BTV cases. PMID:23560090

High Precision Prediction of Functional Sites in Protein Structures

PubMed Central

Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

2014-01-01

We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

A Guided Tour of Mathematical Methods

NASA Astrophysics Data System (ADS)

Snieder, Roel

2009-04-01

1. Introduction; 2. Dimensional analysis; 3. Power series; 4. Spherical and cylindrical co-ordinates; 5. The gradient; 6. The divergence of a vector field; 7. The curl of a vector field; 8. The theorem of Gauss; 9. The theorem of Stokes; 10. The Laplacian; 11. Conservation laws; 12. Scale analysis; 13. Linear algebra; 14. The Dirac delta function; 15. Fourier analysis; 16. Analytic functions; 17. Complex integration; 18. Green's functions: principles; 19. Green's functions: examples; 20. Normal modes; 21. Potential theory; 22. Cartesian tensors; 23. Perturbation theory; 24. Asymptotic evaluation of integrals; 25. Variational calculus; 26. Epilogue, on power and knowledge; References.

Application of information-retrieval methods to the classification of physical data

NASA Technical Reports Server (NTRS)

Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.

1975-01-01

Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.

Estimation of chaotic coupled map lattices using symbolic vector dynamics

NASA Astrophysics Data System (ADS)

Wang, Kai; Pei, Wenjiang; Cheung, Yiu-ming; Shen, Yi; He, Zhenya

2010-01-01

In [K. Wang, W.J. Pei, Z.Y. He, Y.M. Cheung, Phys. Lett. A 367 (2007) 316], an original symbolic vector dynamics based method has been proposed for initial condition estimation in additive white Gaussian noisy environment. The estimation precision of this estimation method is determined by symbolic errors of the symbolic vector sequence gotten by symbolizing the received signal. This Letter further develops the symbolic vector dynamical estimation method. We correct symbolic errors with backward vector and the estimated values by using different symbols, and thus the estimation precision can be improved. Both theoretical and experimental results show that this algorithm enables us to recover initial condition of coupled map lattice exactly in both noisy and noise free cases. Therefore, we provide novel analytical techniques for understanding turbulences in coupled map lattice.

Comparison of Linear and Nonlinear Processing with Acoustic Vector Sensors

DTIC Science & Technology

2008-09-01

can write the general form of the time invariant vector sensor planewave response as mik rm mv V e = i , (2.21) where mik rxm xmv V e = i , mik rym...ymv V e = i , and mik rzm zmv V e = i . Using the vector geometry defined, the response of each component is defined by cosxm mV V θ= , sin...velocity values relative to the other by the acoustic impedance, ρc, according to Equation (2.19) , e.g. , mik r mpm pm pm Pv V e V cρ = =i

Large-scale production of lentiviral vector in a closed system hollow fiber bioreactor

PubMed Central

Sheu, Jonathan; Beltzer, Jim; Fury, Brian; Wilczek, Katarzyna; Tobin, Steve; Falconer, Danny; Nolta, Jan; Bauer, Gerhard

2015-01-01

Lentiviral vectors are widely used in the field of gene therapy as an effective method for permanent gene delivery. While current methods of producing small scale vector batches for research purposes depend largely on culture flasks, the emergence and popularity of lentiviral vectors in translational, preclinical and clinical research has demanded their production on a much larger scale, a task that can be difficult to manage with the numbers of producer cell culture flasks required for large volumes of vector. To generate a large scale, partially closed system method for the manufacturing of clinical grade lentiviral vector suitable for the generation of induced pluripotent stem cells (iPSCs), we developed a method employing a hollow fiber bioreactor traditionally used for cell expansion. We have demonstrated the growth, transfection, and vector-producing capability of 293T producer cells in this system. Vector particle RNA titers after subsequent vector concentration yielded values comparable to lentiviral iPSC induction vector batches produced using traditional culture methods in 225 cm2 flasks (T225s) and in 10-layer cell factories (CF10s), while yielding a volume nearly 145 times larger than the yield from a T225 flask and nearly three times larger than the yield from a CF10. Employing a closed system hollow fiber bioreactor for vector production offers the possibility of manufacturing large quantities of gene therapy vector while minimizing reagent usage, equipment footprint, and open system manipulation. PMID:26151065

A GaAs vector processor based on parallel RISC microprocessors

NASA Astrophysics Data System (ADS)

Misko, Tim A.; Rasset, Terry L.

A vector processor architecture based on the development of a 32-bit microprocessor using gallium arsenide (GaAs) technology has been developed. The McDonnell Douglas vector processor (MVP) will be fabricated completely from GaAs digital integrated circuits. The MVP architecture includes a vector memory of 1 megabyte, a parallel bus architecture with eight processing elements connected in parallel, and a control processor. The processing elements consist of a reduced instruction set CPU (RISC) with four floating-point coprocessor units and necessary memory interface functions. This architecture has been simulated for several benchmark programs including complex fast Fourier transform (FFT), complex inner product, trigonometric functions, and sort-merge routine. The results of this study indicate that the MVP can process a 1024-point complex FFT at a speed of 112 microsec (389 megaflops) while consuming approximately 618 W of power in a volume of approximately 0.1 ft-cubed.

[Ubiquitination of recombinant adeno-associated viral vector and its application].

PubMed

Wang, Qi-zhao; Lu, Ying-hui; Diao, Yong; Xu, Rui-an

2012-09-01

Recombinant adeno-associated virus (rAAV) has been widely used as vector for gene therapy. However, the effectiveness of gene therapy based on rAAV needs to be further improved. Enhancement of the transduction efficiency is one of the most important fields for rAAV-based gene therapy. Recent results have showed that the ubiquitin-proteasome system plays an important role in the trafficking of rAAV vector in cytoplasm, and regulation of its function may significantly improve the transduction efficiency of rAAV vector in various types of cells and tissues.

New Term Weighting Formulas for the Vector Space Method in Information Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chisholm, E.; Kolda, T.G.

The goal in information retrieval is to enable users to automatically and accurately find data relevant to their queries. One possible approach to this problem i use the vector space model, which models documents and queries as vectors in the term space. The components of the vectors are determined by the term weighting scheme, a function of the frequencies of the terms in the document or query as well as throughout the collection. We discuss popular term weighting schemes and present several new schemes that offer improved performance.

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

PubMed

Ge, Jing; Zhang, Guoping

2015-01-01

Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. To develop a new epileptic seizure detection method based on quantitative DVV. This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Multilayer perceptron, fuzzy sets, and classification

NASA Technical Reports Server (NTRS)

Pal, Sankar K.; Mitra, Sushmita

1992-01-01

A fuzzy neural network model based on the multilayer perceptron, using the back-propagation algorithm, and capable of fuzzy classification of patterns is described. The input vector consists of membership values to linguistic properties while the output vector is defined in terms of fuzzy class membership values. This allows efficient modeling of fuzzy or uncertain patterns with appropriate weights being assigned to the backpropagated errors depending upon the membership values at the corresponding outputs. During training, the learning rate is gradually decreased in discrete steps until the network converges to a minimum error solution. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of the conventional MLP, the Bayes classifier, and the other related models.

Insertion of operation-and-indicate instructions for optimized SIMD code

DOEpatents

Eichenberger, Alexander E; Gara, Alan; Gschwind, Michael K

2013-06-04

Mechanisms are provided for inserting indicated instructions for tracking and indicating exceptions in the execution of vectorized code. A portion of first code is received for compilation. The portion of first code is analyzed to identify non-speculative instructions performing designated non-speculative operations in the first code that are candidates for replacement by replacement operation-and-indicate instructions that perform the designated non-speculative operations and further perform an indication operation for indicating any exception conditions corresponding to special exception values present in vector register inputs to the replacement operation-and-indicate instructions. The replacement is performed and second code is generated based on the replacement of the at least one non-speculative instruction. The data processing system executing the compiled code is configured to store special exception values in vector output registers, in response to a speculative instruction generating an exception condition, without initiating exception handling.

Finite size effects in the thermodynamics of a free neutral scalar field

NASA Astrophysics Data System (ADS)

Parvan, A. S.

2018-04-01

The exact analytical lattice results for the partition function of the free neutral scalar field in one spatial dimension in both the configuration and the momentum space were obtained in the framework of the path integral method. The symmetric square matrices of the bilinear forms on the vector space of fields in both configuration space and momentum space were found explicitly. The exact lattice results for the partition function were generalized to the three-dimensional spatial momentum space and the main thermodynamic quantities were derived both on the lattice and in the continuum limit. The thermodynamic properties and the finite volume corrections to the thermodynamic quantities of the free real scalar field were studied. We found that on the finite lattice the exact lattice results for the free massive neutral scalar field agree with the continuum limit only in the region of small values of temperature and volume. However, at these temperatures and volumes the continuum physical quantities for both massive and massless scalar field deviate essentially from their thermodynamic limit values and recover them only at high temperatures or/and large volumes in the thermodynamic limit.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features.

PubMed

Tripathy, Rajesh Kumar; Dandapat, Samarendra

2017-04-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques.

The rotation of ripple pattern and the shape of the collision cascade in ion sputtered thin metal films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, P.; Ghose, D.

The sputter ripple formation in polycrystalline metal thin films of Al, Co, Cu, and Ag has been studied by 16.7 keV Ar{sup +} and O{sub 2}{sup +} ion bombardment as a function of angle of ion incidence. The experimental results show the existence of a critical angle of ion incidence ({theta}{sub c}) beyond which the ripples of wave vectors perpendicular to the projected ion beam direction appear. Monte Carlo simulation (SRIM) is carried out to calculate the depth, longitudinal and lateral straggling widths of energy deposition as these values are crucial in determining the critical angle {theta}{sub c}. It ismore » found that the radial energy distribution of the damage cascade has the maximum slightly away from the ion path in contradiction to the Gaussian distribution and the distribution is better characterized by an exponential function. The lower values of lateral straggling widths as those extracted from the measured critical angles using the Bradley and Harper theory indicate a highly anisotropic deposited-energy distribution.« less

Equivalent magnetic vector potential model for low-frequency magnetic exposure assessment

NASA Astrophysics Data System (ADS)

Diao, Y. L.; Sun, W. N.; He, Y. Q.; Leung, S. W.; Siu, Y. M.

2017-10-01

In this paper, a novel source model based on a magnetic vector potential for the assessment of induced electric field strength in a human body exposed to the low-frequency (LF) magnetic field of an electrical appliance is presented. The construction of the vector potential model requires only a single-component magnetic field to be measured close to the appliance under test, hence relieving considerable practical measurement effort—the radial basis functions (RBFs) are adopted for the interpolation of discrete measurements; the magnetic vector potential model can then be directly constructed by summing a set of simple algebraic functions of RBF parameters. The vector potentials are then incorporated into numerical calculations as the equivalent source for evaluations of the induced electric field in the human body model. The accuracy and effectiveness of the proposed model are demonstrated by comparing the induced electric field in a human model to that of the full-wave simulation. This study presents a simple and effective approach for modelling the LF magnetic source. The result of this study could simplify the compliance test procedure for assessing an electrical appliance regarding LF magnetic exposure.

pTcGW plasmid vectors 1.1 version: a versatile tool for Trypanosoma cruzi gene characterisation

PubMed Central

Kugeratski, Fernanda G; Batista, Michel; Inoue, Alexandre Haruo; Ramos, Bruno Dias; Krieger, Marco Aurelio; Marchini/, Fabricio K

2015-01-01

The functional characterisation of thousands of Trypanosoma cruzi genes remains a challenge. Reverse genetics approaches compatible with high-throughput cloning strategies can provide the tool needed to tackle this challenge. We previously published the pTcGW platform, composed by plasmid vectors carrying different options of N-terminal fusion tags based on Gateway® technology. Here, we present an improved 1.1 version of pTcGW vectors, which is characterised by a fully flexible structure allowing an easy customisation of each element of the vectors in a single cloning step. Additionally, both N and C-terminal fusions are available with new tag options for protein complexes purification. Three of the newly created vectors were successfully used to determine the cellular localisation of four T. cruzi proteins. The 1.1 version of pTcGW platform can be used in a variety of assays, such as protein overexpression, identification of protein-protein interaction and protein localisation. This powerful and versatile tool allows adding valuable functional information to T. cruzi genes and is freely available for scientific community. PMID:26200713

Structured caustic vector vortex optical field: manipulating optical angular momentum flux and polarization rotation.

PubMed

Chen, Rui-Pin; Chen, Zhaozhong; Chew, Khian-Hooi; Li, Pei-Gang; Yu, Zhongliang; Ding, Jianping; He, Sailing

2015-05-29

A caustic vector vortex optical field is experimentally generated and demonstrated by a caustic-based approach. The desired caustic with arbitrary acceleration trajectories, as well as the structured states of polarization (SoP) and vortex orders located in different positions in the field cross-section, is generated by imposing the corresponding spatial phase function in a vector vortex optical field. Our study reveals that different spin and orbital angular momentum flux distributions (including opposite directions) in different positions in the cross-section of a caustic vector vortex optical field can be dynamically managed during propagation by intentionally choosing the initial polarization and vortex topological charges, as a result of the modulation of the caustic phase. We find that the SoP in the field cross-section rotates during propagation due to the existence of the vortex. The unique structured feature of the caustic vector vortex optical field opens the possibility of multi-manipulation of optical angular momentum fluxes and SoP, leading to more complex manipulation of the optical field scenarios. Thus this approach further expands the functionality of an optical system.

Psi- vectors: murine leukemia virus-based self-inactivating and self-activating retroviral vectors.

PubMed Central

Delviks, K A; Hu, W S; Pathak, V K

1997-01-01

We have developed murine leukemia virus (MLV)-based self-inactivating and self-activating vectors to show that the previously demonstrated high-frequency direct repeat deletions are not unique to spleen necrosis virus (SNV) or the neomycin drug resistance gene. Retroviral vectors pKD-HTTK and pKD-HTpTK containing direct repeats composed of segments of the herpes simplex virus type 1 thymidine kinase (HTK) gene were constructed; in pKD-HTpTK, the direct repeat flanked the MLV packaging signal. The generation of hypoxanthine-aminopterin-thymidine-resistant colonies after one cycle of retroviral replication demonstrated functional reconstitution of the HTK gene. Quantitative Southern analysis indicated that direct repeat deletions occurred in 57 and 91% of the KD-HTTK and KD-HTpTK proviruses, respectively. These results demonstrate that (i) deletion of direct repeats occurs at similar high frequencies in SNV and MLV vectors, (ii) MLV psi can be efficiently deleted by using direct repeats, (iii) suicide genes can be functionally reconstituted during reverse transcription, and (iv) the psi region may be a hot spot for reverse transcriptase template switching events. PMID:9223521

Equivalent magnetic vector potential model for low-frequency magnetic exposure assessment.

PubMed

Diao, Y L; Sun, W N; He, Y Q; Leung, S W; Siu, Y M

2017-09-21

In this paper, a novel source model based on a magnetic vector potential for the assessment of induced electric field strength in a human body exposed to the low-frequency (LF) magnetic field of an electrical appliance is presented. The construction of the vector potential model requires only a single-component magnetic field to be measured close to the appliance under test, hence relieving considerable practical measurement effort-the radial basis functions (RBFs) are adopted for the interpolation of discrete measurements; the magnetic vector potential model can then be directly constructed by summing a set of simple algebraic functions of RBF parameters. The vector potentials are then incorporated into numerical calculations as the equivalent source for evaluations of the induced electric field in the human body model. The accuracy and effectiveness of the proposed model are demonstrated by comparing the induced electric field in a human model to that of the full-wave simulation. This study presents a simple and effective approach for modelling the LF magnetic source. The result of this study could simplify the compliance test procedure for assessing an electrical appliance regarding LF magnetic exposure.