Spline methods for approximating quantile functions and generating random samples

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Matthews, C. G.

1985-01-01

Two cubic spline formulations are presented for representing the quantile function (inverse cumulative distribution function) of a random sample of data. Both B-spline and rational spline approximations are compared with analytic representations of the quantile function. It is also shown how these representations can be used to generate random samples for use in simulation studies. Comparisons are made on samples generated from known distributions and a sample of experimental data. The spline representations are more accurate for multimodal and skewed samples and to require much less time to generate samples than the analytic representation.

Incorporating Objective Function Information Into the Feasibility Rule for Constrained Evolutionary Optimization.

PubMed

Wang, Yong; Wang, Bing-Chuan; Li, Han-Xiong; Yen, Gary G

2016-12-01

When solving constrained optimization problems by evolutionary algorithms, an important issue is how to balance constraints and objective function. This paper presents a new method to address the above issue. In our method, after generating an offspring for each parent in the population by making use of differential evolution (DE), the well-known feasibility rule is used to compare the offspring and its parent. Since the feasibility rule prefers constraints to objective function, the objective function information has been exploited as follows: if the offspring cannot survive into the next generation and if the objective function value of the offspring is better than that of the parent, then the offspring is stored into a predefined archive. Subsequently, the individuals in the archive are used to replace some individuals in the population according to a replacement mechanism. Moreover, a mutation strategy is proposed to help the population jump out of a local optimum in the infeasible region. Note that, in the replacement mechanism and the mutation strategy, the comparison of individuals is based on objective function. In addition, the information of objective function has also been utilized to generate offspring in DE. By the above processes, this paper achieves an effective balance between constraints and objective function in constrained evolutionary optimization. The performance of our method has been tested on two sets of benchmark test functions, namely, 24 test functions at IEEE CEC2006 and 18 test functions with 10-D and 30-D at IEEE CEC2010. The experimental results have demonstrated that our method shows better or at least competitive performance against other state-of-the-art methods. Furthermore, the advantage of our method increases with the increase of the number of decision variables.

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure.

PubMed

Zhou, Yang; Wu, Dewei

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT).

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure

PubMed Central

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT). PMID:27597859

Efficient and Controlled Generation of 2D and 3D Bile Duct Tissue from Human Pluripotent Stem Cell-Derived Spheroids.

PubMed

Tian, Lipeng; Deshmukh, Abhijeet; Ye, Zhaohui; Jang, Yoon-Young

2016-08-01

While in vitro liver tissue engineering has been increasingly studied during the last several years, presently engineered liver tissues lack the bile duct system. The lack of bile drainage not only hinders essential digestive functions of the liver, but also leads to accumulation of bile that is toxic to hepatocytes and known to cause liver cirrhosis. Clearly, generation of bile duct tissue is essential for engineering functional and healthy liver. Differentiation of human induced pluripotent stem cells (iPSCs) to bile duct tissue requires long and/or complex culture conditions, and has been inefficient so far. Towards generating a fully functional liver containing biliary system, we have developed defined and controlled conditions for efficient 2D and 3D bile duct epithelial tissue generation. A marker for multipotent liver progenitor in both adult human liver and ductal plate in human fetal liver, EpCAM, is highly expressed in hepatic spheroids generated from human iPSCs. The EpCAM high hepatic spheroids can, not only efficiently generate a monolayer of biliary epithelial cells (cholangiocytes), in a 2D differentiation condition, but also form functional ductal structures in a 3D condition. Importantly, this EpCAM high spheroid based biliary tissue generation is significantly faster than other existing methods and does not require cell sorting. In addition, we show that a knock-in CK7 reporter human iPSC line generated by CRISPR/Cas9 genome editing technology greatly facilitates the analysis of biliary differentiation. This new ductal differentiation method will provide a more efficient method of obtaining bile duct cells and tissues, which may facilitate engineering of complete and functional liver tissue in the future.

Experiences on developing digital down conversion algorithms using Xilinx system generator

NASA Astrophysics Data System (ADS)

Xu, Chengfa; Yuan, Yuan; Zhao, Lizhi

2013-07-01

The Digital Down Conversion (DDC) algorithm is a classical signal processing method which is widely used in radar and communication systems. In this paper, the DDC function is implemented by Xilinx System Generator tool on FPGA. System Generator is an FPGA design tool provided by Xilinx Inc and MathWorks Inc. It is very convenient for programmers to manipulate the design and debug the function, especially for the complex algorithm. Through the developing process of DDC function based on System Generator, the results show that System Generator is a very fast and efficient tool for FPGA design.

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Shih, T. I-P.; Roelke, R. J.

1991-01-01

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

Random phase encoding for optical security

NASA Astrophysics Data System (ADS)

Wang, RuiKang K.; Watson, Ian A.; Chatwin, Christopher R.

1996-09-01

A new optical encoding method for security applications is proposed. The encoded image (encrypted into the security products) is merely a random phase image statistically and randomly generated by a random number generator using a computer, which contains no information from the reference pattern (stored for verification) or the frequency plane filter (a phase-only function for decoding). The phase function in the frequency plane is obtained using a modified phase retrieval algorithm. The proposed method uses two phase-only functions (images) at both the input and frequency planes of the optical processor leading to maximum optical efficiency. Computer simulation shows that the proposed method is robust for optical security applications.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1995-10-17

A method and system for monitoring an industrial process and a sensor are disclosed. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1997-05-13

A method and system are disclosed for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1995-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1997-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

Generation of Stationary Non-Gaussian Time Histories with a Specified Cross-spectral Density

DOE PAGES

Smallwood, David O.

1997-01-01

The paper reviews several methods for the generation of stationary realizations of sampled time histories with non-Gaussian distributions and introduces a new method which can be used to control the cross-spectral density matrix and the probability density functions (pdfs) of the multiple input problem. Discussed first are two methods for the specialized case of matching the auto (power) spectrum, the skewness, and kurtosis using generalized shot noise and using polynomial functions. It is then shown that the skewness and kurtosis can also be controlled by the phase of a complex frequency domain description of the random process. The general casemore » of matching a target probability density function using a zero memory nonlinear (ZMNL) function is then covered. Next methods for generating vectors of random variables with a specified covariance matrix for a class of spherically invariant random vectors (SIRV) are discussed. Finally the general case of matching the cross-spectral density matrix of a vector of inputs with non-Gaussian marginal distributions is presented.« less

Exploiting the functional and taxonomic structure of genomic data by probabilistic topic modeling.

PubMed

Chen, Xin; Hu, Xiaohua; Lim, Tze Y; Shen, Xiajiong; Park, E K; Rosen, Gail L

2012-01-01

In this paper, we present a method that enable both homology-based approach and composition-based approach to further study the functional core (i.e., microbial core and gene core, correspondingly). In the proposed method, the identification of major functionality groups is achieved by generative topic modeling, which is able to extract useful information from unlabeled data. We first show that generative topic model can be used to model the taxon abundance information obtained by homology-based approach and study the microbial core. The model considers each sample as a “document,” which has a mixture of functional groups, while each functional group (also known as a “latent topic”) is a weight mixture of species. Therefore, estimating the generative topic model for taxon abundance data will uncover the distribution over latent functions (latent topic) in each sample. Second, we show that, generative topic model can also be used to study the genome-level composition of “N-mer” features (DNA subreads obtained by composition-based approaches). The model consider each genome as a mixture of latten genetic patterns (latent topics), while each functional pattern is a weighted mixture of the “N-mer” features, thus the existence of core genomes can be indicated by a set of common N-mer features. After studying the mutual information between latent topics and gene regions, we provide an explanation of the functional roles of uncovered latten genetic patterns. The experimental results demonstrate the effectiveness of proposed method.

A grid spacing control technique for algebraic grid generation methods

NASA Technical Reports Server (NTRS)

Smith, R. E.; Kudlinski, R. A.; Everton, E. L.

1982-01-01

A technique which controls the spacing of grid points in algebraically defined coordinate transformations is described. The technique is based on the generation of control functions which map a uniformly distributed computational grid onto parametric variables defining the physical grid. The control functions are smoothed cubic splines. Sets of control points are input for each coordinate directions to outline the control functions. Smoothed cubic spline functions are then generated to approximate the input data. The technique works best in an interactive graphics environment where control inputs and grid displays are nearly instantaneous. The technique is illustrated with the two-boundary grid generation algorithm.

The neural component-process architecture of endogenously generated emotion

PubMed Central

Kanske, Philipp; Singer, Tania

2017-01-01

Abstract Despite the ubiquity of endogenous emotions and their role in both resilience and pathology, the processes supporting their generation are largely unknown. We propose a neural component process model of endogenous generation of emotion (EGE) and test it in two functional magnetic resonance imaging (fMRI) experiments (N = 32/293) where participants generated and regulated positive and negative emotions based on internal representations, usin self-chosen generation methods. EGE activated nodes of salience (SN), default mode (DMN) and frontoparietal control (FPCN) networks. Component processes implemented by these networks were established by investigating their functional associations, activation dynamics and integration. SN activation correlated with subjective affect, with midbrain nodes exclusively distinguishing between positive and negative affect intensity, showing dynamics consistent generation of core affect. Dorsomedial DMN, together with ventral anterior insula, formed a pathway supporting multiple generation methods, with activation dynamics suggesting it is involved in the generation of elaborated experiential representations. SN and DMN both coupled to left frontal FPCN which in turn was associated with both subjective affect and representation formation, consistent with FPCN supporting the executive coordination of the generation process. These results provide a foundation for research into endogenous emotion in normal, pathological and optimal function. PMID:27522089

Inventing and improving ribozyme function: rational design versus iterative selection methods

NASA Technical Reports Server (NTRS)

Breaker, R. R.; Joyce, G. F.

1994-01-01

Two major strategies for generating novel biological catalysts exist. One relies on our knowledge of biopolymer structure and function to aid in the 'rational design' of new enzymes. The other, often called 'irrational design', aims to generate new catalysts, in the absence of detailed physicochemical knowledge, by using selection methods to search a library of molecules for functional variants. Both strategies have been applied, with considerable success, to the remodeling of existing ribozymes and the development of ribozymes with novel catalytic function. The two strategies are by no means mutually exclusive, and are best applied in a complementary fashion to obtain ribozymes with the desired catalytic properties.

Optimal trajectory generation for mechanical arms. M.S. Thesis

NASA Technical Reports Server (NTRS)

Iemenschot, J. A.

1972-01-01

A general method of generating optimal trajectories between an initial and a final position of an n degree of freedom manipulator arm with nonlinear equations of motion is proposed. The method is based on the assumption that the time history of each of the coordinates can be expanded in a series of simple time functions. By searching over the coefficients of the terms in the expansion, trajectories which minimize the value of a given cost function can be obtained. The method has been applied to a planar three degree of freedom arm.

Scenario generation for stochastic optimization problems via the sparse grid method

DOE PAGES

Chen, Michael; Mehrotra, Sanjay; Papp, David

2015-04-19

We study the use of sparse grids in the scenario generation (or discretization) problem in stochastic programming problems where the uncertainty is modeled using a continuous multivariate distribution. We show that, under a regularity assumption on the random function involved, the sequence of optimal objective function values of the sparse grid approximations converges to the true optimal objective function values as the number of scenarios increases. The rate of convergence is also established. We treat separately the special case when the underlying distribution is an affine transform of a product of univariate distributions, and show how the sparse grid methodmore » can be adapted to the distribution by the use of quadrature formulas tailored to the distribution. We numerically compare the performance of the sparse grid method using different quadrature rules with classic quasi-Monte Carlo (QMC) methods, optimal rank-one lattice rules, and Monte Carlo (MC) scenario generation, using a series of utility maximization problems with up to 160 random variables. The results show that the sparse grid method is very efficient, especially if the integrand is sufficiently smooth. In such problems the sparse grid scenario generation method is found to need several orders of magnitude fewer scenarios than MC and QMC scenario generation to achieve the same accuracy. As a result, it is indicated that the method scales well with the dimension of the distribution--especially when the underlying distribution is an affine transform of a product of univariate distributions, in which case the method appears scalable to thousands of random variables.« less

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

A Model for Minimizing Numeric Function Generator Complexity and Delay

DTIC Science & Technology

2007-12-01

allow computation of difficult mathematical functions in less time and with less hardware than commonly employed methods. They compute piecewise...Programmable Gate Arrays (FPGAs). The algorithms and estimation techniques apply to various NFG architectures and mathematical functions. This...thesis compares hardware utilization and propagation delay for various NFG architectures, mathematical functions, word widths, and segmentation methods

Random Item Generation Is Affected by Age

ERIC Educational Resources Information Center

Multani, Namita; Rudzicz, Frank; Wong, Wing Yiu Stephanie; Namasivayam, Aravind Kumar; van Lieshout, Pascal

2016-01-01

Purpose: Random item generation (RIG) involves central executive functioning. Measuring aspects of random sequences can therefore provide a simple method to complement other tools for cognitive assessment. We examine the extent to which RIG relates to specific measures of cognitive function, and whether those measures can be estimated using RIG…

Programmable Numerical Function Generators: Architectures and Synthesis Method

DTIC Science & Technology

2005-08-01

generates HDL (Hardware Descrip- tion Language) code from the design specification described by Scilab [14], a MATLAB-like numerical calculation soft...cad.com/Error-NFG/. [14] Scilab 3.0, INRIA-ENPC, France, http://scilabsoft.inria.fr/ [15] M. J. Schulte and J. E. Stine, “Approximating elementary functions

Amplitude Frequency Response Measurement: A Simple Technique

ERIC Educational Resources Information Center

Satish, L.; Vora, S. C.

2010-01-01

A simple method is described to combine a modern function generator and a digital oscilloscope to configure a setup that can directly measure the amplitude frequency response of a system. This is achieved by synchronously triggering both instruments, with the function generator operated in the "Linear-Sweep" frequency mode, while the oscilloscope…

Scaling properties of the aerodynamic noise generated by low-speed fans

NASA Astrophysics Data System (ADS)

Canepa, Edward; Cattanei, Andrea; Mazzocut Zecchin, Fabio

2017-11-01

The spectral decomposition algorithm presented in the paper may be applied to selected parts of the SPL spectrum, i.e. to specific noise generating mechanisms. It yields the propagation and the generation functions, and indeed the Mach number scaling exponent associated with each mechanism as a function of the Strouhal number. The input data are SPL spectra obtained from measurements taken during speed ramps. Firstly, the basic theory and the implemented algorithm are described. Then, the behaviour of the new method is analysed with reference to numerically generated spectral data and the results are compared with the ones of an existing method based on the assumption that the scaling exponent is constant. Guidelines for the employment of both methods are provided. Finally, the method is applied to measurements taken on a cooling fan mounted on a test plenum designed following the ISO 10302 standards. The most common noise generating mechanisms are present and attention is focused on the low-frequency part of the spectrum, where the mechanisms are superposed. Generally, both propagation and generation functions are determined with better accuracy than the scaling exponent, whose values are usually consistent with expectations based on coherence and compactness of the acoustic sources. For periodic noise, the computed exponent is less accurate, as the related SPL data set has usually a limited size. The scaling exponent is very sensitive to the details of the experimental data, e.g. to slight inconsistencies or random errors.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

PubMed

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

NASA Astrophysics Data System (ADS)

Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

2018-03-01

Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

Dynamic Mesh Adaptation for Front Evolution Using Discontinuous Galerkin Based Weighted Condition Number Mesh Relaxation

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

Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

2016-06-21

A new mesh smoothing method designed to cluster mesh cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function being computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered elds, such as amore » volume fraction or index function, is provided. Results show that the low-order level set works equally well for the weight function as the actual level set. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Dynamic cases for moving interfaces are presented to demonstrate the method's potential usefulness to arbitrary Lagrangian Eulerian (ALE) methods.« less

Membership generation using multilayer neural network

NASA Technical Reports Server (NTRS)

Kim, Jaeseok

1992-01-01

There has been intensive research in neural network applications to pattern recognition problems. Particularly, the back-propagation network has attracted many researchers because of its outstanding performance in pattern recognition applications. In this section, we describe a new method to generate membership functions from training data using a multilayer neural network. The basic idea behind the approach is as follows. The output values of a sigmoid activation function of a neuron bear remarkable resemblance to membership values. Therefore, we can regard the sigmoid activation values as the membership values in fuzzy set theory. Thus, in order to generate class membership values, we first train a suitable multilayer network using a training algorithm such as the back-propagation algorithm. After the training procedure converges, the resulting network can be treated as a membership generation network, where the inputs are feature values and the outputs are membership values in the different classes. This method allows fairly complex membership functions to be generated because the network is highly nonlinear in general. Also, it is to be noted that the membership functions are generated from a classification point of view. For pattern recognition applications, this is highly desirable, although the membership values may not be indicative of the degree of typicality of a feature value in a particular class.

Methods for selective functionalization and separation of carbon nanotubes

NASA Technical Reports Server (NTRS)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

2011-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Conjugate gradient minimisation approach to generating holographic traps for ultracold atoms.

PubMed

Harte, Tiffany; Bruce, Graham D; Keeling, Jonathan; Cassettari, Donatella

2014-11-03

Direct minimisation of a cost function can in principle provide a versatile and highly controllable route to computational hologram generation. Here we show that the careful design of cost functions, combined with numerically efficient conjugate gradient minimisation, establishes a practical method for the generation of holograms for a wide range of target light distributions. This results in a guided optimisation process, with a crucial advantage illustrated by the ability to circumvent optical vortex formation during hologram calculation. We demonstrate the implementation of the conjugate gradient method for both discrete and continuous intensity distributions and discuss its applicability to optical trapping of ultracold atoms.

Elliptic surface grid generation in three-dimensional space

NASA Technical Reports Server (NTRS)

Kania, Lee

1992-01-01

A methodology for surface grid generation in three dimensional space is described. The method solves a Poisson equation for each coordinate on arbitrary surfaces using successive line over-relaxation. The complete surface curvature terms were discretized and retained within the nonhomogeneous term in order to preserve surface definition; there is no need for conventional surface splines. Control functions were formulated to permit control of grid orthogonality and spacing. A method for interpolation of control functions into the domain was devised which permits their specification not only at the surface boundaries but within the interior as well. An interactive surface generation code which makes use of this methodology is currently under development.

Computerized Method for the Generation of Molecular Transmittance Functions in the Infrared.

DTIC Science & Technology

1980-04-01

predict this behavior, we conclude that the first method using linear function of x is accurate enough to be used in the actual application. The...PIECEWISE- ANALITICAL TRANSMISSION FUNCTION.’//20X, * ’STANDARD DEVIATIONS BETWEEN THE ACTUAL TAU AND THE RECOMPUTED’, * ’ TAU VALUES ARE COMPUTED.’////) 77

New method for estimating low-earth-orbit collision probabilities

NASA Technical Reports Server (NTRS)

Vedder, John D.; Tabor, Jill L.

1991-01-01

An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.

Threshold matrix for digital halftoning by genetic algorithm optimization

NASA Astrophysics Data System (ADS)

Alander, Jarmo T.; Mantere, Timo J.; Pyylampi, Tero

1998-10-01

Digital halftoning is used both in low and high resolution high quality printing technologies. Our method is designed to be mainly used for low resolution ink jet marking machines to produce both gray tone and color images. The main problem with digital halftoning is pink noise caused by the human eye's visual transfer function. To compensate for this the random dot patterns used are optimized to contain more blue than pink noise. Several such dot pattern generator threshold matrices have been created automatically by using genetic algorithm optimization, a non-deterministic global optimization method imitating natural evolution and genetics. A hybrid of genetic algorithm with a search method based on local backtracking was developed together with several fitness functions evaluating dot patterns for rectangular grids. By modifying the fitness function, a family of dot generators results, each with its particular statistical features. Several versions of genetic algorithms, backtracking and fitness functions were tested to find a reasonable combination. The generated threshold matrices have been tested by simulating a set of test images using the Khoros image processing system. Even though the work was focused on developing low resolution marking technology, the resulting family of dot generators can be applied also in other halftoning application areas including high resolution printing technology.

Reactive Power Compensation Method Considering Minimum Effective Reactive Power Reserve

NASA Astrophysics Data System (ADS)

Gong, Yiyu; Zhang, Kai; Pu, Zhang; Li, Xuenan; Zuo, Xianghong; Zhen, Jiao; Sudan, Teng

2017-05-01

According to the calculation model of minimum generator reactive power reserve of power system voltage stability under the premise of the guarantee, the reactive power management system with reactive power compensation combined generator, the formation of a multi-objective optimization problem, propose a reactive power reserve is considered the minimum generator reactive power compensation optimization method. This method through the improvement of the objective function and constraint conditions, when the system load growth, relying solely on reactive power generation system can not meet the requirement of safe operation, increase the reactive power reserve to solve the problem of minimum generator reactive power compensation in the case of load node.

High Efficient Differentiation of Functional Hepatocytes from Porcine Induced Pluripotent Stem Cells

PubMed Central

Ao, Ying; Mich-Basso, Jocelyn Danielle; Lin, Bo; Yang, Lei

2014-01-01

Hepatocyte transplantation is considered to be a promising therapy for patients with liver diseases. Induced pluripotent stem cells (iPSCs) provide an unlimited source for the generation of functional hepatocytes. In this study, we generated iPSCs from porcine ear fibroblasts (PEFs) by overexpressing Sox2, Klf4, Oct4, and c-Myc (SKOM), and developed a novel strategy for the efficient differentiation of hepatocyte-like cells from porcine iPSCs by following the processes of early liver development. The differentiated cells displayed the phenotypes of hepatocytes, exhibited classic hepatocyte-associated bio-functions, such as LDL uptake, glycogen storage and urea secretion, as well as possessed the metabolic activities of cytochrome P-450 (CYP) 3A and 2C. Furthermore, we compared the hepatocyte differentiation efficacy of our protocol with another published method, and the results demonstrated that our differentiation strategy could significantly improve the generation of morphological and functional hepatocyte-like cells from porcine iPSCs. In conclusion, this study establishes an efficient method for in vitro generation of functional hepatocytes from porcine iPSCs, which could represent a promising cell source for preclinical testing of cell-based therapeutics for liver failure and for pharmacological applications. PMID:24949734

Control method for turbocharged diesel engines having exhaust gas recirculation

DOEpatents

Kolmanovsky, Ilya V.; Jankovic, Mrdjan J; Jankovic, Miroslava

2000-03-14

A method of controlling the airflow into a compression ignition engine having an EGR and a VGT. The control strategy includes the steps of generating desired EGR and VGT turbine mass flow rates as a function of the desired and measured compressor mass airflow values and exhaust manifold pressure values. The desired compressor mass airflow and exhaust manifold pressure values are generated as a function of the operator-requested fueling rate and engine speed. The EGR and VGT turbine mass flow rates are then inverted to corresponding EGR and VGT actuator positions to achieve the desired compressor mass airflow rate and exhaust manifold pressure. The control strategy also includes a method of estimating the intake manifold pressure used in generating the EGR valve and VGT turbine positions.

Transient Stability Output Margin Estimation Based on Energy Function Method

NASA Astrophysics Data System (ADS)

Miwa, Natsuki; Tanaka, Kazuyuki

In this paper, a new method of estimating critical generation margin (CGM) in power systems is proposed from the viewpoint of transient stability diagnostic. The proposed method has the capability to directly compute the stability limit output for a given contingency based on transient energy function method (TEF). Since CGM can be directly obtained by the limit output using estimated P-θ curves and is easy to understand, it is more useful rather than conventional critical clearing time (CCT) of energy function method. The proposed method can also estimate CGM as its negative value that means unstable in present load profile, then negative CGM can be directly utilized as generator output restriction. The proposed method is verified its accuracy and fast solution ability by applying to simple 3-machine model and IEEJ EAST10-machine standard model. Furthermore the useful application to severity ranking of transient stability for a lot of contingency cases is discussed by using CGM.

Preparation of transition metal nanoparticles and surfaces modified with (CO)polymers synthesized by RAFT

DOEpatents

McCormick, III., Charles L.; Lowe, Andrew B.; Sumerlin, Brent S.

2006-11-21

A new, facile, general one-phase method of generating thio-functionalized transition metal nanoparticles and surfaces modified by (co)polymers synthesized by the RAFT method is described. The method includes the stops of forming a (co)polymer in aqueous solution using the RAFT methodology, forming a colloidal transition metal precursor solution from an appropriate transition metal; adding the metal precursor solution or surface to the (co)polymer solution, adding a reducing agent into the solution to reduce the metal colloid in situ to produce the stabilized nanoparticles or surface, and isolating the stabilized nanoparticles or surface in a manner such that aggregation is minimized. The functionalized surfaces generated using these methods can further undergo planar surface modifications, such as functionalization with a variety of different chemical groups, expanding their utility and application.

Preparation of transition metal nanoparticles and surfaces modified with (co)polymers synthesized by RAFT

DOEpatents

McCormick, III, Charles L.; Lowe, Andrew B [Hattiesburg, MS; Sumerlin, Brent S [Pittsburgh, PA

2011-12-27

A new, facile, general one-phase method of generating thiol-functionalized transition metal nanoparticles and surfaces modified by (co)polymers synthesized by the RAFT method is described. The method includes the steps of forming a (co)polymer in aqueous solution using the RAFT methodology, forming a colloidal transition metal precursor solution from an appropriate transition metal; adding the metal precursor solution or surface to the (co)polymer solution, adding a reducing agent into the solution to reduce the metal colloid in situ to produce the stabilized nanoparticles or surface, and isolating the stabilized nanoparticles or surface in a manner such that aggregation is minimized. The functionalized surfaces generated using these methods can further undergo planar surface modifications, such as functionalization with a variety of different chemical groups, expanding their utility and application.

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

Store Separation Lessons Learned During the Last 30 Years

DTIC Science & Technology

2010-01-01

the same time period the Influence Function Method (IFM) was also developed5. This method allowed for a straight STORE SEPARATION LESSONS LEARNED...developed at Grumman under an Air Force contract. The Influence Function Method (IFM)5,6,7 was used to determine the effect of the aircraft flowfield on...A Chimera Grid Scheme,” Advances in Grid Generation, ASME, June 1983. 5. Meyer, R., Cenko, A., and Yaros, S., “An Influence Function Method for

Bessel function expansion to reduce the calculation time and memory usage for cylindrical computer-generated holograms.

PubMed

Sando, Yusuke; Barada, Daisuke; Jackin, Boaz Jessie; Yatagai, Toyohiko

2017-07-10

This study proposes a method to reduce the calculation time and memory usage required for calculating cylindrical computer-generated holograms. The wavefront on the cylindrical observation surface is represented as a convolution integral in the 3D Fourier domain. The Fourier transformation of the kernel function involving this convolution integral is analytically performed using a Bessel function expansion. The analytical solution can drastically reduce the calculation time and the memory usage without any cost, compared with the numerical method using fast Fourier transform to Fourier transform the kernel function. In this study, we present the analytical derivation, the efficient calculation of Bessel function series, and a numerical simulation. Furthermore, we demonstrate the effectiveness of the analytical solution through comparisons of calculation time and memory usage.

Statistical scaling of geometric characteristics in stochastically generated pore microstructures

DOE PAGES

Hyman, Jeffrey D.; Guadagnini, Alberto; Winter, C. Larrabee

2015-05-21

In this study, we analyze the statistical scaling of structural attributes of virtual porous microstructures that are stochastically generated by thresholding Gaussian random fields. Characterization of the extent at which randomly generated pore spaces can be considered as representative of a particular rock sample depends on the metrics employed to compare the virtual sample against its physical counterpart. Typically, comparisons against features and/patterns of geometric observables, e.g., porosity and specific surface area, flow-related macroscopic parameters, e.g., permeability, or autocorrelation functions are used to assess the representativeness of a virtual sample, and thereby the quality of the generation method. Here, wemore » rely on manifestations of statistical scaling of geometric observables which were recently observed in real millimeter scale rock samples [13] as additional relevant metrics by which to characterize a virtual sample. We explore the statistical scaling of two geometric observables, namely porosity (Φ) and specific surface area (SSA), of porous microstructures generated using the method of Smolarkiewicz and Winter [42] and Hyman and Winter [22]. Our results suggest that the method can produce virtual pore space samples displaying the symptoms of statistical scaling observed in real rock samples. Order q sample structure functions (statistical moments of absolute increments) of Φ and SSA scale as a power of the separation distance (lag) over a range of lags, and extended self-similarity (linear relationship between log structure functions of successive orders) appears to be an intrinsic property of the generated media. The width of the range of lags where power-law scaling is observed and the Hurst coefficient associated with the variables we consider can be controlled by the generation parameters of the method.« less

Eddylicious: A Python package for turbulent inflow generation

NASA Astrophysics Data System (ADS)

Mukha, Timofey; Liefvendahl, Mattias

2018-01-01

A Python package for generating inflow for scale-resolving computer simulations of turbulent flow is presented. The purpose of the package is to unite existing inflow generation methods in a single code-base and make them accessible to users of various Computational Fluid Dynamics (CFD) solvers. The currently existing functionality consists of an accurate inflow generation method suitable for flows with a turbulent boundary layer inflow and input/output routines for coupling with the open-source CFD solver OpenFOAM.

Inspection Methods in Programming.

DTIC Science & Technology

1981-06-01

Counting is a a specialization of Iterative-generation in which the generating function is Oneplus ) Waters’ second category of plan building method...is Oneplus and the initial input is 1. 0 I 180 CHAPTER NINE -ta a acio f igr9-.IeaieGnrtoPln 7 -7 STEADY STATE PLANS 181 TemporalPlan counting...specializalion iterative-generation roles .action(afu nction) ,tail(counting) conslraints .action.op = oneplus A .action.input = 1 The lItcrative-application

Comparing the effects of the second-and third-generation oral contraceptives on sexual functioning.

PubMed

Shahnazi, Mahnaz; Bayatipayan, Somaye; Khalili, Azizeh Farshbaf; Kochaksaraei, Fatemeh Ranjbar; Jafarabadi, Mohammad Asghari; Banoi, Kamala Gaza; Nahaee, Jila

2015-01-01

The aim of this study was to compare the effects of the second- and third-generation oral contraceptives on women's reproductive sexual function. This randomized, double-blind, placebo-controlled clinical trial was conducted on 82 married women of reproductive age in Tehran. Samples were randomized into the groups receiving second- and third-generation oral contraceptive pills. Female Sexual Function Index (FSFI) tool was used before the intervention and 2 and 4 months after the intervention. Data analysis was carried out using analysis of variance (ANOVA) within repeated measures and P < 0.05 were considered significant. There was a statistically significant difference in the positive and negative moods between the experimental and control groups before the intervention in the second and fourth months. The second-generation pills caused a decrease in sexual function in the second month and an increase in sexual function in the fourth month, but the third-generation pills led to an increase in sexual function in the second and fourth months. The increase in sexual function that resulted from using the third-generation pills was significantly higher than that resulted on using the second-generation pills. According to the results of this study, sexual functioning decreased in the second month of using the second-generation pills and sexual performance was significantly more on using the third-generation pills compared to second-generation pills. The most common type of oral contraceptive used in Iran is the second-generation oral contraceptive LD™ (low-dose estrogen), which is freely distributed in health centers. Therefore, it is necessary for women who wish to use these contraceptive methods to be educated and consulted before they start using them. The third-generation contraceptive pills can be recommended to women who wish to use oral contraceptives.

Generativity in College Students: Comparing and Explaining the Impact of Mentoring

ERIC Educational Resources Information Center

Hastings, Lindsay J.; Griesen, James V.; Hoover, Richard E.; Creswell, John W.; Dlugosh, Larry L.

2015-01-01

Preparing college students to be active contributors to the next generation is an important function of higher education. This assumption about generativity forms a cornerstone in this mixed methods study that examined generativity levels among 273 college students at a 4-year public university. MANCOVA results indicated that college students who…

Generator Coordinate Method Analysis of Xe and Ba Isotopes

NASA Astrophysics Data System (ADS)

Higashiyama, Koji; Yoshinaga, Naotaka; Teruya, Eri

Nuclear structure of Xe and Ba isotopes is studied in terms of the quantum-number projected generator coordinate method (GCM). The GCM reproduces well the energy levels of high-spin states as well as low-lying states. The structure of the low-lying states is analyzed through the GCM wave functions.

Single step generation of protein arrays from DNA by cell-free expression and in situ immobilisation (PISA method).

PubMed

He, M; Taussig, M J

2001-08-01

We describe a format for production of protein arrays termed 'protein in situ array' (PISA). A PISA is rapidly generated in one step directly from PCR-generated DNA fragments by cell-free protein expression and in situ immobilisation at a surface. The template for expression is DNA encoding individual proteins or domains, which is produced by PCR using primers designed from information in DNA databases. Coupled transcription and translation is carried out on a surface to which the tagged protein adheres as soon as it is synthesised. Because proteins generated by cell-free synthesis are usually soluble and functional, this method can overcome problems of insolubility or degradation associated with bacterial expression of recombinant proteins. Moreover, the use of PCR-generated DNA enables rapid production of proteins or domains based on genome information alone and will be particularly useful where cloned material is not available. Here we show that human single-chain antibody fragments (three domain, V(H)/K form) and an enzyme (luciferase) can be functionally arrayed by the PISA method.

SU-E-T-259: Particle Swarm Optimization in Radial Dose Function Fitting for a Novel Iodine-125 Seed

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

Wu, X; Duan, J; Popple, R

2014-06-01

Purpose: To determine the coefficients of bi- and tri-exponential functions for the best fit of radial dose functions of the new iodine brachytherapy source: Iodine-125 Seed AgX-100. Methods: The particle swarm optimization (PSO) method was used to search for the coefficients of the biand tri-exponential functions that yield the best fit to data published for a few selected radial distances from the source. The coefficients were encoded into particles, and these particles move through the search space by following their local and global best-known positions. In each generation, particles were evaluated through their fitness function and their positions were changedmore » through their velocities. This procedure was repeated until the convergence criterion was met or the maximum generation was reached. All best particles were found in less than 1,500 generations. Results: For the I-125 seed AgX-100 considered as a point source, the maximum deviation from the published data is less than 2.9% for bi-exponential fitting function and 0.2% for tri-exponential fitting function. For its line source, the maximum deviation is less than 1.1% for bi-exponential fitting function and 0.08% for tri-exponential fitting function. Conclusion: PSO is a powerful method in searching coefficients for bi-exponential and tri-exponential fitting functions. The bi- and tri-exponential models of Iodine-125 seed AgX-100 point and line sources obtained with PSO optimization provide accurate analytical forms of the radial dose function. The tri-exponential fitting function is more accurate than the bi-exponential function.« less

Wavelets and distributed approximating functionals

NASA Astrophysics Data System (ADS)

Wei, G. W.; Kouri, D. J.; Hoffman, D. K.

1998-07-01

A general procedure is proposed for constructing father and mother wavelets that have excellent time-frequency localization and can be used to generate entire wavelet families for use as wavelet transforms. One interesting feature of our father wavelets (scaling functions) is that they belong to a class of generalized delta sequences, which we refer to as distributed approximating functionals (DAFs). We indicate this by the notation wavelet-DAFs. Correspondingly, the mother wavelets generated from these wavelet-DAFs are appropriately called DAF-wavelets. Wavelet-DAFs can be regarded as providing a pointwise (localized) spectral method, which furnishes a bridge between the traditional global methods and local methods for solving partial differential equations. They are shown to provide extremely accurate numerical solutions for a number of nonlinear partial differential equations, including the Korteweg-de Vries (KdV) equation, for which a previous method has encountered difficulties (J. Comput. Phys. 132 (1997) 233).

Monitoring volcanic activity using correlation patterns between infrasound and ground motion

NASA Astrophysics Data System (ADS)

Ichihara, M.; Takeo, M.; Yokoo, A.; Oikawa, J.; Ohminato, T.

2012-02-01

This paper presents a simple method to distinguish infrasonic signals from wind noise using a cross-correlation function of signals from a microphone and a collocated seismometer. The method makes use of a particular feature of the cross-correlation function of vertical ground motion generated by infrasound, and the infrasound itself. Contribution of wind noise to the correlation function is effectively suppressed by separating the microphone and the seismometer by several meters because the correlation length of wind noise is much shorter than wavelengths of infrasound. The method is applied to data from two recent eruptions of Asama and Shinmoe-dake volcanoes, Japan, and demonstrates that the method effectively detects not only the main eruptions, but also minor activity generating weak infrasound hardly visible in the wave traces. In addition, the correlation function gives more information about volcanic activity than infrasound alone, because it reflects both features of incident infrasonic and seismic waves. Therefore, a graphical presentation of temporal variation in the cross-correlation function enables one to see qualitative changes of eruptive activity at a glance. This method is particularly useful when available sensors are limited, and will extend the utility of a single microphone and seismometer in monitoring volcanic activity.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

Intrusion detection using secure signatures

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

Nelson, Trent Darnel; Haile, Jedediah

A method and device for intrusion detection using secure signatures comprising capturing network data. A search hash value, value employing at least one one-way function, is generated from the captured network data using a first hash function. The presence of a search hash value match in a secure signature table comprising search hash values and an encrypted rule is determined. After determining a search hash value match, a decryption key is generated from the captured network data using a second hash function, a hash function different form the first hash function. One or more of the encrypted rules of themore » secure signatures table having a hash value equal to the generated search hash value are then decrypted using the generated decryption key. The one or more decrypted secure signature rules are then processed for a match and one or more user notifications are deployed if a match is identified.« less

Selective functionalization of carbon nanotubes

NASA Technical Reports Server (NTRS)

Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H. (Inventor); Smalley, Richard E. (Inventor)

2009-01-01

The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

Modeling thrombin generation: plasma composition based approach.

PubMed

Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas

2014-01-01

Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

Steel characteristics measurement system using Barkhausen jump sum rate and magnetic field intensity and method of using same

DOEpatents

Kohn, Gabriel; Hicho, George; Swartzendruber, Lydon

1997-01-01

A steel hardness measurement system and method of using same are provided for measuring at least one mechanical or magnetic characteristic of a ferromagnetic sample as a function of at least one magnetic characteristic of the sample. A magnetic field generator subjects the sample to a variable external magnetic field. The magnetic field intensity of the magnetic field generated by the magnetic field generating means is measured and a signal sensor is provided for measuring Barkhausen signals from the sample when the sample is subjected to the external magnetic field. A signal processing unit calculates a jump sum rate first moment as a function of the Barkhausen signals measured by the signal sensor and the magnetic field intensity, and for determining the at least one mechanical or magnetic characteristic as a function of the jump sum rate first moment.

Steel characteristics measurement system using Barkhausen jump sum rate and magnetic field intensity and method of using same

DOEpatents

Kohn, G.; Hicho, G.; Swartzendruber, L.

1997-04-08

A steel hardness measurement system and method of using same are provided for measuring at least one mechanical or magnetic characteristic of a ferromagnetic sample as a function of at least one magnetic characteristic of the sample. A magnetic field generator subjects the sample to a variable external magnetic field. The magnetic field intensity of the magnetic field generated by the magnetic field generating means is measured and a signal sensor is provided for measuring Barkhausen signals from the sample when the sample is subjected to the external magnetic field. A signal processing unit calculates a jump sum rate first moment as a function of the Barkhausen signals measured by the signal sensor and the magnetic field intensity, and for determining the at least one mechanical or magnetic characteristic as a function of the jump sum rate first moment. 7 figs.

Therapeutic Inhibitors of LIN28/let-7 Pathway in Ovarian Cancer

DTIC Science & Technology

2015-09-01

generate loss of function lines (siRNA and the CrispR /Cas9 system). Task 4. Determine oncogenic properties associated with TUTase and LIN28B loss in...of-function cell lines to complement our already generated shRNA lines, we are developing handson experience with CrispR /Cas9 technology to...generate stable cell lines where our genes of interest will be inactivated. The advantage of the CrispR /Cas9 method is that stable lines can be

Dynamic mesh adaptation for front evolution using discontinuous Galerkin based weighted condition number relaxation

DOE PAGES

Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

2017-01-27

A new mesh smoothing method designed to cluster cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered fields, such as a volume fractionmore » or index function, is provided. Results show that the low-order level set works equally well as the actual level set for mesh smoothing. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Lastly, dynamic cases with moving interfaces show the new method is capable of maintaining a desired resolution near the interface with an acceptable number of relaxation iterations per time step, which demonstrates the method's potential to be used as a mesh relaxer for arbitrary Lagrangian Eulerian (ALE) methods.« less

Rotational control of computer generated holograms.

PubMed

Preece, Daryl; Rubinsztein-Dunlop, Halina

2017-11-15

We develop a basis for three-dimensional rotation of arbitrary light fields created by computer generated holograms. By adding an extra phase function into the kinoform, any light field or holographic image can be tilted in the focal plane with minimized distortion. We present two different approaches to rotate an arbitrary hologram: the Scheimpflug method and a novel coordinate transformation method. Experimental results are presented to demonstrate the validity of both proposed methods.

Precision medicine for cancer with next-generation functional diagnostics.

PubMed

Friedman, Adam A; Letai, Anthony; Fisher, David E; Flaherty, Keith T

2015-12-01

Precision medicine is about matching the right drugs to the right patients. Although this approach is technology agnostic, in cancer there is a tendency to make precision medicine synonymous with genomics. However, genome-based cancer therapeutic matching is limited by incomplete biological understanding of the relationship between phenotype and cancer genotype. This limitation can be addressed by functional testing of live patient tumour cells exposed to potential therapies. Recently, several 'next-generation' functional diagnostic technologies have been reported, including novel methods for tumour manipulation, molecularly precise assays of tumour responses and device-based in situ approaches; these address the limitations of the older generation of chemosensitivity tests. The promise of these new technologies suggests a future diagnostic strategy that integrates functional testing with next-generation sequencing and immunoprofiling to precisely match combination therapies to individual cancer patients.

Hybrid texture generator

NASA Astrophysics Data System (ADS)

Miyata, Kazunori; Nakajima, Masayuki

1995-04-01

A method is given for synthesizing a texture by using the interface of a conventional drawing tool. The majority of conventional texture generation methods are based on the procedural approach, and can generate a variety of textures that are adequate for generating a realistic image. But it is hard for a user to imagine what kind of texture will be generated simply by looking at its parameters. Furthermore, it is difficult to design a new texture freely without a knowledge of all the procedures for texture generation. Our method offers a solution to these problems, and has the following four merits: First, a variety of textures can be obtained by combining a set of feature lines and attribute functions. Second, data definitions are flexible. Third, the user can preview a texture together with its feature lines. Fourth, people can design their own textures interactively and freely by using the interface of a conventional drawing tool. For users who want to build this texture generation method into their own programs, we also give the language specifications for generating a texture. This method can interactively provide a variety of textures, and can also be used for typographic design.

Computer method for identification of boiler transfer functions

NASA Technical Reports Server (NTRS)

Miles, J. H.

1971-01-01

An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function to the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

Automated Testcase Generation for Numerical Support Functions in Embedded Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Schnieder, Stefan-Alexander

2014-01-01

We present a tool for the automatic generation of test stimuli for small numerical support functions, e.g., code for trigonometric functions, quaternions, filters, or table lookup. Our tool is based on KLEE to produce a set of test stimuli for full path coverage. We use a method of iterative deepening over abstractions to deal with floating-point values. During actual testing the stimuli exercise the code against a reference implementation. We illustrate our approach with results of experiments with low-level trigonometric functions, interpolation routines, and mathematical support functions from an open source UAS autopilot.

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Perceptually informed synthesis of bandlimited classical waveforms using integrated polynomial interpolation.

PubMed

Välimäki, Vesa; Pekonen, Jussi; Nam, Juhan

2012-01-01

Digital subtractive synthesis is a popular music synthesis method, which requires oscillators that are aliasing-free in a perceptual sense. It is a research challenge to find computationally efficient waveform generation algorithms that produce similar-sounding signals to analog music synthesizers but which are free from audible aliasing. A technique for approximately bandlimited waveform generation is considered that is based on a polynomial correction function, which is defined as the difference of a non-bandlimited step function and a polynomial approximation of the ideal bandlimited step function. It is shown that the ideal bandlimited step function is equivalent to the sine integral, and that integrated polynomial interpolation methods can successfully approximate it. Integrated Lagrange interpolation and B-spline basis functions are considered for polynomial approximation. The polynomial correction function can be added onto samples around each discontinuity in a non-bandlimited waveform to suppress aliasing. Comparison against previously known methods shows that the proposed technique yields the best tradeoff between computational cost and sound quality. The superior method amongst those considered in this study is the integrated third-order B-spline correction function, which offers perceptually aliasing-free sawtooth emulation up to the fundamental frequency of 7.8 kHz at the sample rate of 44.1 kHz. © 2012 Acoustical Society of America.

Optimal Output of Distributed Generation Based On Complex Power Increment

NASA Astrophysics Data System (ADS)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Generation of highly pure Schrödinger's cat states and real-time quadrature measurements via optical filtering

NASA Astrophysics Data System (ADS)

Asavanant, Warit; Nakashima, Kota; Shiozawa, Yu; Yoshikawa, Jun-Ichi; Furusawa, Akira

2017-12-01

Until now, Schr\\"odinger's cat states are generated by subtracting single photons from the whole bandwidth of squeezed vacua. However, it was pointed out recently that the achievable purities are limited in such method (J. Yoshikawa, W. Asavanant, and A. Furusawa, arXiv:1707.08146 [quant-ph] (2017)). In this paper, we used our new photon subtraction method with a narrowband filtering cavity and generated a highly pure Schr\\"odinger's cat state with the value of $-0.184$ at the origin of the Wigner function. To our knowledge, this is the highest value ever reported without any loss corrections. The temporal mode also becomes exponentially rising in our method, which allows us to make a real-time quadrature measurement on Schr\\"odinger's cat states, and we obtained the value of $-0.162$ at the origin of the Wigner function.

Chirped-pulse coherent-OTDR with predistortion

NASA Astrophysics Data System (ADS)

Xiong, Ji; Jiang, Jialin; Wu, Yue; Chen, Yongxiang; Xie, Lianlian; Fu, Yun; Wang, Zinan

2018-03-01

In this paper, a novel method for generating high-quality chirped pulses with IQ modulator is studied theoretically and experimentally, which is a crucial building block for high-performance coherent optical time-domain reflectometry (COTDR). In order to compensate the nonlinearity of the modulator transfer function, we present a predistortion technique for chirped-pulse coherent optical time-domain reflectometry (CP-COTDR), the arcsin predistortion method and the single sideband with a suppressed carrier analog modulation used to generate the high quality chirped optical pulse. The high order sidebands, due to the large amplitude of the modulation signal and the nonlinear transfer function of the IQ modulator, can be relieved by the predistortion process, which means the power and the quality of the generated chirped pulse has been improved. In the experiment, this method increases the peak power of the chirped pulse by 4.2 dB compared to the case without predistortion process, as for the CP-COTDR system, this method increases the signal-to-noise ratio of the demodulated phase variation by 6.3 dB.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Numerical Function Generators Using LUT Cascades

DTIC Science & Technology

2007-06-01

either algebraically (for example, sinðxÞ) or as a table of input/ output values. The user defines the numerical function by using the syntax of Scilab ...defined function in Scilab or specify it directly. Note that, by changing the parser of our system, any format can be used for the design entry. First...Methods for Multiple-Valued Input Address Generators,” Proc. 36th IEEE Int’l Symp. Multiple-Valued Logic (ISMVL ’06), May 2006. [29] Scilab 3.0, INRIA-ENPC

Random mutagenesis by error-prone pol plasmid replication in Escherichia coli.

PubMed

Alexander, David L; Lilly, Joshua; Hernandez, Jaime; Romsdahl, Jillian; Troll, Christopher J; Camps, Manel

2014-01-01

Directed evolution is an approach that mimics natural evolution in the laboratory with the goal of modifying existing enzymatic activities or of generating new ones. The identification of mutants with desired properties involves the generation of genetic diversity coupled with a functional selection or screen. Genetic diversity can be generated using PCR or using in vivo methods such as chemical mutagenesis or error-prone replication of the desired sequence in a mutator strain. In vivo mutagenesis methods facilitate iterative selection because they do not require cloning, but generally produce a low mutation density with mutations not restricted to specific genes or areas within a gene. For this reason, this approach is typically used to generate new biochemical properties when large numbers of mutants can be screened or selected. Here we describe protocols for an advanced in vivo mutagenesis method that is based on error-prone replication of a ColE1 plasmid bearing the gene of interest. Compared to other in vivo mutagenesis methods, this plasmid-targeted approach allows increased mutation loads and facilitates iterative selection approaches. We also describe the mutation spectrum for this mutagenesis methodology in detail, and, using cycle 3 GFP as a target for mutagenesis, we illustrate the phenotypic diversity that can be generated using our method. In sum, error-prone Pol I replication is a mutagenesis method that is ideally suited for the evolution of new biochemical activities when a functional selection is available.

Generating Sudoku puzzles and its applications in teaching mathematics

NASA Astrophysics Data System (ADS)

Evans, Ryan; Lindner, Brett; Shi, Yixun

2011-07-01

This article presents a few methods for generating Sudoku puzzles. These methods are developed based on the concepts of matrix, permutation, and modular functions, and therefore can be used to form application examples or student projects when teaching various mathematics courses. Mathematical properties of these methods are studied, connections between the methods are investigated, and student projects are suggested. Since most students tend to enjoy games, studies like this may help raising students' interests and enhance their problem-solving skills.

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

A method of PSF generation for 3D brightfield deconvolution.

PubMed

Tadrous, P J

2010-02-01

This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high- and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function.

BEACON: automated tool for Bacterial GEnome Annotation ComparisON.

PubMed

Kalkatawi, Manal; Alam, Intikhab; Bajic, Vladimir B

2015-08-18

Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON's utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27%, while the number of genes without any function assignment is reduced. We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/ .

A Statistical Method to Distinguish Functional Brain Networks

PubMed Central

Fujita, André; Vidal, Maciel C.; Takahashi, Daniel Y.

2017-01-01

One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001). PMID:28261045

A Statistical Method to Distinguish Functional Brain Networks.

PubMed

Fujita, André; Vidal, Maciel C; Takahashi, Daniel Y

2017-01-01

One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism ( p < 0.001).

Research on the generation of the background with sea and sky in infrared scene

NASA Astrophysics Data System (ADS)

Dong, Yan-zhi; Han, Yan-li; Lou, Shu-li

2008-03-01

It is important for scene generation to keep the texture of infrared images in simulation of anti-ship infrared imaging guidance. We studied the fractal method and applied it to the infrared scene generation. We adopted the method of horizontal-vertical (HV) partition to encode the original image. Basing on the properties of infrared image with sea-sky background, we took advantage of Local Iteration Function System (LIFS) to decrease the complexity of computation and enhance the processing rate. Some results were listed. The results show that the fractal method can keep the texture of infrared image better and can be used in the infrared scene generation widely in future.

Comparison of Response Surface Construction Methods for Derivative Estimation Using Moving Least Squares, Kriging and Radial Basis Functions

NASA Technical Reports Server (NTRS)

Krishnamurthy, Thiagarajan

2005-01-01

Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.

Bootstrap Methods: A Very Leisurely Look.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Winstead, Wayland H.

The Bootstrap method, a computer-intensive statistical method of estimation, is illustrated using a simple and efficient Statistical Analysis System (SAS) routine. The utility of the method for generating unknown parameters, including standard errors for simple statistics, regression coefficients, discriminant function coefficients, and factor…

Enhancements to the SSME transfer function modeling code

NASA Technical Reports Server (NTRS)

Irwin, R. Dennis; Mitchell, Jerrel R.; Bartholomew, David L.; Glenn, Russell D.

1995-01-01

This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.

Active control of residual tool marks for freeform optics functionalization by novel biaxial servo assisted fly cutting.

PubMed

Zhu, Zhiwei; To, Suet; Zhang, Shaojian

2015-09-01

The inherent residual tool marks (RTM) with particular patterns highly affect optical functions of the generated freeform optics in fast tool servo or slow tool servo (FTS/STS) diamond turning. In the present study, a novel biaxial servo assisted fly cutting (BSFC) method is developed for flexible control of the RTM to be a functional micro/nanotexture in freeform optics generation, which is generally hard to achieve in FTS/STS diamond turning. In the BSFC system, biaxial servo motions along the z-axis and side-feeding directions are mainly adopted for primary surface generation and RTM control, respectively. Active control of the RTM from the two aspects, namely, undesired effect elimination or effective functionalization, are experimentally demonstrated by fabricating a typical F-theta freeform surface with scattering homogenization and two functional microstructures with imposition of secondary phase gratings integrating both reflective and diffractive functions.

Deforming black hole and cosmological solutions by quasiperiodic and/or pattern forming structures in modified and Einstein gravity

NASA Astrophysics Data System (ADS)

Bubuianu, Laurenţiu; Vacaru, Sergiu I.

2018-05-01

We elaborate on the anholonomic frame deformation method, AFDM, for constructing exact solutions with quasiperiodic structure in modified gravity theories, MGTs, and general relativity, GR. Such solutions are described by generic off-diagonal metrics, nonlinear and linear connections and (effective) matter sources with coefficients depending on all spacetime coordinates via corresponding classes of generation and integration functions and (effective) matter sources. There are studied effective free energy functionals and nonlinear evolution equations for generating off-diagonal quasiperiodic deformations of black hole and/or homogeneous cosmological metrics. The physical data for such functionals are stated by different values of constants and prescribed symmetries for defining quasiperiodic structures at cosmological scales, or astrophysical objects in nontrivial gravitational backgrounds some similar forms as in condensed matter physics. It is shown how quasiperiodic structures determined by general nonlinear, or additive, functionals for generating functions and (effective) sources may transform black hole like configurations into cosmological metrics and inversely. We speculate on possible implications of quasiperiodic solutions in dark energy and dark matter physics. Finally, it is concluded that geometric methods for constructing exact solutions consist an important alternative tool to numerical relativity for investigating nonlinear effects in astrophysics and cosmology.

Colour computer-generated holography for point clouds utilizing the Phong illumination model.

PubMed

Symeonidou, Athanasia; Blinder, David; Schelkens, Peter

2018-04-16

A technique integrating the bidirectional reflectance distribution function (BRDF) is proposed to generate realistic high-quality colour computer-generated holograms (CGHs). We build on prior work, namely a fast computer-generated holography method for point clouds that handles occlusions. We extend the method by integrating the Phong illumination model so that the properties of the objects' surfaces are taken into account to achieve natural light phenomena such as reflections and shadows. Our experiments show that rendering holograms with the proposed algorithm provides realistic looking objects without any noteworthy increase to the computational cost.

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

Smallwood, D.O.

It is recognized that some dynamic and noise environments are characterized by time histories which are not Gaussian. An example is high intensity acoustic noise. Another example is some transportation vibration. A better simulation of these environments can be generated if a zero mean non-Gaussian time history can be reproduced with a specified auto (or power) spectral density (ASD or PSD) and a specified probability density function (pdf). After the required time history is synthesized, the waveform can be used for simulation purposes. For example, modem waveform reproduction techniques can be used to reproduce the waveform on electrodynamic or electrohydraulicmore » shakers. Or the waveforms can be used in digital simulations. A method is presented for the generation of realizations of zero mean non-Gaussian random time histories with a specified ASD, and pdf. First a Gaussian time history with the specified auto (or power) spectral density (ASD) is generated. A monotonic nonlinear function relating the Gaussian waveform to the desired realization is then established based on the Cumulative Distribution Function (CDF) of the desired waveform and the known CDF of a Gaussian waveform. The established function is used to transform the Gaussian waveform to a realization of the desired waveform. Since the transformation preserves the zero-crossings and peaks of the original Gaussian waveform, and does not introduce any substantial discontinuities, the ASD is not substantially changed. Several methods are available to generate a realization of a Gaussian distributed waveform with a known ASD. The method of Smallwood and Paez (1993) is an example. However, the generation of random noise with a specified ASD but with a non-Gaussian distribution is less well known.« less

Functional test generation for digital circuits described with a declarative language: LUSTRE

NASA Astrophysics Data System (ADS)

Almahrous, Mazen

1990-08-01

A functional approach to the test generation problem starting from a high level description is proposed. The circuit tested is modeled, using the LUSTRE high level data flow description language. The different LUSTRE primitives are translated to a SATAN format graph in order to evaluate the testability of the circuit and to generate test sequences. Another method of testing the complex circuits comprising an operative part and a control part is defined. It consists of checking experiments for the control part observed through the operative part. It was applied to the automata generated from a LUSTRE description of the circuit.

Generation of realistic virtual nodules based on three-dimensional spatial resolution in lung computed tomography: A pilot phantom study.

PubMed

Narita, Akihiro; Ohkubo, Masaki; Murao, Kohei; Matsumoto, Toru; Wada, Shinichi

2017-10-01

The aim of this feasibility study using phantoms was to propose a novel method for obtaining computer-generated realistic virtual nodules in lung computed tomography (CT). In the proposed methodology, pulmonary nodule images obtained with a CT scanner are deconvolved with the point spread function (PSF) in the scan plane and slice sensitivity profile (SSP) measured for the scanner; the resultant images are referred to as nodule-like object functions. Next, by convolving the nodule-like object function with the PSF and SSP of another (target) scanner, the virtual nodule can be generated so that it has the characteristics of the spatial resolution of the target scanner. To validate the methodology, the authors applied physical nodules of 5-, 7- and 10-mm-diameter (uniform spheres) included in a commercial CT test phantom. The nodule-like object functions were calculated from the sphere images obtained with two scanners (Scanner A and Scanner B); these functions were referred to as nodule-like object functions A and B, respectively. From these, virtual nodules were generated based on the spatial resolution of another scanner (Scanner C). By investigating the agreement of the virtual nodules generated from the nodule-like object functions A and B, the equivalence of the nodule-like object functions obtained from different scanners could be assessed. In addition, these virtual nodules were compared with the real (true) sphere images obtained with Scanner C. As a practical validation, five types of laboratory-made physical nodules with various complicated shapes and heterogeneous densities, similar to real lesions, were used. The nodule-like object functions were calculated from the images of these laboratory-made nodules obtained with Scanner A. From them, virtual nodules were generated based on the spatial resolution of Scanner C and compared with the real images of laboratory-made nodules obtained with Scanner C. Good agreement of the virtual nodules generated from the nodule-like object functions A and B of the phantom spheres was found, suggesting the validity of the nodule-like object functions. The virtual nodules generated from the nodule-like object function A of the phantom spheres were similar to the real images obtained with Scanner C; the root mean square errors (RMSEs) between them were 10.8, 11.1, and 12.5 Hounsfield units (HU) for 5-, 7-, and 10-mm-diameter spheres, respectively. The equivalent results (RMSEs) using the nodule-like object function B were 15.9, 16.8, and 16.5 HU, respectively. These RMSEs were small considering the high contrast between the sphere density and background density (approximately 674 HU). The virtual nodules generated from the nodule-like object functions of the five laboratory-made nodules were similar to the real images obtained with Scanner C; the RMSEs between them ranged from 6.2 to 8.6 HU in five cases. The nodule-like object functions calculated from real nodule images would be effective to generate realistic virtual nodules. The proposed method would be feasible for generating virtual nodules that have the characteristics of the spatial resolution of the CT system used in each institution, allowing for site-specific nodule generation. © 2017 American Association of Physicists in Medicine.

Normal mode-guided transition pathway generation in proteins

PubMed Central

Lee, Byung Ho; Seo, Sangjae; Kim, Min Hyeok; Kim, Youngjin; Jo, Soojin; Choi, Moon-ki; Lee, Hoomin; Choi, Jae Boong

2017-01-01

The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this. PMID:29020017

The Luminosity Function of Star Clusters in 20 Star-Forming Galaxies Based on Hubble Legacy Archive Photometry

NASA Astrophysics Data System (ADS)

Bowers, Ariel; Whitmore, B. C.; Chandar, R.; Larsen, S. S.

2014-01-01

Luminosity functions have been determined for star cluster populations in 20 nearby (4 - 30 Mpc), star-forming galaxies based on ACS source lists generated by the Hubble Legacy Archive (http://hla.stsci.edu). These cluster catalogs provide one of the largest sets of uniform, automatically-generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster luminosity function can be approximated by a power-law, dN/dL ∝ Lα, with an average value for α of -2.37 and rms scatter = 0.18. A comparison of fitting results based on methods which use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum-likelihood) method to give slightly more negative values of α for galaxies with steper luminosity functions. Our uniform database results in a small scatter (0.5 magnitude) in the correlation between the magnitude of the brightest cluster (Mbrightest) and Log of the number of clusters brighter than MI = -9 (Log N). We also examine the magnitude of the brightest cluster vs. Log SFR for a sample including LIRGS and ULIRGS.

Receiver function deconvolution using transdimensional hierarchical Bayesian inference

NASA Astrophysics Data System (ADS)

Kolb, J. M.; Lekić, V.

2014-06-01

Teleseismic waves can convert from shear to compressional (Sp) or compressional to shear (Ps) across impedance contrasts in the subsurface. Deconvolving the parent waveforms (P for Ps or S for Sp) from the daughter waveforms (S for Ps or P for Sp) generates receiver functions which can be used to analyse velocity structure beneath the receiver. Though a variety of deconvolution techniques have been developed, they are all adversely affected by background and signal-generated noise. In order to take into account the unknown noise characteristics, we propose a method based on transdimensional hierarchical Bayesian inference in which both the noise magnitude and noise spectral character are parameters in calculating the likelihood probability distribution. We use a reversible-jump implementation of a Markov chain Monte Carlo algorithm to find an ensemble of receiver functions whose relative fits to the data have been calculated while simultaneously inferring the values of the noise parameters. Our noise parametrization is determined from pre-event noise so that it approximates observed noise characteristics. We test the algorithm on synthetic waveforms contaminated with noise generated from a covariance matrix obtained from observed noise. We show that the method retrieves easily interpretable receiver functions even in the presence of high noise levels. We also show that we can obtain useful estimates of noise amplitude and frequency content. Analysis of the ensemble solutions produced by our method can be used to quantify the uncertainties associated with individual receiver functions as well as with individual features within them, providing an objective way for deciding which features warrant geological interpretation. This method should make possible more robust inferences on subsurface structure using receiver function analysis, especially in areas of poor data coverage or under noisy station conditions.

Rod Electroretinograms Elicited by Silent Substitution Stimuli from the Light-Adapted Human Eye

PubMed Central

Maguire, John; Parry, Neil R. A.; Kremers, Jan; Kommanapalli, Deepika; Murray, Ian J.; McKeefry, Declan J.

2016-01-01

Purpose To demonstrate that silent substitution stimuli can be used to generate electroretinograms (ERGs) that effectively isolate rod photoreceptor function in humans without the need for dark adaptation, and that this approach constitutes a viable alternative to current clinical standard testing protocols. Methods Rod-isolating and non-isolating sinusoidal flicker stimuli were generated on a 4 primary light-emitting diode (LED) Ganzfeld stimulator to elicit ERGs from participants with normal and compromised rod function who had not undergone dark-adaptation. Responses were subjected to Fourier analysis, and the amplitude and phase of the fundamental were used to examine temporal frequency and retinal illuminance response characteristics. Results Electroretinograms elicited by rod-isolating silent substitution stimuli exhibit low-pass temporal frequency response characteristics with an upper response limit of 30 Hz. Responses are optimal between 5 and 8 Hz and between 10 and 100 photopic trolands (Td). There is a significant correlation between the response amplitudes obtained with the silent substitution method and current standard clinical protocols. Analysis of signal-to-noise ratios reveals significant differences between subjects with normal and compromised rod function. Conclusions Silent substitution provides an effective method for the isolation of human rod photoreceptor function in subjects with normal as well as compromised rod function when stimuli are used within appropriate parameter ranges. Translational Relevance This method of generating rod-mediated ERGs can be achieved without time-consuming periods of dark adaptation, provides improved isolation of rod- from cone-based activity, and will lead to the development of faster clinical electrophysiologic testing protocols with improved selectivity. PMID:27617180

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems.

PubMed

Ihme, Matthias; Marsden, Alison L; Pitsch, Heinz

2008-02-01

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.

System and methods for determining masking signals for applying empirical mode decomposition (EMD) and for demodulating intrinsic mode functions obtained from application of EMD

DOEpatents

Senroy, Nilanjan [New Delhi, IN; Suryanarayanan, Siddharth [Littleton, CO

2011-03-15

A computer-implemented method of signal processing is provided. The method includes generating one or more masking signals based upon a computed Fourier transform of a received signal. The method further includes determining one or more intrinsic mode functions (IMFs) of the received signal by performing a masking-signal-based empirical mode decomposition (EMD) using the at least one masking signal.

Brownian dynamics without Green's functions

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

Delong, Steven; Donev, Aleksandar, E-mail: donev@courant.nyu.edu; Usabiaga, Florencio Balboa

2014-04-07

We develop a Fluctuating Immersed Boundary (FIB) method for performing Brownian dynamics simulations of confined particle suspensions. Unlike traditional methods which employ analytical Green's functions for Stokes flow in the confined geometry, the FIB method uses a fluctuating finite-volume Stokes solver to generate the action of the response functions “on the fly.” Importantly, we demonstrate that both the deterministic terms necessary to capture the hydrodynamic interactions among the suspended particles, as well as the stochastic terms necessary to generate the hydrodynamically correlated Brownian motion, can be generated by solving the steady Stokes equations numerically only once per time step. Thismore » is accomplished by including a stochastic contribution to the stress tensor in the fluid equations consistent with fluctuating hydrodynamics. We develop novel temporal integrators that account for the multiplicative nature of the noise in the equations of Brownian dynamics and the strong dependence of the mobility on the configuration for confined systems. Notably, we propose a random finite difference approach to approximating the stochastic drift proportional to the divergence of the configuration-dependent mobility matrix. Through comparisons with analytical and existing computational results, we numerically demonstrate the ability of the FIB method to accurately capture both the static (equilibrium) and dynamic properties of interacting particles in flow.« less

A simplified analytic form for generation of axisymmetric plasma boundaries

DOE PAGES

Luce, Timothy C.

2017-02-23

An improved method has been formulated for generating analytic boundary shapes as input for axisymmetric MHD equilibria. This method uses the family of superellipses as the basis function, as previously introduced. The improvements are a simplified notation, reduction of the number of simultaneous nonlinear equations to be solved, and the realization that not all combinations of input parameters admit a solution to the nonlinear constraint equations. The method tests for the existence of a self-consistent solution and, when no solution exists, it uses a deterministic method to find a nearby solution. As a result, examples of generation of boundaries, includingmore » tests with an equilibrium solver, are given.« less

An accurate method for evaluating the kernel of the integral equation relating lift to downwash in unsteady potential flow

NASA Technical Reports Server (NTRS)

Desmarais, R. N.

1982-01-01

The method is capable of generating approximations of arbitrary accuracy. It is based on approximating the algebraic part of the nonelementary integrals in the kernel by exponential functions and then integrating termwise. The exponent spacing in the approximation is a geometric sequence. The coefficients and exponent multiplier of the exponential approximation are computed by least squares so the method is completely automated. Exponential approximates generated in this manner are two orders of magnitude more accurate than the exponential approximation that is currently most often used for this purpose. The method can be used to generate approximations to attain any desired trade-off between accuracy and computing cost.

A simplified analytic form for generation of axisymmetric plasma boundaries

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

Luce, Timothy C.

An improved method has been formulated for generating analytic boundary shapes as input for axisymmetric MHD equilibria. This method uses the family of superellipses as the basis function, as previously introduced. The improvements are a simplified notation, reduction of the number of simultaneous nonlinear equations to be solved, and the realization that not all combinations of input parameters admit a solution to the nonlinear constraint equations. The method tests for the existence of a self-consistent solution and, when no solution exists, it uses a deterministic method to find a nearby solution. As a result, examples of generation of boundaries, includingmore » tests with an equilibrium solver, are given.« less

mrpy: Renormalized generalized gamma distribution for HMF and galaxy ensemble properties comparisons

NASA Astrophysics Data System (ADS)

Murray, Steven G.; Robotham, Aaron S. G.; Power, Chris

2018-02-01

mrpy calculates the MRP parameterization of the Halo Mass Function. It calculates basic statistics of the truncated generalized gamma distribution (TGGD) with the TGGD class, including mean, mode, variance, skewness, pdf, and cdf. It generates MRP quantities with the MRP class, such as differential number counts and cumulative number counts, and offers various methods for generating normalizations. It can generate the MRP-based halo mass function as a function of physical parameters via the mrp_b13 function, and fit MRP parameters to data in the form of arbitrary curves and in the form of a sample of variates with the SimFit class. mrpy also calculates analytic hessians and jacobians at any point, and allows the user to alternate parameterizations of the same form via the reparameterize module.

Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons.

PubMed

Jo, Junghyun; Xiao, Yixin; Sun, Alfred Xuyang; Cukuroglu, Engin; Tran, Hoang-Dai; Göke, Jonathan; Tan, Zi Ying; Saw, Tzuen Yih; Tan, Cheng-Peow; Lokman, Hidayat; Lee, Younghwan; Kim, Donghoon; Ko, Han Seok; Kim, Seong-Oh; Park, Jae Hyeon; Cho, Nam-Joon; Hyde, Thomas M; Kleinman, Joel E; Shin, Joo Heon; Weinberger, Daniel R; Tan, Eng King; Je, Hyunsoo Shawn; Ng, Huck-Hui

2016-08-04

Recent advances in 3D culture systems have led to the generation of brain organoids that resemble different human brain regions; however, a 3D organoid model of the midbrain containing functional midbrain dopaminergic (mDA) neurons has not been reported. We developed a method to differentiate human pluripotent stem cells into a large multicellular organoid-like structure that contains distinct layers of neuronal cells expressing characteristic markers of human midbrain. Importantly, we detected electrically active and functionally mature mDA neurons and dopamine production in our 3D midbrain-like organoids (MLOs). In contrast to human mDA neurons generated using 2D methods or MLOs generated from mouse embryonic stem cells, our human MLOs produced neuromelanin-like granules that were structurally similar to those isolated from human substantia nigra tissues. Thus our MLOs bearing features of the human midbrain may provide a tractable in vitro system to study the human midbrain and its related diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis and modeling of localized heat generation by tumor-targeted nanoparticles (Monte Carlo methods)

NASA Astrophysics Data System (ADS)

Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan

2016-04-01

We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.

Complementary DNA libraries: an overview.

PubMed

Ying, Shao-Yao

2004-07-01

The generation of complete and full-length cDNA libraries for potential functional assays of specific gene sequences is essential for most molecules in biotechnology and biomedical research. The field of cDNA library generation has changed rapidly in the past 10 yr. This review presents an overview of the method available for the basic information of generating cDNA libraries, including the definition of the cDNA library, different kinds of cDNA libraries, difference between methods for cDNA library generation using conventional approaches and a novel strategy, and the quality of cDNA libraries. It is anticipated that the high-quality cDNA libraries so generated would facilitate studies involving genechips and the microarray, differential display, subtractive hybridization, gene cloning, and peptide library generation.

Integrated circuit test-port architecture and method and apparatus of test-port generation

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

Teifel, John

A method and apparatus are provided for generating RTL code for a test-port interface of an integrated circuit. In an embodiment, a test-port table is provided as input data. A computer automatically parses the test-port table into data structures and analyzes it to determine input, output, local, and output-enable port names. The computer generates address-detect and test-enable logic constructed from combinational functions. The computer generates one-hot multiplexer logic for at least some of the output ports. The one-hot multiplexer logic for each port is generated so as to enable the port to toggle between data signals and test signals. Themore » computer then completes the generation of the RTL code.« less

Synthesis and optimization of four bar mechanism with six design parameters

NASA Astrophysics Data System (ADS)

Jaiswal, Ankur; Jawale, H. P.

2018-04-01

Function generation is synthesis of mechanism for specific task, involves complexity for specially synthesis above five precision of coupler points. Thus pertains to large structural error. The methodology for arriving to better precision solution is to use the optimization technique. Work presented herein considers methods of optimization of structural error in closed kinematic chain with single degree of freedom, for generating functions like log(x), ex, tan(x), sin(x) with five precision points. The equation in Freudenstein-Chebyshev method is used to develop five point synthesis of mechanism. The extended formulation is proposed and results are obtained to verify existing results in literature. Optimization of structural error is carried out using least square approach. Comparative structural error analysis is presented on optimized error through least square method and extended Freudenstein-Chebyshev method.

A third-generation density-functional-theory-based method for calculating canonical molecular orbitals of large molecules.

PubMed

Hirano, Toshiyuki; Sato, Fumitoshi

2014-07-28

We used grid-free modified Cholesky decomposition (CD) to develop a density-functional-theory (DFT)-based method for calculating the canonical molecular orbitals (CMOs) of large molecules. Our method can be used to calculate standard CMOs, analytically compute exchange-correlation terms, and maximise the capacity of next-generation supercomputers. Cholesky vectors were first analytically downscaled using low-rank pivoted CD and CD with adaptive metric (CDAM). The obtained Cholesky vectors were distributed and stored on each computer node in a parallel computer, and the Coulomb, Fock exchange, and pure exchange-correlation terms were calculated by multiplying the Cholesky vectors without evaluating molecular integrals in self-consistent field iterations. Our method enables DFT and massively distributed memory parallel computers to be used in order to very efficiently calculate the CMOs of large molecules.

Analyzing the Effect of Multi-fuel and Practical Constraints on Realistic Economic Load Dispatch using Novel Two-stage PSO

NASA Astrophysics Data System (ADS)

Chintalapudi, V. S.; Sirigiri, Sivanagaraju

2017-04-01

In power system restructuring, pricing the electrical power plays a vital role in cost allocation between suppliers and consumers. In optimal power dispatch problem, not only the cost of active power generation but also the costs of reactive power generated by the generators should be considered to increase the effectiveness of the problem. As the characteristics of reactive power cost curve are similar to that of active power cost curve, a nonconvex reactive power cost function is formulated. In this paper, a more realistic multi-fuel total cost objective is formulated by considering active and reactive power costs of generators. The formulated cost function is optimized by satisfying equality, in-equality and practical constraints using the proposed uniform distributed two-stage particle swarm optimization. The proposed algorithm is a combination of uniform distribution of control variables (to start the iterative process with good initial value) and two-stage initialization processes (to obtain best final value in less number of iterations) can enhance the effectiveness of convergence characteristics. Obtained results for the considered standard test functions and electrical systems indicate the effectiveness of the proposed algorithm and can obtain efficient solution when compared to existing methods. Hence, the proposed method is a promising method and can be easily applied to optimize the power system objectives.

Solving the Hamilton-Jacobi equation for general relativity

NASA Astrophysics Data System (ADS)

Parry, J.; Salopek, D. S.; Stewart, J. M.

1994-03-01

We demonstrate a systematic method for solving the Hamilton-Jacobi equation for general relativity with the inclusion of matter fields. The generating functional is expanded in a series of spatial gradients. Each term is manifestly invariant under reparametrizations of the spatial coordinates (``gauge invariant''). At each order we solve the Hamiltonian constraint using a conformal transformation of the three-metric as well as a line integral in superspace. This gives a recursion relation for the generating functional which then may be solved to arbitrary order simply by functionally differentiating previous orders. At fourth order in spatial gradients we demonstrate solutions for irrotational dust as well as for a scalar field. We explicitly evolve the three-metric to the same order. This method can be used to derive the Zel'dovich approximation for general relativity.

Assessing Smart Phones for Generating Life-space Indicators.

PubMed

Wan, Neng; Qu, Wenyu; Whittington, Jackie; Witbrodt, Bradley C; Henderson, Mary Pearl; Goulding, Evan H; Schenk, A Katrin; Bonasera, Stephen J; Lin, Ge

2013-04-01

Life-space is a promising method for estimating older adults' functional status. However, traditional life-space measures are costly and time consuming because they often rely on active subject participation. This study assesses the feasibility of using the global positioning system (GPS) function of smart phones to generate life-space indicators. We first evaluated the location accuracy of smart phone collected GPS points versus those acquired by a commercial GPS unit. We then assessed the specificity of the smart phone processed life-space information against the traditional diary method. Our results suggested comparable location accuracy between the smart phone and the standard GPS unit in most outdoor situations. In addition, the smart phone method revealed more comprehensive life-space information than the diary method, which leads to higher and more consistent life-space scores. We conclude that the smart phone method is more reliable than traditional methods for measuring life-space. Further improvements will be required to develop a robust application of this method that is suitable for health-related practices.

Analysis of Classes of Superlinear Semipositone Problems with Nonlinear Boundary Conditions

NASA Astrophysics Data System (ADS)

Morris, Quinn A.

We study positive radial solutions for classes of steady state reaction diffusion problems on the exterior of a ball with both Dirichlet and nonlinear boundary conditions. We consider p-Laplacian problems (p > 1) with reaction terms which are superlinear at infinity and semipositone. In the case p = 2, using variational methods, we establish the existence of a solution, and via detailed analysis of the Green's function, we prove the positivity of the solution. In the case p ≠ 2, we again use variational methods to establish the existence of a solution, but the positivity of the solution is achieved via sophisticated a priori estimates. In the case p ≠ 2, the Green's function analysis is no longer available. Our results significantly enhance the literature on superlinear semipositone problems. Finally, we provide algorithms for the numerical generation of exact bifurcation curves for one-dimensional problems. In the autonomous case, we extend and analyze a quadrature method, and using nonlinear solvers in Mathematica, generate bifurcation curves. In the nonautonomous case, we employ shooting methods in Mathematica to generate bifurcation curves.

CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences.

PubMed

Dawson, Natalie L; Sillitoe, Ian; Lees, Jonathan G; Lam, Su Datt; Orengo, Christine A

2017-01-01

This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.

Maximizing photovoltaic power generation of a space-dart configured satellite

NASA Astrophysics Data System (ADS)

Lee, Dae Young; Cutler, James W.; Mancewicz, Joe; Ridley, Aaron J.

2015-06-01

Many small satellites are power constrained due to their minimal solar panel area and the eclipse environment of low-Earth orbit. As with larger satellites, these small satellites, including CubeSats, use deployable power arrays to increase power production. This presents a design opportunity to develop various objective functions related to energy management and methods for optimizing these functions over a satellite design. A novel power generation model was created, and a simulation system was developed to evaluate various objective functions describing energy management for complex satellite designs. The model uses a spacecraft-body-fixed spherical coordinate system to analyze the complex geometry of a satellite's self-induced shadowing with computation provided by the Open Graphics Library. As an example design problem, a CubeSat configured as a space-dart with four deployable panels is optimized. Due to the fast computation speed of the solution, an exhaustive search over the design space is used to find the solar panel deployment angles which maximize total power generation. Simulation results are presented for a variety of orbit scenarios. The method is extendable to a variety of complex satellite geometries and power generation systems.

Controlled surface functionality of magnetic nanoparticles by layer-by-layer assembled nano-films

NASA Astrophysics Data System (ADS)

Choi, Daheui; Son, Boram; Park, Tai Hyun; Hong, Jinkee

2015-04-01

Over the past several years, the preparation of functionalized nanoparticles has been aggressively pursued in order to develop desired structures, compositions, and structural order. Among the various nanoparticles, iron oxide magnetic nanoparticles (MNPs) have shown great promise because the material generated using these MNPs can be used in a variety of biomedical applications and possible bioactive functionalities. In this study, we report the development of various functionalized MNPs (F-MNPs) generated using the layer-by-layer (LbL) self-assembly method. To provide broad functional opportunities, we fabricated F-MNP bio-toolbox by using three different materials: synthetic polymers, natural polymers, and carbon materials. Each of these F-MNPs displays distinct properties, such as enhanced thickness or unique morphologies. In an effort to explore their biomedical applications, we generated basic fibroblast growth factor (bFGF)-loaded F-MNPs. The bFGF-loaded F-MNPs exhibited different release mechanisms and loading amounts, depending on the film material and composition order. Moreover, bFGF-loaded F-MNPs displayed higher biocompatibility and possessed superior proliferation properties than the bare MNPs and pure bFGF, respectively. We conclude that by simply optimizing the building materials and the nanoparticle's film composition, MNPs exhibiting various bioactive properties can be generated.Over the past several years, the preparation of functionalized nanoparticles has been aggressively pursued in order to develop desired structures, compositions, and structural order. Among the various nanoparticles, iron oxide magnetic nanoparticles (MNPs) have shown great promise because the material generated using these MNPs can be used in a variety of biomedical applications and possible bioactive functionalities. In this study, we report the development of various functionalized MNPs (F-MNPs) generated using the layer-by-layer (LbL) self-assembly method. To provide broad functional opportunities, we fabricated F-MNP bio-toolbox by using three different materials: synthetic polymers, natural polymers, and carbon materials. Each of these F-MNPs displays distinct properties, such as enhanced thickness or unique morphologies. In an effort to explore their biomedical applications, we generated basic fibroblast growth factor (bFGF)-loaded F-MNPs. The bFGF-loaded F-MNPs exhibited different release mechanisms and loading amounts, depending on the film material and composition order. Moreover, bFGF-loaded F-MNPs displayed higher biocompatibility and possessed superior proliferation properties than the bare MNPs and pure bFGF, respectively. We conclude that by simply optimizing the building materials and the nanoparticle's film composition, MNPs exhibiting various bioactive properties can be generated. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07373h

Transport Coefficients from Large Deviation Functions

NASA Astrophysics Data System (ADS)

Gao, Chloe; Limmer, David

2017-10-01

We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.

Object tracking mask-based NLUT on GPUs for real-time generation of holographic videos of three-dimensional scenes.

PubMed

Kwon, M-W; Kim, S-C; Yoon, S-E; Ho, Y-S; Kim, E-S

2015-02-09

A new object tracking mask-based novel-look-up-table (OTM-NLUT) method is proposed and implemented on graphics-processing-units (GPUs) for real-time generation of holographic videos of three-dimensional (3-D) scenes. Since the proposed method is designed to be matched with software and memory structures of the GPU, the number of compute-unified-device-architecture (CUDA) kernel function calls and the computer-generated hologram (CGH) buffer size of the proposed method have been significantly reduced. It therefore results in a great increase of the computational speed of the proposed method and enables real-time generation of CGH patterns of 3-D scenes. Experimental results show that the proposed method can generate 31.1 frames of Fresnel CGH patterns with 1,920 × 1,080 pixels per second, on average, for three test 3-D video scenarios with 12,666 object points on three GPU boards of NVIDIA GTX TITAN, and confirm the feasibility of the proposed method in the practical application of electro-holographic 3-D displays.

Testing Pairwise Association between Spatially Autocorrelated Variables: A New Approach Using Surrogate Lattice Data

PubMed Central

Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre

2012-01-01

Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material. PMID:23144961

Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 1314 and Method 1315

EPA Science Inventory

This report summarizes the results of an interlaboratory study conducted to generate precision estimates for two leaching methods under review by the U.S. EPA’s OSWER for inclusion into the EPA’s SW-846: Method 1314: Liquid-Solid Partitioning as a Function of Liquid...

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without linear bias to show optimal versus sub-optimal solution spaces. Basic analysis of the Actinobacillus succinogenes system using sampling shows that in order to achieve the maximal succinic acid production CO₂ must be taken into the system. Solutions involving release of CO₂ all give sub-optimal succinic acid production.

Study of high-performance canonical molecular orbitals calculation for proteins

NASA Astrophysics Data System (ADS)

Hirano, Toshiyuki; Sato, Fumitoshi

2017-11-01

The canonical molecular orbital (CMO) calculation can help to understand chemical properties and reactions in proteins. However, it is difficult to perform the CMO calculation of proteins because of its self-consistent field (SCF) convergence problem and expensive computational cost. To certainly obtain the CMO of proteins, we work in research and development of high-performance CMO applications and perform experimental studies. We have proposed the third-generation density-functional calculation method of calculating the SCF, which is more advanced than the FILE and direct method. Our method is based on Cholesky decomposition for two-electron integrals calculation and the modified grid-free method for the pure-XC term evaluation. By using the third-generation density-functional calculation method, the Coulomb, the Fock-exchange, and the pure-XC terms can be given by simple linear algebraic procedure in the SCF loop. Therefore, we can expect to get a good parallel performance in solving the SCF problem by using a well-optimized linear algebra library such as BLAS on the distributed memory parallel computers. The third-generation density-functional calculation method is implemented to our program, ProteinDF. To achieve computing electronic structure of the large molecule, not only overcoming expensive computation cost and also good initial guess for safe SCF convergence are required. In order to prepare a precise initial guess for the macromolecular system, we have developed the quasi-canonical localized orbital (QCLO) method. The QCLO has the characteristics of both localized and canonical orbital in a certain region of the molecule. We have succeeded in the CMO calculations of proteins by using the QCLO method. For simplified and semi-automated calculation of the QCLO method, we have also developed a Python-based program, QCLObot.

Topology optimized design of functionally graded piezoelectric ultrasonic transducers

NASA Astrophysics Data System (ADS)

Rubio, Wilfredo Montealegre; Buiochi, Flávio; Adamowski, Julio Cezar; Silva, Emílio C. N.

2010-01-01

This work presents a new approach to systematically design piezoelectric ultrasonic transducers based on Topology Optimization Method (TOM) and Functionally Graded Material (FGM) concepts. The main goal is to find the optimal material distribution of Functionally Graded Piezoelectric Ultrasonic Transducers, to achieve the following requirements: (i) the transducer must be designed to have a multi-modal or uni-modal frequency response, which defines the kind of generated acoustic wave, either short pulse or continuous wave, respectively; (ii) the transducer is required to oscillate in a thickness extensional mode or piston-like mode, aiming at acoustic wave generation applications. Two kinds of piezoelectric materials are mixed for producing the FGM transducer. Material type 1 represents a PZT-5A piezoelectric ceramic and material type 2 represents a PZT-5H piezoelectric ceramic. To illustrate the proposed method, two Functionally Graded Piezoelectric Ultrasonic Transducers are designed. The TOM has shown to be a useful tool for designing Functionally Graded Piezoelectric Ultrasonic Transducers with uni-modal or multi-modal dynamic behavior.

Targeted organ generation using Mixl1-inducible mouse pluripotent stem cells in blastocyst complementation.

PubMed

Kobayashi, Toshihiro; Kato-Itoh, Megumi; Nakauchi, Hiromitsu

2015-01-15

Generation of functional organs from patients' own cells is one of the ultimate goals of regenerative medicine. As a novel approach to creation of organs from pluripotent stem cells (PSCs), we employed blastocyst complementation in organogenesis-disabled animals and successfully generated PSC-derived pancreas and kidneys. Blastocyst complementation, which exploits the capacity of PSCs to participate in forming chimeras, does not, however, exclude contribution of PSCs to the development of tissues-including neural cells or germ cells-other than those specifically targeted by disabling of organogenesis. This fact provokes ethical controversy if human PSCs are to be used. In this study, we demonstrated that forced expression of Mix-like protein 1 (encoded by Mixl1) can be used to guide contribution of mouse embryonic stem cells to endodermal organs after blastocyst injection. We then succeeded in applying this method to generate functional pancreas in pancreatogenesis-disabled Pdx1 knockout mice using a newly developed tetraploid-based organ-complementation method. These findings hold promise for targeted organ generation from patients' own PSCs in livestock animals.

Algebraic grid generation with corner singularities

NASA Technical Reports Server (NTRS)

Vinokur, M.; Lombard, C. K.

1983-01-01

A simple noniterative algebraic procedure is presented for generating smooth computational meshes on a quadrilateral topology. Coordinate distribution and normal derivative are provided on all boundaries, one of which may include a slope discontinuity. The boundary conditions are sufficient to guarantee continuity of global meshes formed of joined patches generated by the procedure. The method extends to 3-D. The procedure involves a synthesis of prior techniques stretching functions, cubic blending functions, and transfinite interpolation - to which is added the functional form of the corner solution. The procedure introduces the concept of generalized blending, which is implemented as an automatic scaling of the boundary derivatives for effective interpolation. Some implications of the treatment at boundaries for techniques solving elliptic PDE's are discussed in an Appendix.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

Differentially Private Synthesization of Multi-Dimensional Data using Copula Functions

PubMed Central

Li, Haoran; Xiong, Li; Jiang, Xiaoqian

2014-01-01

Differential privacy has recently emerged in private statistical data release as one of the strongest privacy guarantees. Most of the existing techniques that generate differentially private histograms or synthetic data only work well for single dimensional or low-dimensional histograms. They become problematic for high dimensional and large domain data due to increased perturbation error and computation complexity. In this paper, we propose DPCopula, a differentially private data synthesization technique using Copula functions for multi-dimensional data. The core of our method is to compute a differentially private copula function from which we can sample synthetic data. Copula functions are used to describe the dependence between multivariate random vectors and allow us to build the multivariate joint distribution using one-dimensional marginal distributions. We present two methods for estimating the parameters of the copula functions with differential privacy: maximum likelihood estimation and Kendall’s τ estimation. We present formal proofs for the privacy guarantee as well as the convergence property of our methods. Extensive experiments using both real datasets and synthetic datasets demonstrate that DPCopula generates highly accurate synthetic multi-dimensional data with significantly better utility than state-of-the-art techniques. PMID:25405241

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

Dendritic cells (DCs) can be successfully generated from leukemic blasts in individual patients with AML or MDS: an evaluation of different methods.

PubMed

Kremser, Andreas; Dressig, Julia; Grabrucker, Christine; Liepert, Anja; Kroell, Tanja; Scholl, Nina; Schmid, Christoph; Tischer, Johanna; Kufner, Stefanie; Salih, Helmut; Kolb, Hans Jochem; Schmetzer, Helga

2010-01-01

Myeloid-leukemic cells (AML, MDS, CML) can be differentiated to leukemia-derived dendritic cell [DC (DCleu)] potentially presenting the whole leukemic antigen repertoire without knowledge of distinct leukemia antigens and are regarded as promising candidates for a vaccination strategy. We studied the capability of 6 serum-free DC culture methods, chosen according to different mechanisms, to induce DC differentiation in 137 cases of AML and 52 cases of MDS. DC-stimulating substances were cytokines ("standard-medium", "MCM-Mimic", "cytokine-method"), bacterial lysates ("Picibanil"), double-stranded RNA ["Poly (I:C)"] or a cytokine bypass method ("Ca-ionophore"). The quality/quantity of DC generated was estimated by flow cytometry studying (co) expressions of "DC"antigens, costimulatory, maturation, and blast-antigens. Comparing these methods on average 15% to 32% DC, depending on methods used, could be obtained from blast-containing mononuclear cells (MNC) in AML/MDS cases with a DC viability of more than 60%. In all, 39% to 64% of these DC were mature; 31% to 52% of leukemic blasts could be converted to DCleu and DCleu-proportions in the suspension were 2% to 70% (13%). Average results of all culture methods tested were comparable, however not every given case of AML could be differentiated to DC with 1 selected method. However performing a pre-analysis with 3 DC-generating methods (MCM-Mimic, Picibanil, Ca-ionophore) we could generate DC in any given case. Functional analyses provided proof, that DC primed T cells to antileukemia-directed cytotoxic cells, although an anti-leukemic reaction was not achieved in every case. In summary our data show that a successful, quantitative DC/DCleu generation is possible with the best of 3 previously tested methods in any given case. Reasons for different functional behaviors of DC-primed T cells must be evaluated to design a practicable DC-based vaccination strategy.

Cumulant generating function formula of heat transfer in ballistic systems with lead-lead coupling and general nonlinear systems

NASA Astrophysics Data System (ADS)

Li, Huanan

2013-03-01

Based on a two-time observation protocol, we consider heat transfer in a given time interval tM in a lead-junction-lead system taking coupling between the leads into account. In view of the two-time observation, consistency conditions are carefully verified in our specific family of quantum histories. Furthermore, its implication is briefly explored. Then using the nonequilibrium Green's function method, we obtain an exact formula for the cumulant generating function for heat transfer between the two leads, valid in both transient and steady-state regimes. Also, a compact formula for the cumulant generating function in the long-time limit is derived, for which the Gallavotti-Cohen fluctuation symmetry is explicitly verified. In addition, we briefly discuss Di Ventra's repartitioning trick regarding whether the repartitioning procedure of the total Hamiltonian affects the nonequilibrium steady-state current fluctuation. All kinds of properties of nonequilibrium current fluctuations, such as the fluctuation theorem in different time regimes, could be readily given according to these exact formulas. Finally a practical formalism dealing with cumulants of heat transfer across general nonlinear quantum systems is established based on field theoretical/algebraic method.

On a method for generating inequalities for the zeros of certain functions

NASA Astrophysics Data System (ADS)

Gatteschi, Luigi; Giordano, Carla

2007-10-01

In this paper we describe a general procedure which yields inequalities satisfied by the zeros of a given function. The method requires the knowledge of a two-term approximation of the function with bound for the error term. The method was successfully applied many years ago [L. Gatteschi, On the zeros of certain functions with application to Bessel functions, Nederl. Akad. Wetensch. Proc. Ser. 55(3)(1952), Indag. Math. 14(1952) 224-229] and more recently too [L. Gatteschi and C. Giordano, Error bounds for McMahon's asymptotic approximations of the zeros of the Bessel functions, Integral Transform Special Functions, 10(2000) 41-56], to the zeros of the Bessel functions of the first kind. Here, we present the results of the application of the method to get inequalities satisfied by the zeros of the derivative of the function . This function plays an important role in the asymptotic study of the stationary points of the solutions of certain differential equations.

Computerized Method for the Generation of Molecular Transmittance Functions in the Infrared Region.

DTIC Science & Technology

1979-12-31

exponent of the double exponential function were ’bumpy’ for some cases. Since the nature of the transmittance does not predict this behavior, we...T ,IS RECOMPUTED FOR THE ORIGIONAL DATA *USING THE PIECEWISE- ANALITICAL TRANSMISSION FUNCTION.’//20X, *’STANDARD DEVIATIONS BETWEEN THE ACTUAL TAU

Language Lateralization in Children Using Functional Transcranial Doppler Sonography

ERIC Educational Resources Information Center

Haag, Anja; Moeller, Nicola; Knake, Susanne; Hermsen, Anke; Oertel, Wolfgang H.; Rosenow, Felix; Hamer, Hajo M.

2010-01-01

Aim: Language lateralization with functional transcranial Doppler sonography (fTCD) and lexical word generation has been shown to have high concordance with the Wada test and functional magnetic resonance imaging in adults. We evaluated a nonlexical paradigm to determine language dominance in children. Method: In 23 right-handed children (12…

Linkage of Recognition and Replication Functions by Assembling Combinatorial Antibody Fab Libraries Along Phage Surfaces

NASA Astrophysics Data System (ADS)

Kang, Angray S.; Barbas, Carlos F.; Janda, Kim D.; Benkovic, Stephen J.; Lerner, Richard A.

1991-05-01

We describe a method based on a phagemid vector with helper phage rescue for the construction and rapid analysis of combinatorial antibody Fab libraries. This approach should allow the generation and selection of many monoclonal antibodies. Antibody genes are expressed in concert with phage morphogenesis, thereby allowing incorporation of functional Fab molecules along the surface of filamentous phage. The power of the method depends upon the linkage of recognition and replication functions and is not limited to antibody molecules.

The design of real time infrared image generation software based on Creator and Vega

NASA Astrophysics Data System (ADS)

Wang, Rui-feng; Wu, Wei-dong; Huo, Jun-xiu

2013-09-01

Considering the requirement of high reality and real-time quality dynamic infrared image of an infrared image simulation, a method to design real-time infrared image simulation application on the platform of VC++ is proposed. This is based on visual simulation software Creator and Vega. The functions of Creator are introduced simply, and the main features of Vega developing environment are analyzed. The methods of infrared modeling and background are offered, the designing flow chart of the developing process of IR image real-time generation software and the functions of TMM Tool and MAT Tool and sensor module are explained, at the same time, the real-time of software is designed.

Analytical solutions for two-dimensional Stokes flow singularities in a no-slip wedge of arbitrary angle

PubMed Central

Brzezicki, Samuel J.

2017-01-01

An analytical method to find the flow generated by the basic singularities of Stokes flow in a wedge of arbitrary angle is presented. Specifically, we solve a biharmonic equation for the stream function of the flow generated by a point stresslet singularity and satisfying no-slip boundary conditions on the two walls of the wedge. The method, which is readily adapted to any other singularity type, takes full account of any transcendental singularities arising at the corner of the wedge. The approach is also applicable to problems of plane strain/stress of an elastic solid where the biharmonic equation also governs the Airy stress function. PMID:28690412

Analytical solutions for two-dimensional Stokes flow singularities in a no-slip wedge of arbitrary angle.

PubMed

Crowdy, Darren G; Brzezicki, Samuel J

2017-06-01

An analytical method to find the flow generated by the basic singularities of Stokes flow in a wedge of arbitrary angle is presented. Specifically, we solve a biharmonic equation for the stream function of the flow generated by a point stresslet singularity and satisfying no-slip boundary conditions on the two walls of the wedge. The method, which is readily adapted to any other singularity type, takes full account of any transcendental singularities arising at the corner of the wedge. The approach is also applicable to problems of plane strain/stress of an elastic solid where the biharmonic equation also governs the Airy stress function.

[Elastic registration method to compute deformation functions for mitral valve].

PubMed

Yang, Jinyu; Zhang, Wan; Yin, Ran; Deng, Yuxiao; Wei, Yunfeng; Zeng, Junyi; Wen, Tong; Ding, Lu; Liu, Xiaojian; Li, Yipeng

2014-10-01

Mitral valve disease is one of the most popular heart valve diseases. Precise positioning and displaying of the valve characteristics is necessary for the minimally invasive mitral valve repairing procedures. This paper presents a multi-resolution elastic registration method to compute the deformation functions constructed from cubic B-splines in three dimensional ultrasound images, in which the objective functional to be optimized was generated by maximum likelihood method based on the probabilistic distribution of the ultrasound speckle noise. The algorithm was then applied to register the mitral valve voxels. Numerical results proved the effectiveness of the algorithm.

A study of numerical methods for computing reentry trajectories for shuttle-type space vehicles

NASA Technical Reports Server (NTRS)

1972-01-01

The reuseable exterior insulation system (REI) is studied to determine the optimal reentry trajectory for a space shuttle, which minimizes the heat input to the fuselage. The REI is composed of titanium, covered by a surface insulation material. The method of perturbation functions was used to generate the trajectories, and proved to be an effective technique for generating families of solutions, once an initial trajectory has been obtained.

Three-directional motion-compensation mask-based novel look-up table on graphics processing units for video-rate generation of digital holographic videos of three-dimensional scenes.

PubMed

Kwon, Min-Woo; Kim, Seung-Cheol; Kim, Eun-Soo

2016-01-20

A three-directional motion-compensation mask-based novel look-up table method is proposed and implemented on graphics processing units (GPUs) for video-rate generation of digital holographic videos of three-dimensional (3D) scenes. Since the proposed method is designed to be well matched with the software and memory structures of GPUs, the number of compute-unified-device-architecture kernel function calls can be significantly reduced. This results in a great increase of the computational speed of the proposed method, allowing video-rate generation of the computer-generated hologram (CGH) patterns of 3D scenes. Experimental results reveal that the proposed method can generate 39.8 frames of Fresnel CGH patterns with 1920×1080 pixels per second for the test 3D video scenario with 12,088 object points on dual GPU boards of NVIDIA GTX TITANs, and they confirm the feasibility of the proposed method in the practical application fields of electroholographic 3D displays.

Roles, intents, and actions: First-year teachers' uses of discourse during elementary science instruction

NASA Astrophysics Data System (ADS)

Newman, William J., Jr.

In this study, I examined how three first-year elementary teachers constructed and used classroom discourse during science instruction. The three participants, though graduates from different universities, learned to teach science through similar science methods courses, which stressed the importance of inquiry-based science instruction. The participants taught different grade levels, and two of them taught at the same school. Data sources included field notes, videotapes, audiotapes, and semi-structured teacher interviews. While monologic and dialogic discourse existed in all three classrooms, monologic discourse was more prominent, especially when the discourse was teacher controlled. Dialogic discourse occurred most often during student-centered activities. The teachers constructed discourse with authoritative function to present science content and determine student comprehension. Generative function was most likely during student-based small group discussions. Monologic character often aligned with authoritative function, and dialogic character often aligned with generative function. However, monologic/generative and dialogic/authoritative discourse events did occur, contributing to the development of a discourse theory model. The teacher explanations for discourse included classroom control, inadequate planning, time constraints, life experiences, science education standards, and assessment. The teachers relied on their texts, kits, and state science standards to determine the content and methods for science instruction. They rarely reported that their science methods courses influenced how they taught science. The observed lessons rarely aligned with science education reform descriptions of appropriate science instruction. Implications include the need for in-service programs for beginning science teachers, curricular reform for science texts and kits, and explicit instruction of discourse strategies in science methods courses and in-service programs.

Pervasive Transcription of a Herpesvirus Genome Generates Functionally Important RNAs

PubMed Central

Canny, Susan P.; Reese, Tiffany A.; Johnson, L. Steven; Zhang, Xin; Kambal, Amal; Duan, Erning; Liu, Catherine Y.; Virgin, Herbert W.

2014-01-01

ABSTRACT Pervasive transcription is observed in a wide range of organisms, including humans, mice, and viruses, but the functional significance of the resulting transcripts remains uncertain. Current genetic approaches are often limited by their emphasis on protein-coding open reading frames (ORFs). We previously identified extensive pervasive transcription from the murine gammaherpesvirus 68 (MHV68) genome outside known ORFs and antisense to known genes (termed expressed genomic regions [EGRs]). Similar antisense transcripts have been identified in many other herpesviruses, including Kaposi’s sarcoma-associated herpesvirus and human and murine cytomegalovirus. Despite their prevalence, whether these RNAs have any functional importance in the viral life cycle is unknown, and one interpretation is that these are merely “noise” generated by functionally unimportant transcriptional events. To determine whether pervasive transcription of a herpesvirus genome generates RNA molecules that are functionally important, we used a strand-specific functional approach to target transcripts from thirteen EGRs in MHV68. We found that targeting transcripts from six EGRs reduced viral protein expression, proving that pervasive transcription can generate functionally important RNAs. We characterized transcripts emanating from EGRs 26 and 27 in detail using several methods, including RNA sequencing, and identified several novel polyadenylated transcripts that were enriched in the nuclei of infected cells. These data provide the first evidence of the functional importance of regions of pervasive transcription emanating from MHV68 EGRs. Therefore, studies utilizing mutation of a herpesvirus genome must account for possible effects on RNAs generated by pervasive transcription. PMID:24618256

Rapid Generation of Human Genetic Loss-of-Function iPSC Lines by Simultaneous Reprogramming and Gene Editing.

PubMed

Tidball, Andrew M; Dang, Louis T; Glenn, Trevor W; Kilbane, Emma G; Klarr, Daniel J; Margolis, Joshua L; Uhler, Michael D; Parent, Jack M

2017-09-12

Specifically ablating genes in human induced pluripotent stem cells (iPSCs) allows for studies of gene function as well as disease mechanisms in disorders caused by loss-of-function (LOF) mutations. While techniques exist for engineering such lines, we have developed and rigorously validated a method of simultaneous iPSC reprogramming while generating CRISPR/Cas9-dependent insertions/deletions (indels). This approach allows for the efficient and rapid formation of genetic LOF human disease cell models with isogenic controls. The rate of mutagenized lines was strikingly consistent across experiments targeting four different human epileptic encephalopathy genes and a metabolic enzyme-encoding gene, and was more efficient and consistent than using CRISPR gene editing of established iPSC lines. The ability of our streamlined method to reproducibly generate heterozygous and homozygous LOF iPSC lines with passage-matched isogenic controls in a single step provides for the rapid development of LOF disease models with ideal control lines, even in the absence of patient tissue. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Information loss in approximately bayesian data assimilation: a comparison of generative and discriminative approaches to estimating agricultural yield

USDA-ARS?s Scientific Manuscript database

Data assimilation and regression are two commonly used methods for predicting agricultural yield from remote sensing observations. Data assimilation is a generative approach because it requires explicit approximations of the Bayesian prior and likelihood to compute the probability density function...

Investigation of ODE integrators using interactive graphics. [Ordinary Differential Equations

NASA Technical Reports Server (NTRS)

Brown, R. L.

1978-01-01

Two FORTRAN programs using an interactive graphic terminal to generate accuracy and stability plots for given multistep ordinary differential equation (ODE) integrators are described. The first treats the fixed stepsize linear case with complex variable solutions, and generates plots to show accuracy and error response to step driving function of a numerical solution, as well as the linear stability region. The second generates an analog to the stability region for classes of non-linear ODE's as well as accuracy plots. Both systems can compute method coefficients from a simple specification of the method. Example plots are given.

Generating mammalian stable cell lines by electroporation.

PubMed

A Longo, Patti; Kavran, Jennifer M; Kim, Min-Sung; Leahy, Daniel J

2013-01-01

Expression of functional, recombinant mammalian proteins often requires expression in mammalian cells (see Single Cell Cloning of a Stable Mammalian Cell Line). If the expressed protein needs to be made frequently, it can be best to generate a stable cell line instead of performing repeated transient transfections into mammalian cells. Here, we describe a method to generate stable cell lines via electroporation followed by selection steps. This protocol will be limited to the CHO dhfr-Urlaub et al. (1983) and LEC1 cell lines, which in our experience perform the best with this method. Copyright © 2013 Elsevier Inc. All rights reserved.

Fiber-optic delay-line stabilization of heterodyne optical signal generator and method using same

NASA Technical Reports Server (NTRS)

Logan, Ronald T. (Inventor)

1997-01-01

The present invention is a laser heterodyne frequency generator system with a stabilizer for use in the microwave and millimeter-wave frequency ranges utilizing a photonic mixer as a photonic phase detector in a stable optical fiber delay-line. Phase and frequency fluctuations of the heterodyne laser signal generators are stabilized at microwave and millimeter wave frequencies by a delay line system operating as a frequency discriminator. The present invention is free from amplifier and mixer 1/.function. noise at microwave and millimeter-wave frequencies that typically limit phase noise performance in electronic cavity stabilized electronic oscillators. Thus, 1/.function. noise due to conventional mixers is eliminated and stable optical heterodyne generation of electrical signals is achieved.

SUBGR: A Program to Generate Subgroup Data for the Subgroup Resonance Self-Shielding Calculation

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

Kim, Kang Seog

2016-06-06

The Subgroup Data Generation (SUBGR) program generates subgroup data, including levels and weights from the resonance self-shielded cross section table as a function of background cross section. Depending on the nuclide and the energy range, these subgroup data can be generated by (a) narrow resonance approximation, (b) pointwise flux calculations for homogeneous media; and (c) pointwise flux calculations for heterogeneous lattice cells. The latter two options are performed by the AMPX module IRFFACTOR. These subgroup data are to be used in the Consortium for Advanced Simulation of Light Water Reactors (CASL) neutronic simulator MPACT, for which the primary resonance self-shieldingmore » method is the subgroup method.« less

Structure guided GANs

NASA Astrophysics Data System (ADS)

Cao, Feidao; Zhao, Huaici; Liu, Pengfei

2017-11-01

Generative adversarial networks (GANs) has achieved success in many fields. However, there are some samples generated by many GAN-based works, whose structure is ambiguous. In this work, we propose Structure Guided GANs that introduce structural similar into GANs to overcome the problem. In order to achieve our goal, we introduce an encoder and a decoder into a generator to design a new generator and take real samples as part of the input of a generator. And we modify the loss function of the generator accordingly. By comparison with WGAN, experimental results show that our proposed method overcomes largely sample structure ambiguous and can generate higher quality samples.

Effect of Forcing Function on Nonlinear Acoustic Standing Waves

NASA Technical Reports Server (NTRS)

Finkheiner, Joshua R.; Li, Xiao-Fan; Raman, Ganesh; Daniels, Chris; Steinetz, Bruce

2003-01-01

Nonlinear acoustic standing waves of high amplitude have been demonstrated by utilizing the effects of resonator shape to prevent the pressure waves from entering saturation. Experimentally, nonlinear acoustic standing waves have been generated by shaking an entire resonating cavity. While this promotes more efficient energy transfer than a piston-driven resonator, it also introduces complicated structural dynamics into the system. Experiments have shown that these dynamics result in resonator forcing functions comprised of a sum of several Fourier modes. However, previous numerical studies of the acoustics generated within the resonator assumed simple sinusoidal waves as the driving force. Using a previously developed numerical code, this paper demonstrates the effects of using a forcing function constructed with a series of harmonic sinusoidal waves on resonating cavities. From these results, a method will be demonstrated which allows the direct numerical analysis of experimentally generated nonlinear acoustic waves in resonators driven by harmonic forcing functions.

A probabilistic approach to photovoltaic generator performance prediction

NASA Astrophysics Data System (ADS)

Khallat, M. A.; Rahman, S.

1986-09-01

A method for predicting the performance of a photovoltaic (PV) generator based on long term climatological data and expected cell performance is described. The equations for cell model formulation are provided. Use of the statistical model for characterizing the insolation level is discussed. The insolation data is fitted to appropriate probability distribution functions (Weibull, beta, normal). The probability distribution functions are utilized to evaluate the capacity factors of PV panels or arrays. An example is presented revealing the applicability of the procedure.

Multi-dimensional Rankings, Program Termination, and Complexity Bounds of Flowchart Programs

NASA Astrophysics Data System (ADS)

Alias, Christophe; Darte, Alain; Feautrier, Paul; Gonnord, Laure

Proving the termination of a flowchart program can be done by exhibiting a ranking function, i.e., a function from the program states to a well-founded set, which strictly decreases at each program step. A standard method to automatically generate such a function is to compute invariants for each program point and to search for a ranking in a restricted class of functions that can be handled with linear programming techniques. Previous algorithms based on affine rankings either are applicable only to simple loops (i.e., single-node flowcharts) and rely on enumeration, or are not complete in the sense that they are not guaranteed to find a ranking in the class of functions they consider, if one exists. Our first contribution is to propose an efficient algorithm to compute ranking functions: It can handle flowcharts of arbitrary structure, the class of candidate rankings it explores is larger, and our method, although greedy, is provably complete. Our second contribution is to show how to use the ranking functions we generate to get upper bounds for the computational complexity (number of transitions) of the source program. This estimate is a polynomial, which means that we can handle programs with more than linear complexity. We applied the method on a collection of test cases from the literature. We also show the links and differences with previous techniques based on the insertion of counters.

Nitric oxide therapies for local inhibition of platelets' activitation on blood-contacting surfaces

NASA Astrophysics Data System (ADS)

Amoako, Kagya Agyeman

Blood-contacting devices interact with blood during their function much like the endothelium that modulates hemostasis. The surfaces of these devices however, lack endothelial-like properties, and consequently, upon blood contact, activate clotting factors to form clots. Systemic heparinization for inhibiting clot formation can cause bleeding and surface coatings show insignificant benefits. This research investigated nitric oxide (NO) production mimicry of the endothehum on artificial lungs (ALs) and pediatric catheters. Their surfaces were functionalized either by (1) entrapping NO donors inside their bulk, (2) incorporating catalysts to generate NO from NO-donors or (3) supplementing NO into sweep gas of artificial lungs. Pediatric catheters functionalized with NO-donor thin coats using method 1 is limited by short NO release duration. Method 2 has not been applied to large surface-area, low-flow devices like the AL. In this work NO-generating silicone membranes were synthesized and characterized to determine the relationship between surface properties, NO flux, and blood clotting time. These outcomes helped develop and optimize NO-generating gas-exchange silicone fibers that represent the majority of ALs surface area. The first NO-generating AL prototypes, using those fibers, were manufactured, incorporated into NO-generating circuits and tested for their non-thrombogenicity. To test for NO-release duration and non-thrombogenicity, catheters were fabricated to incorporate NO-donors inside their walls, characterized for NO flux and release duration by chemilumincscence, and tested for patency using a thrombogenicity model in rabbits. Methods 1-2 involve material modification using complicated and expensive chemical formulations and/or manufacturing. Method 3 however, functionalizes ALs by only adding NO into sweep gas. Decade-long anti-clotting testing using a wide range of NO concentrations has been conducted without knowledge of what concentration yields endothelial NO flux levels in the AL. This concentration was determined for the MC3 Biolung and the Terumo capiox rx25 ALs in vitro. All these ideas have shown positive results in short-term studies, and each may play a necessary role in inhibiting clot formation in future ALs. The sufficiency however, of each idea or of a combination for clot inhibition in long-term ALs remains to be determined.

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

Generating multi-double-scroll attractors via nonautonomous approach.

PubMed

Hong, Qinghui; Xie, Qingguo; Shen, Yi; Wang, Xiaoping

2016-08-01

It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

[Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

PubMed

Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

2018-01-01

To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

On the Convergence Analysis of the Optimized Gradient Method.

PubMed

Kim, Donghwan; Fessler, Jeffrey A

2017-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov's fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization.

On the Convergence Analysis of the Optimized Gradient Method

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2016-01-01

This paper considers the problem of unconstrained minimization of smooth convex functions having Lipschitz continuous gradients with known Lipschitz constant. We recently proposed the optimized gradient method for this problem and showed that it has a worst-case convergence bound for the cost function decrease that is twice as small as that of Nesterov’s fast gradient method, yet has a similarly efficient practical implementation. Drori showed recently that the optimized gradient method has optimal complexity for the cost function decrease over the general class of first-order methods. This optimality makes it important to study fully the convergence properties of the optimized gradient method. The previous worst-case convergence bound for the optimized gradient method was derived for only the last iterate of a secondary sequence. This paper provides an analytic convergence bound for the primary sequence generated by the optimized gradient method. We then discuss additional convergence properties of the optimized gradient method, including the interesting fact that the optimized gradient method has two types of worstcase functions: a piecewise affine-quadratic function and a quadratic function. These results help complete the theory of an optimal first-order method for smooth convex minimization. PMID:28461707

Post-transcriptional labeling by using Suzuki-Miyaura cross-coupling generates functional RNA probes.

PubMed

Walunj, Manisha B; Tanpure, Arun A; Srivatsan, Seergazhi G

2018-06-20

Pd-catalyzed C-C bond formation, an important vertebra in the spine of synthetic chemistry, is emerging as a valuable chemoselective transformation for post-synthetic functionalization of biomacromolecules. While methods are available for labeling protein and DNA, development of an analogous procedure to label RNA by cross-coupling reactions remains a major challenge. Herein, we describe a new Pd-mediated RNA oligonucleotide (ON) labeling method that involves post-transcriptional functionalization of iodouridine-labeled RNA transcripts by using Suzuki-Miyaura cross-coupling reaction. 5-Iodouridine triphosphate (IUTP) is efficiently incorporated into RNA ONs at one or more sites by T7 RNA polymerase. Further, using a catalytic system made of Pd(OAc)2 and 2-aminopyrimidine-4,6-diol (ADHP) or dimethylamino-substituted ADHP (DMADHP), we established a modular method to functionalize iodouridine-labeled RNA ONs in the presence of various boronic acid and ester substrates under very mild conditions (37°C and pH 8.5). This method is highly chemoselective, and offers direct access to RNA ONs labeled with commonly used fluorescent and affinity tags and new fluorogenic environment-sensitive nucleoside probes in a ligand-controlled stereoselective fashion. Taken together, this simple approach of generating functional RNA ON probes by Suzuki-Miyaura coupling will be a very important addition to the resources and tools available for analyzing RNA motifs.

An alternative extragradient projection method for quasi-equilibrium problems.

PubMed

Chen, Haibin; Wang, Yiju; Xu, Yi

2018-01-01

For the quasi-equilibrium problem where the players' costs and their strategies both depend on the rival's decisions, an alternative extragradient projection method for solving it is designed. Different from the classical extragradient projection method whose generated sequence has the contraction property with respect to the solution set, the newly designed method possesses an expansion property with respect to a given initial point. The global convergence of the method is established under the assumptions of pseudomonotonicity of the equilibrium function and of continuity of the underlying multi-valued mapping. Furthermore, we show that the generated sequence converges to the nearest point in the solution set to the initial point. Numerical experiments show the efficiency of the method.

Quantitative Photochemical Immobilization of Biomolecules on Planar and Corrugated Substrates: A Versatile Strategy for Creating Functional Biointerfaces

PubMed Central

Martin, Teresa A.; Herman, Christine T.; Limpoco, Francis T.; Michael, Madeline C.; Potts, Gregory K.; Bailey, Ryan C.

2014-01-01

Methods for the generation of substrates presenting biomolecules in a spatially controlled manner are enabling tools for applications in biosensor systems, microarray technologies, fundamental biological studies and biointerface science. We have implemented a method to create biomolecular patterns by using light to control the direct covalent immobilization of biomolecules onto benzophenone-modified glass substrates. We have generated substrates presenting up to three different biomolecules patterned in sequence, and demonstrate biomolecular photopatterning on corrugated substrates. The chemistry of the underlying monolayer was optimized to incorporate poly(ethylene glycol) to enable adhesive cell adhesion onto patterned extracellular matrix proteins. Substrates were characterized with contact angle goniometry, AFM, and immunofluorescence microscopy. Importantly, radioimmunoassays were performed to quantify the site density of immobilized biomolecules on photopatterned substrates. Retention of function of photopatterned proteins was demonstrated both by native ligand recognition and cell adhesion to photopatterned substrates, revealing that substrates generated with this method are suitable for probing specific cell receptor-ligand interactions. This molecularly general photochemical patterning method is an enabling tool that will allow the creation of substrates presenting both biochemical and topographical variation, which is an important feature of many native biointerfaces. PMID:21793535

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced.more » The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

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

Wang, Qin; Florita, Anthony R; Krishnan, Venkat K

2017-08-31

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) ismore » analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.« less

Global optimization framework for solar building design

NASA Astrophysics Data System (ADS)

Silva, N.; Alves, N.; Pascoal-Faria, P.

2017-07-01

The generative modeling paradigm is a shift from static models to flexible models. It describes a modeling process using functions, methods and operators. The result is an algorithmic description of the construction process. Each evaluation of such an algorithm creates a model instance, which depends on its input parameters (width, height, volume, roof angle, orientation, location). These values are normally chosen according to aesthetic aspects and style. In this study, the model's parameters are automatically generated according to an objective function. A generative model can be optimized according to its parameters, in this way, the best solution for a constrained problem is determined. Besides the establishment of an overall framework design, this work consists on the identification of different building shapes and their main parameters, the creation of an algorithmic description for these main shapes and the formulation of the objective function, respecting a building's energy consumption (solar energy, heating and insulation). Additionally, the conception of an optimization pipeline, combining an energy calculation tool with a geometric scripting engine is presented. The methods developed leads to an automated and optimized 3D shape generation for the projected building (based on the desired conditions and according to specific constrains). The approach proposed will help in the construction of real buildings that account for less energy consumption and for a more sustainable world.

Habitat suitability criteria via parametric distributions: estimation, model selection and uncertainty

USGS Publications Warehouse

Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.

2016-01-01

Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Factor analysis for delineation of organ structures, creation of in- and output functions, and standardization of multicenter kinetic modeling

NASA Astrophysics Data System (ADS)

Schiepers, Christiaan; Hoh, Carl K.; Dahlbom, Magnus; Wu, Hsiao-Ming; Phelps, Michael E.

1999-05-01

PET imaging can quantify metabolic processes in-vivo; this requires the measurement of an input function which is invasive and labor intensive. A non-invasive, semi-automated, image based method of input function generation would be efficient, patient friendly, and allow quantitative PET to be applied routinely. A fully automated procedure would be ideal for studies across institutions. Factor analysis (FA) was applied as processing tool for definition of temporally changing structures in the field of view. FA has been proposed earlier, but the perceived mathematical difficulty has prevented widespread use. FA was utilized to delineate structures and extract blood and tissue time-activity-curves (TACs). These TACs were used as input and output functions for tracer kinetic modeling, the results of which were compared with those from an input function obtained with serial blood sampling. Dynamic image data of myocardial perfusion studies with N-13 ammonia, O-15 water, or Rb-82, cancer studies with F-18 FDG, and skeletal studies with F-18 fluoride were evaluated. Correlation coefficients of kinetic parameters obtained with factor and plasma input functions were high. Linear regression usually furnished a slope near unity. Processing time was 7 min/patient on an UltraSPARC. Conclusion: FA can non-invasively generate input functions from image data eliminating the need for blood sampling. Output (tissue) functions can be simultaneously generated. The method is simple, requires no sophisticated operator interaction and has little inter-operator variability. FA is well suited for studies across institutions and standardized evaluations.

A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection.

PubMed

Hua, Chengcheng; Wang, Hong; Wang, Hong; Lu, Shaowen; Liu, Chong; Khalid, Syed Madiha

2018-04-11

Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of this study is to detect the proficiency of operators during their mineral grinding process controlling based on FBN. To save the search time, a novel semi-data-driven method of computing functional brain connection based on stacked autoencoder (BCSAE) is proposed in this paper. This method uses stacked autoencoder (SAE) to encode the multi-channel EEG data into codes and then computes the dissimilarity between the codes from every pair of electrodes to build FBN. The highlight of this method is that the SAE has a multi-layered structure and is semi-supervised, which means it can dig deeper information and generate better features. Then an experiment was performed, the EEG of the operators were collected while they were operating and analyzed to detect their proficiency. The results show that the BCSAE method generated more number of separable features with less redundancy, and the average accuracy of classification (96.18%) is higher than that of the control methods: PLV (92.19%) and PLI (78.39%).

Identification of boiler inlet transfer functions and estimation of system parameters

NASA Technical Reports Server (NTRS)

Miles, J. H.

1972-01-01

An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function of the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

PubMed

Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Simulation of random road microprofile based on specified correlation function

NASA Astrophysics Data System (ADS)

Rykov, S. P.; Rykova, O. A.; Koval, V. S.; Vlasov, V. G.; Fedotov, K. V.

2018-03-01

The paper aims to develop a numerical simulation method and an algorithm for a random microprofile of special roads based on the specified correlation function. The paper used methods of correlation, spectrum and numerical analysis. It proves that the transfer function of the generating filter for known expressions of spectrum input and output filter characteristics can be calculated using a theorem on nonnegative and fractional rational factorization and integral transformation. The model of the random function equivalent of the real road surface microprofile enables us to assess springing system parameters and identify ranges of variations.

General method of solving the Schroedinger equation of atoms and molecules

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

Nakatsuji, Hiroshi

2005-12-15

We propose a general method of solving the Schroedinger equation of atoms and molecules. We first construct the wave function having the exact structure, using the ICI (iterative configuration or complement interaction) method and then optimize the variables involved by the variational principle. Based on the scaled Schroedinger equation and related principles, we can avoid the singularity problem of atoms and molecules and formulate a general method of calculating the exact wave functions in an analytical expansion form. We choose initial function {psi}{sub 0} and scaling g function, and then the ICI method automatically generates the wave function that hasmore » the exact structure by using the Hamiltonian of the system. The Hamiltonian contains all the information of the system. The free ICI method provides a flexible and variationally favorable procedure of constructing the exact wave function. We explain the computational procedure of the analytical ICI method routinely performed in our laboratory. Simple examples are given using hydrogen atom for the nuclear singularity case, the Hooke's atom for the electron singularity case, and the helium atom for both cases.« less

A new method to calculate the beam charge for an integrating current transformer

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

Wu Yuchi; Han Dan; Zhu Bin

2012-09-15

The integrating current transformer (ICT) is a magnetic sensor widely used to precisely measure the charge of an ultra-short-pulse charged particle beam generated by traditional accelerators and new laser-plasma particle accelerators. In this paper, we present a new method to calculate the beam charge in an ICT based on circuit analysis. The output transfer function shows an invariable signal profile for an ultra-short electron bunch, so the function can be used to evaluate the signal quality and calculate the beam charge through signal fitting. We obtain a set of parameters in the output function from a standard signal generated bymore » an ultra-short electron bunch (about 1 ps in duration) at a radio frequency linear electron accelerator at Tsinghua University. These parameters can be used to obtain the beam charge by signal fitting with excellent accuracy.« less

Improvements on non-equilibrium and transport Green function techniques: The next-generation TRANSIESTA

NASA Astrophysics Data System (ADS)

Papior, Nick; Lorente, Nicolás; Frederiksen, Thomas; García, Alberto; Brandbyge, Mads

2017-03-01

We present novel methods implemented within the non-equilibrium Green function code (NEGF) TRANSIESTA based on density functional theory (DFT). Our flexible, next-generation DFT-NEGF code handles devices with one or multiple electrodes (Ne ≥ 1) with individual chemical potentials and electronic temperatures. We describe its novel methods for electrostatic gating, contour optimizations, and assertion of charge conservation, as well as the newly implemented algorithms for optimized and scalable matrix inversion, performance-critical pivoting, and hybrid parallelization. Additionally, a generic NEGF "post-processing" code (TBTRANS/PHTRANS) for electron and phonon transport is presented with several novelties such as Hamiltonian interpolations, Ne ≥ 1 electrode capability, bond-currents, generalized interface for user-defined tight-binding transport, transmission projection using eigenstates of a projected Hamiltonian, and fast inversion algorithms for large-scale simulations easily exceeding 106 atoms on workstation computers. The new features of both codes are demonstrated and bench-marked for relevant test systems.

Experimental observation of acoustic emissions generated by a pulsed proton beam from a hospital-based clinical cyclotron

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

Jones, Kevin C.; Solberg, Timothy D.; Avery, Stephen, E-mail: Stephen.Avery@uphs.upenn.edu

Purpose: To measure the acoustic signal generated by a pulsed proton spill from a hospital-based clinical cyclotron. Methods: An electronic function generator modulated the IBA C230 isochronous cyclotron to create a pulsed proton beam. The acoustic emissions generated by the proton beam were measured in water using a hydrophone. The acoustic measurements were repeated with increasing proton current and increasing distance between detector and beam. Results: The cyclotron generated proton spills with rise times of 18 μs and a maximum measured instantaneous proton current of 790 nA. Acoustic emissions generated by the proton energy deposition were measured to be onmore » the order of mPa. The origin of the acoustic wave was identified as the proton beam based on the correlation between acoustic emission arrival time and distance between the hydrophone and proton beam. The acoustic frequency spectrum peaked at 10 kHz, and the acoustic pressure amplitude increased monotonically with increasing proton current. Conclusions: The authors report the first observation of acoustic emissions generated by a proton beam from a hospital-based clinical cyclotron. When modulated by an electronic function generator, the cyclotron is capable of creating proton spills with fast rise times (18 μs) and high instantaneous currents (790 nA). Measurements of the proton-generated acoustic emissions in a clinical setting may provide a method for in vivo proton range verification and patient monitoring.« less

Concentrated solar power generation using solar receivers

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

Anderson, Bruce N.; Treece, William Dean; Brown, Dan

Inventive concentrated solar power systems using solar receivers, and related devices and methods, are generally described. Low pressure solar receivers are provided that function to convert solar radiation energy to thermal energy of a working fluid, e.g., a working fluid of a power generation or thermal storage system. In some embodiments, low pressure solar receivers are provided herein that are useful in conjunction with gas turbine based power generation systems.

Model-Driven Engineering: Automatic Code Generation and Beyond

DTIC Science & Technology

2015-03-01

and Weblogic as well as cloud environments such as Mi- crosoft Azure and Amazon Web Services®. Finally, while the generated code has dependencies on...code generation in the context of the full system lifecycle from development to sustainment. Acquisition programs in govern- ment or large commercial...Acquirers are concerned with the full system lifecycle, and they need confidence that the development methods will enable the system to meet the functional

Phase dilemma in natural orbital functional theory from the N-representability perspective

NASA Astrophysics Data System (ADS)

Mitxelena, Ion; Rodriguez-Mayorga, Mauricio; Piris, Mario

2018-06-01

Any rigorous approach to first-order reduced density matrix ( Γ) functional theory faces the phase dilemma, that is, having to deal with a large number of possible combinations of signs in terms of the electron-electron interaction energy. This problem was discovered by reducing a ground-state energy generated from an approximate N-particle wavefunction into a functional of Γ, known as the top-down method. Here, we show that the phase dilemma also appears in the bottom-up method, in which the functional E[ Γ] is generated by progressive inclusion of N-representability conditions on the reconstructed two-particle reduced density matrix. It is shown that an adequate choice of signs is essential to accurately describe model systems with strong non-dynamic (static) electron correlation, specifically, the one-dimensional Hubbard model with periodic boundary conditions and hydrogen rings. For the latter, the Piris natural orbital functional 7 (PNOF7), with phases equal to -1 for the inter-pair energy terms containing the exchange-time-inversion integrals, agrees with exact diagonalization results.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

A comparison of small-field tissue phantom ratio data generation methods for an Elekta Agility 6 MV photon beam

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

Richmond, Neil, E-mail: neil.richmond@stees.nhs.uk; Brackenridge, Robert

2014-04-01

Tissue-phantom ratios (TPRs) are a common dosimetric quantity used to describe the change in dose with depth in tissue. These can be challenging and time consuming to measure. The conversion of percentage depth dose (PDD) data using standard formulae is widely employed as an alternative method in generating TPR. However, the applicability of these formulae for small fields has been questioned in the literature. Functional representation has also been proposed for small-field TPR production. This article compares measured TPR data for small 6 MV photon fields against that generated by conversion of PDD using standard formulae to assess the efficacymore » of the conversion data. By functionally fitting the measured TPR data for square fields greater than 4 cm in length, the TPR curves for smaller fields are generated and compared with measurements. TPRs and PDDs were measured in a water tank for a range of square field sizes. The PDDs were converted to TPRs using standard formulae. TPRs for fields of 4 × 4 cm{sup 2} and larger were used to create functional fits. The parameterization coefficients were used to construct extrapolated TPR curves for 1 × 1 cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields. The TPR data generated using standard formulae were in excellent agreement with direct TPR measurements. The TPR data for 1 × 1-cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields created by extrapolation of the larger field functional fits gave inaccurate initial results. The corresponding mean differences for the 3 fields were 4.0%, 2.0%, and 0.9%. Generation of TPR data using a standard PDD-conversion methodology has been shown to give good agreement with our directly measured data for small fields. However, extrapolation of TPR data using the functional fit to fields of 4 × 4 cm{sup 2} or larger resulted in generation of TPR curves that did not compare well with the measured data.« less

GridMan: A grid manipulation system

NASA Technical Reports Server (NTRS)

Eiseman, Peter R.; Wang, Zhu

1992-01-01

GridMan is an interactive grid manipulation system. It operates on grids to produce new grids which conform to user demands. The input grids are not constrained to come from any particular source. They may be generated by algebraic methods, elliptic methods, hyperbolic methods, parabolic methods, or some combination of methods. The methods are included in the various available structured grid generation codes. These codes perform the basic assembly function for the various elements of the initial grid. For block structured grids, the assembly can be quite complex due to a large number of clock corners, edges, and faces for which various connections and orientations must be properly identified. The grid generation codes are distinguished among themselves by their balance between interactive and automatic actions and by their modest variations in control. The basic form of GridMan provides a much more substantial level of grid control and will take its input from any of the structured grid generation codes. The communication link to the outside codes is a data file which contains the grid or section of grid.

Multispectral photoacoustic method for the early detection and diagnosis of osteoporosis

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Eyal, Avishay; Gannot, Israel

2013-03-01

Osteoporosis is a major health problem worldwide, with healthcare costs of billions of dollars annually. The risk of fracture depends on the bone mineral density (measured in clinical practice) as well as on the bone microstructure and functional status. Since pure ultrasonic methods can measure bone strength and spectroscopic optical methods can provide valuable functional information, a hybrid multispectral photoacoustic technique can be of great value. We have developed such a system based on a tunable Ti:Sapph laser at 750 - 950 nm, followed by an acousto-optic modulator to generate photoacoustic signals with frequencies of 0.5 - 2.5 MHz. Another system was based on two directly modulated 830nm laser diodes. The systems were used to photoacoustically excite the proximal end of a rat tibia. Spectrum analyzer with tracking generator was used for measuring both the amplitude and the phase at the distal end. Scanning along both the optical wavelength as well as the acoustic frequency enables full mapping of the bone transfer function. Analyzing this function along the wavelength axis allows deducing the gross biochemical composition related to the bone functional and pathological state. Analyzing the amplitude and phase along the acoustic frequency axis yields the speed of sound dispersion and the broadband ultrasonic attenuation - both have shown clinical relevance.

Febrile Seizures and Behavioural and Cognitive Outcomes in Preschool Children: The Generation R Study

ERIC Educational Resources Information Center

Visser, Annemarie M.; Jaddoe, Vincent W. V.; Ghassabian, Akhgar; Schenk, Jacqueline J.; Verhulst, Frank C.; Hofman, Albert; Tiemeier, Henning; Moll, Henriette A.; Arts, Willem Frans M.

2012-01-01

Aim: General developmental outcome is known to be good in school-aged children who experienced febrile seizures. We examined cognitive and behavioural outcomes in preschool children with febrile seizures, including language and executive functioning outcomes. Method: This work was performed in the Generation R Study, a population-based cohort…

Deep sequencing methods for protein engineering and design.

PubMed

Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.

PubMed

Jiang, Z; Chen, W; Burkhart, C

2013-11-01

Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Band-limited Green's Functions for Quantitative Evaluation of Acoustic Emission Using the Finite Element Method

NASA Technical Reports Server (NTRS)

Leser, William P.; Yuan, Fuh-Gwo; Leser, William P.

2013-01-01

A method of numerically estimating dynamic Green's functions using the finite element method is proposed. These Green's functions are accurate in a limited frequency range dependent on the mesh size used to generate them. This range can often match or exceed the frequency sensitivity of the traditional acoustic emission sensors. An algorithm is also developed to characterize an acoustic emission source by obtaining information about its strength and temporal dependence. This information can then be used to reproduce the source in a finite element model for further analysis. Numerical examples are presented that demonstrate the ability of the band-limited Green's functions approach to determine the moment tensor coefficients of several reference signals to within seven percent, as well as accurately reproduce the source-time function.

POLYANA-A tool for the calculation of molecular radial distribution functions based on Molecular Dynamics trajectories

NASA Astrophysics Data System (ADS)

Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios

2015-12-01

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.

Frontier production function estimates for steam electric generation: a comparative analysis

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

Kopp, R.J.; Smith, V.K.

1980-04-01

The performance of three frontier steam electric generation estimators is compared in terms of the consideration given to new production technologies and their technical efficiency. The Cobb-Douglas, constant elasticity of substitution, and translog production functions are examined, using the Aigner-Chu linear programming, the sophisticated Aigner-Lovell-Schmidt stochastic frontier, and the direct method of adjusted ordinary least squares frontier estimators. The use of Cobb-Douglas specification is judged to have narrowed the perceived difference between competing estimators. The choice of frontier estimator is concluded to have a greater effect on the plant efficiency than functional form. 19 references. (DCK)

Auxiliary-field-based trial wave functions in quantum Monte Carlo calculations

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

Chang, Chia -Chen; Rubenstein, Brenda M.; Morales, Miguel A.

2016-12-19

Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen limited use in second-quantized QMC methods, particularly in projection methods that involve a stochastic evolution of the wave function in imaginary time. Here we propose a scheme for generating Jastrow-type correlated trial wave functions for auxiliary-field QMC methods. The method is based on decoupling the two-body Jastrow into one-body projectors coupled to auxiliary fields, which then operate on a single determinant to produce a multideterminant trial wavemore » function. We demonstrate that intelligent sampling of the most significant determinants in this expansion can produce compact trial wave functions that reduce errors in the calculated energies. Lastly, our technique may be readily generalized to accommodate a wide range of two-body Jastrow factors and applied to a variety of model and chemical systems.« less

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

Dag, Serkan; Yildirim, Bora; Sabuncuoglu, Baris

The objective of this study is to develop crack growth analysis methods for functionally graded materials (FGMs) subjected to mode I cyclic loading. The study presents finite elements based computational procedures for both two and three dimensional problems to examine fatigue crack growth in functionally graded materials. Developed methods allow the computation of crack length and generation of crack front profile for a graded medium subjected to fluctuating stresses. The results presented for an elliptical crack embedded in a functionally graded medium, illustrate the competing effects of ellipse aspect ratio and material property gradation on the fatigue crack growth behavior.

Investigation of another approach in topology optimization

NASA Astrophysics Data System (ADS)

Krotkikh, A. A.; Maximov, P. V.

2018-05-01

The paper presents investigation of another approach in topology optimization. The authors realized the method of topology optimization with using ideas of the SIMP method which was created by Martin P. Bends0e. There are many ways in objective function formulation of topology optimization methods. In terms of elasticity theory, the objective function of the SIMP method is a compliance of an object which should be minimized. The main idea of this paper was avoiding the filtering procedure in the SIMP method. Reformulation of the statement of the problem in terms of function minimization allows us to solve this by big variety of methods. The authors decided to use the interior point method which was realized in Wolfram Mathematica. This way can generate side effects which should be investigated for preventing their appearing in future. Results comparison of the SIMP method and the suggested method are presented in paper and analyzed.

Accurate evaluation and analysis of functional genomics data and methods

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2016-01-01

The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner. PMID:22268703

A machine learning approach for efficient uncertainty quantification using multiscale methods

NASA Astrophysics Data System (ADS)

Chan, Shing; Elsheikh, Ahmed H.

2018-02-01

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.

MIPS bacterial genomes functional annotation benchmark dataset.

PubMed

Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

2005-05-15

Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

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

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

PubMed

Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

2018-04-17

The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

Analysis and Modeling of Shear Waves Generated by Explosions at the San Andreas Fault Observatory at Depth

DTIC Science & Technology

2011-09-01

No. BAA09-69 ABSTRACT Using multiple deployments of an 80-element, three-component borehole seismic array stretching from the surface to 2.3 km...NNSA). 14. ABSTRACT Using multiple deployments of an 80-element, three-component borehole seismic array stretching from the surface to 2.3 km depth...generated using the direct Green’s function (DGF) method of Friederich and Dalkolmo (1995). This method synthesizes the seismic wavefield for a spherically

Therapeutic Inhibitors of LIN28/let-7 Pathway in Ovarian Cancer

DTIC Science & Technology

2015-09-01

of-function cell lines to complement our already generated shRNA lines, we are developing handson experience with CrispR /Cas9 technology to...generate stable cell lines where our genes of interest will be inactivated. The advantage of the CrispR /Cas9 method is that stable lines can be...ovarian cancer cell lines using two distinct RNAi methods, shRNA and siRNA. We plan to explore the feasibility of using the CrispR /Cas9 system to

Advances in generation of functional β-cells from induced pluripotent stem cells as a cure for diabetes mellitus.

PubMed

Kalra, Kunal; Chandrabose, Srijaya Thekkeparambil; Ramasamy, Thamil Selvee; Kasim, Noor Hayaty Binti Abu

2018-06-04

Diabetes mellitus is one of the leading cause for death worldwide. Loss and functional failure of pancreatic β-cells, the parenchyma cells in the islets of Langerhans onsets and progresses diabetes mellitus. The increasing incidence of this metabolic disorder necessitates efficient strategies to produce functional β-cells for treating diabetes mellitus. Human induced pluripotent stem cells (hiPSC), holds potential for treating diabetes owning to their self-renewal capacity and ability to differentiate into β-cells. iPSC technology also provides unlimited starting material to generate differentiated cells for regenerative applications. Progress has also been made in establishing in-vitro culture protocols to yield definitive endoderm, pancreatic endoderm progenitor cells and β-cells via different reprogramming strategies and growth factor supplementation. However, these generated β-cells are still immature, lack functional characteristics and exhibit lower capability in reversing the diseases conditions. Current methods employed to generate mature and functional β-cells include; use of small and large molecules to enhance the reprogramming and differentiation efficiency, 3D culture systems to improve the functional properties and heterogeneity of differentiated cells. This review details recent advancements in the generation of mature β-cells by reprogramming stem cells into iPSCs that is further programmed to β-cells. It also provides deeper insight of current reprogramming protocols and their efficacy, focusing on the underlying mechanism of chemical based approach to generate iPSCs. Furthermore, we have highlighted the recent differentiation strategies both in-vitro and in-vivo to date and the future prospects in generation of mature β-cells. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Variants of glycerol dehydrogenase having D-lactate dehydrogenase activity and uses thereof

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

Wang, Qingzhao; Shanmugam, Keelnatham T.; Ingram, Lonnie O'Neal

The present invention provides methods of designing and generating glycerol dehydrogenase (GlyDH) variants that have altered function as compared to a parent polypeptide. The present invention further provides nucleic acids encoding GlyDH polypeptide variants having altered function as compared to the parent polypeptide. Host cells comprising polynucleotides encoding GlyDH variants and methods of producing lactic acids are also provided in various aspects of the invention.

High-performance single cell genetic analysis using microfluidic emulsion generator arrays.

PubMed

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T; Mathies, Richard A

2010-04-15

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex polymerase chain reaction (PCR). Microfabricated emulsion generator array (MEGA) devices containing 4, 32, and 96 channels are developed to confer a flexible capability of generating up to 3.4 x 10(6) nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed and the beads are pooled and rapidly analyzed by multicolor flow cytometry. Using Escherichia coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1/10(5). This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations.

High-Performance Single Cell Genetic Analysis Using Microfluidic Emulsion Generator Arrays

PubMed Central

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T.; Mathies, Richard A.

2010-01-01

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex PCR. Microfabricated emulsion generator array (MEGA) devices containing 4, 32 and 96 channels are developed to confer a flexible capability of generating up to 3.4 × 106 nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed, the beads are pooled and rapidly analyzed by multi-color flow cytometry. Using E. coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1:105. This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations. PMID:20192178

System and method for characterizing synthesizing and/or canceling out acoustic signals from inanimate sound sources

DOEpatents

Holzrichter, John F.; Burnett, Greg C.; Ng, Lawrence C.

2003-01-01

A system and method for characterizing, synthesizing, and/or canceling out acoustic signals from inanimate sound sources is disclosed. Propagating wave electromagnetic sensors monitor excitation sources in sound producing systems, such as machines, musical instruments, and various other structures. Acoustical output from these sound producing systems is also monitored. From such information, a transfer function characterizing the sound producing system is generated. From the transfer function, acoustical output from the sound producing system may be synthesized or canceled. The methods disclosed enable accurate calculation of matched transfer functions relating specific excitations to specific acoustical outputs. Knowledge of such signals and functions can be used to effect various sound replication, sound source identification, and sound cancellation applications.

System and method for characterizing, synthesizing, and/or canceling out acoustic signals from inanimate sound sources

DOEpatents

Holzrichter, John F; Burnett, Greg C; Ng, Lawrence C

2013-05-21

A system and method for characterizing, synthesizing, and/or canceling out acoustic signals from inanimate sound sources is disclosed. Propagating wave electromagnetic sensors monitor excitation sources in sound producing systems, such as machines, musical instruments, and various other structures. Acoustical output from these sound producing systems is also monitored. From such information, a transfer function characterizing the sound producing system is generated. From the transfer function, acoustical output from the sound producing system may be synthesized or canceled. The methods disclosed enable accurate calculation of matched transfer functions relating specific excitations to specific acoustical outputs. Knowledge of such signals and functions can be used to effect various sound replication, sound source identification, and sound cancellation applications.

System and method for characterizing, synthesizing, and/or canceling out acoustic signals from inanimate sound sources

DOEpatents

Holzrichter, John F.; Burnett, Greg C.; Ng, Lawrence C.

2007-10-16

A system and method for characterizing, synthesizing, and/or canceling out acoustic signals from inanimate sound sources is disclosed. Propagating wave electromagnetic sensors monitor excitation sources in sound producing systems, such as machines, musical instruments, and various other structures. Acoustical output from these sound producing systems is also monitored. From such information, a transfer function characterizing the sound producing system is generated. From the transfer function, acoustical output from the sound producing system may be synthesized or canceled. The methods disclosed enable accurate calculation of matched transfer functions relating specific excitations to specific acoustical outputs. Knowledge of such signals and functions can be used to effect various sound replication, sound source identification, and sound cancellation applications.

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Securing Digital Audio using Complex Quadratic Map

NASA Astrophysics Data System (ADS)

Suryadi, MT; Satria Gunawan, Tjandra; Satria, Yudi

2018-03-01

In This digital era, exchanging data are common and easy to do, therefore it is vulnerable to be attacked and manipulated from unauthorized parties. One data type that is vulnerable to attack is digital audio. So, we need data securing method that is not vulnerable and fast. One of the methods that match all of those criteria is securing the data using chaos function. Chaos function that is used in this research is complex quadratic map (CQM). There are some parameter value that causing the key stream that is generated by CQM function to pass all 15 NIST test, this means that the key stream that is generated using this CQM is proven to be random. In addition, samples of encrypted digital sound when tested using goodness of fit test are proven to be uniform, so securing digital audio using this method is not vulnerable to frequency analysis attack. The key space is very huge about 8.1×l031 possible keys and the key sensitivity is very small about 10-10, therefore this method is also not vulnerable against brute-force attack. And finally, the processing speed for both encryption and decryption process on average about 450 times faster that its digital audio duration.

Green's function methods in heavy ion shielding

NASA Technical Reports Server (NTRS)

Wilson, John W.; Costen, Robert C.; Shinn, Judy L.; Badavi, Francis F.

1993-01-01

An analytic solution to the heavy ion transport in terms of Green's function is used to generate a highly efficient computer code for space applications. The efficiency of the computer code is accomplished by a nonperturbative technique extending Green's function over the solution domain. The computer code can also be applied to accelerator boundary conditions to allow code validation in laboratory experiments.

Generation of a Three-Dimensional Kidney Structure from Pluripotent Stem Cells.

PubMed

Yoshimura, Yasuhiro; Taguchi, Atsuhiro; Nishinakamura, Ryuichi

2017-01-01

The kidney is a vital organ that has an important role in the maintenance of homeostasis by fluid volume regulation and waste product excretion. This role cannot be performed without the three-dimensional (3D) structure of the kidney. Therefore, it is important to generate the 3D structure of the kidney when inducing functional kidney tissue or the whole organ from pluripotent stem cells. In this chapter, we describe the detailed methods to induce kidney progenitor cells from pluripotent stem cells, which are based on embryological development. We also provide a method to generate 3D kidney tissue with vascularized glomeruli upon transplantation.

Cylindric partitions, {{\\boldsymbol{ W }}}_{r} characters and the Andrews-Gordon-Bressoud identities

NASA Astrophysics Data System (ADS)

Foda, O.; Welsh, T. A.

2016-04-01

We study the Andrews-Gordon-Bressoud (AGB) generalisations of the Rogers-Ramanujan q-series identities in the context of cylindric partitions. We recall the definition of r-cylindric partitions, and provide a simple proof of Borodin’s product expression for their generating functions, that can be regarded as a limiting case of an unpublished proof by Krattenthaler. We also recall the relationships between the r-cylindric partition generating functions, the principal characters of {\\hat{{sl}}}r algebras, the {{\\boldsymbol{ M }}}r r,r+d minimal model characters of {{\\boldsymbol{ W }}}r algebras, and the r-string abaci generating functions, providing simple proofs for each. We then set r = 2, and use two-cylindric partitions to re-derive the AGB identities as follows. Firstly, we use Borodin’s product expression for the generating functions of the two-cylindric partitions with infinitely long parts, to obtain the product sides of the AGB identities, times a factor {(q;q)}∞ -1, which is the generating function of ordinary partitions. Next, we obtain a bijection from the two-cylindric partitions, via two-string abaci, into decorated versions of Bressoud’s restricted lattice paths. Extending Bressoud’s method of transforming between restricted paths that obey different restrictions, we obtain sum expressions with manifestly non-negative coefficients for the generating functions of the two-cylindric partitions which contains a factor {(q;q)}∞ -1. Equating the product and sum expressions of the same two-cylindric partitions, and canceling a factor of {(q;q)}∞ -1 on each side, we obtain the AGB identities.

Description of quasiparticle and satellite properties via cumulant expansions of the retarded one-particle Green's function

DOE PAGES

Mayers, Matthew Z.; Hybertsen, Mark S.; Reichman, David R.

2016-08-22

A cumulant-based GW approximation for the retarded one-particle Green's function is proposed, motivated by an exact relation between the improper Dyson self-energy and the cumulant generating function. We explore qualitative aspects of this method within a simple one-electron independent phonon model, where it is seen that the method preserves the energy moment of the spectral weight while also reproducing the exact Green's function in the weak-coupling limit. For the three-dimensional electron gas, this method predicts multiple satellites at the bottom of the band, albeit with inaccurate peak spacing. But, its quasiparticle properties and correlation energies are more accurate than bothmore » previous cumulant methods and standard G0W0. These results point to features that may be exploited within the framework of cumulant-based methods and suggest promising directions for future exploration and improvements of cumulant-based GW approaches.« less

The MusIC method: a fast and quasi-optimal solution to the muscle forces estimation problem.

PubMed

Muller, A; Pontonnier, C; Dumont, G

2018-02-01

The present paper aims at presenting a fast and quasi-optimal method of muscle forces estimation: the MusIC method. It consists in interpolating a first estimation in a database generated offline thanks to a classical optimization problem, and then correcting it to respect the motion dynamics. Three different cost functions - two polynomial criteria and a min/max criterion - were tested on a planar musculoskeletal model. The MusIC method provides a computation frequency approximately 10 times higher compared to a classical optimization problem with a relative mean error of 4% on cost function evaluation.

Grey Comprehensive Evaluation of Biomass Power Generation Project Based on Group Judgement

NASA Astrophysics Data System (ADS)

Xia, Huicong; Niu, Dongxiao

2017-06-01

The comprehensive evaluation of benefit is an important task needed to be carried out at all stages of biomass power generation projects. This paper proposed an improved grey comprehensive evaluation method based on triangle whiten function. To improve the objectivity of weight calculation result of only reference comparison judgment method, this paper introduced group judgment to the weighting process. In the process of grey comprehensive evaluation, this paper invited a number of experts to estimate the benefit level of projects, and optimized the basic estimations based on the minimum variance principle to improve the accuracy of evaluation result. Taking a biomass power generation project as an example, the grey comprehensive evaluation result showed that the benefit level of this project was good. This example demonstrates the feasibility of grey comprehensive evaluation method based on group judgment for benefit evaluation of biomass power generation project.

Ortho Image and DTM Generation with Intelligent Methods

NASA Astrophysics Data System (ADS)

Bagheri, H.; Sadeghian, S.

2013-10-01

Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

MacroEvoLution: A New Method for the Rapid Generation of Novel Scaffold-Diverse Macrocyclic Libraries.

PubMed

Saupe, Jörn; Kunz, Oliver; Haustedt, Lars Ole; Jakupovic, Sven; Mang, Christian

2017-09-04

Macrocycles are a structural class bearing great promise for future challenges in medicinal chemistry. Nevertheless, there are few flexible approaches for the rapid generation of structurally diverse macrocyclic compound collections. Here, an efficient method for the generation of novel macrocyclic peptide-based scaffolds is reported. The process, named here as "MacroEvoLution", is based on a cyclization screening approach that gives reliable access to novel macrocyclic architectures. Classification of building blocks into specific pools ensures that scaffolds with orthogonally addressable functionalities are generated, which can easily be used for the generation of structurally diverse compound libraries. The method grants rapid access to novel scaffolds with scalable synthesis (multi gram scale) and the introduction of further diversity at a late stage. Despite being developed for peptidic systems, the approach can easily be extended for the synthesis of systems with a decreased peptidic character. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Generating multi-double-scroll attractors via nonautonomous approach

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

Hong, Qinghui; Xie, Qingguo, E-mail: qgxie@mail.hust.edu.cn; Shen, Yi

It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify themore » availability and feasibility of this method.« less

Generation of Synthetic Copolymer Libraries by Combinatorial Assembly on Nucleic Acid Templates.

PubMed

Kong, Dehui; Yeung, Wayland; Hili, Ryan

2016-07-11

Recent advances in nucleic acid-templated copolymerization have expanded the scope of sequence-controlled synthetic copolymers beyond the molecular architectures witnessed in nature. This has enabled the power of molecular evolution to be applied to synthetic copolymer libraries to evolve molecular function ranging from molecular recognition to catalysis. This Review seeks to summarize different approaches available to generate sequence-defined monodispersed synthetic copolymer libraries using nucleic acid-templated polymerization. Key concepts and principles governing nucleic acid-templated polymerization, as well as the fidelity of various copolymerization technologies, will be described. The Review will focus on methods that enable the combinatorial generation of copolymer libraries and their molecular evolution for desired function.

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

NASA Astrophysics Data System (ADS)

Nie, Xiaokai; Luo, Jingjing; Coca, Daniel; Birkin, Mark; Chen, Jing

2018-03-01

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

EVALUATION OF ANALYTICAL REPORTING ERRORS GENERATED AS DESCRIBED IN SW-846 METHOD 8261A

EPA Science Inventory

SW-846 Method 8261A incorporates the vacuum distillation of analytes from samples, and their recoveries are characterized by internal standards. The internal standards measure recoveries with confidence intervals as functions of physical properties. The frequency the calculate...

Virus-induced gene silencing (VIGS) in barley seedling leaves

USDA-ARS?s Scientific Manuscript database

Virus-induced gene silencing (VIGS) is one of the most potent reverse genetics technologies for gene functional characterization. This method exploits a dsRNA-mediated antiviral defense mechanism in plants. Using this method allows researchers to generate rapid phenotypic data in a relatively rapid ...

Asymptotics of bivariate generating functions with algebraic singularities

NASA Astrophysics Data System (ADS)

Greenwood, Torin

Flajolet and Odlyzko (1990) derived asymptotic formulae the coefficients of a class of uni- variate generating functions with algebraic singularities. Gao and Richmond (1992) and Hwang (1996, 1998) extended these results to classes of multivariate generating functions, in both cases by reducing to the univariate case. Pemantle and Wilson (2013) outlined new multivariate ana- lytic techniques and used them to analyze the coefficients of rational generating functions. After overviewing these methods, we use them to find asymptotic formulae for the coefficients of a broad class of bivariate generating functions with algebraic singularities. Beginning with the Cauchy integral formula, we explicity deform the contour of integration so that it hugs a set of critical points. The asymptotic contribution to the integral comes from analyzing the integrand near these points, leading to explicit asymptotic formulae. Next, we use this formula to analyze an example from current research. In the following chapter, we apply multivariate analytic techniques to quan- tum walks. Bressler and Pemantle (2007) found a (d + 1)-dimensional rational generating function whose coefficients described the amplitude of a particle at a position in the integer lattice after n steps. Here, the minimal critical points form a curve on the (d + 1)-dimensional unit torus. We find asymptotic formulae for the amplitude of a particle in a given position, normalized by the number of steps n, as n approaches infinity. Each critical point contributes to the asymptotics for a specific normalized position. Using Groebner bases in Maple again, we compute the explicit locations of peak amplitudes. In a scaling window of size the square root of n near the peaks, each amplitude is asymptotic to an Airy function.

Seismic modeling with radial basis function-generated finite differences (RBF-FD) – a simplified treatment of interfaces

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

Martin, Bradley, E-mail: brma7253@colorado.edu; Fornberg, Bengt, E-mail: Fornberg@colorado.edu

In a previous study of seismic modeling with radial basis function-generated finite differences (RBF-FD), we outlined a numerical method for solving 2-D wave equations in domains with material interfaces between different regions. The method was applicable on a mesh-free set of data nodes. It included all information about interfaces within the weights of the stencils (allowing the use of traditional time integrators), and was shown to solve problems of the 2-D elastic wave equation to 3rd-order accuracy. In the present paper, we discuss a refinement of that method that makes it simpler to implement. It can also improve accuracy formore » the case of smoothly-variable model parameter values near interfaces. We give several test cases that demonstrate the method solving 2-D elastic wave equation problems to 4th-order accuracy, even in the presence of smoothly-curved interfaces with jump discontinuities in the model parameters.« less

Seismic modeling with radial basis function-generated finite differences (RBF-FD) - a simplified treatment of interfaces

NASA Astrophysics Data System (ADS)

Martin, Bradley; Fornberg, Bengt

2017-04-01

In a previous study of seismic modeling with radial basis function-generated finite differences (RBF-FD), we outlined a numerical method for solving 2-D wave equations in domains with material interfaces between different regions. The method was applicable on a mesh-free set of data nodes. It included all information about interfaces within the weights of the stencils (allowing the use of traditional time integrators), and was shown to solve problems of the 2-D elastic wave equation to 3rd-order accuracy. In the present paper, we discuss a refinement of that method that makes it simpler to implement. It can also improve accuracy for the case of smoothly-variable model parameter values near interfaces. We give several test cases that demonstrate the method solving 2-D elastic wave equation problems to 4th-order accuracy, even in the presence of smoothly-curved interfaces with jump discontinuities in the model parameters.

Experimental investigation of complex circular Airy beam characteristics

NASA Astrophysics Data System (ADS)

Porfirev, A. P.; Fomchenkov, S. A.; Khonina, S. N.

2018-04-01

We demonstrate a new type of circular Airy beams, the so-called azimuthally modulated circular Airy beams, generated by utilizing a diffraction element, whose transmission function is the sum of the transmission function of the element generating a "petal" pattern and the transmission function of the element generating a circular Airy beam. We experimentally investigate the propagation dynamics of such beams and demonstrate that their autofocusing and selfhealing properties are strongly dependent on the number of generated petals. These beams are a combination of a conventional circular Airy beam and vortex laser beams (or their superpositions). Using a spatial light modulator, we demonstrate that these beams have unique properties such as autofocusing, "nondiffractive" propagation and self-healing after passing through an obstacle. The experimental results are in good agreement with the simulation. We believe that these results can be very useful for lensless laser fabrication and laser manipulation techniques, as well as for development of new filament plasma multi-channel formation methods.

Generation and Assessment of Functional Biomaterial Scaffolds for Applications in Cardiovascular Tissue Engineering and Regenerative Medicine

PubMed Central

Hinderer, Svenja; Brauchle, Eva

2015-01-01

Current clinically applicable tissue and organ replacement therapies are limited in the field of cardiovascular regenerative medicine. The available options do not regenerate damaged tissues and organs, and, in the majority of the cases, show insufficient restoration of tissue function. To date, anticoagulant drug‐free heart valve replacements or growing valves for pediatric patients, hemocompatible and thrombus‐free vascular substitutes that are smaller than 6 mm, and stem cell‐recruiting delivery systems that induce myocardial regeneration are still only visions of researchers and medical professionals worldwide and far from being the standard of clinical treatment. The design of functional off‐the‐shelf biomaterials as well as automatable and up‐scalable biomaterial processing methods are the focus of current research endeavors and of great interest for fields of tissue engineering and regenerative medicine. Here, various approaches that aim to overcome the current limitations are reviewed, focusing on biomaterials design and generation methods for myocardium, heart valves, and blood vessels. Furthermore, novel contact‐ and marker‐free biomaterial and extracellular matrix assessment methods are highlighted. PMID:25778713

Rapid computation of photoacoustic fields from normal and pathological red blood cells using a Green's function method

NASA Astrophysics Data System (ADS)

Saha, Ratan K.; Fadhel, Muhannad N.; Lawrence, Aamna; Karmakar, Subhajit; Adhikari, Arunabha; Kolios, Michael C.

2017-03-01

Photoacoustic (PA) field calculations using a Green's function approach is presented. The method has been applied to predict PA spectra generated by normal (discocyte) and pathological (stomatocyte) red blood cells (RBCs). The contours of normal and pathological RBCs were generated by employing a popular parametric model and accordingly, fitted with the Legendre polynomial expansions for surface parametrization. The first frequency minimum of theoretical PA spectrum approximately appears at 607 MHz for a discocyte and 410 MHz for a stomatocyte when computed from the direction of symmetry axis. The same feature occurs nearly at 247 and 331 MHz, respectively, for those particles when measured along the perpendicular direction. The average experimental spectrum for normal RBCs is found to be flat over a bandwidth of 150-500 MHz when measured along the direction of symmetry axis. For spherical RBCs, both the theoretical and experimental spectra demonstrate negative slope over a bandwidth of 250-500 MHz. Using the Green's function method discussed, it may be possible to rapidly characterize cellular morphology from single-particle PA spectra.

Electron-hole pairs generation rate estimation irradiated by isotope Nickel-63 in silicone using GEANT4

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Sidorov, V. G.; Zelenkov, P. V.; Khoroshko, A. Y.; Lelekov, A. T.

2015-10-01

To optimize parameters of beta-electrical converter of isotope Nickel-63 radiation, model of the distribution of EHP generation rate in semiconductor must be derived. By using Monte-Carlo methods in GEANT4 system with ultra-low energy electron physics models this distribution in silicon calculated and approximated with Gauss function. Maximal efficient isotope layer thickness and maximal energy efficiency of EHP generation were estimated.

A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization

PubMed Central

Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang

2015-01-01

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence—with at most a linear convergence rate—because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method. PMID:26381742

A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization.

PubMed

Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang

2015-01-01

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

PubMed

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

GENIE - Generation of computational geometry-grids for internal-external flow configurations

NASA Technical Reports Server (NTRS)

Soni, B. K.

1988-01-01

Progress realized in the development of a master geometry-grid generation code GENIE is presented. The grid refinement process is enhanced by developing strategies to utilize bezier curves/surfaces and splines along with weighted transfinite interpolation technique and by formulating new forcing function for the elliptic solver based on the minimization of a non-orthogonality functional. A two step grid adaptation procedure is developed by optimally blending adaptive weightings with weighted transfinite interpolation technique. Examples of 2D-3D grids are provided to illustrate the success of these methods.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

PubMed

Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Risk aversion and uncertainty in cost-effectiveness analysis: the expected-utility, moment-generating function approach.

PubMed

Elbasha, Elamin H

2005-05-01

The availability of patient-level data from clinical trials has spurred a lot of interest in developing methods for quantifying and presenting uncertainty in cost-effectiveness analysis (CEA). Although the majority has focused on developing methods for using sample data to estimate a confidence interval for an incremental cost-effectiveness ratio (ICER), a small strand of the literature has emphasized the importance of incorporating risk preferences and the trade-off between the mean and the variance of returns to investment in health and medicine (mean-variance analysis). This paper shows how the exponential utility-moment-generating function approach is a natural extension to this branch of the literature for modelling choices from healthcare interventions with uncertain costs and effects. The paper assumes an exponential utility function, which implies constant absolute risk aversion, and is based on the fact that the expected value of this function results in a convenient expression that depends only on the moment-generating function of the random variables. The mean-variance approach is shown to be a special case of this more general framework. The paper characterizes the solution to the resource allocation problem using standard optimization techniques and derives the summary measure researchers need to estimate for each programme, when the assumption of risk neutrality does not hold, and compares it to the standard incremental cost-effectiveness ratio. The importance of choosing the correct distribution of costs and effects and the issues related to estimation of the parameters of the distribution are also discussed. An empirical example to illustrate the methods and concepts is provided. Copyright 2004 John Wiley & Sons, Ltd

Negative Example Selection for Protein Function Prediction: The NoGO Database

PubMed Central

Youngs, Noah; Penfold-Brown, Duncan; Bonneau, Richard; Shasha, Dennis

2014-01-01

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html). PMID:24922051

Iron(II)-catalyzed intermolecular amino-oxygenation of olefins through the N-O bond cleavage of functionalized hydroxylamines.

PubMed

Lu, Deng-Fu; Zhu, Cheng-Liang; Jia, Zhen-Xin; Xu, Hao

2014-09-24

An iron-catalyzed diastereoselective intermolecular olefin amino-oxygenation reaction is reported, which proceeds via an iron-nitrenoid generated by the N-O bond cleavage of a functionalized hydroxylamine. In this reaction, a bench-stable hydroxylamine derivative is used as the amination reagent and oxidant. This method tolerates a range of synthetically valuable substrates that have been all incompatible with existing amino-oxygenation methods. It can also provide amino alcohol derivatives with regio- and stereochemical arrays complementary to known amino-oxygenation methods.

Decomposing Multifractal Crossovers

PubMed Central

Nagy, Zoltan; Mukli, Peter; Herman, Peter; Eke, Andras

2017-01-01

Physiological processes—such as, the brain's resting-state electrical activity or hemodynamic fluctuations—exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for the topology of multifractal metrics free of the masking effect of the underlying random noise. PMID:28798694

Improved Evolutionary Programming with Various Crossover Techniques for Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Tangpatiphan, Kritsana; Yokoyama, Akihiko

This paper presents an Improved Evolutionary Programming (IEP) for solving the Optimal Power Flow (OPF) problem, which is considered as a non-linear, non-smooth, and multimodal optimization problem in power system operation. The total generator fuel cost is regarded as an objective function to be minimized. The proposed method is an Evolutionary Programming (EP)-based algorithm with making use of various crossover techniques, normally applied in Real Coded Genetic Algorithm (RCGA). The effectiveness of the proposed approach is investigated on the IEEE 30-bus system with three different types of fuel cost functions; namely the quadratic cost curve, the piecewise quadratic cost curve, and the quadratic cost curve superimposed by sine component. These three cost curves represent the generator fuel cost functions with a simplified model and more accurate models of a combined-cycle generating unit and a thermal unit with value-point loading effect respectively. The OPF solutions by the proposed method and Pure Evolutionary Programming (PEP) are observed and compared. The simulation results indicate that IEP requires less computing time than PEP with better solutions in some cases. Moreover, the influences of important IEP parameters on the OPF solution are described in details.

An Artificial Functional Family Filter in Homolog Searching in Next-generation Sequencing Metagenomics

PubMed Central

Du, Ruofei; Mercante, Donald; Fang, Zhide

2013-01-01

In functional metagenomics, BLAST homology search is a common method to classify metagenomic reads into protein/domain sequence families such as Clusters of Orthologous Groups of proteins (COGs) in order to quantify the abundance of each COG in the community. The resulting functional profile of the community is then used in downstream analysis to correlate the change in abundance to environmental perturbation, clinical variation, and so on. However, the short read length coupled with next-generation sequencing technologies poses a barrier in this approach, essentially because similarity significance cannot be discerned by searching with short reads. Consequently, artificial functional families are produced, in which those with a large number of reads assigned decreases the accuracy of functional profile dramatically. There is no method available to address this problem. We intended to fill this gap in this paper. We revealed that BLAST similarity scores of homologues for short reads from COG protein members coding sequences are distributed differently from the scores of those derived elsewhere. We showed that, by choosing an appropriate score cut-off, we are able to filter out most artificial families and simultaneously to preserve sufficient information in order to build the functional profile. We also showed that, by incorporated application of BLAST and RPS-BLAST, some artificial families with large read counts can be further identified after the score cutoff filtration. Evaluated on three experimental metagenomic datasets with different coverages, we found that the proposed method is robust against read coverage and consistently outperforms the other E-value cutoff methods currently used in literatures. PMID:23516532

SU-G-BRC-02: A Novel Multi-Criteria Optimization Approach to Generate Deliverable Intensity-Modulated Radiation Therapy (IMRT) Treatment Plans

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

Kirlik, G; D’Souza, W; Zhang, H

2016-06-15

Purpose: To present a novel multi-criteria optimization (MCO) solution approach that generates treatment plans with deliverable apertures using column generation. Methods: We demonstrate our method with 10 locally advanced head-and-neck cancer cases retrospectively. In our MCO formulation, we defined an objective function for each structure in the treatment volume. This resulted in 9 objective functions, including 3 distinct objectives for primary target volume, high-risk and low-risk target volumes, 5 objectives for each of the organs-at-risk (OARs) (two parotid glands, spinal cord, brain stem and oral cavity), and one for the non-target non-OAR normal tissue. Conditional value-at-risk (CVaR) constraints were utilizedmore » to ensure at least certain fraction of the target volumes receiving the prescription doses. To directly generate deliverable plans, column generation algorithm was embedded within our MCO approach for aperture shape generation. Final dose distributions for all plans were generated using a Monte Carlo kernel-superposition dose calculation. We compared the MCO plans with the clinical plans, which were created by clinicians. Results: At least 95% target coverage was achieved by both MCO plans and clinical plans. However, the average conformity indices of clinical plans and the MCO plans were 1.95 and 1.35, respectively (31% reduction, p<0.01). Compared to the conventional clinical plan, the proposed MCO method achieved average reductions in left parotid mean dose of 5% (p=0.06), right parotid mean dose of 18% (p<0.01), oral cavity mean dose of 21% (p=0.03), spinal cord maximum dose of 20% (p<0.01), brain stem maximum dose of 61% (p<0.01), and normal tissue maximum dose of 5% (p<0.01), respectively. Conclusion: We demonstrated that the proposed MCO method was able to obtain deliverable IMRT treatment plans while achieving significant improvements in dosimetric plan quality.« less

Numerical Grid Generation and Potential Airfoil Analysis and Design

DTIC Science & Technology

1988-01-01

Gauss- Seidel , SOR and ADI iterative methods e JACOBI METHOD In the Jacobi method each new value of a function is computed entirely from old values...preceding iteration and adding the inhomogeneous (boundary condition) term. * GAUSS- SEIDEL METHOD When we compute I in a Jacobi method, we have already...Gauss- Seidel method. Sufficient condition for p convergence of the Gauss- Seidel method is diagonal-dominance of [A].9W e SUCESSIVE OVER-RELAXATION (SOR

The stability of a class of synchronous generator damping model

NASA Astrophysics Data System (ADS)

Liu, Jun

2018-03-01

Electricity is indispensable to modern society and the most convenient energy, it can be easily transformed into other forms of energy, has been widely used in engineering, transportation and so on, this paper studied the generator model with damping machine, using the Lyapunov function method, we obtain sufficient conditions for the asymptotic stability of the model.

A Differential Evolution Algorithm Based on Nikaido-Isoda Function for Solving Nash Equilibrium in Nonlinear Continuous Games

PubMed Central

He, Feng; Zhang, Wei; Zhang, Guoqiang

2016-01-01

A differential evolution algorithm for solving Nash equilibrium in nonlinear continuous games is presented in this paper, called NIDE (Nikaido-Isoda differential evolution). At each generation, parent and child strategy profiles are compared one by one pairwisely, adapting Nikaido-Isoda function as fitness function. In practice, the NE of nonlinear game model with cubic cost function and quadratic demand function is solved, and this method could also be applied to non-concave payoff functions. Moreover, the NIDE is compared with the existing Nash Domination Evolutionary Multiplayer Optimization (NDEMO), the result showed that NIDE was significantly better than NDEMO with less iterations and shorter running time. These numerical examples suggested that the NIDE method is potentially useful. PMID:27589229

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

PubMed Central

Down, Thomas A.; Rakyan, Vardhman K.; Turner, Daniel J.; Flicek, Paul; Li, Heng; Kulesha, Eugene; Gräf, Stefan; Johnson, Nathan; Herrero, Javier; Tomazou, Eleni M.; Thorne, Natalie P.; Bäckdahl, Liselotte; Herberth, Marlis; Howe, Kevin L.; Jackson, David K.; Miretti, Marcos M.; Marioni, John C.; Birney, Ewan; Hubbard, Tim J. P.; Durbin, Richard; Tavaré, Simon; Beck, Stephan

2009-01-01

DNA methylation is an indispensible epigenetic modification of mammalian genomes. Consequently there is great interest in strategies for genome-wide/whole-genome DNA methylation analysis, and immunoprecipitation-based methods have proven to be a powerful option. Such methods are rapidly shifting the bottleneck from data generation to data analysis, necessitating the development of better analytical tools. Until now, a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling has been the inability to estimate absolute methylation levels. Here we report the development of a novel cross-platform algorithm – Bayesian Tool for Methylation Analysis (Batman) – for analyzing Methylated DNA Immunoprecipitation (MeDIP) profiles generated using arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). The latter is an approach we have developed to elucidate the first high-resolution whole-genome DNA methylation profile (DNA methylome) of any mammalian genome. MeDIP-seq/MeDIP-chip combined with Batman represent robust, quantitative, and cost-effective functional genomic strategies for elucidating the function of DNA methylation. PMID:18612301

Method and apparatus for smart battery charging including a plurality of controllers each monitoring input variables

DOEpatents

Hammerstrom, Donald J.

2013-10-15

A method for managing the charging and discharging of batteries wherein at least one battery is connected to a battery charger, the battery charger is connected to a power supply. A plurality of controllers in communication with one and another are provided, each of the controllers monitoring a subset of input variables. A set of charging constraints may then generated for each controller as a function of the subset of input variables. A set of objectives for each controller may also be generated. A preferred charge rate for each controller is generated as a function of either the set of objectives, the charging constraints, or both, using an algorithm that accounts for each of the preferred charge rates for each of the controllers and/or that does not violate any of the charging constraints. A current flow between the battery and the battery charger is then provided at the actual charge rate.

MSTor version 2013: A new version of the computer code for the multi-structural torsional anharmonicity, now with a coupled torsional potential

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Meana-Pañeda, Rubén; Truhlar, Donald G.

2013-08-01

We present an improved version of the MSTor program package, which calculates partition functions and thermodynamic functions of complex molecules involving multiple torsions; the method is based on either a coupled torsional potential or an uncoupled torsional potential. The program can also carry out calculations in the multiple-structure local harmonic approximation. The program package also includes seven utility codes that can be used as stand-alone programs to calculate reduced moment of inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files for the MSTor calculation and Voronoi calculation, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Restrictions: There is no limit on the number of torsions that can be included in either the Voronoi calculation or the full MS-T calculation. In practice, the range of problems that can be addressed with the present method consists of all multitorsional problems for which one can afford to calculate all the conformational structures and their frequencies. Unusual features: The method can be applied to transition states as well as stable molecules. The program package also includes the hull program for the calculation of Voronoi volumes, the symmetry program for determining point group symmetry of a molecule, and seven utility codes that can be used as stand-alone programs to calculate reduced moment-of-inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes of the torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Additional comments: The program package includes a manual, installation script, and input and output files for a test suite. Running time: There are 26 test runs. The running time of the test runs on a single processor of the Itasca computer is less than 2 s. References: [1] MS-T(C) method: Quantum Thermochemistry: Multi-Structural Method with Torsional Anharmonicity Based on a Coupled Torsional Potential, J. Zheng and D.G. Truhlar, Journal of Chemical Theory and Computation 9 (2013) 1356-1367, DOI: http://dx.doi.org/10.1021/ct3010722. [2] MS-T(U) method: Practical Methods for Including Torsional Anharmonicity in Thermochemical Calculations of Complex Molecules: The Internal-Coordinate Multi-Structural Approximation, J. Zheng, T. Yu, E. Papajak, I, M. Alecu, S.L. Mielke, and D.G. Truhlar, Physical Chemistry Chemical Physics 13 (2011) 10885-10907.

Cumulant generating function formula of heat transfer in ballistic systems with lead-lead coupling

NASA Astrophysics Data System (ADS)

Li, Huanan; Agarwalla, Bijay Kumar; Wang, Jian-Sheng

2012-10-01

Based on a two-time observation protocol, we consider heat transfer in a given time interval tM in a lead-junction-lead system taking coupling between the leads into account. In view of the two-time observation, consistency conditions are carefully verified in our specific family of quantum histories. Furthermore, its implication is briefly explored. Then using the nonequilibrium Green's function method, we obtain an exact formula for the cumulant generating function for heat transfer between the two leads, valid in both transient and steady-state regimes. Also, a compact formula for the cumulant generating function in the long-time limit is derived, for which the Gallavotti-Cohen fluctuation symmetry is explicitly verified. In addition, we briefly discuss Di Ventra's repartitioning trick regarding whether the repartitioning procedure of the total Hamiltonian affects the nonequilibrium steady-state current fluctuation. All kinds of properties of nonequilibrium current fluctuations, such as the fluctuation theorem in different time regimes, could be readily given according to these exact formulas.

Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval.

PubMed

Xu, Xing; Shen, Fumin; Yang, Yang; Shen, Heng Tao; Li, Xuelong

2017-05-01

Hashing based methods have attracted considerable attention for efficient cross-modal retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to learn compact binary codes that construct the underlying correlations between heterogeneous features from different modalities. A majority of recent approaches aim at learning hash functions to preserve the pairwise similarities defined by given class labels. However, these methods fail to explicitly explore the discriminative property of class labels during hash function learning. In addition, they usually discard the discrete constraints imposed on the to-be-learned binary codes, and compromise to solve a relaxed problem with quantization to obtain the approximate binary solution. Therefore, the binary codes generated by these methods are suboptimal and less discriminative to different classes. To overcome these drawbacks, we propose a novel cross-modal hashing method, termed discrete cross-modal hashing (DCH), which directly learns discriminative binary codes while retaining the discrete constraints. Specifically, DCH learns modality-specific hash functions for generating unified binary codes, and these binary codes are viewed as representative features for discriminative classification with class labels. An effective discrete optimization algorithm is developed for DCH to jointly learn the modality-specific hash function and the unified binary codes. Extensive experiments on three benchmark data sets highlight the superiority of DCH under various cross-modal scenarios and show its state-of-the-art performance.

dftools: Distribution function fitting

NASA Astrophysics Data System (ADS)

Obreschkow, Danail

2018-05-01

dftools, written in R, finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a mass function (D=1), a mass-size distribution (D=2) or the mass-spin-morphology distribution (D=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions.

Statistical methods for convergence detection of multi-objective evolutionary algorithms.

PubMed

Trautmann, H; Wagner, T; Naujoks, B; Preuss, M; Mehnen, J

2009-01-01

In this paper, two approaches for estimating the generation in which a multi-objective evolutionary algorithm (MOEA) shows statistically significant signs of convergence are introduced. A set-based perspective is taken where convergence is measured by performance indicators. The proposed techniques fulfill the requirements of proper statistical assessment on the one hand and efficient optimisation for real-world problems on the other hand. The first approach accounts for the stochastic nature of the MOEA by repeating the optimisation runs for increasing generation numbers and analysing the performance indicators using statistical tools. This technique results in a very robust offline procedure. Moreover, an online convergence detection method is introduced as well. This method automatically stops the MOEA when either the variance of the performance indicators falls below a specified threshold or a stagnation of their overall trend is detected. Both methods are analysed and compared for two MOEA and on different classes of benchmark functions. It is shown that the methods successfully operate on all stated problems needing less function evaluations while preserving good approximation quality at the same time.

Generation of three-dimensional delaunay meshes from weakly structured and inconsistent data

NASA Astrophysics Data System (ADS)

Garanzha, V. A.; Kudryavtseva, L. N.

2012-03-01

A method is proposed for the generation of three-dimensional tetrahedral meshes from incomplete, weakly structured, and inconsistent data describing a geometric model. The method is based on the construction of a piecewise smooth scalar function defining the body so that its boundary is the zero isosurface of the function. Such implicit description of three-dimensional domains can be defined analytically or can be constructed from a cloud of points, a set of cross sections, or a "soup" of individual vertices, edges, and faces. By applying Boolean operations over domains, simple primitives can be combined with reconstruction results to produce complex geometric models without resorting to specialized software. Sharp edges and conical vertices on the domain boundary are reproduced automatically without using special algorithms. Refs. 42. Figs. 25.

Generalized serial search code acquisition - The equivalent circular state diagram approach

NASA Technical Reports Server (NTRS)

Polydoros, A.; Simon, M. K.

1984-01-01

A transform-domain method for deriving the generating function of the acquisition process resulting from an arbitrary serial search strategy is presented. The method relies on equivalent circular state diagrams, uses Mason's formula from flow-graph theory, and employs a minimum number of required parameters. The transform-domain approach is briefly described and the concept of equivalent circular state diagrams is introduced and exploited to derive the generating function and resulting mean acquisition time for three particular cases of interest, the continuous/center Z search, the broken/center Z search, and the expanding window search. An optimization of the latter technique is performed whereby the number of partial windows which minimizes the mean acquisition time is determined. The numerical results satisfy certain intuitive predictions and provide useful design guidelines for such systems.

Advances in plant gene-targeted and functional markers: a review

PubMed Central

2013-01-01

Public genomic databases have provided new directions for molecular marker development and initiated a shift in the types of PCR-based techniques commonly used in plant science. Alongside commonly used arbitrarily amplified DNA markers, other methods have been developed. Targeted fingerprinting marker techniques are based on the well-established practices of arbitrarily amplified DNA methods, but employ novel methodological innovations such as the incorporation of gene or promoter elements in the primers. These markers provide good reproducibility and increased resolution by the concurrent incidence of dominant and co-dominant bands. Despite their promising features, these semi-random markers suffer from possible problems of collision and non-homology analogous to those found with randomly generated fingerprints. Transposable elements, present in abundance in plant genomes, may also be used to generate fingerprints. These markers provide increased genomic coverage by utilizing specific targeted sites and produce bands that mostly seem to be homologous. The biggest drawback with most of these techniques is that prior genomic information about retrotransposons is needed for primer design, prohibiting universal applications. Another class of recently developed methods exploits length polymorphism present in arrays of multi-copy gene families such as cytochrome P450 and β-tubulin genes to provide cross-species amplification and transferability. A specific class of marker makes use of common features of plant resistance genes to generate bands linked to a given phenotype, or to reveal genetic diversity. Conserved DNA-based strategies have limited genome coverage and may fail to reveal genetic diversity, while resistance genes may be under specific evolutionary selection. Markers may also be generated from functional and/or transcribed regions of the genome using different gene-targeting approaches coupled with the use of RNA information. Such techniques have the potential to generate phenotypically linked functional markers, especially when fingerprints are generated from the transcribed or expressed region of the genome. It is to be expected that these recently developed techniques will generate larger datasets, but their shortcomings should also be acknowledged and carefully investigated. PMID:23406322

Thermal Density Functional Theory: Time-Dependent Linear Response and Approximate Functionals from the Fluctuation-Dissipation Theorem

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

Pribram-Jones, Aurora; Grabowski, Paul E.; Burke, Kieron

We present that the van Leeuwen proof of linear-response time-dependent density functional theory (TDDFT) is generalized to thermal ensembles. This allows generalization to finite temperatures of the Gross-Kohn relation, the exchange-correlation kernel of TDDFT, and fluctuation dissipation theorem for DFT. Finally, this produces a natural method for generating new thermal exchange-correlation approximations.

Thermal Density Functional Theory: Time-Dependent Linear Response and Approximate Functionals from the Fluctuation-Dissipation Theorem

DOE PAGES

Pribram-Jones, Aurora; Grabowski, Paul E.; Burke, Kieron

2016-06-08

We present that the van Leeuwen proof of linear-response time-dependent density functional theory (TDDFT) is generalized to thermal ensembles. This allows generalization to finite temperatures of the Gross-Kohn relation, the exchange-correlation kernel of TDDFT, and fluctuation dissipation theorem for DFT. Finally, this produces a natural method for generating new thermal exchange-correlation approximations.

Insights into the chicken IgY with emphasis on the generation and applications of chicken recombinant monoclonal antibodies.

PubMed

Lee, Warren; Syed Atif, Ali; Tan, Soo Choon; Leow, Chiuan Herng

2017-08-01

The advantages of chicken (Gallus gallus domesticus) antibodies as immunodiagnostic and immunotherapeutic biomolecules has only been recently recognized. Even so, chicken antibodies remain less-well characterized than their mammalian counterparts. This review aims at providing a current overview of the structure, function, development and generation of chicken antibodies. Additionally, brief but comprehensive insights into current knowledge pertaining to the immunogenetic framework and diversity-generation of the chicken immunoglobulin repertoire which have contributed to the establishment of recombinant chicken mAb-generating methods are discussed. Focus is provided on the current methods used to generate antibodies from chickens with added emphasis on the generation of recombinant chicken mAbs and its derivative formats. The advantages and limitations of established protocols for the generation of chicken mAbs are highlighted. The various applications of recombinant chicken mAbs and its derivative formats in immunodiagnostics and immunotherapy are further detailed. Copyright © 2017 Elsevier B.V. All rights reserved.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

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

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE PAGES

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

2017-10-17

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Cumulants of heat transfer across nonlinear quantum systems

NASA Astrophysics Data System (ADS)

Li, Huanan; Agarwalla, Bijay Kumar; Li, Baowen; Wang, Jian-Sheng

2013-12-01

We consider thermal conduction across a general nonlinear phononic junction. Based on two-time observation protocol and the nonequilibrium Green's function method, heat transfer in steady-state regimes is studied, and practical formulas for the calculation of the cumulant generating function are obtained. As an application, the general formalism is used to study anharmonic effects on fluctuation of steady-state heat transfer across a single-site junction with a quartic nonlinear on-site pinning potential. An explicit nonlinear modification to the cumulant generating function exact up to the first order is given, in which the Gallavotti-Cohen fluctuation symmetry is found still valid. Numerically a self-consistent procedure is introduced, which works well for strong nonlinearity.

Exact analytic solution of position-dependent mass Schrödinger equation

NASA Astrophysics Data System (ADS)

Rajbongshi, Hangshadhar

2018-03-01

Exact analytic solution of position-dependent mass Schrödinger equation is generated by using extended transformation, a method of mapping a known system into a new system equipped with energy eigenvalues and corresponding wave functions. First order transformation is performed on D-dimensional radial Schrödinger equation with constant mass by taking trigonometric Pöschl-Teller potential as known system. The exactly solvable potentials with position-dependent mass generated for different choices of mass functions through first order transformation are also taken as known systems in the second order transformation performed on D-dimensional radial position-dependent mass Schrödinger equation. The solutions are fitted for "Zhu and Kroemer" ordering of ambiguity. All the wave functions corresponding to nonzero energy eigenvalues are normalizable. The new findings are that the normalizability condition of the wave functions remains independent of mass functions, and some of the generated potentials show a family relationship among themselves where power law potentials also get related to non-power law potentials and vice versa through the transformation.

Generation of Knock-in Mouse by Genome Editing.

PubMed

Fujii, Wataru

2017-01-01

Knock-in mice are useful for evaluating endogenous gene expressions and functions in vivo. Instead of the conventional gene-targeting method using embryonic stem cells, an exogenous DNA sequence can be inserted into the target locus in the zygote using genome editing technology. In this chapter, I describe the generation of epitope-tagged mice using engineered endonuclease and single-stranded oligodeoxynucleotide through the mouse zygote as an example of how to generate a knock-in mouse by genome editing.

Feynman-Kac formula for stochastic hybrid systems.

PubMed

Bressloff, Paul C

2017-01-01

We derive a Feynman-Kac formula for functionals of a stochastic hybrid system evolving according to a piecewise deterministic Markov process. We first derive a stochastic Liouville equation for the moment generator of the stochastic functional, given a particular realization of the underlying discrete Markov process; the latter generates transitions between different dynamical equations for the continuous process. We then analyze the stochastic Liouville equation using methods recently developed for diffusion processes in randomly switching environments. In particular, we obtain dynamical equations for the moment generating function, averaged with respect to realizations of the discrete Markov process. The resulting Feynman-Kac formula takes the form of a differential Chapman-Kolmogorov equation. We illustrate the theory by calculating the occupation time for a one-dimensional velocity jump process on the infinite or semi-infinite real line. Finally, we present an alternative derivation of the Feynman-Kac formula based on a recent path-integral formulation of stochastic hybrid systems.

Three dimensional single molecule localization using a phase retrieved pupilfunction

PubMed Central

Liu, Sheng; Kromann, Emil B.; Krueger, Wesley D.; Bewersdorf, Joerg; Lidke, Keith A.

2013-01-01

Localization-based superresolution imaging is dependent on finding the positions of individualfluorophores in a sample by fitting the observed single-molecule intensity pattern to the microscopepoint spread function (PSF). For three-dimensional imaging, system-specific aberrations of theoptical system can lead to inaccurate localizations when the PSF model does not account for theseaberrations. Here we describe the use of phase-retrieved pupil functions to generate a more accuratePSF and therefore more accurate 3D localizations. The complex-valued pupil function containsinformation about the system-specific aberrations and can thus be used to generate the PSF forarbitrary defocus. Further, it can be modified to include depth dependent aberrations. We describethe phase retrieval process, the method for including depth dependent aberrations, and a fastfitting algorithm using graphics processing units. The superior localization accuracy of the pupilfunction generated PSF is demonstrated with dual focal plane 3D superresolution imaging ofbiological structures. PMID:24514501

Method and apparatus for measuring response time

DOEpatents

Johanson, Edward W.; August, Charles

1985-01-01

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

Method and apparatus for measuring response time

DOEpatents

Johanson, E.W.; August, C.

1983-08-11

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

On the constrained minimization of smooth Kurdyka—Łojasiewicz functions with the scaled gradient projection method

NASA Astrophysics Data System (ADS)

Prato, Marco; Bonettini, Silvia; Loris, Ignace; Porta, Federica; Rebegoldi, Simone

2016-10-01

The scaled gradient projection (SGP) method is a first-order optimization method applicable to the constrained minimization of smooth functions and exploiting a scaling matrix multiplying the gradient and a variable steplength parameter to improve the convergence of the scheme. For a general nonconvex function, the limit points of the sequence generated by SGP have been proved to be stationary, while in the convex case and with some restrictions on the choice of the scaling matrix the sequence itself converges to a constrained minimum point. In this paper we extend these convergence results by showing that the SGP sequence converges to a limit point provided that the objective function satisfies the Kurdyka-Łojasiewicz property at each point of its domain and its gradient is Lipschitz continuous.

Cortical Reorganization of Language Functioning Following Perinatal Left MCA Stroke

ERIC Educational Resources Information Center

Tillema, Jan-Mendelt; Byars, Anna W.; Jacola, Lisa M.; Schapiro, Mark B.; Schmithorst, Vince J.; Szaflarski, Jerzy P.; Holland, Scott K.

2008-01-01

Objective: Functional MRI was used to determine differences in patterns of cortical activation between children who suffered perinatal left middle cerebral artery (MCA) stroke and healthy children performing a silent verb generation task. Methods: Ten children with prior perinatal left MCA stroke (age 6-16 years) and ten healthy age matched…

CyClus: a fast, comprehensive cylindrical interface approximation clustering/reranking method for rigid-body protein-protein docking decoys.

PubMed

Omori, Satoshi; Kitao, Akio

2013-06-01

We propose a fast clustering and reranking method, CyClus, for protein-protein docking decoys. This method enables comprehensive clustering of whole decoys generated by rigid-body docking using cylindrical approximation of the protein-proteininterface and hierarchical clustering procedures. We demonstrate the clustering and reranking of 54,000 decoy structures generated by ZDOCK for each complex within a few minutes. After parameter tuning for the test set in ZDOCK benchmark 2.0 with the ZDOCK and ZRANK scoring functions, blind tests for the incremental data in ZDOCK benchmark 3.0 and 4.0 were conducted. CyClus successfully generated smaller subsets of decoys containing near-native decoys. For example, the number of decoys required to create subsets containing near-native decoys with 80% probability was reduced from 22% to 50% of the number required in the original ZDOCK. Although specific ZDOCK and ZRANK results were demonstrated, the CyClus algorithm was designed to be more general and can be applied to a wide range of decoys and scoring functions by adjusting just two parameters, p and T. CyClus results were also compared to those from ClusPro. Copyright © 2013 Wiley Periodicals, Inc.

Relativistic density functional theory with picture-change corrected electron density based on infinite-order Douglas-Kroll-Hess method

NASA Astrophysics Data System (ADS)

Oyama, Takuro; Ikabata, Yasuhiro; Seino, Junji; Nakai, Hiromi

2017-07-01

This Letter proposes a density functional treatment based on the two-component relativistic scheme at the infinite-order Douglas-Kroll-Hess (IODKH) level. The exchange-correlation energy and potential are calculated using the electron density based on the picture-change corrected density operator transformed by the IODKH method. Numerical assessments indicated that the picture-change uncorrected density functional terms generate significant errors, on the order of hartree for heavy atoms. The present scheme was found to reproduce the energetics in the four-component treatment with high accuracy.

Generation of juvenile rainbow trout derived from cryopreserved whole ovaries by intraperitoneal transplantation of ovarian germ cells.

PubMed

Lee, Seungki; Katayama, Naoto; Yoshizaki, Goro

2016-09-23

Cryopreservation of fish sperm offers the practical applications in the selective breeding and biodiversity conservation. However, because of the lack of cryopreservation methods for fish eggs and embryos, maternally inherited cytoplasmic compartments cannot be successfully preserved. We previously developed an alternative method to derive functional eggs and sperm from cryopreserved whole testis by transplanting testicular cells into female and male recipients. However, if target fish had ovaries, the previous method employing male-derived germ cells would be ineffective. Here, we aimed to generate functional gametes from cryopreserved whole ovaries by transplanting ovarian germ cells into peritoneal cavity of sterile hatchlings. Cryopreservation conditions for rainbow trout ovaries (1.0 M DMSO, 0.1 M trehalose, and 10% egg yolk) were optimized by testing several different cryoprotective agents. Ovarian germ cells from thawed ovaries were intraperitoneally transplanted into allogeneic triploid hatchlings. Transplanted germ cells migrated toward and were incorporated into recipient gonads, where they underwent gametogenesis. Transplantation efficiency of ovarian germ cells remained stable after cryopreservation period up to 1185 days. Although all triploid recipients that did not undergo transplantation were functionally sterile, 5 of 25 female recipients and 7 of 25 male recipients reached sexual maturity at 2.5 years post-transplantation. Inseminating the resultant eggs and sperm generated viable offspring displaying the donor characteristics of orange body color, green fluorescence, and chromosome numbers. This method is thus a breakthrough tool for the conservation of endangered fish species that are crucial to cryopreserve the genetic resources of female fish. Copyright © 2016 Elsevier Inc. All rights reserved.

Development of deterministic transport methods for low energy neutrons for shielding in space

NASA Technical Reports Server (NTRS)

Ganapol, Barry

1993-01-01

Transport of low energy neutrons associated with the galactic cosmic ray cascade is analyzed in this dissertation. A benchmark quality analytical algorithm is demonstrated for use with BRYNTRN, a computer program written by the High Energy Physics Division of NASA Langley Research Center, which is used to design and analyze shielding against the radiation created by the cascade. BRYNTRN uses numerical methods to solve the integral transport equations for baryons with the straight-ahead approximation, and numerical and empirical methods to generate the interaction probabilities. The straight-ahead approximation is adequate for charged particles, but not for neutrons. As NASA Langley improves BRYNTRN to include low energy neutrons, a benchmark quality solution is needed for comparison. The neutron transport algorithm demonstrated in this dissertation uses the closed-form Green's function solution to the galactic cosmic ray cascade transport equations to generate a source of neutrons. A basis function expansion for finite heterogeneous and semi-infinite homogeneous slabs with multiple energy groups and isotropic scattering is used to generate neutron fluxes resulting from the cascade. This method, called the FN method, is used to solve the neutral particle linear Boltzmann transport equation. As a demonstration of the algorithm coded in the programs MGSLAB and MGSEMI, neutron and ion fluxes are shown for a beam of fluorine ions at 1000 MeV per nucleon incident on semi-infinite and finite aluminum slabs. Also, to demonstrate that the shielding effectiveness against the radiation from the galactic cosmic ray cascade is not directly proportional to shield thickness, a graph of transmitted total neutron scalar flux versus slab thickness is shown. A simple model based on the nuclear liquid drop assumption is used to generate cross sections for the galactic cosmic ray cascade. The ENDF/B V database is used to generate the total and scattering cross sections for neutrons in aluminum. As an external verification, the results from MGSLAB and MGSEMI were compared to ANISN/PC, a routinely used neutron transport code, showing excellent agreement. In an application to an aluminum shield, the FN method seems to generate reasonable results.

Problems and methods of calculating the Legendre functions of arbitrary degree and order

NASA Astrophysics Data System (ADS)

Novikova, Elena; Dmitrenko, Alexander

2016-12-01

The known standard recursion methods of computing the full normalized associated Legendre functions do not give the necessary precision due to application of IEEE754-2008 standard, that creates a problems of underflow and overflow. The analysis of the problems of the calculation of the Legendre functions shows that the problem underflow is not dangerous by itself. The main problem that generates the gross errors in its calculations is the problem named the effect of "absolute zero". Once appeared in a forward column recursion, "absolute zero" converts to zero all values which are multiplied by it, regardless of whether a zero result of multiplication is real or not. Three methods of calculating of the Legendre functions, that removed the effect of "absolute zero" from the calculations are discussed here. These methods are also of interest because they almost have no limit for the maximum degree of Legendre functions. It is shown that the numerical accuracy of these three methods is the same. But, the CPU calculation time of the Legendre functions with Fukushima method is minimal. Therefore, the Fukushima method is the best. Its main advantage is computational speed which is an important factor in calculation of such large amount of the Legendre functions as 2 401 336 for EGM2008.

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

Electromagnetic field of a bunch intersecting a dielectric plate in a waveguide

NASA Astrophysics Data System (ADS)

Alekhina, Tatiana Yu; Tyukhtin, Andrey V.

2014-05-01

The electromagnetic field (EMF) of a bunch moving uniformly and traversing a dielectric plate located in a waveguide is investigated. The main attention is focused on the case when Cherenkov radiation is generated in the plate. Analysis of the field components of the mode is performed with methods of the complex variable function theory. An algorithm of computation using the exact expressions for the EMF is also presented. Consideration of the EMF structure for different time moments is given. It is shown that Cherenkov-transition radiation (CTR) is generated in the vacuum area after the plate under certain conditions. Results obtained might be of interest for development of new methods of generation of electromagnetic radiation.

Estimating probable flaw distributions in PWR steam generator tubes

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

Gorman, J.A.; Turner, A.P.L.

1997-02-01

This paper describes methods for estimating the number and size distributions of flaws of various types in PWR steam generator tubes. These estimates are needed when calculating the probable primary to secondary leakage through steam generator tubes under postulated accidents such as severe core accidents and steam line breaks. The paper describes methods for two types of predictions: (1) the numbers of tubes with detectable flaws of various types as a function of time, and (2) the distributions in size of these flaws. Results are provided for hypothetical severely affected, moderately affected and lightly affected units. Discussion is provided regardingmore » uncertainties and assumptions in the data and analyses.« less

Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

PubMed

Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F

2012-01-01

Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.

Nonlinear identification using a B-spline neural network and chaotic immune approaches

NASA Astrophysics Data System (ADS)

dos Santos Coelho, Leandro; Pessôa, Marcelo Wicthoff

2009-11-01

One of the important applications of B-spline neural network (BSNN) is to approximate nonlinear functions defined on a compact subset of a Euclidean space in a highly parallel manner. Recently, BSNN, a type of basis function neural network, has received increasing attention and has been applied in the field of nonlinear identification. BSNNs have the potential to "learn" the process model from input-output data or "learn" fault knowledge from past experience. BSNN can be used as function approximators to construct the analytical model for residual generation too. However, BSNN is trained by gradient-based methods that may fall into local minima during the learning procedure. When using feed-forward BSNNs, the quality of approximation depends on the control points (knots) placement of spline functions. This paper describes the application of a modified artificial immune network inspired optimization method - the opt-aiNet - combined with sequences generate by Hénon map to provide a stochastic search to adjust the control points of a BSNN. The numerical results presented here indicate that artificial immune network optimization methods are useful for building good BSNN model for the nonlinear identification of two case studies: (i) the benchmark of Box and Jenkins gas furnace, and (ii) an experimental ball-and-tube system.

Transformation of two and three-dimensional regions by elliptic systems

NASA Technical Reports Server (NTRS)

Mastin, C. Wayne

1991-01-01

A reliable linear system is presented for grid generation in 2-D and 3-D. The method is robust in the sense that convergence is guaranteed but is not as reliable as other nonlinear elliptic methods in generating nonfolding grids. The construction of nonfolding grids depends on having reasonable approximations of cell aspect ratios and an appropriate distribution of grid points on the boundary of the region. Some guidelines are included on approximating the aspect ratios, but little help is offered on setting up the boundary grid other than to say that in 2-D the boundary correspondence should be close to that generated by a conformal mapping. It is assumed that the functions which control the grid distribution depend only on the computational variables and not on the physical variables. Whether this is actually the case depends on how the grid is constructed. In a dynamic adaptive procedure where the grid is constructed in the process of solving a fluid flow problem, the grid is usually updated at fixed iteration counts using the current value of the control function. Since the control function is not being updated during the iteration of the grid equations, the grid construction is a linear procedure. However, in the case of a static adaptive procedure where a trial solution is computed and used to construct an adaptive grid, the control functions may be recomputed at every step of the grid iteration.

Whitecaps, sea-salt aerosols, and climate

NASA Astrophysics Data System (ADS)

Anguelova, Magdalena Dimitrova

Oceanic whitecaps are the major source of sea-salt aerosols. Because these aerosols are dominant in remote marine air, they control the radiative properties of the clean background atmosphere by scattering sunlight, changing cloud properties and lifetime, and providing media for chemical reactions. Including sea-salt effects in climate models improves predictions, but simulating their generation is first necessary. To make the sea-salt generation function currently used in climate models more relevant for aerosol investigations, this study proposes two modifications. First, the conventional relation between whitecap coverage, W, and the 10-meter wind speed, U10, used in typical generation functions is expanded to include additional factors that affect whitecaps and sea-salt aerosol formation. Second, the sea-salt generation function is extended to smaller sizes; sea-salt aerosol with initial radii from 0.4 to 20 mum can now be modeled. To achieve these goals, this thesis develops a new method for estimating whitecap coverage on a global scale using satellite measurements of the brightness temperature of the ocean surface. Whitecap coverage evaluated with this method incorporates the effects of atmospheric stability, sea-surface temperature, salinity, wind fetch, wind duration, and the amount of surface-active material. Assimilating satellite-derived values for whitecap coverage in the sea-salt generation function incorporates the effects of all environmental factors on sea-salt production and predicts realistic sea-salt aerosol loadings into the atmosphere. An extensive database of whitecap coverage and sea-salt aerosol fluxes has been compiled with the new method and is used to investigate their spatial and temporal characteristics. The composite effect of all environmental factors suggests a more uniform latitudinal distribution of whitecaps and sea-salt aerosols than that predicted from wind speed alone. The effect of sea-surface temperature, TS, is parameterized for the first time using regression analysis. The resulting parameterization W( U10, TS) is a better predictor of whitecap coverage than the conventional W(U 10) relation. This thesis also considers the contribution of oceanic whitecaps to ocean albedo and CO2 transfer and evaluates the direct effect of sea-salt aerosols on climate, the sea-salt contribution to CCN formation, and the role of sea-salt aerosols in atmospheric chemistry.

Interactive Sonification Exploring Emergent Behavior Applying Models for Biological Information and Listening

PubMed Central

Choi, Insook

2018-01-01

Sonification is an open-ended design task to construct sound informing a listener of data. Understanding application context is critical for shaping design requirements for data translation into sound. Sonification requires methodology to maintain reproducibility when data sources exhibit non-linear properties of self-organization and emergent behavior. This research formalizes interactive sonification in an extensible model to support reproducibility when data exhibits emergent behavior. In the absence of sonification theory, extensibility demonstrates relevant methods across case studies. The interactive sonification framework foregrounds three factors: reproducible system implementation for generating sonification; interactive mechanisms enhancing a listener's multisensory observations; and reproducible data from models that characterize emergent behavior. Supramodal attention research suggests interactive exploration with auditory feedback can generate context for recognizing irregular patterns and transient dynamics. The sonification framework provides circular causality as a signal pathway for modeling a listener interacting with emergent behavior. The extensible sonification model adopts a data acquisition pathway to formalize functional symmetry across three subsystems: Experimental Data Source, Sound Generation, and Guided Exploration. To differentiate time criticality and dimensionality of emerging dynamics, tuning functions are applied between subsystems to maintain scale and symmetry of concurrent processes and temporal dynamics. Tuning functions accommodate sonification design strategies that yield order parameter values to render emerging patterns discoverable as well as rehearsable, to reproduce desired instances for clinical listeners. Case studies are implemented with two computational models, Chua's circuit and Swarm Chemistry social agent simulation, generating data in real-time that exhibits emergent behavior. Heuristic Listening is introduced as an informal model of a listener's clinical attention to data sonification through multisensory interaction in a context of structured inquiry. Three methods are introduced to assess the proposed sonification framework: Listening Scenario classification, data flow Attunement, and Sonification Design Patterns to classify sound control. Case study implementations are assessed against these methods comparing levels of abstraction between experimental data and sound generation. Outcomes demonstrate the framework performance as a reference model for representing experimental implementations, also for identifying common sonification structures having different experimental implementations, identifying common functions implemented in different subsystems, and comparing impact of affordances across multiple implementations of listening scenarios. PMID:29755311

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

GENOPT 2016: Design of a generalization-based challenge in global optimization

NASA Astrophysics Data System (ADS)

Battiti, Roberto; Sergeyev, Yaroslav; Brunato, Mauro; Kvasov, Dmitri

2016-10-01

While comparing results on benchmark functions is a widely used practice to demonstrate the competitiveness of global optimization algorithms, fixed benchmarks can lead to a negative data mining process. To avoid this negative effect, the GENOPT contest benchmarks can be used which are based on randomized function generators, designed for scientific experiments, with fixed statistical characteristics but individual variation of the generated instances. The generators are available to participants for off-line tests and online tuning schemes, but the final competition is based on random seeds communicated in the last phase through a cooperative process. A brief presentation and discussion of the methods and results obtained in the framework of the GENOPT contest are given in this contribution.

Generation of Spinal Motor Neurons from Human Pluripotent Stem Cells.

PubMed

Santos, David P; Kiskinis, Evangelos

2017-01-01

Human embryonic stem cells (ESCs) are characterized by their unique ability to self-renew indefinitely, as well as to differentiate into any cell type of the human body. Induced pluripotent stem cells (iPSCs) share these salient characteristics with ESCs and can easily be generated from any given individual by reprogramming somatic cell types such as fibroblasts or blood cells. The spinal motor neuron (MN) is a specialized neuronal subtype that synapses with muscle to control movement. Here, we present a method to generate functional, postmitotic, spinal motor neurons through the directed differentiation of ESCs and iPSCs by the use of small molecules. These cells can be utilized to study the development and function of human motor neurons in healthy and disease states.

Adversarial Threshold Neural Computer for Molecular de Novo Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Vanhaelen, Quentin; Ivanenkov, Yan; Aladinskaya, Anastasia V; Aliper, Alex; Zhavoronkov, Alex

2018-03-30

In this article, we propose the deep neural network Adversarial Threshold Neural Computer (ATNC). The ATNC model is intended for the de novo design of novel small-molecule organic structures. The model is based on generative adversarial network architecture and reinforcement learning. ATNC uses a Differentiable Neural Computer as a generator and has a new specific block, called adversarial threshold (AT). AT acts as a filter between the agent (generator) and the environment (discriminator + objective reward functions). Furthermore, to generate more diverse molecules we introduce a new objective reward function named Internal Diversity Clustering (IDC). In this work, ATNC is tested and compared with the ORGANIC model. Both models were trained on the SMILES string representation of the molecules, using four objective functions (internal similarity, Muegge druglikeness filter, presence or absence of sp 3 -rich fragments, and IDC). The SMILES representations of 15K druglike molecules from the ChemDiv collection were used as a training data set. For the different functions, ATNC outperforms ORGANIC. Combined with the IDC, ATNC generates 72% of valid and 77% of unique SMILES strings, while ORGANIC generates only 7% of valid and 86% of unique SMILES strings. For each set of molecules generated by ATNC and ORGANIC, we analyzed distributions of four molecular descriptors (number of atoms, molecular weight, logP, and tpsa) and calculated five chemical statistical features (internal diversity, number of unique heterocycles, number of clusters, number of singletons, and number of compounds that have not been passed through medicinal chemistry filters). Analysis of key molecular descriptors and chemical statistical features demonstrated that the molecules generated by ATNC elicited better druglikeness properties. We also performed in vitro validation of the molecules generated by ATNC; results indicated that ATNC is an effective method for producing hit compounds.

High throughput mutagenesis for identification of residues regulating human prostacyclin (hIP) receptor expression and function.

PubMed

Bill, Anke; Rosethorne, Elizabeth M; Kent, Toby C; Fawcett, Lindsay; Burchell, Lynn; van Diepen, Michiel T; Marelli, Anthony; Batalov, Sergey; Miraglia, Loren; Orth, Anthony P; Renaud, Nicole A; Charlton, Steven J; Gosling, Martin; Gaither, L Alex; Groot-Kormelink, Paul J

2014-01-01

The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structure-function relationship of GPCRs.

High Throughput Mutagenesis for Identification of Residues Regulating Human Prostacyclin (hIP) Receptor Expression and Function

PubMed Central

Kent, Toby C.; Fawcett, Lindsay; Burchell, Lynn; van Diepen, Michiel T.; Marelli, Anthony; Batalov, Sergey; Miraglia, Loren; Orth, Anthony P.; Renaud, Nicole A.; Charlton, Steven J.; Gosling, Martin; Gaither, L. Alex; Groot-Kormelink, Paul J.

2014-01-01

The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structure-function relationship of GPCRs. PMID:24886841

Counting the number of Feynman graphs in QCD

NASA Astrophysics Data System (ADS)

Kaneko, T.

2018-05-01

Information about the number of Feynman graphs for a given physical process in a given field theory is especially useful for confirming the result of a Feynman graph generator used in an automatic system of perturbative calculations. A method of counting the number of Feynman graphs with weight of symmetry factor was established based on zero-dimensional field theory, and was used in scalar theories and QED. In this article this method is generalized to more complicated models by direct calculation of generating functions on a computer algebra system. This method is applied to QCD with and without counter terms, where many higher order are being calculated automatically.

Aphasia

MedlinePlus

... of speech-generating applications on mobile devices like tablets can also provide an alternative way to communicate ... on using advanced imaging methods, such as functional magnetic resonance imaging (fMRI), to explore how language is processed in ...

Genome Editing of Monkey.

PubMed

Liu, Zhen; Cai, Yijun; Sun, Qiang

2017-01-01

Gene-modified monkey models would be particularly valuable in biomedical and neuroscience research. Virus-based transgenic and programmable nucleases-based site-specific gene editing methods (TALEN, CRISPR-cas9) enable the generation of gene-modified monkeys with gain or loss of function of specific genes. Here, we describe the generation of transgenic and knock-out (KO) monkeys with high efficiency by lentivirus and programmable nucleases.

A comparison of different methods to implement higher order derivatives of density functionals

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

van Dam, Hubertus J.J.

Density functional theory is the dominant approach in electronic structure methods today. To calculate properties higher order derivatives of the density functionals are required. These derivatives might be implemented manually,by automatic differentiation, or by symbolic algebra programs. Different authors have cited different reasons for using the particular method of their choice. This paper presents work where all three approaches were used and the strengths and weaknesses of each approach are considered. It is found that all three methods produce code that is suffficiently performanted for practical applications, despite the fact that our symbolic algebra generated code and our automatic differentiationmore » code still have scope for significant optimization. The automatic differentiation approach is the best option for producing readable and maintainable code.« less

Symmetric and anti-symmetric LS hyperon potentials from lattice QCD

NASA Astrophysics Data System (ADS)

Ishii, Noriyoshi; Murano, Keiko; Nemura, Hidekatsu; Sasaki, Kenji; Inoue, Takashi; HAL QCD Collaboration

2014-09-01

We present recent results of odd-parity hyperon-hyperon potentials from lattice QCD. By using HAL QCD method, we generate hyperon-hyperon potentials from Nambu-Bethe-Salpeter (NBS) wave functions generated by lattice QCD simulation in the flavor SU(3) limit. Potentials in the irreducible flavor SU(3) representations are combined to make a Lambda-N potential which has a strong symmetric LS potential and a weak anti-symmetric LS potential. We discuss a possible cancellation between symmetric and anti-symmetric LS (Lambda-N) potentials after the coupled Sigma-N sector is integrated out. We present recent results of odd-parity hyperon-hyperon potentials from lattice QCD. By using HAL QCD method, we generate hyperon-hyperon potentials from Nambu-Bethe-Salpeter (NBS) wave functions generated by lattice QCD simulation in the flavor SU(3) limit. Potentials in the irreducible flavor SU(3) representations are combined to make a Lambda-N potential which has a strong symmetric LS potential and a weak anti-symmetric LS potential. We discuss a possible cancellation between symmetric and anti-symmetric LS (Lambda-N) potentials after the coupled Sigma-N sector is integrated out. This work is supported by JSPS KAKENHI Grant Number 25400244.

Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

PubMed

Yamazaki, Keisuke

2015-09-01

Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.

a New Method for Calculating the Fractal Dimension of Surface Topography

NASA Astrophysics Data System (ADS)

Zuo, Xue; Zhu, Hua; Zhou, Yuankai; Li, Yan

2015-06-01

A new method termed as three-dimensional root-mean-square (3D-RMS) method, is proposed to calculate the fractal dimension (FD) of machined surfaces. The measure of this method is the root-mean-square value of surface data, and the scale is the side length of square in the projection plane. In order to evaluate the calculation accuracy of the proposed method, the isotropic surfaces with deterministic FD are generated based on the fractional Brownian function and Weierstrass-Mandelbrot (WM) fractal function, and two kinds of anisotropic surfaces are generated by stretching or rotating a WM fractal curve. Their FDs are estimated by the proposed method, as well as differential boxing-counting (DBC) method, triangular prism surface area (TPSA) method and variation method (VM). The results show that the 3D-RMS method performs better than the other methods with a lower relative error for both isotropic and anisotropic surfaces, especially for the surfaces with dimensions higher than 2.5, since the relative error between the estimated value and its theoretical value decreases with theoretical FD. Finally, the electrodeposited surface, end-turning surface and grinding surface are chosen as examples to illustrate the application of 3D-RMS method on the real machined surfaces. This method gives a new way to accurately calculate the FD from the surface topographic data.

Boundary-Layer Receptivity and Integrated Transition Prediction

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan; Choudhari, Meelan

2005-01-01

The adjoint parabold stability equations (PSE) formulation is used to calculate the boundary layer receptivity to localized surface roughness and suction for compressible boundary layers. Receptivity efficiency functions predicted by the adjoint PSE approach agree well with results based on other nonparallel methods including linearized Navier-Stokes equations for both Tollmien-Schlichting waves and crossflow instability in swept wing boundary layers. The receptivity efficiency function can be regarded as the Green's function to the disturbance amplitude evolution in a nonparallel (growing) boundary layer. Given the Fourier transformed geometry factor distribution along the chordwise direction, the linear disturbance amplitude evolution for a finite size, distributed nonuniformity can be computed by evaluating the integral effects of both disturbance generation and linear amplification. The synergistic approach via the linear adjoint PSE for receptivity and nonlinear PSE for disturbance evolution downstream of the leading edge forms the basis for an integrated transition prediction tool. Eventually, such physics-based, high fidelity prediction methods could simulate the transition process from the disturbance generation through the nonlinear breakdown in a holistic manner.

A Study on the Secure User Profiling Structure and Procedure for Home Healthcare Systems.

PubMed

Ko, Hoon; Song, MoonBae

2016-01-01

Despite of various benefits such as a convenience and efficiency, home healthcare systems have some inherent security risks that may cause a serious leak on personal health information. This work presents a Secure User Profiling Structure which has the patient information including their health information. A patient and a hospital keep it at that same time, they share the updated data. While they share the data and communicate, the data can be leaked. To solve the security problems, a secure communication channel with a hash function and an One-Time Password between a client and a hospital should be established and to generate an input value to an OTP, it uses a dual hash-function. This work presents a dual hash function-based approach to generate the One-Time Password ensuring a secure communication channel with the secured key. In result, attackers are unable to decrypt the leaked information because of the secured key; in addition, the proposed method outperforms the existing methods in terms of computation cost.

Method for improving catalyst function in auto-thermal and partial oxidation reformer-based processors

DOEpatents

Ahmed, Shabbir; Papadias, Dionissios D.; Lee, Sheldon H.D.; Ahluwalia, Rajesh K.

2014-08-26

The invention provides a method for reforming fuel, the method comprising contacting the fuel to an oxidation catalyst so as to partially oxidize the fuel and generate heat; warming incoming fuel with the heat while simultaneously warming a reforming catalyst with the heat; and reacting the partially oxidized fuel with steam using the reforming catalyst.

The Hurwitz Enumeration Problem of Branched Covers and Hodge Integrals

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

Song, Yun S.

We use algebraic methods to compute the simple Hurwitz numbers for arbitrary source and target Riemann surfaces. For an elliptic curve target, we reproduce the results previously obtained by string theorists. Motivated by the Gromov-Witten potentials, we find a general generating function for the simple Hurwitz numbers in terms of the representation theory of the symmetric group S{sub n}. We also find a generating function for Hodge integrals on the moduli space {bar M}{sub g,2} of Riemann surfaces with two marked points, similar to that found by Faber and Pandharipande for the case of one marked point.

Comparison of different eigensolvers for calculating vibrational spectra using low-rank, sum-of-product basis functions

NASA Astrophysics Data System (ADS)

Leclerc, Arnaud; Thomas, Phillip S.; Carrington, Tucker

2017-08-01

Vibrational spectra and wavefunctions of polyatomic molecules can be calculated at low memory cost using low-rank sum-of-product (SOP) decompositions to represent basis functions generated using an iterative eigensolver. Using a SOP tensor format does not determine the iterative eigensolver. The choice of the interative eigensolver is limited by the need to restrict the rank of the SOP basis functions at every stage of the calculation. We have adapted, implemented and compared different reduced-rank algorithms based on standard iterative methods (block-Davidson algorithm, Chebyshev iteration) to calculate vibrational energy levels and wavefunctions of the 12-dimensional acetonitrile molecule. The effect of using low-rank SOP basis functions on the different methods is analysed and the numerical results are compared with those obtained with the reduced rank block power method. Relative merits of the different algorithms are presented, showing that the advantage of using a more sophisticated method, although mitigated by the use of reduced-rank SOP functions, is noticeable in terms of CPU time.

Automated method for relating regional pulmonary structure and function: integration of dynamic multislice CT and thin-slice high-resolution CT

NASA Astrophysics Data System (ADS)

Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.

1993-07-01

We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.

Multi-scale clustering of functional data with application to hydraulic gradients in wetlands

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Sharp, Julia L.; Peck, Rory G.; Rosenberry, Donald O.

2011-01-01

A new set of methods are developed to perform cluster analysis of functions, motivated by a data set consisting of hydraulic gradients at several locations distributed across a wetland complex. The methods build on previous work on clustering of functions, such as Tarpey and Kinateder (2003) and Hitchcock et al. (2007), but explore functions generated from an additive model decomposition (Wood, 2006) of the original time se- ries. Our decomposition targets two aspects of the series, using an adaptive smoother for the trend and circular spline for the diurnal variation in the series. Different measures for comparing locations are discussed, including a method for efficiently clustering time series that are of different lengths using a functional data approach. The complicated nature of these wetlands are highlighted by the shifting group memberships depending on which scale of variation and year of the study are considered.

CONORBIT: constrained optimization by radial basis function interpolation in trust regions

DOE PAGES

Regis, Rommel G.; Wild, Stefan M.

2016-09-26

Here, this paper presents CONORBIT (CONstrained Optimization by Radial Basis function Interpolation in Trust regions), a derivative-free algorithm for constrained black-box optimization where the objective and constraint functions are computationally expensive. CONORBIT employs a trust-region framework that uses interpolating radial basis function (RBF) models for the objective and constraint functions, and is an extension of the ORBIT algorithm. It uses a small margin for the RBF constraint models to facilitate the generation of feasible iterates, and extensive numerical tests confirm that such a margin is helpful in improving performance. CONORBIT is compared with other algorithms on 27 test problems, amore » chemical process optimization problem, and an automotive application. Numerical results show that CONORBIT performs better than COBYLA, a sequential penalty derivative-free method, an augmented Lagrangian method, a direct search method, and another RBF-based algorithm on the test problems and on the automotive application.« less

Method for utilizing properties of the sinc(x) function for phase retrieval on nyquist-under-sampled data

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor); Smith, Jeffrey Scott (Inventor); Aronstein, David L. (Inventor)

2012-01-01

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for simulating propagation of an electromagnetic field, performing phase retrieval, or sampling a band-limited function. A system practicing the method generates transformed data using a discrete Fourier transform which samples a band-limited function f(x) without interpolating or modifying received data associated with the function f(x), wherein an interval between repeated copies in a periodic extension of the function f(x) obtained from the discrete Fourier transform is associated with a sampling ratio Q, defined as a ratio of a sampling frequency to a band-limited frequency, and wherein Q is assigned a value between 1 and 2 such that substantially no aliasing occurs in the transformed data, and retrieves a phase in the received data based on the transformed data, wherein the phase is used as feedback to an optical system.

Comparison of Bootstrapping and Markov Chain Monte Carlo for Copula Analysis of Hydrological Droughts

NASA Astrophysics Data System (ADS)

Yang, P.; Ng, T. L.; Yang, W.

2015-12-01

Effective water resources management depends on the reliable estimation of the uncertainty of drought events. Confidence intervals (CIs) are commonly applied to quantify this uncertainty. A CI seeks to be at the minimal length necessary to cover the true value of the estimated variable with the desired probability. In drought analysis where two or more variables (e.g., duration and severity) are often used to describe a drought, copulas have been found suitable for representing the joint probability behavior of these variables. However, the comprehensive assessment of the parameter uncertainties of copulas of droughts has been largely ignored, and the few studies that have recognized this issue have not explicitly compared the various methods to produce the best CIs. Thus, the objective of this study to compare the CIs generated using two widely applied uncertainty estimation methods, bootstrapping and Markov Chain Monte Carlo (MCMC). To achieve this objective, (1) the marginal distributions lognormal, Gamma, and Generalized Extreme Value, and the copula functions Clayton, Frank, and Plackett are selected to construct joint probability functions of two drought related variables. (2) The resulting joint functions are then fitted to 200 sets of simulated realizations of drought events with known distribution and extreme parameters and (3) from there, using bootstrapping and MCMC, CIs of the parameters are generated and compared. The effect of an informative prior on the CIs generated by MCMC is also evaluated. CIs are produced for different sample sizes (50, 100, and 200) of the simulated drought events for fitting the joint probability functions. Preliminary results assuming lognormal marginal distributions and the Clayton copula function suggest that for cases with small or medium sample sizes (~50-100), MCMC to be superior method if an informative prior exists. Where an informative prior is unavailable, for small sample sizes (~50), both bootstrapping and MCMC yield the same level of performance, and for medium sample sizes (~100), bootstrapping is better. For cases with a large sample size (~200), there is little difference between the CIs generated using bootstrapping and MCMC regardless of whether or not an informative prior exists.

CORALINA: a universal method for the generation of gRNA libraries for CRISPR-based screening.

PubMed

Köferle, Anna; Worf, Karolina; Breunig, Christopher; Baumann, Valentin; Herrero, Javier; Wiesbeck, Maximilian; Hutter, Lukas H; Götz, Magdalena; Fuchs, Christiane; Beck, Stephan; Stricker, Stefan H

2016-11-14

The bacterial CRISPR system is fast becoming the most popular genetic and epigenetic engineering tool due to its universal applicability and adaptability. The desire to deploy CRISPR-based methods in a large variety of species and contexts has created an urgent need for the development of easy, time- and cost-effective methods enabling large-scale screening approaches. Here we describe CORALINA (comprehensive gRNA library generation through controlled nuclease activity), a method for the generation of comprehensive gRNA libraries for CRISPR-based screens. CORALINA gRNA libraries can be derived from any source of DNA without the need of complex oligonucleotide synthesis. We show the utility of CORALINA for human and mouse genomic DNA, its reproducibility in covering the most relevant genomic features including regulatory, coding and non-coding sequences and confirm the functionality of CORALINA generated gRNAs. The simplicity and cost-effectiveness make CORALINA suitable for any experimental system. The unprecedented sequence complexities obtainable with CORALINA libraries are a necessary pre-requisite for less biased large scale genomic and epigenomic screens.

Modeling multilayer x-ray reflectivity using genetic algorithms

NASA Astrophysics Data System (ADS)

Sánchez del Río, M.; Pareschi, G.; Michetschläger, C.

2000-06-01

The x-ray reflectivity of a multilayer is a non-linear function of many parameters (materials, layer thickness, density, roughness). Non-linear fitting of experimental data with simulations requires the use of initial values sufficiently close to the optimum value. This is a difficult task when the topology of the space of the variables is highly structured. We apply global optimization methods to fit multilayer reflectivity. Genetic algorithms are stochastic methods based on the model of natural evolution: the improvement of a population along successive generations. A complete set of initial parameters constitutes an individual. The population is a collection of individuals. Each generation is built from the parent generation by applying some operators (selection, crossover, mutation, etc.) on the members of the parent generation. The pressure of selection drives the population to include "good" individuals. For large number of generations, the best individuals will approximate the optimum parameters. Some results on fitting experimental hard x-ray reflectivity data for Ni/C and W/Si multilayers using genetic algorithms are presented. This method can also be applied to design multilayers optimized for a target application.

Programming function into mechanical forms by directed assembly of silk bulk materials

PubMed Central

Patel, Nereus; Duggan, Thomas; Perotto, Giovanni; Shirman, Elijah; Li, Chunmei; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-01-01

We report simple, water-based fabrication methods based on protein self-assembly to generate 3D silk fibroin bulk materials that can be easily hybridized with water-soluble molecules to obtain multiple solid formats with predesigned functions. Controlling self-assembly leads to robust, machinable formats that exhibit thermoplastic behavior consenting material reshaping at the nanoscale, microscale, and macroscale. We illustrate the versatility of the approach by realizing demonstrator devices where large silk monoliths can be generated, polished, and reshaped into functional mechanical components that can be nanopatterned, embed optical function, heated on demand in response to infrared light, or can visualize mechanical failure through colorimetric chemistries embedded in the assembled (bulk) protein matrix. Finally, we show an enzyme-loaded solid mechanical part, illustrating the ability to incorporate biological function within the bulk material with possible utility for sustained release in robust, programmably shapeable mechanical formats. PMID:28028213

Expert system for testing industrial processes and determining sensor status

DOEpatents

Gross, K.C.; Singer, R.M.

1998-06-02

A method and system are disclosed for monitoring both an industrial process and a sensor. The method and system include determining a minimum number of sensor pairs needed to test the industrial process as well as the sensor for evaluating the state of operation of both. The technique further includes generating a first and second signal characteristic of an industrial process variable. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the pair of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 24 figs.

Expert system for testing industrial processes and determining sensor status

DOEpatents

Gross, Kenneth C.; Singer, Ralph M.

1998-01-01

A method and system for monitoring both an industrial process and a sensor. The method and system include determining a minimum number of sensor pairs needed to test the industrial process as well as the sensor for evaluating the state of operation of both. The technique further includes generating a first and second signal characteristic of an industrial process variable. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the pair of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

Large deviation function for a driven underdamped particle in a periodic potential

NASA Astrophysics Data System (ADS)

Fischer, Lukas P.; Pietzonka, Patrick; Seifert, Udo

2018-02-01

Employing large deviation theory, we explore current fluctuations of underdamped Brownian motion for the paradigmatic example of a single particle in a one-dimensional periodic potential. Two different approaches to the large deviation function of the particle current are presented. First, we derive an explicit expression for the large deviation functional of the empirical phase space density, which replaces the level 2.5 functional used for overdamped dynamics. Using this approach, we obtain several bounds on the large deviation function of the particle current. We compare these to bounds for overdamped dynamics that have recently been derived, motivated by the thermodynamic uncertainty relation. Second, we provide a method to calculate the large deviation function via the cumulant generating function. We use this method to assess the tightness of the bounds in a numerical case study for a cosine potential.

Offspring Generation Method for interactive Genetic Algorithm considering Multimodal Preference

NASA Astrophysics Data System (ADS)

Ito, Fuyuko; Hiroyasu, Tomoyuki; Miki, Mitsunori; Yokouchi, Hisatake

In interactive genetic algorithms (iGAs), computer simulations prepare design candidates that are then evaluated by the user. Therefore, iGA can predict a user's preferences. Conventional iGA problems involve a search for a single optimum solution, and iGA were developed to find this single optimum. On the other hand, our target problems have several peaks in a function and there are small differences among these peaks. For such problems, it is better to show all the peaks to the user. Product recommendation in shopping sites on the web is one example of such problems. Several types of preference trend should be prepared for users in shopping sites. Exploitation and exploration are important mechanisms in GA search. To perform effective exploitation, the offspring generation method (crossover) is very important. Here, we introduced a new offspring generation method for iGA in multimodal problems. In the proposed method, individuals are clustered into subgroups and offspring are generated in each group. The proposed method was applied to an experimental iGA system to examine its effectiveness. In the experimental iGA system, users can decide on preferable t-shirts to buy. The results of the subjective experiment confirmed that the proposed method enables offspring generation with consideration of multimodal preferences, and the proposed mechanism was also shown not to adversely affect the performance of preference prediction.

Optical generation of millimeter-wave pulses using a fiber Bragg grating in a fiber-optics system.

PubMed

Ye, Qing; Qu, Ronghui; Fang, Zujie

2007-04-10

A scheme is proposed to transform an optical pulse into a millimeter-wave frequency modulation pulse by using a weak fiber Bragg grating (FBG) in a fiber-optics system. The Fourier transformation method is used to obtain the required spectrum response function of the FBG for the Gaussian pulse, soliton pulse, and Lorenz shape pulse. On the condition of the first-order Born approximation of the weak fiber grating, the relation of the refractive index distribution and the spectrum response function of the FBG satisfies the Fourier transformation, and the corresponding refractive index distribution forms are obtained for single-frequency modulation and linear-frequency modulation millimeter-wave pulse generation. The performances of the designed fiber gratings are also studied by a numerical simulation method for a supershort pulse transmission.

The Harmonic Oscillator with a Gaussian Perturbation: Evaluation of the Integrals and Example Applications

ERIC Educational Resources Information Center

Earl, Boyd L.

2008-01-01

A general result for the integrals of the Gaussian function over the harmonic oscillator wavefunctions is derived using generating functions. Using this result, an example problem of a harmonic oscillator with various Gaussian perturbations is explored in order to compare the results of precise numerical solution, the variational method, and…

A Multidimensional Examination of the Acculturation and Psychological Functioning of a Sample of Immigrant Chinese Mothers in the US

ERIC Educational Resources Information Center

Tahseen, Madiha; Cheah, Charissa S. L.

2012-01-01

The present research used the cluster analysis method to examine the acculturation of immigrant Chinese mothers (ICMs), and the demographic characteristics and psychological functioning associated with each acculturation style. The sample was comprised of 83 first-generation ICMs of preschool children residing in Maryland, United States (US).…

Functional Transcranial Doppler Sonography and a Spatial Orientation Paradigm Identify the Non-Dominant Hemisphere

ERIC Educational Resources Information Center

Dorst, J.; Haag, A.; Knake, S.; Oertel, W. H.; Hamer, H. M.; Rosenow, F.

2008-01-01

Rationale: Functional transcranial Doppler sonography (fTCD) during word generation is well established for language lateralization. In this study, we evaluated a fTCD paradigm to reliably identify the non-dominant hemisphere. Methods: Twenty-nine right-handed healthy subjects (27.1 [plus or minus] 7.6 years) performed the "cube perspective test"…

Numerical solutions of a control problem governed by functional differential equations

NASA Technical Reports Server (NTRS)

Banks, H. T.; Thrift, P. R.; Burns, J. A.; Cliff, E. M.

1978-01-01

A numerical procedure is proposed for solving optimal control problems governed by linear retarded functional differential equations. The procedure is based on the idea of 'averaging approximations', due to Banks and Burns (1975). For illustration, numerical results generated on an IBM 370/158 computer, which demonstrate the rapid convergence of the method are presented.

Analysis of Thermal Power Generation Capacity for a Skutterudite-Based Thermoelectric Functional Structure

NASA Astrophysics Data System (ADS)

Sun, Yajing; Chen, Gang; Bai, Guanghui; Yang, Xuqiu; Li, Peng; Zhai, Pengcheng

2017-05-01

Due to military or other requirements for hypersonic aircraft, the energy supply devices with the advantages of small size and light weight are urgently needed. Compared with the traditional energy supply method, the skutterudite-based thermoelectric (TE) functional structure is expected to generate electrical energy with a smaller structural space in the hypersonic aircraft. This paper mainly focuses on the responded thermal and electrical characteristics of the skutterudite-based TE functional structure (TEFS) under strong heat flux loads. We conduct TE simulations on the transient model of the TEFS with consideration of the heat flux loads and thermal radiation in the hot end and the cooling effect of the phase change material (PCM) in the cold end. We investigate several influential factors on the power generation capacity, such as the phase transition temperature of the PCM, the heat flux loads, the thickness of the TE materials and the thermal conductivity of the frame materials. The results show that better power generation capacity can be achieved with thicker TE materials, lower phase transition temperature and suitable thermal conductivity of the frame materials.

Extension of the method of moments for population balances involving fractional moments and application to a typical agglomeration problem.

PubMed

Alexiadis, Alessio; Vanni, Marco; Gardin, Pascal

2004-08-01

The method of moment (MOM) is a powerful tool for solving population balance. Nevertheless it cannot be used in every circumstance. Sometimes, in fact, it is not possible to write the governing equations in closed form. Higher moments, for instance, could appear in the evolution of the lower ones. This obstacle has often been resolved by prescribing some functional form for the particle size distribution. Another example is the occurrence of fractional moment, usually connected with the presence of fractal aggregates. For this case we propose a procedure that does not need any assumption on the form of the distribution but it is based on the "moments generating function" (that is the Laplace transform of the distribution). An important result of probability theory is that the kth derivative of the moments generating function represents the kth moment of the original distribution. This result concerns integer moments but, taking in account the Weyl fractional derivative, could be extended to fractional orders. Approximating fractional derivative makes it possible to express the fractional moments in terms of the integer ones and so to use regularly the method of moments.

Generation and Assessment of Functional Biomaterial Scaffolds for Applications in Cardiovascular Tissue Engineering and Regenerative Medicine.

PubMed

Hinderer, Svenja; Brauchle, Eva; Schenke-Layland, Katja

2015-11-18

Current clinically applicable tissue and organ replacement therapies are limited in the field of cardiovascular regenerative medicine. The available options do not regenerate damaged tissues and organs, and, in the majority of the cases, show insufficient restoration of tissue function. To date, anticoagulant drug-free heart valve replacements or growing valves for pediatric patients, hemocompatible and thrombus-free vascular substitutes that are smaller than 6 mm, and stem cell-recruiting delivery systems that induce myocardial regeneration are still only visions of researchers and medical professionals worldwide and far from being the standard of clinical treatment. The design of functional off-the-shelf biomaterials as well as automatable and up-scalable biomaterial processing methods are the focus of current research endeavors and of great interest for fields of tissue engineering and regenerative medicine. Here, various approaches that aim to overcome the current limitations are reviewed, focusing on biomaterials design and generation methods for myocardium, heart valves, and blood vessels. Furthermore, novel contact- and marker-free biomaterial and extracellular matrix assessment methods are highlighted. © 2015 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel approach for tomographic reconstruction of gas concentration distributions in air: Use of smooth basis functions and simulated annealing

NASA Astrophysics Data System (ADS)

Drescher, A. C.; Gadgil, A. J.; Price, P. N.; Nazaroff, W. W.

Optical remote sensing and iterative computed tomography (CT) can be applied to measure the spatial distribution of gaseous pollutant concentrations. We conducted chamber experiments to test this combination of techniques using an open path Fourier transform infrared spectrometer (OP-FTIR) and a standard algebraic reconstruction technique (ART). Although ART converged to solutions that showed excellent agreement with the measured ray-integral concentrations, the solutions were inconsistent with simultaneously gathered point-sample concentration measurements. A new CT method was developed that combines (1) the superposition of bivariate Gaussians to represent the concentration distribution and (2) a simulated annealing minimization routine to find the parameters of the Gaussian basis functions that result in the best fit to the ray-integral concentration data. This method, named smooth basis function minimization (SBFM), generated reconstructions that agreed well, both qualitatively and quantitatively, with the concentration profiles generated from point sampling. We present an analysis of two sets of experimental data that compares the performance of ART and SBFM. We conclude that SBFM is a superior CT reconstruction method for practical indoor and outdoor air monitoring applications.

Machine fault feature extraction based on intrinsic mode functions

NASA Astrophysics Data System (ADS)

Fan, Xianfeng; Zuo, Ming J.

2008-04-01

This work employs empirical mode decomposition (EMD) to decompose raw vibration signals into intrinsic mode functions (IMFs) that represent the oscillatory modes generated by the components that make up the mechanical systems generating the vibration signals. The motivation here is to develop vibration signal analysis programs that are self-adaptive and that can detect machine faults at the earliest onset of deterioration. The change in velocity of the amplitude of some IMFs over a particular unit time will increase when the vibration is stimulated by a component fault. Therefore, the amplitude acceleration energy in the intrinsic mode functions is proposed as an indicator of the impulsive features that are often associated with mechanical component faults. The periodicity of the amplitude acceleration energy for each IMF is extracted by spectrum analysis. A spectrum amplitude index is introduced as a method to select the optimal result. A comparison study of the method proposed here and some well-established techniques for detecting machinery faults is conducted through the analysis of both gear and bearing vibration signals. The results indicate that the proposed method has superior capability to extract machine fault features from vibration signals.

Generation and development of RNA ligase ribozymes with modular architecture through "design and selection".

PubMed

Fujita, Yuki; Ishikawa, Junya; Furuta, Hiroyuki; Ikawa, Yoshiya

2010-08-26

In vitro selection with long random RNA libraries has been used as a powerful method to generate novel functional RNAs, although it often requires laborious structural analysis of isolated RNA molecules. Rational RNA design is an attractive alternative to avoid this laborious step, but rational design of catalytic modules is still a challenging task. A hybrid strategy of in vitro selection and rational design has been proposed. With this strategy termed "design and selection," new ribozymes can be generated through installation of catalytic modules onto RNA scaffolds with defined 3D structures. This approach, the concept of which was inspired by the modular architecture of naturally occurring ribozymes, allows prediction of the overall architectures of the resulting ribozymes, and the structural modularity of the resulting ribozymes allows modification of their structures and functions. In this review, we summarize the design, generation, properties, and engineering of four classes of ligase ribozyme generated by design and selection.

Textbook Citations as a Measure of Journal Influence on International Business Education

ERIC Educational Resources Information Center

Urbancic, Frank R.

2006-01-01

Previously published rankings of journals in relation to international business research are based on a survey method or a journal-based citation method wherein functional discipline journals are excluded from consideration. The narrow focus of these studies has generated criticism for perpetuating an international business silo perspective. In…

High-order time-marching reinitialization for regional level-set functions

NASA Astrophysics Data System (ADS)

Pan, Shucheng; Lyu, Xiuxiu; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-02-01

In this work, the time-marching reinitialization method is extended to compute the unsigned distance function in multi-region systems involving arbitrary number of regions. High order and interface preservation are achieved by applying a simple mapping that transforms the regional level-set function to the level-set function and a high-order two-step reinitialization method which is a combination of the closest point finding procedure and the HJ-WENO scheme. The convergence failure of the closest point finding procedure in three dimensions is addressed by employing a proposed multiple junction treatment and a directional optimization algorithm. Simple test cases show that our method exhibits 4th-order accuracy for reinitializing the regional level-set functions and strictly satisfies the interface-preserving property. The reinitialization results for more complex cases with randomly generated diagrams show the capability our method for arbitrary number of regions N, with a computational effort independent of N. The proposed method has been applied to dynamic interfaces with different types of flows, and the results demonstrate high accuracy and robustness.

Model misspecification detection by means of multiple generator errors, using the observed potential map.

PubMed

Zhang, Z; Jewett, D L

1994-01-01

Due to model misspecification, currently-used Dipole Source Localization (DSL) methods may contain Multiple-Generator Errors (MulGenErrs) when fitting simultaneously-active dipoles. The size of the MulGenErr is a function of both the model used, and the dipole parameters, including the dipoles' waveforms (time-varying magnitudes). For a given fitting model, by examining the variation of the MulGenErrs (or the fit parameters) under different waveforms for the same generating-dipoles, the accuracy of the fitting model for this set of dipoles can be determined. This method of testing model misspecification can be applied to evoked potential maps even when the parameters of the generating-dipoles are unknown. The dipole parameters fitted in a model should only be accepted if the model can be shown to be sufficiently accurate.

Figure-ground segmentation based on class-independent shape priors

NASA Astrophysics Data System (ADS)

Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.

Extending compile-time reverse mode and exploiting partial separability in ADIFOR

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

Bischof, C.H.; El-Khadiri, M.

1992-10-01

The numerical methods employed in the solution of many scientific computing problems require the computation of the gradient of a function f: R[sup n] [yields] R. ADIFOR is a source translator that, given a collection of subroutines to compute f, generates Fortran 77 code for computing the derivative of this function. Using the so-called torsion problem from the MINPACK-2 test collection as an example, this paper explores two issues in automatic differentiation: the efficient computation of derivatives for partial separable functions and the use of the compile-time reverse mode for the generation of derivatives. We show that orders of magnitudesmore » of improvement are possible when exploiting partial separability and maximizing use of the reverse mode.« less

Cryo-chemical decellularization of the whole liver for mesenchymal stem cells-based functional hepatic tissue engineering.

PubMed

Jiang, Wei-Cheng; Cheng, Yu-Hao; Yen, Meng-Hua; Chang, Yin; Yang, Vincent W; Lee, Oscar K

2014-04-01

Liver transplantation is the ultimate treatment for severe hepatic failure to date. However, the limited supply of donor organs has severely hampered this treatment. So far, great potentials of using mesenchymal stem cells (MSCs) to replenish the hepatic cell population have been shown; nevertheless, there still is a lack of an optimal three-dimensional scaffold for generation of well-transplantable hepatic tissues. In this study, we utilized a cryo-chemical decellularization method which combines physical and chemical approach to generate acellular liver scaffolds (ALS) from the whole liver. The produced ALS provides a biomimetic three-dimensional environment to support hepatic differentiation of MSCs, evidenced by expression of hepatic-associated genes and marker protein, glycogen storage, albumin secretion, and urea production. It is also found that hepatic differentiation of MSCs within the ALS is much more efficient than two-dimensional culture in vitro. Importantly, the hepatic-like tissues (HLT) generated by repopulating ALS with MSCs are able to act as functional grafts and rescue lethal hepatic failure after transplantation in vivo. In summary, the cryo-chemical method used in this study is suitable for decellularization of liver and create acellular scaffolds that can support hepatic differentiation of MSCs and be used to fabricate functional tissue-engineered liver constructs. Copyright © 2014 Elsevier Ltd. All rights reserved.

The constraints satisfaction problem approach in the design of an architectural functional layout

NASA Astrophysics Data System (ADS)

Zawidzki, Machi; Tateyama, Kazuyoshi; Nishikawa, Ikuko

2011-09-01

A design support system with a new strategy for finding the optimal functional configurations of rooms for architectural layouts is presented. A set of configurations satisfying given constraints is generated and ranked according to multiple objectives. The method can be applied to problems in architectural practice, urban or graphic design-wherever allocation of related geometrical elements of known shape is optimized. Although the methodology is shown using simplified examples-a single story residential building with two apartments each having two rooms-the results resemble realistic functional layouts. One example of a practical size problem of a layout of three apartments with a total of 20 rooms is demonstrated, where the generated solution can be used as a base for a realistic architectural blueprint. The discretization of design space is discussed, followed by application of a backtrack search algorithm used for generating a set of potentially 'good' room configurations. Next the solutions are classified by a machine learning method (FFN) as 'proper' or 'improper' according to the internal communication criteria. Examples of interactive ranking of the 'proper' configurations according to multiple criteria and choosing 'the best' ones are presented. The proposed framework is general and universal-the criteria, parameters and weights can be individually defined by a user and the search algorithm can be adjusted to a specific problem.

Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions

PubMed Central

2017-01-01

Background A new generation of user-centric information systems is emerging in health care as patient health record (PHR) systems. These systems create a platform supporting the new vision of health services that empowers patients and enables patient-provider communication, with the goal of improving health outcomes and reducing costs. This evolution has generated new sets of data and capabilities, providing opportunities and challenges at the user, system, and industry levels. Objective The objective of our study was to assess PHR data types and functionalities through a review of the literature to inform the health care informatics community, and to provide recommendations for PHR design, research, and practice. Methods We conducted a review of the literature to assess PHR data types and functionalities. We searched PubMed, Embase, and MEDLINE databases from 1966 to 2015 for studies of PHRs, resulting in 1822 articles, from which we selected a total of 106 articles for a detailed review of PHR data content. Results We present several key findings related to the scope and functionalities in PHR systems. We also present a functional taxonomy and chronological analysis of PHR data types and functionalities, to improve understanding and provide insights for future directions. Functional taxonomy analysis of the extracted data revealed the presence of new PHR data sources such as tracking devices and data types such as time-series data. Chronological data analysis showed an evolution of PHR system functionalities over time, from simple data access to data modification and, more recently, automated assessment, prediction, and recommendation. Conclusions Efforts are needed to improve (1) PHR data quality through patient-centered user interface design and standardized patient-generated data guidelines, (2) data integrity through consolidation of various types and sources, (3) PHR functionality through application of new data analytics methods, and (4) metrics to evaluate clinical outcomes associated with automated PHR system use, and costs associated with PHR data storage and analytics. PMID:29141839

Phase pupil functions for focal-depth enhancement derived from a Wigner distribution function.

PubMed

Zalvidea, D; Sicre, E E

1998-06-10

A method for obtaining phase-retardation functions, which give rise to an increase of the image focal depth, is proposed. To this end, the Wigner distribution function corresponding to a specific aperture that has an associated small depth of focus in image space is conveniently sheared in the phase-space domain to generate a new Wigner distribution function. From this new function a more uniform on-axis image irradiance can be accomplished. This approach is illustrated by comparison of the imaging performance of both the derived phase function and a previously reported logarithmic phase distribution.

Simplified DFT methods for consistent structures and energies of large systems

NASA Astrophysics Data System (ADS)

Caldeweyher, Eike; Gerit Brandenburg, Jan

2018-05-01

Kohn–Sham density functional theory (DFT) is routinely used for the fast electronic structure computation of large systems and will most likely continue to be the method of choice for the generation of reliable geometries in the foreseeable future. Here, we present a hierarchy of simplified DFT methods designed for consistent structures and non-covalent interactions of large systems with particular focus on molecular crystals. The covered methods are a minimal basis set Hartree–Fock (HF-3c), a small basis set screened exchange hybrid functional (HSE-3c), and a generalized gradient approximated functional evaluated in a medium-sized basis set (B97-3c), all augmented with semi-classical correction potentials. We give an overview on the methods design, a comprehensive evaluation on established benchmark sets for geometries and lattice energies of molecular crystals, and highlight some realistic applications on large organic crystals with several hundreds of atoms in the primitive unit cell.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Feasibility of inverse problem solution for determination of city emission function from night sky radiance measurements

NASA Astrophysics Data System (ADS)

Petržala, Jaromír

2018-07-01

The knowledge of the emission function of a city is crucial for simulation of sky glow in its vicinity. The indirect methods to achieve this function from radiances measured over a part of the sky have been recently developed. In principle, such methods represent an ill-posed inverse problem. This paper deals with the theoretical feasibility study of various approaches to solving of given inverse problem. Particularly, it means testing of fitness of various stabilizing functionals within the Tikhonov's regularization. Further, the L-curve and generalized cross validation methods were investigated as indicators of an optimal regularization parameter. At first, we created the theoretical model for calculation of a sky spectral radiance in the form of a functional of an emission spectral radiance. Consequently, all the mentioned approaches were examined in numerical experiments with synthetical data generated for the fictitious city and loaded by random errors. The results demonstrate that the second order Tikhonov's regularization method together with regularization parameter choice by the L-curve maximum curvature criterion provide solutions which are in good agreement with the supposed model emission functions.

Generation of the neutron response function of an NE213 scintillator for fusion applications

NASA Astrophysics Data System (ADS)

Binda, F.; Eriksson, J.; Ericsson, G.; Hellesen, C.; Conroy, S.; Nocente, M.; Sundén, E. Andersson; JET Contributors

2017-09-01

In this work we present a method to evaluate the neutron response function of an NE213 liquid scintillator. This method is particularly useful when the proton light yield function of the detector has not been measured, since it is based on a proton light yield function taken from literature, MCNPX simulations, measurements of gamma-rays from a calibration source and measurements of neutrons from fusion experiments with ohmic plasmas. The inclusion of the latter improves the description of the proton light yield function in the energy range of interest (around 2.46 MeV). We apply this method to an NE213 detector installed at JET, inside the radiation shielding of the magnetic proton recoil (MPRu) spectrometer, and present the results from the calibration along with some examples of application of the response function to perform neutron emission spectroscopy (NES) of fusion plasmas. We also investigate how the choice of the proton light yield function affects the NES analysis, finding that the result does not change significantly. This points to the fact that the method for the evaluation of the neutron response function is robust and gives reliable results.

Idler-efficiency-enhanced long-wave infrared beam generation using aperiodic orientation-patterned GaAs gratings.

PubMed

Gürkan Figen, Ziya; Aytür, Orhan; Arıkan, Orhan

2016-03-20

In this paper, we design aperiodic gratings based on orientation-patterned gallium arsenide (OP-GaAs) for converting 2.1 μm pump laser radiation into long-wave infrared (8-12 μm) in an idler-efficiency-enhanced scheme. These single OP-GaAs gratings placed in an optical parametric oscillator (OPO) or an optical parametric generator (OPG) can simultaneously phase match two optical parametric amplification (OPA) processes, OPA 1 and OPA 2. We use two design methods that allow simultaneous phase matching of two arbitrary χ⁽²⁾ processes and also free adjustment of their relative strength. The first aperiodic grating design method (Method 1) relies on generating a grating structure that has domain walls located at the zeros of the summation of two cosine functions, each of which has a spatial frequency that equals one of the phase-mismatch terms of the two processes. Some of the domain walls are discarded considering the minimum domain length that is achievable in the production process. In this paper, we propose a second design method (Method 2) that relies on discretizing the crystal length with sample lengths that are much smaller than the minimum domain length and testing each sample's contribution in such a way that the sign of the nonlinearity maximizes the magnitude sum of the real and imaginary parts of the Fourier transform of the grating function at the relevant phase mismatches. Method 2 produces a similar performance as Method 1 in terms of the maximization of the height of either Fourier peak located at the relevant phase mismatch while allowing an adjustable relative height for the two peaks. To our knowledge, this is the first time that aperiodic OP-GaAs gratings have been proposed for efficient long-wave infrared beam generation based on simultaneous phase matching.

Optical image encryption using triplet of functions

NASA Astrophysics Data System (ADS)

Yatish; Fatima, Areeba; Nishchal, Naveen Kumar

2018-03-01

We propose an image encryption scheme that brings into play a technique using a triplet of functions to manipulate complex-valued functions. Optical cryptosystems using this method are an easier approach toward the ciphertext generation that avoids the use of holographic setup to record phase. The features of this method were shown in the context of double random phase encoding and phase-truncated Fourier transform-based cryptosystems using gyrator transform. In the first step, the complex function is split into two matrices. These matrices are separated, so they contain the real and imaginary parts. In the next step, these two matrices and a random distribution function are acted upon by one of the functions in the triplet. During decryption, the other two functions in the triplet help us retrieve the complex-valued function. The simulation results demonstrate the effectiveness of the proposed idea. To check the robustness of the proposed scheme, attack analyses were carried out.

The numerical solution of ordinary differential equations by the Taylor series method

NASA Technical Reports Server (NTRS)

Silver, A. H.; Sullivan, E.

1973-01-01

A programming implementation of the Taylor series method is presented for solving ordinary differential equations. The compiler is written in PL/1, and the target language is FORTRAN IV. The reduction of a differential system to rational form is described along with the procedures required for automatic numerical integration. The Taylor method is compared with two other methods for a number of differential equations. Algorithms using the Taylor method to find the zeroes of a given differential equation and to evaluate partial derivatives are presented. An annotated listing of the PL/1 program which performs the reduction and code generation is given. Listings of the FORTRAN routines used by the Taylor series method are included along with a compilation of all the recurrence formulas used to generate the Taylor coefficients for non-rational functions.

Strategies for the generation of parametric images of [11C]PIB with plasma input functions considering discriminations and reproducibility.

PubMed

Edison, Paul; Brooks, David J; Turkheimer, Federico E; Archer, Hilary A; Hinz, Rainer

2009-11-01

Pittsburgh compound B or [11C]PIB is an amyloid imaging agent which shows a clear differentiation between subjects with Alzheimer's disease (AD) and controls. However the observed signal difference in other forms of dementia such as dementia with Lewy bodies (DLB) is smaller, and mild cognitively impaired (MCI) subjects and some healthy elderly normals may show intermediate levels of [11C]PIB binding. The cerebellum, a commonly used reference region for non-specific tracer uptake in [11C]PIB studies in AD may not be valid in Prion disorders or monogenic forms of AD. The aim of this work was to: 1-compare methods for generating parametric maps of [11C]PIB retention in tissue using a plasma input function in respect of their ability to discriminate between AD subjects and controls and 2-estimate the test-retest reproducibility in AD subjects. 12 AD subjects (5 of which underwent a repeat scan within 6 weeks) and 10 control subjects had 90 minute [11C]PIB dynamic PET scans, and arterial plasma input functions were measured. Parametric maps were generated with graphical analysis of reversible binding (Logan plot), irreversible binding (Patlak plot), and spectral analysis. Between group differentiation was calculated using Student's t-test and comparisons between different methods were made using p values. Reproducibility was assessed by intraclass correlation coefficients (ICC). We found that the 75 min value of the impulse response function showed the best group differentiation and had a higher ICC than volume of distribution maps generated from Logan and spectral analysis. Patlak analysis of [11C]PIB binding was the least reproducible.

Free boundary skin current MHD (magnetohydrodynamic) equilibria

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

Reusch, M.F.

1988-02-01

Function theoretic methods in the complex plane are used to develop simple parametric hodograph formulae which generate sharp boundary equilibria of arbitrary shape. The related method of Gorenflo and Merkel is discussed. A numerical technique for the construction of solutions, based on one of the methods is presented. A study is made of the bifurcations of an equilibrium of general form. 28 refs., 9 figs.

Timing generator of scientific grade CCD camera and its implementation based on FPGA technology

NASA Astrophysics Data System (ADS)

Si, Guoliang; Li, Yunfei; Guo, Yongfei

2010-10-01

The Timing Generator's functions of Scientific Grade CCD Camera is briefly presented: it generates various kinds of impulse sequence for the TDI-CCD, video processor and imaging data output, acting as the synchronous coordinator for time in the CCD imaging unit. The IL-E2TDI-CCD sensor produced by DALSA Co.Ltd. use in the Scientific Grade CCD Camera. Driving schedules of IL-E2 TDI-CCD sensor has been examined in detail, the timing generator has been designed for Scientific Grade CCD Camera. FPGA is chosen as the hardware design platform, schedule generator is described with VHDL. The designed generator has been successfully fulfilled function simulation with EDA software and fitted into XC2VP20-FF1152 (a kind of FPGA products made by XILINX). The experiments indicate that the new method improves the integrated level of the system. The Scientific Grade CCD camera system's high reliability, stability and low power supply are achieved. At the same time, the period of design and experiment is sharply shorted.

Structure function monitor

DOEpatents

McGraw, John T [Placitas, NM; Zimmer, Peter C [Albuquerque, NM; Ackermann, Mark R [Albuquerque, NM

2012-01-24

Methods and apparatus for a structure function monitor provide for generation of parameters characterizing a refractive medium. In an embodiment, a structure function monitor acquires images of a pupil plane and an image plane and, from these images, retrieves the phase over an aperture, unwraps the retrieved phase, and analyzes the unwrapped retrieved phase. In an embodiment, analysis yields atmospheric parameters measured at spatial scales from zero to the diameter of a telescope used to collect light from a source.

A Response Function Approach for Rapid Far-Field Tsunami Forecasting

NASA Astrophysics Data System (ADS)

Tolkova, Elena; Nicolsky, Dmitry; Wang, Dailin

2017-08-01

Predicting tsunami impacts at remote coasts largely relies on tsunami en-route measurements in an open ocean. In this work, these measurements are used to generate instant tsunami predictions in deep water and near the coast. The predictions are generated as a response or a combination of responses to one or more tsunameters, with each response obtained as a convolution of real-time tsunameter measurements and a pre-computed pulse response function (PRF). Practical implementation of this method requires tables of PRFs in a 3D parameter space: earthquake location-tsunameter-forecasted site. Examples of hindcasting the 2010 Chilean and the 2011 Tohoku-Oki tsunamis along the US West Coast and beyond demonstrated high accuracy of the suggested technology in application to trans-Pacific seismically generated tsunamis.

Laser fresnel distance measuring system and method

NASA Technical Reports Server (NTRS)

Campbell, Jonathan W. (Inventor); Lehner, David L. (Inventor); Smalley, Larry L. (Inventor); Smith, legal representative, Molly C. (Inventor); Sanders, Alvin J. (Inventor); Earl, Dennis Duncan (Inventor); Allison, Stephen W. (Inventor); Smith, Kelly L. (Inventor)

2008-01-01

A method and system for determining range to a target are provided. A beam of electromagnetic energy is transmitted through an aperture in an opaque screen such that a portion of the beam passes through the aperture to generate a region of diffraction that varies as a function of distance from the aperture. An imaging system is focused on a target plane in the region of diffraction with the generated image being compared to known diffraction patterns. Each known diffraction pattern has a unique value associated therewith that is indicative of a distance from the aperture. A match between the generated image and at least one of the known diffraction patterns is indicative of a distance between the aperture and target plane.

Method and apparatus for controlling multiple motors

DOEpatents

Jones, Rollin G.; Kortegaard, Bert L.; Jones, David F.

1987-01-01

A method and apparatus are provided for simultaneously controlling a plurality of stepper motors. Addressing circuitry generates address data for each motor in a periodic address sequence. Memory circuits respond to the address data for each motor by accessing a corresponding memory location containing a first operational data set functionally related to a direction for moving the motor, speed data, and rate of speed change. First logic circuits respond to the first data set to generate a motor step command. Second logic circuits respond to the command from the first logic circuits to generate a third data set for replacing the first data set in memory with a current operational motor status, which becomes the first data set when the motor is next addressed.

MSTor: A program for calculating partition functions, free energies, enthalpies, entropies, and heat capacities of complex molecules including torsional anharmonicity

NASA Astrophysics Data System (ADS)

Zheng, Jingjing; Mielke, Steven L.; Clarkson, Kenneth L.; Truhlar, Donald G.

2012-08-01

We present a Fortran program package, MSTor, which calculates partition functions and thermodynamic functions of complex molecules involving multiple torsional motions by the recently proposed MS-T method. This method interpolates between the local harmonic approximation in the low-temperature limit, and the limit of free internal rotation of all torsions at high temperature. The program can also carry out calculations in the multiple-structure local harmonic approximation. The program package also includes six utility codes that can be used as stand-alone programs to calculate reduced moment of inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomains defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Catalogue identifier: AEMF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 77 434 No. of bytes in distributed program, including test data, etc.: 3 264 737 Distribution format: tar.gz Programming language: Fortran 90, C, and Perl Computer: Itasca (HP Linux cluster, each node has two-socket, quad-core 2.8 GHz Intel Xeon X5560 “Nehalem EP” processors), Calhoun (SGI Altix XE 1300 cluster, each node containing two quad-core 2.66 GHz Intel Xeon “Clovertown”-class processors sharing 16 GB of main memory), Koronis (Altix UV 1000 server with 190 6-core Intel Xeon X7542 “Westmere” processors at 2.66 GHz), Elmo (Sun Fire X4600 Linux cluster with AMD Opteron cores), and Mac Pro (two 2.8 GHz Quad-core Intel Xeon processors) Operating system: Linux/Unix/Mac OS RAM: 2 Mbytes Classification: 16.3, 16.12, 23 Nature of problem: Calculation of the partition functions and thermodynamic functions (standard-state energy, enthalpy, entropy, and free energy as functions of temperatures) of complex molecules involving multiple torsional motions. Solution method: The multi-structural approximation with torsional anharmonicity (MS-T). The program also provides results for the multi-structural local harmonic approximation [1]. Restrictions: There is no limit on the number of torsions that can be included in either the Voronoi calculation or the full MS-T calculation. In practice, the range of problems that can be addressed with the present method consists of all multi-torsional problems for which one can afford to calculate all the conformations and their frequencies. Unusual features: The method can be applied to transition states as well as stable molecules. The program package also includes the hull program for the calculation of Voronoi volumes and six utility codes that can be used as stand-alone programs to calculate reduced moment-of-inertia matrices by the method of Kilpatrick and Pitzer, to generate conformational structures, to calculate, either analytically or by Monte Carlo sampling, volumes for torsional subdomain defined by Voronoi tessellation of the conformational subspace, to generate template input files, and to calculate one-dimensional torsional partition functions using the torsional eigenvalue summation method. Additional comments: The program package includes a manual, installation script, and input and output files for a test suite. Running time: There are 24 test runs. The running time of the test runs on a single processor of the Itasca computer is less than 2 seconds. J. Zheng, T. Yu, E. Papajak, I.M. Alecu, S.L. Mielke, D.G. Truhlar, Practical methods for including torsional anharmonicity in thermochemical calculations of complex molecules: The internal-coordinate multi-structural approximation, Phys. Chem. Chem. Phys. 13 (2011) 10885-10907.

Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.

PubMed

Saller, Maximilian A C; Habershon, Scott

2017-07-11

Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.

Differentiation of Inflammation-Responsive Astrocytes from Glial Progenitors Generated from Human Induced Pluripotent Stem Cells.

PubMed

Santos, Renata; Vadodaria, Krishna C; Jaeger, Baptiste N; Mei, Arianna; Lefcochilos-Fogelquist, Sabrina; Mendes, Ana P D; Erikson, Galina; Shokhirev, Maxim; Randolph-Moore, Lynne; Fredlender, Callie; Dave, Sonia; Oefner, Ruth; Fitzpatrick, Conor; Pena, Monique; Barron, Jerika J; Ku, Manching; Denli, Ahmet M; Kerman, Bilal E; Charnay, Patrick; Kelsoe, John R; Marchetto, Maria C; Gage, Fred H

2017-06-06

Astrocyte dysfunction and neuroinflammation are detrimental features in multiple pathologies of the CNS. Therefore, the development of methods that produce functional human astrocytes represents an advance in the study of neurological diseases. Here we report an efficient method for inflammation-responsive astrocyte generation from induced pluripotent stem cells (iPSCs) and embryonic stem cells. This protocol uses an intermediate glial progenitor stage and generates functional astrocytes that show levels of glutamate uptake and calcium activation comparable with those observed in human primary astrocytes. Stimulation of stem cell-derived astrocytes with interleukin-1β or tumor necrosis factor α elicits a strong and rapid pro-inflammatory response. RNA-sequencing transcriptome profiling confirmed that similar gene expression changes occurred in iPSC-derived and primary astrocytes upon stimulation with interleukin-1β. This protocol represents an important tool for modeling in-a-dish neurological diseases with an inflammatory component, allowing for the investigation of the role of diseased astrocytes in neuronal degeneration. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Optimization of Multiple and Multipurpose Reservoir System Operations by Using Matrix Structure (Case Study: Karun and Dez Reservoir Dams)

PubMed Central

Othman, Faridah; Taghieh, Mahmood

2016-01-01

Optimal operation of water resources in multiple and multipurpose reservoirs is very complicated. This is because of the number of dams, each dam’s location (Series and parallel), conflict in objectives and the stochastic nature of the inflow of water in the system. In this paper, performance optimization of the system of Karun and Dez reservoir dams have been studied and investigated with the purposes of hydroelectric energy generation and providing water demand in 6 dams. On the Karun River, 5 dams have been built in the series arrangements, and the Dez dam has been built parallel to those 5 dams. One of the main achievements in this research is the implementation of the structure of production of hydroelectric energy as a function of matrix in MATLAB software. The results show that the role of objective function structure for generating hydroelectric energy in weighting method algorithm is more important than water supply. Nonetheless by implementing ε- constraint method algorithm, we can both increase hydroelectric power generation and supply around 85% of agricultural and industrial demands. PMID:27248152

Method and system for providing precise multi-function modulation

NASA Technical Reports Server (NTRS)

Davarian, Faramaz (Inventor); Sumida, Joe T. (Inventor)

1989-01-01

A method and system is disclosed which provides precise multi-function digitally implementable modulation for a communication system. The invention provides a modulation signal for a communication system in response to an input signal from a data source. A digitized time response is generated from samples of a time domain representation of a spectrum profile of a selected modulation scheme. The invention generates and stores coefficients for each input symbol in accordance with the selected modulation scheme. The output signal is provided by a plurality of samples, each sample being generated by summing the products of a predetermined number of the coefficients and a predetermined number of the samples of the digitized time response. In a specific illustrative implementation, the samples of the output signals are converted to analog signals, filtered and used to modulate a carrier in a conventional manner. The invention is versatile in that it allows for the storage of the digitized time responses and corresponding coefficient lookup table of a number of modulation schemes, any of which may then be selected for use in accordance with the teachings of the invention.

Gröbner Bases and Generation of Difference Schemes for Partial Differential Equations

NASA Astrophysics Data System (ADS)

Gerdt, Vladimir P.; Blinkov, Yuri A.; Mozzhilkin, Vladimir V.

2006-05-01

In this paper we present an algorithmic approach to the generation of fully conservative difference schemes for linear partial differential equations. The approach is based on enlargement of the equations in their integral conservation law form by extra integral relations between unknown functions and their derivatives, and on discretization of the obtained system. The structure of the discrete system depends on numerical approximation methods for the integrals occurring in the enlarged system. As a result of the discretization, a system of linear polynomial difference equations is derived for the unknown functions and their partial derivatives. A difference scheme is constructed by elimination of all the partial derivatives. The elimination can be achieved by selecting a proper elimination ranking and by computing a Gröbner basis of the linear difference ideal generated by the polynomials in the discrete system. For these purposes we use the difference form of Janet-like Gröbner bases and their implementation in Maple. As illustration of the described methods and algorithms, we construct a number of difference schemes for Burgers and Falkowich-Karman equations and discuss their numerical properties.

Parameter estimation of history-dependent leaky integrate-and-fire neurons using maximum-likelihood methods

PubMed Central

Dong, Yi; Mihalas, Stefan; Russell, Alexander; Etienne-Cummings, Ralph; Niebur, Ernst

2012-01-01

When a neuronal spike train is observed, what can we say about the properties of the neuron that generated it? A natural way to answer this question is to make an assumption about the type of neuron, select an appropriate model for this type, and then to choose the model parameters as those that are most likely to generate the observed spike train. This is the maximum likelihood method. If the neuron obeys simple integrate and fire dynamics, Paninski, Pillow, and Simoncelli (2004) showed that its negative log-likelihood function is convex and that its unique global minimum can thus be found by gradient descent techniques. The global minimum property requires independence of spike time intervals. Lack of history dependence is, however, an important constraint that is not fulfilled in many biological neurons which are known to generate a rich repertoire of spiking behaviors that are incompatible with history independence. Therefore, we expanded the integrate and fire model by including one additional variable, a variable threshold (Mihalas & Niebur, 2009) allowing for history-dependent firing patterns. This neuronal model produces a large number of spiking behaviors while still being linear. Linearity is important as it maintains the distribution of the random variables and still allows for maximum likelihood methods to be used. In this study we show that, although convexity of the negative log-likelihood is not guaranteed for this model, the minimum of the negative log-likelihood function yields a good estimate for the model parameters, in particular if the noise level is treated as a free parameter. Furthermore, we show that a nonlinear function minimization method (r-algorithm with space dilation) frequently reaches the global minimum. PMID:21851282

Pyrococcus furiosus strains and methods of using same

DOEpatents

Lipscomb, Gina L; Farkas, Joel Andrew; Adams, Michael W. W.; Westpheling, Janet

2015-01-06

Provided herein are methods for transforming a Pyrococcus furiosus with a polynucleotide. In one embodiment, the method includes contacting a P. furiosus with a polynucleotide under conditions suitable for uptake of the polynucleotide by the P. furiosus, and identifying transformants at a frequency of, for instance, at least 10.sup.3 transformants per microgram DNA. Also provided are isolated Pyrococcus furiosus having the characteristics of Pyrococcus furiosus COM1, and plasmids that include an origin of replication that functions in a Pyrococcus furiosus. The plasmid is stable in a recipient P. furiosus without selection for more than 100 generations and is structurally unchanged after replication in P. furiosus for more than 100 generations.

New Analytical Solution of the Equilibrium Ampere's Law Using the Walker's Method: a Didactic Example

NASA Astrophysics Data System (ADS)

Sousa, A. N. Laurindo; Ojeda-González, A.; Prestes, A.; Klausner, V.; Caritá, L. A.

2018-02-01

This work aims to demonstrate the analytical solution of the Grad-Shafranov (GS) equation or generalized Ampere's law, which is important in the studies of self-consistent 2.5-D solution for current sheet structures. A detailed mathematical development is presented to obtain the generating function as shown by Walker (RSPSA 91, 410, 1915). Therefore, we study the general solution of the GS equation in terms of the Walker's generating function in details without omitting any step. The Walker's generating function g( ζ) is written in a new way as the tangent of an unspecified function K( ζ). In this trend, the general solution of the GS equation is expressed as exp(- 2Ψ) = 4| K '( ζ)|2/cos2[ K( ζ) - K( ζ ∗)]. In order to investigate whether our proposal would simplify the mathematical effort to find new generating functions, we use Harris's solution as a test, in this case K( ζ) = arctan(exp( i ζ)). In summary, one of the article purposes is to present a review of the Harris's solution. In an attempt to find a simplified solution, we propose a new way to write the GS solution using g( ζ) = tan( K( ζ)). We also present a new analytical solution to the equilibrium Ampere's law using g( ζ) = cosh( b ζ), which includes a generalization of the Harris model and presents isolated magnetic islands.

New Analytical Solution of the Equilibrium Ampere's Law Using the Walker's Method: a Didactic Example

NASA Astrophysics Data System (ADS)

Sousa, A. N. Laurindo; Ojeda-González, A.; Prestes, A.; Klausner, V.; Caritá, L. A.

2017-12-01

This work aims to demonstrate the analytical solution of the Grad-Shafranov (GS) equation or generalized Ampere's law, which is important in the studies of self-consistent 2.5-D solution for current sheet structures. A detailed mathematical development is presented to obtain the generating function as shown by Walker (RSPSA 91, 410, 1915). Therefore, we study the general solution of the GS equation in terms of the Walker's generating function in details without omitting any step. The Walker's generating function g(ζ) is written in a new way as the tangent of an unspecified function K(ζ). In this trend, the general solution of the GS equation is expressed as exp(- 2Ψ) = 4|K '(ζ)|2/cos2[K(ζ) - K(ζ ∗)]. In order to investigate whether our proposal would simplify the mathematical effort to find new generating functions, we use Harris's solution as a test, in this case K(ζ) = arctan(exp(i ζ)). In summary, one of the article purposes is to present a review of the Harris's solution. In an attempt to find a simplified solution, we propose a new way to write the GS solution using g(ζ) = tan(K(ζ)). We also present a new analytical solution to the equilibrium Ampere's law using g(ζ) = cosh(b ζ), which includes a generalization of the Harris model and presents isolated magnetic islands.

Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases.

PubMed

Hitomi, Yuki; Tokunaga, Katsushi

2017-01-01

Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

A Novel Polygonal Finite Element Method: Virtual Node Method

NASA Astrophysics Data System (ADS)

Tang, X. H.; Zheng, C.; Zhang, J. H.

2010-05-01

Polygonal finite element method (PFEM), which can construct shape functions on polygonal elements, provides greater flexibility in mesh generation. However, the non-polynomial form of traditional PFEM, such as Wachspress method and Mean Value method, leads to inexact numerical integration. Since the integration technique for non-polynomial functions is immature. To overcome this shortcoming, a great number of integration points have to be used to obtain sufficiently exact results, which increases computational cost. In this paper, a novel polygonal finite element method is proposed and called as virtual node method (VNM). The features of present method can be list as: (1) It is a PFEM with polynomial form. Thereby, Hammer integral and Gauss integral can be naturally used to obtain exact numerical integration; (2) Shape functions of VNM satisfy all the requirements of finite element method. To test the performance of VNM, intensive numerical tests are carried out. It found that, in standard patch test, VNM can achieve significantly better results than Wachspress method and Mean Value method. Moreover, it is observed that VNM can achieve better results than triangular 3-node elements in the accuracy test.

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

A Lagrange multiplier and Hopfield-type barrier function method for the traveling salesman problem.

PubMed

Dang, Chuangyin; Xu, Lei

2002-02-01

A Lagrange multiplier and Hopfield-type barrier function method is proposed for approximating a solution of the traveling salesman problem. The method is derived from applications of Lagrange multipliers and a Hopfield-type barrier function and attempts to produce a solution of high quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the method searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that lower and upper bounds on variables are always satisfied automatically if the step length is a number between zero and one. At each iteration, the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the method converges to a stationary point of the barrier problem without any condition on the objective function. Theoretical and numerical results show that the method seems more effective and efficient than the softassign algorithm.

Application of neural networks with orthogonal activation functions in control of dynamical systems

NASA Astrophysics Data System (ADS)

Nikolić, Saša S.; Antić, Dragan S.; Milojković, Marko T.; Milovanović, Miroslav B.; Perić, Staniša Lj.; Mitić, Darko B.

2016-04-01

In this article, we present a new method for the synthesis of almost and quasi-orthogonal polynomials of arbitrary order. Filters designed on the bases of these functions are generators of generalised quasi-orthogonal signals for which we derived and presented necessary mathematical background. Based on theoretical results, we designed and practically implemented generalised first-order (k = 1) quasi-orthogonal filter and proved its quasi-orthogonality via performed experiments. Designed filters can be applied in many scientific areas. In this article, generated functions were successfully implemented in Nonlinear Auto Regressive eXogenous (NARX) neural network as activation functions. One practical application of the designed orthogonal neural network is demonstrated through the example of control of the complex technical non-linear system - laboratory magnetic levitation system. Obtained results were compared with neural networks with standard activation functions and orthogonal functions of trigonometric shape. The proposed network demonstrated superiority over existing solutions in the sense of system performances.

NERC Policy 10: Measurement of two generation and load balancing IOS

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

Spicer, P.J.; Galow, G.G.

1999-11-01

Policy 10 will describe specific standards and metrics for most of the reliability functions described in the Interconnected Operations Services Working Group (IOS WG) report. The purpose of this paper is to discuss, in detail, the proposed metrics for two generation and load balancing IOSs: Regulation; Load Following. For purposes of this paper, metrics include both measurement and performance evaluation. The measurement methods discussed are included in the current draft of the proposed Policy 10. The performance evaluation method discussed is offered by the authors for consideration by the IOS ITF (Implementation Task Force) for inclusion into Policy 10.

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

NASA Astrophysics Data System (ADS)

Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

The “Silent Dog” Method: Analyzing the Impact of Self-Generated Rules When Teaching Different Computer Chains to Boys with Autism

PubMed Central

Arntzen, Erik; Halstadtro, Lill-Beathe; Halstadtro, Monica

2009-01-01

The purpose of the study was to extend the literature on verbal self-regulation by using the “silent dog” method to evaluate the role of verbal regulation over nonverbal behavior in 2 individuals with autism. Participants were required to talk-aloud while performing functional computer tasks.Then the effects of distracters with increasing demands on target behavior were evaluated as well as whether self-talk emitted by Participant 1 could be used to alter Participant 2's performance. Results suggest that participants' tasks seemed to be under control of self-instructions, and the rules generated from Participants 1's self-talk were effective in teaching computer skills to Participant 2. The silent dog method was useful in evaluating the possible role of self-generated rules in teaching computer skills to participants with autism. PMID:22477428

The "silent dog" method: analyzing the impact of self-generated rules when teaching different computer chains to boys with autism.

PubMed

Arntzen, Erik; Halstadtro, Lill-Beathe; Halstadtro, Monica

2009-01-01

The purpose of the study was to extend the literature on verbal self-regulation by using the "silent dog" method to evaluate the role of verbal regulation over nonverbal behavior in 2 individuals with autism. Participants were required to talk-aloud while performing functional computer tasks.Then the effects of distracters with increasing demands on target behavior were evaluated as well as whether self-talk emitted by Participant 1 could be used to alter Participant 2's performance. Results suggest that participants' tasks seemed to be under control of self-instructions, and the rules generated from Participants 1's self-talk were effective in teaching computer skills to Participant 2. The silent dog method was useful in evaluating the possible role of self-generated rules in teaching computer skills to participants with autism.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

PubMed

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

PubMed Central

Martin, Mario; Contreras-Hernández, Enrique; Béjar, Javier; Esposito, Gennaro; Chávez, Diógenes; Glusman, Silvio; Cortés, Ulises; Rudomin, Pablo

2015-01-01

Previous studies aimed to disclose the functional organization of the neuronal networks involved in the generation of the spontaneous cord dorsum potentials (CDPs) generated in the lumbosacral spinal segments used predetermined templates to select specific classes of spontaneous CDPs. Since this procedure was time consuming and required continuous supervision, it was limited to the analysis of two specific types of CDPs (negative CDPs and negative positive CDPs), thus excluding potentials that may reflect activation of other neuronal networks of presumed functional relevance. We now present a novel procedure based in machine learning that allows the efficient and unbiased selection of a variety of spontaneous CDPs with different shapes and amplitudes. The reliability and performance of the present method is evaluated by analyzing the effects on the probabilities of generation of different classes of spontaneous CDPs induced by the intradermic injection of small amounts of capsaicin in the anesthetized cat, a procedure known to induce a state of central sensitization leading to allodynia and hyperalgesia. The results obtained with the selection method presently described allowed detection of spontaneous CDPs with specific shapes and amplitudes that are assumed to represent the activation of functionally coupled sets of dorsal horn neurones that acquire different, structured configurations in response to nociceptive stimuli. These changes are considered as responses tending to adequate transmission of sensory information to specific functional requirements as part of homeostatic adjustments. PMID:26379540

Custom implant design for large cranial defects.

PubMed

Marreiros, Filipe M M; Heuzé, Y; Verius, M; Unterhofer, C; Freysinger, W; Recheis, W

2016-12-01

The aim of this work was to introduce a computer-aided design (CAD) tool that enables the design of large skull defect (>100 [Formula: see text]) implants. Functional and aesthetically correct custom implants are extremely important for patients with large cranial defects. For these cases, preoperative fabrication of implants is recommended to avoid problems of donor site morbidity, sufficiency of donor material and quality. Finally, crafting the correct shape is a non-trivial task increasingly complicated by defect size. We present a CAD tool to design such implants for the neurocranium. A combination of geometric morphometrics and radial basis functions, namely thin-plate splines, allows semiautomatic implant generation. The method uses symmetry and the best fitting shape to estimate missing data directly within the radiologic volume data. In addition, this approach delivers correct implant fitting via a boundary fitting approach. This method generates a smooth implant surface, free of sharp edges that follows the main contours of the boundary, enabling accurate implant placement in the defect site intraoperatively. The present approach is evaluated and compared to existing methods. A mean error of 89.29 % (72.64-100 %) missing landmarks with an error less or equal to 1 mm was obtained. In conclusion, the results show that our CAD tool can generate patient-specific implants with high accuracy.

Automatically-generated rectal dose constraints in intensity-modulated radiation therapy for prostate cancer

NASA Astrophysics Data System (ADS)

Hwang, Taejin; Kim, Yong Nam; Kim, Soo Kon; Kang, Sei-Kwon; Cheong, Kwang-Ho; Park, Soah; Yoon, Jai-Woong; Han, Taejin; Kim, Haeyoung; Lee, Meyeon; Kim, Kyoung-Joo; Bae, Hoonsik; Suh, Tae-Suk

2015-06-01

The dose constraint during prostate intensity-modulated radiation therapy (IMRT) optimization should be patient-specific for better rectum sparing. The aims of this study are to suggest a novel method for automatically generating a patient-specific dose constraint by using an experience-based dose volume histogram (DVH) of the rectum and to evaluate the potential of such a dose constraint qualitatively. The normal tissue complication probabilities (NTCPs) of the rectum with respect to V %ratio in our study were divided into three groups, where V %ratio was defined as the percent ratio of the rectal volume overlapping the planning target volume (PTV) to the rectal volume: (1) the rectal NTCPs in the previous study (clinical data), (2) those statistically generated by using the standard normal distribution (calculated data), and (3) those generated by combining the calculated data and the clinical data (mixed data). In the calculated data, a random number whose mean value was on the fitted curve described in the clinical data and whose standard deviation was 1% was generated by using the `randn' function in the MATLAB program and was used. For each group, we validated whether the probability density function (PDF) of the rectal NTCP could be automatically generated with the density estimation method by using a Gaussian kernel. The results revealed that the rectal NTCP probability increased in proportion to V %ratio , that the predictive rectal NTCP was patient-specific, and that the starting point of IMRT optimization for the given patient might be different. The PDF of the rectal NTCP was obtained automatically for each group except that the smoothness of the probability distribution increased with increasing number of data and with increasing window width. We showed that during the prostate IMRT optimization, the patient-specific dose constraints could be automatically generated and that our method could reduce the IMRT optimization time as well as maintain the IMRT plan quality.

A Robust Deconvolution Method based on Transdimensional Hierarchical Bayesian Inference

NASA Astrophysics Data System (ADS)

Kolb, J.; Lekic, V.

2012-12-01

Analysis of P-S and S-P conversions allows us to map receiver side crustal and lithospheric structure. This analysis often involves deconvolution of the parent wave field from the scattered wave field as a means of suppressing source-side complexity. A variety of deconvolution techniques exist including damped spectral division, Wiener filtering, iterative time-domain deconvolution, and the multitaper method. All of these techniques require estimates of noise characteristics as input parameters. We present a deconvolution method based on transdimensional Hierarchical Bayesian inference in which both noise magnitude and noise correlation are used as parameters in calculating the likelihood probability distribution. Because the noise for P-S and S-P conversion analysis in terms of receiver functions is a combination of both background noise - which is relatively easy to characterize - and signal-generated noise - which is much more difficult to quantify - we treat measurement errors as an known quantity, characterized by a probability density function whose mean and variance are model parameters. This transdimensional Hierarchical Bayesian approach has been successfully used previously in the inversion of receiver functions in terms of shear and compressional wave speeds of an unknown number of layers [1]. In our method we used a Markov chain Monte Carlo (MCMC) algorithm to find the receiver function that best fits the data while accurately assessing the noise parameters. In order to parameterize the receiver function we model the receiver function as an unknown number of Gaussians of unknown amplitude and width. The algorithm takes multiple steps before calculating the acceptance probability of a new model, in order to avoid getting trapped in local misfit minima. Using both observed and synthetic data, we show that the MCMC deconvolution method can accurately obtain a receiver function as well as an estimate of the noise parameters given the parent and daughter components. Furthermore, we demonstrate that this new approach is far less susceptible to generating spurious features even at high noise levels. Finally, the method yields not only the most-likely receiver function, but also quantifies its full uncertainty. [1] Bodin, T., M. Sambridge, H. Tkalčić, P. Arroucau, K. Gallagher, and N. Rawlinson (2012), Transdimensional inversion of receiver functions and surface wave dispersion, J. Geophys. Res., 117, B02301

Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT)

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

Men Chunhua; Romeijn, H. Edwin; Jia Xun

2010-11-15

Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequentialmore » way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. Results: The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. Conclusions: The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.« less

Reprint of "Cortical Reorganization of Language Functioning Following Perinatal Left MCA Stroke" [Brain and Language 105 (2008) 99-111

ERIC Educational Resources Information Center

Tillema, Jan-Mendelt; Byars, Anna W.; Jacola, Lisa M.; Schapiro, Mark B.; Schmithorst, Vince J.; Szaflarski, Jerzy P.; Holland, Scott K.

2008-01-01

Objective: Functional MRI was used to determine differences in patterns of cortical activation between children who suffered perinatal left middle cerebral artery (MCA) stroke and healthy children performing a silent verb generation task. Methods: Ten children with prior perinatal left MCA stroke (age 6-16 years) and ten healthy age matched…

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.

Enhanced H2O2 Production at Reductive Potentials from Oxidized Boron-Doped Ultrananocrystalline Diamond Electrodes.

PubMed

Thostenson, James O; Ngaboyamahina, Edgard; Sellgren, Katelyn L; Hawkins, Brian T; Piascik, Jeffrey R; Klem, Ethan J D; Parker, Charles B; Deshusses, Marc A; Stoner, Brian R; Glass, Jeffrey T

2017-05-17

This work investigates the surface chemistry of H 2 O 2 generation on a boron-doped ultrananocrystalline diamond (BD-UNCD) electrode. It is motivated by the need to efficiently disinfect liquid waste in resource constrained environments with limited electrical power. X-ray photoelectron spectroscopy was used to identify functional groups on the BD-UNCD electrode surfaces while the electrochemical potentials of generation for these functional groups were determined via cyclic voltammetry, chronocoulometry, and chronoamperometry. A colorimetric technique was employed to determine the concentration and current efficiency of H 2 O 2 produced at different potentials. Results showed that preanodization of an as-grown BD-UNCD electrode can enhance the production of H 2 O 2 in a strong acidic environment (pH 0.5) at reductive potentials. It is proposed that the electrogeneration of functional groups at oxidative potentials during preanodization allows for an increased current density during the successive electrolysis at reductive potentials that correlates to an enhanced production of H 2 O 2 . Through potential cycling methods, and by optimizing the applied potentials and duty cycle, the functional groups can be stabilized allowing continuous production of H 2 O 2 more efficiently compared to static potential methods.

Processing data base information having nonwhite noise

DOEpatents

Gross, Kenneth C.; Morreale, Patricia

1995-01-01

A method and system for processing a set of data from an industrial process and/or a sensor. The method and system can include processing data from either real or calculated data related to an industrial process variable. One of the data sets can be an artificial signal data set generated by an autoregressive moving average technique. After obtaining two data sets associated with one physical variable, a difference function data set is obtained by determining the arithmetic difference between the two pairs of data sets over time. A frequency domain transformation is made of the difference function data set to obtain Fourier modes describing a composite function data set. A residual function data set is obtained by subtracting the composite function data set from the difference function data set and the residual function data set (free of nonwhite noise) is analyzed by a statistical probability ratio test to provide a validated data base.

Postpolymerization Modifications of Alkene-Functional Polycarbonates for the Development of Advanced Materials Biomaterials.

PubMed

Thomas, Anthony W; Dove, Andrew P

2016-12-01

Functional aliphatic polycarbonates have attracted significant attention as materials for use as biomedical polymers in recent years. The incorporation of pendent functionality offers a facile method of modifying materials postpolymerization, thus enabling functionalities not compatible with ring-opening polymerization (ROP) to be introduced into the polymer. In particular, polycarbonates bearing alkene-terminated functional groups have generated considerable interest as a result of their ease of synthesis, and the wide range of materials that can be obtained by performing simple postpolymerization modifications on this functionality, for example, through radical thiol-ene addition, Michael addition, and epoxidation reactions. This review presents an in-depth appraisal of the methods used to modify alkene-functional polycarbonates postpolymerization, and the diversity of practical applications for which these materials and their derivatives have been used. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neural modeling and functional neuroimaging.

PubMed

Horwitz, B; Sporns, O

1994-01-01

Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America. Copyright © 1994 Wiley-Liss, Inc.

Glycofunctionalization of Poly(lactic- co-glycolic acid) Polymers: Building Blocks for the Generation of Defined Sugar-Coated Nanoparticles.

PubMed

Palmioli, Alessandro; La Ferla, Barbara

2018-06-15

A set of poly(lactic- co-glycolic acid) polymers functionalized with different monosaccharides as well as glycodendrimers and surface-decorated nanoparticles (NPs) were synthesized and characterized. The functionalization of the polymer was carried out through amide bond formation with amino-modified sugar monomers and through a biocompatible chemoselective method exploiting the reducing end of a free sugar. The assemblage of the NPs adopting a nanoprecipitation method was straightforward and allowed the preparation of sugars/sugar dendrimer coated NPs.

MODERATOR ELEMENTS FOR UNIFORM POWER NUCLEAR REACTOR

DOEpatents

Balent, R.

1963-03-12

This patent describes a method of obtaining a flatter flux and more uniform power generation across the core of a nuclear reactor. The method comprises using moderator elements having differing moderating strength. The elements have an increasing amount of the better moderating material as a function of radial and/or axial distance from the reactor core center. (AEC)

Reduction of shock induced noise in imperfectly expanded supersonic jets using convex optimization

NASA Astrophysics Data System (ADS)

Adhikari, Sam

2007-11-01

Imperfectly expanded jets generate screech noise. The imbalance between the backpressure and the exit pressure of the imperfectly expanded jets produce shock cells and expansion or compression waves from the nozzle. The instability waves and the shock cells interact to generate the screech sound. The mathematical model consists of cylindrical coordinate based full Navier-Stokes equations and large-eddy-simulation turbulence modeling. Analytical and computational analysis of the three-dimensional helical effects provide a model that relates several parameters with shock cell patterns, screech frequency and distribution of shock generation locations. Convex optimization techniques minimize the shock cell patterns and the instability waves. The objective functions are (convex) quadratic and the constraint functions are affine. In the quadratic optimization programs, minimization of the quadratic functions over a set of polyhedrons provides the optimal result. Various industry standard methods like regression analysis, distance between polyhedra, bounding variance, Markowitz optimization, and second order cone programming is used for Quadratic Optimization.

Non-homologous end joining-mediated functional marker selection for DNA cloning in the yeast Kluyveromyces marxianus.

PubMed

Hoshida, Hisashi; Murakami, Nobutada; Suzuki, Ayako; Tamura, Ryoko; Asakawa, Jun; Abdel-Banat, Babiker M A; Nonklang, Sanom; Nakamura, Mikiko; Akada, Rinji

2014-01-01

The cloning of DNA fragments into vectors or host genomes has traditionally been performed using Escherichia coli with restriction enzymes and DNA ligase or homologous recombination-based reactions. We report here a novel DNA cloning method that does not require DNA end processing or homologous recombination, but that ensures highly accurate cloning. The method exploits the efficient non-homologous end-joining (NHEJ) activity of the yeast Kluyveromyces marxianus and consists of a novel functional marker selection system. First, to demonstrate the applicability of NHEJ to DNA cloning, a C-terminal-truncated non-functional ura3 selection marker and the truncated region were PCR-amplified separately, mixed and directly used for the transformation. URA3(+) transformants appeared on the selection plates, indicating that the two DNA fragments were correctly joined by NHEJ to generate a functional URA3 gene that had inserted into the yeast chromosome. To develop the cloning system, the shortest URA3 C-terminal encoding sequence that could restore the function of a truncated non-functional ura3 was determined by deletion analysis, and was included in the primers to amplify target DNAs for cloning. Transformation with PCR-amplified target DNAs and C-terminal truncated ura3 produced numerous transformant colonies, in which a functional URA3 gene was generated and was integrated into the chromosome with the target DNAs. Several K. marxianus circular plasmids with different selection markers were also developed for NHEJ-based cloning and recombinant DNA construction. The one-step DNA cloning method developed here is a relatively simple and reliable procedure among the DNA cloning systems developed to date. Copyright © 2013 John Wiley & Sons, Ltd.

Fuel management optimization using genetic algorithms and code independence

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

DeChaine, M.D.; Feltus, M.A.

1994-12-31

Fuel management optimization is a hard problem for traditional optimization techniques. Loading pattern optimization is a large combinatorial problem without analytical derivative information. Therefore, methods designed for continuous functions, such as linear programming, do not always work well. Genetic algorithms (GAs) address these problems and, therefore, appear ideal for fuel management optimization. They do not require derivative information and work well with combinatorial. functions. The GAs are a stochastic method based on concepts from biological genetics. They take a group of candidate solutions, called the population, and use selection, crossover, and mutation operators to create the next generation of bettermore » solutions. The selection operator is a {open_quotes}survival-of-the-fittest{close_quotes} operation and chooses the solutions for the next generation. The crossover operator is analogous to biological mating, where children inherit a mixture of traits from their parents, and the mutation operator makes small random changes to the solutions.« less

A 3D printing method for droplet-based biomolecular materials

NASA Astrophysics Data System (ADS)

Challita, Elio J.; Najem, Joseph S.; Freeman, Eric C.; Leo, Donald J.

2017-04-01

The field of developing biomolecular droplet-based materials using a bottom-up approach remains underexplored. Producing tissue-like materials, from entirely synthetic components, presents an innovative method to reconstruct the functions of life within artificial materials. Aqueous droplets, encased with lipid monolayers, may be linked via bilayer interfaces to make up structures that resemble biological tissues. Here we present the design and development of an easy-to-build 3D printer for the fabrication of tissue-like biomolecular materials from cell-sized aqueous droplets. The droplets are generated using a snap off technique, capable of generating 30 droplets per minute. The printed network of droplets may also be functionalized with various types of membrane proteins to achieve desired engineering applications like sensing and actuation, or to mimic electrical communication in biological systems. Voltage sensitive channels are introduced into selected droplets to create a conductive path with the material in the presence of an external field.

Model predictive control system and method for integrated gasification combined cycle power generation

DOEpatents

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Drift-wave turbulence and zonal flow generation.

PubMed

Balescu, R

2003-10-01

Drift-wave turbulence in a plasma is analyzed on the basis of the wave Liouville equation, describing the evolution of the distribution function of wave packets (quasiparticles) characterized by position x and wave vector k. A closed kinetic equation is derived for the ensemble-averaged part of this function by the methods of nonequilibrium statistical mechanics. It has the form of a non-Markovian advection-diffusion equation describing coupled diffusion processes in x and k spaces. General forms of the diffusion coefficients are obtained in terms of Lagrangian velocity correlations. The latter are calculated in the decorrelation trajectory approximation, a method recently developed for an accurate measure of the important trapping phenomena of particles in the rugged electrostatic potential. The analysis of individual decorrelation trajectories provides an illustration of the fragmentation of drift-wave structures in the radial direction and the generation of long-wavelength structures in the poloidal direction that are identified as zonal flows.

Inkjet Printing of Viscous Monodisperse Microdroplets by Laser-Induced Flow Focusing

NASA Astrophysics Data System (ADS)

Delrot, Paul; Modestino, Miguel A.; Gallaire, François; Psaltis, Demetri; Moser, Christophe

2016-08-01

The on-demand generation of viscous microdroplets to print functional or biological materials remains challenging using conventional inkjet-printing methods, mainly due to aggregation and clogging issues. In an effort to overcome these limitations, we implement a jetting method to print viscous microdroplets by laser-induced shockwaves. We experimentally investigate the dependence of the jetting regimes and the droplet size on the laser-pulse energy and on the inks' physical properties. The range of printable liquids with our device is significantly extended compared to conventional inkjet printers's performances. In addition, the laser-induced flow-focusing phenomenon allows us to controllably generate viscous microdroplets up to 210 mPa s with a diameter smaller than the nozzle from which they originated (200 μ m ). Inks containing proteins are printed without altering their functional properties, thus demonstrating that this jetting technique is potentially suitable for bioprinting.

Fitting psychometric functions using a fixed-slope parameter: an advanced alternative for estimating odor thresholds with data generated by ASTM E679.

PubMed

Peng, Mei; Jaeger, Sara R; Hautus, Michael J

2014-03-01

Psychometric functions are predominately used for estimating detection thresholds in vision and audition. However, the requirement of large data quantities for fitting psychometric functions (>30 replications) reduces their suitability in olfactory studies because olfactory response data are often limited (<4 replications) due to the susceptibility of human olfactory receptors to fatigue and adaptation. This article introduces a new method for fitting individual-judge psychometric functions to olfactory data obtained using the current standard protocol-American Society for Testing and Materials (ASTM) E679. The slope parameter of the individual-judge psychometric function is fixed to be the same as that of the group function; the same-shaped symmetrical sigmoid function is fitted only using the intercept. This study evaluated the proposed method by comparing it with 2 available methods. Comparison to conventional psychometric functions (fitted slope and intercept) indicated that the assumption of a fixed slope did not compromise precision of the threshold estimates. No systematic difference was obtained between the proposed method and the ASTM method in terms of group threshold estimates or threshold distributions, but there were changes in the rank, by threshold, of judges in the group. Overall, the fixed-slope psychometric function is recommended for obtaining relatively reliable individual threshold estimates when the quantity of data is limited.

Assessment of the MPACT Resonance Data Generation Procedure

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

Kim, Kang Seog; Williams, Mark L.

Currently, heterogeneous models are being used to generate resonance self-shielded cross-section tables as a function of background cross sections for important nuclides such as 235U and 238U by performing the CENTRM (Continuous Energy Transport Model) slowing down calculation with the MOC (Method of Characteristics) spatial discretization and ESSM (Embedded Self-Shielding Method) calculations to obtain background cross sections. And then the resonance self-shielded cross section tables are converted into subgroup data which are to be used in estimating problem-dependent self-shielded cross sections in MPACT (Michigan Parallel Characteristics Transport Code). Although this procedure has been developed and thus resonance data have beenmore » generated and validated by benchmark calculations, assessment has never been performed to review if the resonance data are properly generated by the procedure and utilized in MPACT. This study focuses on assessing the procedure and a proper use in MPACT.« less

Method and apparatus for loss of control inhibitor systems

NASA Technical Reports Server (NTRS)

A'Harrah, Ralph C. (Inventor)

2007-01-01

Active and adaptive systems and methods to prevent loss of control incidents by providing tactile feedback to a vehicle operator are disclosed. According to the present invention, an operator gives a control input to an inceptor. An inceptor sensor measures an inceptor input value of the control input. The inceptor input is used as an input to a Steady-State Inceptor Input/Effector Output Model that models the vehicle control system design. A desired effector output from the inceptor input is generated from the model. The desired effector output is compared to an actual effector output to get a distortion metric. A feedback force is generated as a function of the distortion metric. The feedback force is used as an input to a feedback force generator which generates a loss of control inhibitor system (LOCIS) force back to the inceptor. The LOCIS force is felt by the operator through the inceptor.

Generation of nondiffracting Bessel beam using digital micromirror device.

PubMed

Gong, Lei; Ren, Yu-Xuan; Xue, Guo-Sheng; Wang, Qian-Chang; Zhou, Jin-Hua; Zhong, Min-Cheng; Wang, Zi-Qiang; Li, Yin-Mei

2013-07-01

We experimentally demonstrated Bessel-like beams utilizing digital micromirror device (DMD). DMD with images imitating the equivalent axicon can shape the collimated Gaussian beam into Bessel beam. We reconstructed the 3D spatial field of the generated beam through a stack of measured cross-sectional images. The output beams have the profile of Bessel function after intensity modulation, and the beams extend at least 50 mm while the lateral dimension of the spot remains nearly invariant. Furthermore, the self-healing property has also been investigated, and all the experimental results agree well with simulated results numerically calculated through beam propagation method. Our observations demonstrate that the DMD offers a simple and efficient method to generate Bessel beams with distinct nondiffracting and self-reconstruction behaviors. The generated Bessel beams will potentially expand the applications to the optical manipulation and high-resolution fluorescence imaging owing to the unique nondiffracting property.

Accelerated computer generated holography using sparse bases in the STFT domain.

PubMed

Blinder, David; Schelkens, Peter

2018-01-22

Computer-generated holography at high resolutions is a computationally intensive task. Efficient algorithms are needed to generate holograms at acceptable speeds, especially for real-time and interactive applications such as holographic displays. We propose a novel technique to generate holograms using a sparse basis representation in the short-time Fourier space combined with a wavefront-recording plane placed in the middle of the 3D object. By computing the point spread functions in the transform domain, we update only a small subset of the precomputed largest-magnitude coefficients to significantly accelerate the algorithm over conventional look-up table methods. We implement the algorithm on a GPU, and report a speedup factor of over 30. We show that this transform is superior over wavelet-based approaches, and show quantitative and qualitative improvements over the state-of-the-art WASABI method; we report accuracy gains of 2dB PSNR, as well improved view preservation.

Fast dictionary generation and searching for magnetic resonance fingerprinting.

PubMed

Jun Xie; Mengye Lyu; Jian Zhang; Hui, Edward S; Wu, Ed X; Ze Wang

2017-07-01

A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi-parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

PubMed

Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

2016-01-01

This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

Partition functions for heterotic WZW conformal field theories

NASA Astrophysics Data System (ADS)

Gannon, Terry

1993-08-01

Thus far in the search for, and classification of, "physical" modular invariant partition functions ΣN LRχ Lχ R∗ the attention has been focused on the symmetric case where the holomorphic and anti-holomorphic sectors, and hence the characters χLand χR, are associated with the same Kac-Moody algebras ĝL = ĝR and levels κ L = κ R. In this paper we consider the more general possibility where ( ĝL, κ L) may not equal ( ĝR, κ R). We discuss which choices of algebras and levels may correspond to well-defined conformal field theories, we find the "smallest" such heterotic (i.e. asymmetric) partition functions, and we give a method, generalizing the Roberts-Terao-Warner lattice method, for explicitly constructing many other modular invariants. We conclude the paper by proving that this new lattice method will succeed in generating all the heterotic partition functions, for all choices of algebras and levels.

Geometry of quantum Hall states: Gravitational anomaly and transport coefficients

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

Can, Tankut, E-mail: tcan@scgp.stonybrook.edu; Laskin, Michael; Wiegmann, Paul B.

2015-11-15

We show that universal transport coefficients of the fractional quantum Hall effect (FQHE) can be understood as a response to variations of spatial geometry. Some transport properties are essentially governed by the gravitational anomaly. We develop a general method to compute correlation functions of FQH states in a curved space, where local transformation properties of these states are examined through local geometric variations. We introduce the notion of a generating functional and relate it to geometric invariant functionals recently studied in geometry. We develop two complementary methods to study the geometry of the FQHE. One method is based on iteratingmore » a Ward identity, while the other is based on a field theoretical formulation of the FQHE through a path integral formalism.« less

Communication: Extended multi-state complete active space second-order perturbation theory: Energy and nuclear gradients

NASA Astrophysics Data System (ADS)

Shiozaki, Toru; Győrffy, Werner; Celani, Paolo; Werner, Hans-Joachim

2011-08-01

The extended multireference quasi-degenerate perturbation theory, proposed by Granovsky [J. Chem. Phys. 134, 214113 (2011)], is combined with internally contracted multi-state complete active space second-order perturbation theory (XMS-CASPT2). The first-order wavefunction is expanded in terms of the union of internally contracted basis functions generated from all the reference functions, which guarantees invariance of the theory with respect to unitary rotations of the reference functions. The method yields improved potentials in the vicinity of avoided crossings and conical intersections. The theory for computing nuclear energy gradients for MS-CASPT2 and XMS-CASPT2 is also presented and the first implementation of these gradient methods is reported. A number of illustrative applications of the new methods are presented.

A new approach for describing glass transition kinetics.

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

Vasin, N. M.; Shchelkachev, M. G.; Vinokur, V. M.

2010-04-01

We use a functional integral technique generalizing the Keldysh diagram technique to describe glass transition kinetics. We show that the Keldysh functional approach takes the dynamical determinant arising in the glass dynamics into account exactly and generalizes the traditional approach based on using the supersymmetric dynamic generating functional method. In contrast to the supersymmetric method, this approach allows avoiding additional Grassmannian fields and tracking the violation of the fluctuation-dissipation theorem explicitly. We use this method to describe the dynamics of an Edwards-Anderson soft spin-glass-type model near the paramagnet-glass transition. We show that a Vogel-Fulcher-type dynamics arises in the fluctuation regionmore » only if the fluctuation-dissipation theorem is violated in the process of dynamical renormalization of the Keldysh action in the replica space.« less

Explicit polarization (X-Pol) potential using ab initio molecular orbital theory and density functional theory.

PubMed

Song, Lingchun; Han, Jaebeom; Lin, Yen-lin; Xie, Wangshen; Gao, Jiali

2009-10-29

The explicit polarization (X-Pol) method has been examined using ab initio molecular orbital theory and density functional theory. The X-Pol potential was designed to provide a novel theoretical framework for developing next-generation force fields for biomolecular simulations. Importantly, the X-Pol potential is a general method, which can be employed with any level of electronic structure theory. The present study illustrates the implementation of the X-Pol method using ab initio Hartree-Fock theory and hybrid density functional theory. The computational results are illustrated by considering a set of bimolecular complexes of small organic molecules and ions with water. The computed interaction energies and hydrogen bond geometries are in good accord with CCSD(T) calculations and B3LYP/aug-cc-pVDZ optimizations.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

PubMed

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

The time-frequency method of signal analysis in internal combustion engine diagnostics

NASA Astrophysics Data System (ADS)

Avramchuk, V. S.; Kazmin, V. P.; Faerman, V. A.; Le, V. T.

2017-01-01

The paper presents the results of the study of applicability of time-frequency correlation functions to solving the problems of internal combustion engine fault diagnostics. The proposed methods are theoretically justified and experimentally tested. In particular, the method’s applicability is illustrated by the example of specially generated signals that simulate the vibration of an engine both during the normal operation and in the case of a malfunction in the system supplying fuel to the cylinders. This method was confirmed during an experiment with an automobile internal combustion engine. The study offers the main findings of the simulation and the experiment and highlights certain characteristic features of time-frequency autocorrelation functions that allow one to identify malfunctions in an engine’s cylinder. The possibility in principle of using time-frequency correlation functions in function testing of the internal combustion engine is demonstrated. The paper’s conclusion proposes further research directions including the application of the method to diagnosing automobile gearboxes.

Pathways to Sustainability: 8-year follow-up from the PROSPER Project

PubMed Central

Welsh, Janet A.; Chilenski, Sarah M.; Johnson, Lesley; Greenberg, Mark T.; Spoth, Richard L.

2016-01-01

The large-scale dissemination of evidence-based practices (EBPs) is often hindered by problems with sustaining initiatives past a period of initial grant funding. Communities often have difficulty generating resources needed to sustain and grow their initiatives, resulting in limited public health impact. The PROSPER project, initiated in 2001, provided community coalitions with intensive technical assistance around marketing, communications, and revenue generating strategies. Past reports from PROSPER have indicated that these coalitions were successful with sustaining their programming, and that sustainability could be predicted by early aspects of team functioning and leadership. The current study examines financial sustainability eight years following the discontinuation of grant funding, with an emphasis on sources of revenue and the relationships between revenue generation, team functioning, and EBP participation. This study used four waves of data related to resource generation collected between 2004-2010 by PROSPER teams in Iowa and Pennsylvania. Teams reported annually on the amount and sources of funding procured, as well as annual reports of team functioning and leadership and annual reports of EBP participation by youth and parents. Data revealed that teams' overall revenue generation increased over time. There was significant variation in success with revenue generation at both the community level and across the two states. Teams accessed a variety of sources. Cash revenue generation was positively and predictively associated with EBP participation, but relationships with team functioning and leadership ratings varied significantly by state. State level differences in in-kind support were also apparent. The results indicated that there are different pathways to sustainability, and that no one method works for all teams. The presence of state level infrastructures available to support prevention appeared to account for significant differences in sustainability success between Pennsylvania and Iowa. PMID:26892601

Pathways to Sustainability: 8-Year Follow-Up From the PROSPER Project.

PubMed

Welsh, Janet A; Chilenski, Sarah M; Johnson, Lesley; Greenberg, Mark T; Spoth, Richard L

2016-06-01

The large-scale dissemination of evidence-based practices (EBPs) is often hindered by problems with sustaining initiatives past a period of initial grant funding. Communities often have difficulty generating resources needed to sustain and grow their initiatives, resulting in limited public health impact. The PROSPER project, initiated in 2001, provided community coalitions with intensive technical assistance around marketing, communications, and revenue generating strategies. Past reports from PROSPER have indicated that these coalitions were successful with sustaining their programming, and that sustainability could be predicted by early aspects of team functioning and leadership. The current study examines financial sustainability 8 years following the discontinuation of grant funding, with an emphasis on sources of revenue and the relationships between revenue generation, team functioning, and EBP participation. This study used four waves of data related to resource generation collected between 2004 and 2010 by PROSPER teams in Iowa and Pennsylvania. Teams reported annually on the amount and sources of funding procured, as well as annual reports of team functioning and leadership and annual reports of EBP participation by youth and parents. Data revealed that teams' overall revenue generation increased over time. There was significant variation in success with revenue generation at both the community level and across the two states. Teams accessed a variety of sources. Cash revenue generation was positively and predictively associated with EBP participation, but relationships with team functioning and leadership ratings varied significantly by state. State level differences in in-kind support were also apparent. The results indicated that there are different pathways to sustainability, and that no one method works for all teams. The presence of state level infrastructures available to support prevention appeared to account for significant differences in sustainability success between Pennsylvania and Iowa.

Conditional knockout of retinal determination genes in differentiating cells in Drosophila.

PubMed

Jin, Meng; Eblimit, Aiden; Pulikkathara, Merlyn; Corr, Stuart; Chen, Rui; Mardon, Graeme

2016-08-01

Conditional gene knockout in postmitotic cells is a valuable technique which allows the study of gene function with spatiotemporal control. Surprisingly, in contrast to its long-term and extensive use in mouse studies, this technology is lacking in Drosophila. Here, we use a novel method for generating complete loss of eyes absent (eya) or sine oculis (so) function in postmitotic cells posterior to the morphogenetic furrow (MF). Specifically, genomic rescue constructs with flippase recognition target (FRT) sequences flanking essential exons are used to generate conditional null alleles. By removing gene function in differentiating cells, we show that eya and so are dispensable for larval photoreceptor differentiation, but are required for differentiation during pupal development. Both eya and so are necessary for photoreceptor survival and the apoptosis caused by loss of eya or so function is likely a secondary consequence of inappropriate differentiation. We also confirm their requirement for cone cell development and reveal a novel role in interommatidial bristle (IOB) formation. In addition, so is required for normal eye disc morphology. This is the first report of a knockout method to study eya and so function in postmitotic cells. This technology will open the door to a large array of new functional studies in virtually any tissue and at any stage of development or in adults. © 2016 Federation of European Biochemical Societies.

Identification and tracking of hairpin vortex auto-generation in turbulent wall-bounded flow

NASA Astrophysics Data System (ADS)

Huang, Yangzi; Green, Melissa

2016-11-01

Hairpin vortices have been widely accepted as component structures of turbulent boundary layers. Their properties (size, vorticity, energy) and dynamic phenomena (origin, growth, breakdown) have been shown to correlate to the complex, multi-scaled turbulent motions observed in both experiments and simulations. As established in the literature, the passage of a hairpin vortex creates a wall-normal ejection of fluid, which encounters the high-speed freestream resulting in near-wall shear and increased drag. A previously generated simulation of an isolated hairpin vortex is used to study the auto-generation of a secondary vortex structure. Eulerian methods such as the Q criterion and Γ2 function, as well as Lagrangian methods are used to visualize the three-dimensional hairpin vortices and the auto-generation process. The circulation development and wall-normal location of both primary and secondary hairpin heads are studied to determine if there is a correlation between the strength and height of the primary hairpin vortex with the secondary hairpin vortex auto-generation.

Scalable Generation of Universal Platelets from Human Induced Pluripotent Stem Cells

PubMed Central

Feng, Qiang; Shabrani, Namrata; Thon, Jonathan N.; Huo, Hongguang; Thiel, Austin; Machlus, Kellie R.; Kim, Kyungho; Brooks, Julie; Li, Feng; Luo, Chenmei; Kimbrel, Erin A.; Wang, Jiwu; Kim, Kwang-Soo; Italiano, Joseph; Cho, Jaehyung; Lu, Shi-Jiang; Lanza, Robert

2014-01-01

Summary Human induced pluripotent stem cells (iPSCs) provide a potentially replenishable source for the production of transfusable platelets. Here, we describe a method to generate megakaryocytes (MKs) and functional platelets from iPSCs in a scalable manner under serum/feeder-free conditions. The method also permits the cryopreservation of MK progenitors, enabling a rapid “surge” capacity when large numbers of platelets are needed. Ultrastructural/morphological analyses show no major differences between iPSC platelets and human blood platelets. iPSC platelets form aggregates, lamellipodia, and filopodia after activation and circulate in macrophage-depleted animals and incorporate into developing mouse thrombi in a manner identical to human platelets. By knocking out the β2-microglobulin gene, we have generated platelets that are negative for the major histocompatibility antigens. The scalable generation of HLA-ABC-negative platelets from a renewable cell source represents an important step toward generating universal platelets for transfusion as well as a potential strategy for the management of platelet refractoriness. PMID:25418726

Scalable generation of universal platelets from human induced pluripotent stem cells.

PubMed

Feng, Qiang; Shabrani, Namrata; Thon, Jonathan N; Huo, Hongguang; Thiel, Austin; Machlus, Kellie R; Kim, Kyungho; Brooks, Julie; Li, Feng; Luo, Chenmei; Kimbrel, Erin A; Wang, Jiwu; Kim, Kwang-Soo; Italiano, Joseph; Cho, Jaehyung; Lu, Shi-Jiang; Lanza, Robert

2014-11-11

Human induced pluripotent stem cells (iPSCs) provide a potentially replenishable source for the production of transfusable platelets. Here, we describe a method to generate megakaryocytes (MKs) and functional platelets from iPSCs in a scalable manner under serum/feeder-free conditions. The method also permits the cryopreservation of MK progenitors, enabling a rapid "surge" capacity when large numbers of platelets are needed. Ultrastructural/morphological analyses show no major differences between iPSC platelets and human blood platelets. iPSC platelets form aggregates, lamellipodia, and filopodia after activation and circulate in macrophage-depleted animals and incorporate into developing mouse thrombi in a manner identical to human platelets. By knocking out the β2-microglobulin gene, we have generated platelets that are negative for the major histocompatibility antigens. The scalable generation of HLA-ABC-negative platelets from a renewable cell source represents an important step toward generating universal platelets for transfusion as well as a potential strategy for the management of platelet refractoriness.

A method to calibrate phase fluctuation in polarization-sensitive swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Lu, Zenghai; Kasaragod, Deepa K.; Matcher, Stephen J.

2011-06-01

A phase fluctuation calibration method is presented for polarization-sensitive swept-source optical coherence tomography (PS-SS-OCT) using continuous polarization modulation. The method consists of the generation of a continuous triggered tone-burst waveform rather than an asynchronous waveform by use of a function generator and the removal of the global phases of the measured Jones matrices by use of matrix normalization. This could remove the use of auxiliary optical components for the phase fluctuation compensation in the system, which reduces the system complexity. Phase fluctuation calibration is necessary to obtain the reference Jones matrix by averaging the measured Jones matrices at sample surfaces. Measurements on an equine tendon sample were made by the PS-SS-OCT system to validate the proposed method.

Stochastic Methods for Aircraft Design

NASA Technical Reports Server (NTRS)

Pelz, Richard B.; Ogot, Madara

1998-01-01

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

Extending compile-time reverse mode and exploiting partial separability in ADIFOR. ADIFOR Working Note No. 7

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

Bischof, C.H.; El-Khadiri, M.

1992-10-01

The numerical methods employed in the solution of many scientific computing problems require the computation of the gradient of a function f: R{sup n} {yields} R. ADIFOR is a source translator that, given a collection of subroutines to compute f, generates Fortran 77 code for computing the derivative of this function. Using the so-called torsion problem from the MINPACK-2 test collection as an example, this paper explores two issues in automatic differentiation: the efficient computation of derivatives for partial separable functions and the use of the compile-time reverse mode for the generation of derivatives. We show that orders of magnitudesmore » of improvement are possible when exploiting partial separability and maximizing use of the reverse mode.« less

Transforming User Needs into Functional Requirements for an Antibiotic Clinical Decision Support System

PubMed Central

Bright, T.J.

2013-01-01

Summary Background Many informatics studies use content analysis to generate functional requirements for system development. Explication of this translational process from qualitative data to functional requirements can strengthen the understanding and scientific rigor when applying content analysis in informatics studies. Objective To describe a user-centered approach transforming emergent themes derived from focus group data into functional requirements for informatics solutions and to illustrate these methods to the development of an antibiotic clinical decision support system (CDS). Methods The approach consisted of five steps: 1) identify unmet therapeutic planning information needs via Focus Group Study-I, 2) develop a coding framework of therapeutic planning themes to refine the domain scope to antibiotic therapeutic planning, 3) identify functional requirements of an antibiotic CDS system via Focus Group Study-II, 4) discover informatics solutions and functional requirements from coded data, and 5) determine the types of information needed to support the antibiotic CDS system and link with the identified informatics solutions and functional requirements. Results The coding framework for Focus Group Study-I revealed unmet therapeutic planning needs. Twelve subthemes emerged and were clustered into four themes; analysis indicated a need for an antibiotic CDS intervention. Focus Group Study-II included five types of information needs. Comments from the Barrier/Challenge to information access and Function/Feature themes produced three informatics solutions and 13 functional requirements of an antibiotic CDS system. Comments from the Patient, Institution, and Domain themes generated required data elements for each informatics solution. Conclusion This study presents one example explicating content analysis of focus group data and the analysis process to functional requirements from narrative data. Illustration of this 5-step method was used to develop an antibiotic CDS system, resolving unmet antibiotic prescribing needs. As a reusable approach, these techniques can be refined and applied to resolve unmet information needs with informatics interventions in additional domains. PMID:24454586

Identification of the functional groups on the surface of nanoparticles formed in photonucleation of aldehydes generated during forest fire events

NASA Astrophysics Data System (ADS)

Dultsev, Fedor N.; Mik, Ivan A.; Dubtsov, Sergei N.; Dultseva, Galina G.

2014-11-01

We describe the new procedure developed to determine the functional groups on the surface of nanoparticles formed in photonucleation of furfural, one of the aldehydes generated during forest fire events. The procedure is based on the detection of nanoparticle rupture from chemically modified surface of the quartz crystal microbalance oscillating in the thickness shear mode under voltage sweep. The rupture force is determined from the voltage at which the rupture occurs. It depends on particle mass and on the affinity of the surface functional groups of the particle to the groups that are present on the modified QCM surface. It was demonstrated with the amine modification of the surface that the nanoparticles formed in furfural photonucleation contain carbonyl and carboxyl groups. The applicability of the method for the investigation of functional groups on the surface of the nanoparticles of atmospheric aerosol is demonstrated.

Method for Smoke Spread Testing of Large Premises

NASA Astrophysics Data System (ADS)

Walmerdahl, P.; Werling, P.

2001-11-01

A method for performing non-destructive smoke spread tests has been developed, tested and applied to several existing buildings. Burning methanol in different size steel trays cooled by water generates the heat source. Several tray sizes are available to cover fire sources up to nearly 1MW. The smoke is supplied by means of a suitable number of smoke generators that produce a smoke, which can be described as a non-toxic aerosol. The advantage of the method is that it provides a means for performing non-destructive tests in already existing buildings and other installations for the purpose of evaluating the functionality and design of the active fire protection measures such as smoke extraction systems, etc. In the report, the method is described in detail and experimental data from the try-out of the method are also presented in addition to a discussion on applicability and flexibility of the method.

Parametric Methods for Dynamic 11C-Phenytoin PET Studies.

PubMed

Mansor, Syahir; Yaqub, Maqsood; Boellaard, Ronald; Froklage, Femke E; de Vries, Anke; Bakker, Esther D M; Voskuyl, Rob A; Eriksson, Jonas; Schwarte, Lothar A; Verbeek, Joost; Windhorst, Albert D; Lammertsma, Adriaan A

2017-03-01

In this study, the performance of various methods for generating quantitative parametric images of dynamic 11 C-phenytoin PET studies was evaluated. Methods: Double-baseline 60-min dynamic 11 C-phenytoin PET studies, including online arterial sampling, were acquired for 6 healthy subjects. Parametric images were generated using Logan plot analysis, a basis function method, and spectral analysis. Parametric distribution volume (V T ) and influx rate ( K 1 ) were compared with those obtained from nonlinear regression analysis of time-activity curves. In addition, global and regional test-retest (TRT) variability was determined for parametric K 1 and V T values. Results: Biases in V T observed with all parametric methods were less than 5%. For K 1 , spectral analysis showed a negative bias of 16%. The mean TRT variabilities of V T and K 1 were less than 10% for all methods. Shortening the scan duration to 45 min provided similar V T and K 1 with comparable TRT performance compared with 60-min data. Conclusion: Among the various parametric methods tested, the basis function method provided parametric V T and K 1 values with the least bias compared with nonlinear regression data and showed TRT variabilities lower than 5%, also for smaller volume-of-interest sizes (i.e., higher noise levels) and shorter scan duration. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Equilibrium Molecular Thermodynamics from Kirkwood Sampling

PubMed Central

2015-01-01

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys.2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, where Kirkwood sampling is used for generating trial Monte Carlo moves. Using this method, equilibrium distributions corresponding to different temperatures and potential energy functions can be generated from a given set of low-order correlations. Since Kirkwood samples are generated independently, this method is ideally suited for massively parallel distributed computing. The second approach is a variant of reservoir replica exchange, where Kirkwood sampling is used to construct a reservoir of conformations, which exchanges conformations with the replicas performing equilibrium sampling corresponding to different thermodynamic states. Coupling with the Kirkwood reservoir enhances sampling by facilitating global jumps in the conformational space. The efficiency of both methods depends on the overlap of the Kirkwood distribution with the target equilibrium distribution. We present proof-of-concept results for a model nine-atom linear molecule and alanine dipeptide. PMID:25915525

A hybrid fault diagnosis method based on second generation wavelet de-noising and local mean decomposition for rotating machinery.

PubMed

Liu, Zhiwen; He, Zhengjia; Guo, Wei; Tang, Zhangchun

2016-03-01

In order to extract fault features of large-scale power equipment from strong background noise, a hybrid fault diagnosis method based on the second generation wavelet de-noising (SGWD) and the local mean decomposition (LMD) is proposed in this paper. In this method, a de-noising algorithm of second generation wavelet transform (SGWT) using neighboring coefficients was employed as the pretreatment to remove noise in rotating machinery vibration signals by virtue of its good effect in enhancing the signal-noise ratio (SNR). Then, the LMD method is used to decompose the de-noised signals into several product functions (PFs). The PF corresponding to the faulty feature signal is selected according to the correlation coefficients criterion. Finally, the frequency spectrum is analyzed by applying the FFT to the selected PF. The proposed method is applied to analyze the vibration signals collected from an experimental gearbox and a real locomotive rolling bearing. The results demonstrate that the proposed method has better performances such as high SNR and fast convergence speed than the normal LMD method. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Tight-binding analysis of Si and GaAs ultrathin bodies with subatomic wave-function resolution

NASA Astrophysics Data System (ADS)

Tan, Yaohua P.; Povolotskyi, Michael; Kubis, Tillmann; Boykin, Timothy B.; Klimeck, Gerhard

2015-08-01

Empirical tight-binding (ETB) methods are widely used in atomistic device simulations. Traditional ways of generating the ETB parameters rely on direct fitting to bulk experiments or theoretical electronic bands. However, ETB calculations based on existing parameters lead to unphysical results in ultrasmall structures like the As-terminated GaAs ultrathin bodies (UTBs). In this work, it is shown that more transferable ETB parameters with a short interaction range can be obtained by a process of mapping ab initio bands and wave functions to ETB models. This process enables the calibration of not only the ETB energy bands but also the ETB wave functions with corresponding ab initio calculations. Based on the mapping process, ETB models of Si and GaAs are parameterized with respect to hybrid functional calculations. Highly localized ETB basis functions are obtained. Both the ETB energy bands and wave functions with subatomic resolution of UTBs show good agreement with the corresponding hybrid functional calculations. The ETB methods can then be used to explain realistically extended devices in nonequilibrium that cannot be tackled with ab initio methods.

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

Malware analysis using visualized image matrices.

PubMed

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

[Techniques for rapid production of monoclonal antibodies for use with antibody technology].

PubMed

Kamada, Haruhiko

2012-01-01

A monoclonal antibody (Mab), due to its specific binding ability to a target protein, can potentially be one of the most useful tools for the functional analysis of proteins in recent proteomics-based research. However, the production of Mab is a very time-consuming and laborious process (i.e., preparation of recombinant antigens, immunization of animals, preparation of hybridomas), making it the rate-limiting step in using Mabs in high-throughput proteomics research, which heavily relies on comprehensive and rapid methods. Therefore, there is a great demand for new methods to efficiently generate Mabs against a group of proteins identified by proteome analysis. Here, we describe a useful method called "Antibody proteomic technique" for the rapid generations of Mabs to pharmaceutical target, which were identified by proteomic analyses of disease samples (ex. tumor tissue, etc.). We also introduce another method to find profitable targets on vasculature, which is called "Vascular proteomic technique". Our results suggest that this method for the rapid generation of Mabs to proteins may be very useful in proteomics-based research as well as in clinical applications.

A modified adjoint-based grid adaptation and error correction method for unstructured grid

NASA Astrophysics Data System (ADS)

Cui, Pengcheng; Li, Bin; Tang, Jing; Chen, Jiangtao; Deng, Youqi

2018-05-01

Grid adaptation is an important strategy to improve the accuracy of output functions (e.g. drag, lift, etc.) in computational fluid dynamics (CFD) analysis and design applications. This paper presents a modified robust grid adaptation and error correction method for reducing simulation errors in integral outputs. The procedure is based on discrete adjoint optimization theory in which the estimated global error of output functions can be directly related to the local residual error. According to this relationship, local residual error contribution can be used as an indicator in a grid adaptation strategy designed to generate refined grids for accurately estimating the output functions. This grid adaptation and error correction method is applied to subsonic and supersonic simulations around three-dimensional configurations. Numerical results demonstrate that the sensitive grids to output functions are detected and refined after grid adaptation, and the accuracy of output functions is obviously improved after error correction. The proposed grid adaptation and error correction method is shown to compare very favorably in terms of output accuracy and computational efficiency relative to the traditional featured-based grid adaptation.

Approximate analytical relationships for linear optimal aeroelastic flight control laws

NASA Astrophysics Data System (ADS)

Kassem, Ayman Hamdy

1998-09-01

This dissertation introduces new methods to uncover functional relationships between design parameters of a contemporary control design technique and the resulting closed-loop properties. Three new methods are developed for generating such relationships through analytical expressions: the Direct Eigen-Based Technique, the Order of Magnitude Technique, and the Cost Function Imbedding Technique. Efforts concentrated on the linear-quadratic state-feedback control-design technique applied to an aeroelastic flight control task. For this specific application, simple and accurate analytical expressions for the closed-loop eigenvalues and zeros in terms of basic parameters such as stability and control derivatives, structural vibration damping and natural frequency, and cost function weights are generated. These expressions explicitly indicate how the weights augment the short period and aeroelastic modes, as well as the closed-loop zeros, and by what physical mechanism. The analytical expressions are used to address topics such as damping, nonminimum phase behavior, stability, and performance with robustness considerations, and design modifications. This type of knowledge is invaluable to the flight control designer and would be more difficult to formulate when obtained from numerical-based sensitivity analysis.

Conditioning 3D object-based models to dense well data

NASA Astrophysics Data System (ADS)

Wang, Yimin C.; Pyrcz, Michael J.; Catuneanu, Octavian; Boisvert, Jeff B.

2018-06-01

Object-based stochastic simulation models are used to generate categorical variable models with a realistic representation of complicated reservoir heterogeneity. A limitation of object-based modeling is the difficulty of conditioning to dense data. One method to achieve data conditioning is to apply optimization techniques. Optimization algorithms can utilize an objective function measuring the conditioning level of each object while also considering the geological realism of the object. Here, an objective function is optimized with implicit filtering which considers constraints on object parameters. Thousands of objects conditioned to data are generated and stored in a database. A set of objects are selected with linear integer programming to generate the final realization and honor all well data, proportions and other desirable geological features. Although any parameterizable object can be considered, objects from fluvial reservoirs are used to illustrate the ability to simultaneously condition multiple types of geologic features. Channels, levees, crevasse splays and oxbow lakes are parameterized based on location, path, orientation and profile shapes. Functions mimicking natural river sinuosity are used for the centerline model. Channel stacking pattern constraints are also included to enhance the geological realism of object interactions. Spatial layout correlations between different types of objects are modeled. Three case studies demonstrate the flexibility of the proposed optimization-simulation method. These examples include multiple channels with high sinuosity, as well as fragmented channels affected by limited preservation. In all cases the proposed method reproduces input parameters for the object geometries and matches the dense well constraints. The proposed methodology expands the applicability of object-based simulation to complex and heterogeneous geological environments with dense sampling.

Automated pulmonary lobar ventilation measurements using volume-matched thoracic CT and MRI

NASA Astrophysics Data System (ADS)

Guo, F.; Svenningsen, S.; Bluemke, E.; Rajchl, M.; Yuan, J.; Fenster, A.; Parraga, G.

2015-03-01

Objectives: To develop and evaluate an automated registration and segmentation pipeline for regional lobar pulmonary structure-function measurements, using volume-matched thoracic CT and MRI in order to guide therapy. Methods: Ten subjects underwent pulmonary function tests and volume-matched 1H and 3He MRI and thoracic CT during a single 2-hr visit. CT was registered to 1H MRI using an affine method that incorporated block-matching and this was followed by a deformable step using free-form deformation. The resultant deformation field was used to deform the associated CT lobe mask that was generated using commercial software. 3He-1H image registration used the same two-step registration method and 3He ventilation was segmented using hierarchical k-means clustering. Whole lung and lobar 3He ventilation and ventilation defect percent (VDP) were generated by mapping ventilation defects to CT-defined whole lung and lobe volumes. Target CT-3He registration accuracy was evaluated using region- , surface distance- and volume-based metrics. Automated whole lung and lobar VDP was compared with semi-automated and manual results using paired t-tests. Results: The proposed pipeline yielded regional spatial agreement of 88.0+/-0.9% and surface distance error of 3.9+/-0.5 mm. Automated and manual whole lung and lobar ventilation and VDP were not significantly different and they were significantly correlated (r = 0.77, p < 0.0001). Conclusion: The proposed automated pipeline can be used to generate regional pulmonary structural-functional maps with high accuracy and robustness, providing an important tool for image-guided pulmonary interventions.

Genome Editing in Rats Using TALE Nucleases.

PubMed

Tesson, Laurent; Remy, Séverine; Ménoret, Séverine; Usal, Claire; Thinard, Reynald; Savignard, Chloé; De Cian, Anne; Giovannangeli, Carine; Concordet, Jean-Paul; Anegon, Ignacio

2016-01-01

The rat is an important animal model to understand gene function and model human diseases. Since recent years, the development of gene-specific nucleases has become important for generating new rat models of human diseases, to analyze the role of genes and to generate human antibodies. Transcription activator-like (TALE) nucleases efficiently create gene-specific knockout rats and lead to the possibility of gene targeting by homology-directed recombination (HDR) and generating knock-in rats. We describe a detailed protocol for generating knockout and knock-in rats via microinjection of TALE nucleases into fertilized eggs. This technology is an efficient, cost- and time-effective method for creating new rat models.

The use of Galerkin finite-element methods to solve mass-transport equations

USGS Publications Warehouse

Grove, David B.

1977-01-01

The partial differential equation that describes the transport and reaction of chemical solutes in porous media was solved using the Galerkin finite-element technique. These finite elements were superimposed over finite-difference cells used to solve the flow equation. Both convection and flow due to hydraulic dispersion were considered. Linear and Hermite cubic approximations (basis functions) provided satisfactory results: however, the linear functions were computationally more efficient for two-dimensional problems. Successive over relaxation (SOR) and iteration techniques using Tchebyschef polynomials were used to solve the sparce matrices generated using the linear and Hermite cubic functions, respectively. Comparisons of the finite-element methods to the finite-difference methods, and to analytical results, indicated that a high degree of accuracy may be obtained using the method outlined. The technique was applied to a field problem involving an aquifer contaminated with chloride, tritium, and strontium-90. (Woodard-USGS)

A novel method for energy harvesting simulation based on scenario generation

NASA Astrophysics Data System (ADS)

Wang, Zhe; Li, Taoshen; Xiao, Nan; Ye, Jin; Wu, Min

2018-06-01

Energy harvesting network (EHN) is a new form of computer networks. It converts ambient energy into usable electric energy and supply the electrical energy as a primary or secondary power source to the communication devices. However, most of the EHN uses the analytical probability distribution function to describe the energy harvesting process, which cannot accurately identify the actual situation for the lack of authenticity. We propose an EHN simulation method based on scenario generation in this paper. Firstly, instead of setting a probability distribution in advance, it uses optimal scenario reduction technology to generate representative scenarios in single period based on the historical data of the harvested energy. Secondly, it uses homogeneous simulated annealing algorithm to generate optimal daily energy harvesting scenario sequences to get a more accurate simulation of the random characteristics of the energy harvesting network. Then taking the actual wind power data as an example, the accuracy and stability of the method are verified by comparing with the real data. Finally, we cite an instance to optimize the network throughput, which indicate the feasibility and effectiveness of the method we proposed from the optimal solution and data analysis in energy harvesting simulation.

HEPMath 1.4: A mathematica package for semi-automatic computations in high energy physics

NASA Astrophysics Data System (ADS)

Wiebusch, Martin

2015-10-01

This article introduces the Mathematica package HEPMath which provides a number of utilities and algorithms for High Energy Physics computations in Mathematica. Its functionality is similar to packages like FormCalc or FeynCalc, but it takes a more complete and extensible approach to implementing common High Energy Physics notations in the Mathematica language, in particular those related to tensors and index contractions. It also provides a more flexible method for the generation of numerical code which is based on new features for C code generation in Mathematica. In particular it can automatically generate Python extension modules which make the compiled functions callable from Python, thus eliminating the need to write any code in a low-level language like C or Fortran. It also contains seamless interfaces to LHAPDF, FeynArts, and LoopTools.

A Large Class of Exact Solutions to the One-Dimensional Schrodinger Equation

ERIC Educational Resources Information Center

Karaoglu, Bekir

2007-01-01

A remarkable property of a large class of functions is exploited to generate exact solutions to the one-dimensional Schrodinger equation. The method is simple and easy to implement. (Contains 1 table and 1 figure.)

TDIGG - TWO-DIMENSIONAL, INTERACTIVE GRID GENERATION CODE

NASA Technical Reports Server (NTRS)

Vu, B. T.

1994-01-01

TDIGG is a fast and versatile program for generating two-dimensional computational grids for use with finite-difference flow-solvers. Both algebraic and elliptic grid generation systems are included. The method for grid generation by algebraic transformation is based on an interpolation algorithm and the elliptic grid generation is established by solving the partial differential equation (PDE). Non-uniform grid distributions are carried out using a hyperbolic tangent stretching function. For algebraic grid systems, interpolations in one direction (univariate) and two directions (bivariate) are considered. These interpolations are associated with linear or cubic Lagrangian/Hermite/Bezier polynomial functions. The algebraic grids can subsequently be smoothed using an elliptic solver. For elliptic grid systems, the PDE can be in the form of Laplace (zero forcing function) or Poisson. The forcing functions in the Poisson equation come from the boundary or the entire domain of the initial algebraic grids. A graphics interface procedure using the Silicon Graphics (GL) Library is included to allow users to visualize the grid variations at each iteration. This will allow users to interactively modify the grid to match their applications. TDIGG is written in FORTRAN 77 for Silicon Graphics IRIS series computers running IRIX. This package requires either MIT's X Window System, Version 11 Revision 4 or SGI (Motif) Window System. A sample executable is provided on the distribution medium. It requires 148K of RAM for execution. The standard distribution medium is a .25 inch streaming magnetic IRIX tape cartridge in UNIX tar format. This program was developed in 1992.

Symmetric and asymmetric hybrid cryptosystem based on compressive sensing and computer generated holography

NASA Astrophysics Data System (ADS)

Ma, Lihong; Jin, Weimin

2018-01-01

A novel symmetric and asymmetric hybrid optical cryptosystem is proposed based on compressive sensing combined with computer generated holography. In this method there are six encryption keys, among which two decryption phase masks are different from the two random phase masks used in the encryption process. Therefore, the encryption system has the feature of both symmetric and asymmetric cryptography. On the other hand, because computer generated holography can flexibly digitalize the encrypted information and compressive sensing can significantly reduce data volume, what is more, the final encryption image is real function by phase truncation, the method favors the storage and transmission of the encryption data. The experimental results demonstrate that the proposed encryption scheme boosts the security and has high robustness against noise and occlusion attacks.

Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

PubMed

Wang, J; Hao, Z; Wang, H

2018-01-01

The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

Modulation of the pupil function of microscope objective lens for multifocal multi-photon microscopy using a spatial light modulator

NASA Astrophysics Data System (ADS)

Matsumoto, Naoya; Okazaki, Shigetoshi; Takamoto, Hisayoshi; Inoue, Takashi; Terakawa, Susumu

2014-02-01

We propose a method for high precision modulation of the pupil function of a microscope objective lens to improve the performance of multifocal multi-photon microscopy (MMM). To modulate the pupil function, we adopt a spatial light modulator (SLM) and place it at the conjugate position of the objective lens. The SLM can generate an arbitrary number of spots to excite the multiple fluorescence spots (MFS) at the desired positions and intensities by applying an appropriate computer-generated hologram (CGH). This flexibility allows us to control the MFS according to the photobleaching level of a fluorescent protein and phototoxicity of a specimen. However, when a large number of excitation spots are generated, the intensity distribution of the MFS is significantly different from the one originally designed due to misalignment of the optical setup and characteristics of the SLM. As a result, the image of a specimen obtained using laser scanning for the MFS has block noise segments because the SLM could not generate a uniform MFS. To improve the intensity distribution of the MFS, we adaptively redesigned the CGH based on the observed MFS. We experimentally demonstrate an improvement in the uniformity of a 10 × 10 MFS grid using a dye solution. The simplicity of the proposed method will allow it to be applied for calibration of MMM before observing living tissue. After the MMM calibration, we performed laser scanning with two-photon excitation to observe a real specimen without detecting block noise segments.

Design of motor induction 3-Phase from waste industry to generator for microhydro at isolated village

NASA Astrophysics Data System (ADS)

Rimbawati; Azis Hutasuhut, Abdul; Irsan Pasaribu, Faisal; Cholish; Muharnif

2017-09-01

There is an electric machine that can operate as a generator either single-phase or three-phase in almost every household and industry today. This electric engine cannot be labeled as a generator but can be functioned as a generator. The machine that is mentioned is “squirrel cage motors” or it is well-known as induction motor that can be found in water pumps, washing machines, fans, blowers and other industrial machines. The induction motor can be functioned as a generator when the rotational speed of the rotor is made larger than the speed of the rotary field. In this regard, this study aims to modify the remains of 3-phase induction motor to be a permanent generator. Data of research based conducted on the river flow of Rumah Sumbul Village, STM Hulu district of Deli Serdang. The method of this research is by changing rotor and stator winding on a 3 phase induction motor, so it can produce a generator with rotation speed of 500 rpm. Based on the research, it can be concluded that the output voltage generator has occurred a voltage drop 10% between before and after loading for Star circuit and 2% for Delta circuit.

An intertwined method for making low-rank, sum-of-product basis functions that makes it possible to compute vibrational spectra of molecules with more than 10 atoms

PubMed Central

Thomas, Phillip S.

2017-01-01

We propose a method for solving the vibrational Schrödinger equation with which one can compute spectra for molecules with more than ten atoms. It uses sum-of-product (SOP) basis functions stored in a canonical polyadic tensor format and generated by evaluating matrix-vector products. By doing a sequence of partial optimizations, in each of which the factors in a SOP basis function for a single coordinate are optimized, the rank of the basis functions is reduced as matrix-vector products are computed. This is better than using an alternating least squares method to reduce the rank, as is done in the reduced-rank block power method. Partial optimization is better because it speeds up the calculation by about an order of magnitude and allows one to significantly reduce the memory cost. We demonstrate the effectiveness of the new method by computing vibrational spectra of two molecules, ethylene oxide (C2H4O) and cyclopentadiene (C5H6), with 7 and 11 atoms, respectively. PMID:28571348

Complex plane integration in the modelling of electromagnetic fields in layered media: part 1. Application to a very large loop

NASA Astrophysics Data System (ADS)

Silva, Valdelírio da Silva e.; Régis, Cícero; Howard, Allen Q., Jr.

2014-02-01

This paper analyses the details of a procedure for the numerical integration of Hankel transforms in the calculation of the electromagnetic fields generated by a large horizontal loop over a 1D earth. The method performs the integration by deforming the integration path into the complex plane and applying Cauchy's theorem on a modified version of the integrand. The modification is the replacement of the Bessel functions J0 and J1 by the Hankel functions H_0^{(1)} and H_1^{(1)} respectively. The integration in the complex plane takes advantage of the exponentially decaying behaviour of the Hankel functions, allowing calculation on very small segments, instead of the infinite line of the original improper integrals. A crucial point in this problem is the location of the poles. The companion paper shows two methods to estimate the pole locations. We have used this method to calculate the fields of very large loops. Our results show that this method allows the estimation of the integrals with fewer evaluations of the integrand functions than other methods.

An intertwined method for making low-rank, sum-of-product basis functions that makes it possible to compute vibrational spectra of molecules with more than 10 atoms.

PubMed

Thomas, Phillip S; Carrington, Tucker

2017-05-28

We propose a method for solving the vibrational Schrödinger equation with which one can compute spectra for molecules with more than ten atoms. It uses sum-of-product (SOP) basis functions stored in a canonical polyadic tensor format and generated by evaluating matrix-vector products. By doing a sequence of partial optimizations, in each of which the factors in a SOP basis function for a single coordinate are optimized, the rank of the basis functions is reduced as matrix-vector products are computed. This is better than using an alternating least squares method to reduce the rank, as is done in the reduced-rank block power method. Partial optimization is better because it speeds up the calculation by about an order of magnitude and allows one to significantly reduce the memory cost. We demonstrate the effectiveness of the new method by computing vibrational spectra of two molecules, ethylene oxide (C 2 H 4 O) and cyclopentadiene (C 5 H 6 ), with 7 and 11 atoms, respectively.

Control design based on a linear state function observer

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1992-01-01

An approach to the design of low-order controllers for large scale systems is proposed. The method is derived from the theory of linear state function observers. First, the realization of a state feedback control law is interpreted as the observation of a linear function of the state vector. The linear state function to be reconstructed is the given control law. Then, based on the derivation for linear state function observers, the observer design is formulated as a parameter optimization problem. The optimization objective is to generate a matrix that is close to the given feedback gain matrix. Based on that matrix, the form of the observer and a new control law can be determined. A four-disk system and a lightly damped beam are presented as examples to demonstrate the applicability and efficacy of the proposed method.

Dual C-H functionalization of N-aryl amines: synthesis of polycyclic amines via an oxidative Povarov approach.

PubMed

Min, Chang; Sanchawala, Abbas; Seidel, Daniel

2014-05-16

Iminium ions generated in situ via copper(I) bromide catalyzed oxidation of N-aryl amines readily undergo [4 + 2] cycloadditions with a range of dienophiles. This method involves the functionalization of both a C(sp(3))-H and a C(sp(2))-H bond and enables the rapid construction of polycyclic amines under relatively mild conditions.

The natural neighbor series manuals and source codes

NASA Astrophysics Data System (ADS)

Watson, Dave

1999-05-01

This software series is concerned with reconstruction of spatial functions by interpolating a set of discrete observations having two or three independent variables. There are three components in this series: (1) nngridr: an implementation of natural neighbor interpolation, 1994, (2) modemap: an implementation of natural neighbor interpolation on the sphere, 1998 and (3) orebody: an implementation of natural neighbor isosurface generation (publication incomplete). Interpolation is important to geologists because it can offer graphical insights into significant geological structure and behavior, which, although inherent in the data, may not be otherwise apparent. It also is the first step in numerical integration, which provides a primary avenue to detailed quantification of the observed spatial function. Interpolation is implemented by selecting a surface-generating rule that controls the form of a `bridge' built across the interstices between adjacent observations. The cataloging and classification of the many such rules that have been reported is a subject in itself ( Watson, 1992), and the merits of various approaches have been debated at length. However, for practical purposes, interpolation methods are usually judged on how satisfactorily they handle problematic data sets. Sparse scattered data or traverse data, especially if the functional values are highly variable, generally tests interpolation methods most severely; but one method, natural neighbor interpolation, usually does produce preferable results for such data.

Exploring oxidative ageing behaviour of hydrocarbons using ab initio molecular dynamics analysis

NASA Astrophysics Data System (ADS)

Pan, Tongyan; Cheng, Cheng

2016-06-01

With a proper approximate solution to the Schrödinger Equation of a multi-electron system, the method of ab initio molecular dynamics (AIMD) performs first-principles molecular dynamics analysis without pre-defining interatomic potentials as are mandatory in traditional molecular dynamics analyses. The objective of this study is to determine the oxidative-ageing pathway of petroleum asphalt as a typical hydrocarbon system, using the AIMD method. This objective was accomplished in three steps, including (1) identifying a group of representative asphalt molecules to model, (2) determining an atomistic modelling method that can effectively simulate the production of critical functional groups in oxidative ageing of hydrocarbons and (3) evaluating the oxidative-ageing pathway of a hydrocarbon system. The determination of oxidative-ageing pathway of hydrocarbons was done by tracking the generations of critical functional groups in the course of oxidative ageing. The chemical elements of carbon, nitrogen and sulphur all experience oxidative reactions, producing polarised functional groups such as ketones, aldehydes or carboxylic acids, pyrrolic groups and sulphoxides. The electrostatic forces of the polarised groups generated in oxidation are responsible for the behaviour of aged hydrocarbons. The developed AIMD model can be used for modelling the ageing of generic hydrocarbon polymers and developing antioxidants without running expensive experiments.

De novo design and engineering of functional metal and porphyrin-binding protein domains

NASA Astrophysics Data System (ADS)

Everson, Bernard H.

In this work, I describe an approach to the rational, iterative design and characterization of two functional cofactor-binding protein domains. First, a hybrid computational/experimental method was developed with the aim of algorithmically generating a suite of porphyrin-binding protein sequences with minimal mutual sequence information. This method was explored by generating libraries of sequences, which were then expressed and evaluated for function. One successful sequence is shown to bind a variety of porphyrin-like cofactors, and exhibits light- activated electron transfer in mixed hemin:chlorin e6 and hemin:Zn(II)-protoporphyrin IX complexes. These results imply that many sophisticated functions such as cofactor binding and electron transfer require only a very small number of residue positions in a protein sequence to be fixed. Net charge and hydrophobic content are important in determining protein solubility and stability. Accordingly, rational modifications were made to the aforementioned design procedure in order to improve its overall success rate. The effects of these modifications are explored using two `next-generation' sequence libraries, which were separately expressed and evaluated. Particular modifications to these design parameters are demonstrated to effectively double the purification success rate of the procedure. Finally, I describe the redesign of the artificial di-iron protein DF2 into CDM13, a single chain di-Manganese four-helix bundle. CDM13 acts as a functional model of natural manganese catalase, exhibiting a kcat of 0.08s-1 under steady-state conditions. The bound manganese cofactors have a reduction potential of +805 mV vs NHE, which is too high for efficient dismutation of hydrogen peroxide. These results indicate that as a high-potential manganese complex, CDM13 may represent a promising first step toward a polypeptide model of the Oxygen Evolving Complex of the photosynthetic enzyme Photosystem II.

Assessing directed evolution methods for the generation of biosynthetic enzymes with potential in drug biosynthesis

PubMed Central

Nannemann, David P; Birmingham, William R; Scism, Robert A; Bachmann, Brian O

2011-01-01

To address the synthesis of increasingly structurally diverse small-molecule drugs, methods for the generation of efficient and selective biological catalysts are becoming increasingly important. ‘Directed evolution’ is an umbrella term referring to a variety of methods for improving or altering the function of enzymes using a nature-inspired twofold strategy of mutagenesis followed by selection. This article provides an objective assessment of the effectiveness of directed evolution campaigns in generating enzymes with improved catalytic parameters for new substrates from the last decade, excluding studies that aimed to select for only improved physical properties and those that lack kinetic characterization. An analysis of the trends of methodologies and their success rates from 81 qualifying examples in the literature reveals the average fold improvement for kcat (or Vmax), Km and kcat/Km to be 366-, 12- and 2548-fold, respectively, whereas the median fold improvements are 5.4, 3 and 15.6. Further analysis by enzyme class, library-generation methodology and screening methodology explores relationships between successful campaigns and the methodologies employed. PMID:21644826

Utilization of group theory in studies of molecular clusters

NASA Astrophysics Data System (ADS)

Ocak, Mahir E.

The structure of the molecular symmetry group of molecular clusters was analyzed and it is shown that the molecular symmetry group of a molecular cluster can be written as direct products and semidirect products of its subgroups. Symmetry adaptation of basis functions in direct product groups and semidirect product groups was considered in general and the sequential symmetry adaptation procedure which is already known for direct product groups was extended to the case of semidirect product groups. By using the sequential symmetry adaptation procedure a new method for calculating the VRT spectra of molecular clusters which is named as Monomer Basis Representation (MBR) method is developed. In the MBR method, calculations starts with a single monomer with the purpose of obtaining an optimized basis for that monomer as a linear combination of some primitive basis functions. Then, an optimized basis for each identical monomer is generated from the optimized basis of this monomer. By using the optimized bases of the monomers, a basis is generated generated for the solution of the full problem, and the VRT spectra of the cluster is obtained by using this basis. Since an optimized basis is used for each monomer which has a much smaller size than the primitive basis from which the optimized bases are generated, the MBR method leads to an exponential optimization in the size of the basis that is required for the calculations. Application of the MBR method has been illustrated by calculating the VRT spectra of water dimer by using the SAPT-5st potential surface of Groenenboom et al. The rest of the calculations are in good agreement with both the original calculations of Groenenboom et al. and also with the experimental results. Comparing the size of the optimized basis with the size of the primitive basis, it can be said that the method works efficiently. Because of its efficiency, the MBR method can be used for studies of clusters bigger than dimers. Thus, MBR method can be used for studying the many-body terms and for deriving accurate potential surfaces.

PipeOnline 2.0: automated EST processing and functional data sorting.

PubMed

Ayoubi, Patricia; Jin, Xiaojing; Leite, Saul; Liu, Xianghui; Martajaja, Jeson; Abduraham, Abdurashid; Wan, Qiaolan; Yan, Wei; Misawa, Eduardo; Prade, Rolf A

2002-11-01

Expressed sequence tags (ESTs) are generated and deposited in the public domain, as redundant, unannotated, single-pass reactions, with virtually no biological content. PipeOnline automatically analyses and transforms large collections of raw DNA-sequence data from chromatograms or FASTA files by calling the quality of bases, screening and removing vector sequences, assembling and rewriting consensus sequences of redundant input files into a unigene EST data set and finally through translation, amino acid sequence similarity searches, annotation of public databases and functional data. PipeOnline generates an annotated database, retaining the processed unigene sequence, clone/file history, alignments with similar sequences, and proposed functional classification, if available. Functional annotation is automatic and based on a novel method that relies on homology of amino acid sequence multiplicity within GenBank records. Records are examined through a function ordered browser or keyword queries with automated export of results. PipeOnline offers customization for individual projects (MyPipeOnline), automated updating and alert service. PipeOnline is available at http://stress-genomics.org.

An accurate two-dimensional LBIC solution for bipolar transistors

NASA Astrophysics Data System (ADS)

Benarab, A.; Baudrand, H.; Lescure, M.; Boucher, J.

1988-05-01

A complete solution of the diffusion problem of carriers generated by a located light beam in the emitter and base region of a bipolar structure is presented. Green's function method and moment method are used to solve the 2-D diffusion equation in these regions. From the Green's functions solution of these equations, the light beam induced currents (LBIC) in the different junctions of the structure due to an extended generation represented by a rectangular light spot; are thus decided. The equations of these currents depend both on the parameters which characterise the structure, surface states, dimensions of the emitter and the base region, and the characteristics of the light spot, that is to say, the width and the wavelength. Curves illustrating the variation of the various LBIC in the base region junctions as a function of the impact point of the light beam ( x0) for different values of these parameters are discussed. In particular, the study of the base-emitter currents when the light beam is swept right across the sample illustrates clearly a good geometrical definition of the emitter region up to base end of the emitter-base space-charge areas and a "whirl" lateral diffusion beneath this region, (i.e. the diffusion of the generated carriers near the surface towards the horizontal base-emitter junction and those created beneath this junction towards the lateral (B-E) junctions).

On methods for the detection of reactive oxygen species generation by human spermatozoa: analysis of the cellular responses to catechol oestrogen, lipid aldehyde, menadione and arachidonic acid.

PubMed

Aitken, R J; Smith, T B; Lord, T; Kuczera, L; Koppers, A J; Naumovski, N; Connaughton, H; Baker, M A; De Iuliis, G N

2013-03-01

Oxidative stress is known to have a major impact on human sperm function and, as a result, there is a need to develop sensitive methods for measuring reactive oxygen species (ROS) generation by these cells. A variety of techniques have been developed for this purpose including chemiluminescence (luminol and lucigenin), flow cytometry (MitoSOX Red, dihydroethidium, 4,5-diaminofluorescein diacetate and 2',7'-dichlorodihydrofluorescein diacetate) and spectrophotometry (nitroblue tetrazolium). The relative sensitivity of these assays and their comparative ability to detect ROS generated in different subcellular compartments of human spermatozoa, have not previously been investigated. To address this issue, we have compared the performance of these assays when ROS generation was triggered with a variety of reagents including 2-hydroxyestradiol, menadione, 4-hydroxynonenal and arachidonic acid. The results revealed that menadione predominantly induced release of ROS into the extracellular space where these metabolites could be readily detected by luminol-peroxidase and, to a lesser extent, 2',7'-dichlorodihydrofluorescein. However, such sensitivity to extracellular ROS meant that these assays were particularly vulnerable to interference by leucocytes. The remaining reagents predominantly elicited ROS generation by the sperm mitochondria and could be optimally detected by MitoSOX Red and DHE. Examination of spontaneous ROS generation by defective human spermatozoa revealed that MitoSOX Red was the most effective indicator of oxidative stress, thereby emphasizing the general importance of mitochondrial dysregulation in the aetiology of defective sperm function. © 2013 American Society of Andrology and European Academy of Andrology.

Algebraic grid generation using tensor product B-splines. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Saunders, B. V.

1985-01-01

Finite difference methods are more successful if the accompanying grid has lines which are smooth and nearly orthogonal. The development of an algorithm which produces such a grid when given the boundary description. Topological considerations in structuring the grid generation mapping are discussed. The concept of the degree of a mapping and how it can be used to determine what requirements are necessary if a mapping is to produce a suitable grid is examined. The grid generation algorithm uses a mapping composed of bicubic B-splines. Boundary coefficients are chosen so that the splines produce Schoenberg's variation diminishing spline approximation to the boundary. Interior coefficients are initially chosen to give a variation diminishing approximation to the transfinite bilinear interpolant of the function mapping the boundary of the unit square onto the boundary grid. The practicality of optimizing the grid by minimizing a functional involving the Jacobian of the grid generation mapping at each interior grid point and the dot product of vectors tangent to the grid lines is investigated. Grids generated by using the algorithm are presented.

Large Eddy Simulation of Entropy Generation in a Turbulent Mixing Layer

NASA Astrophysics Data System (ADS)

Sheikhi, Reza H.; Safari, Mehdi; Hadi, Fatemeh

2013-11-01

Entropy transport equation is considered in large eddy simulation (LES) of turbulent flows. The irreversible entropy generation in this equation provides a more general description of subgrid scale (SGS) dissipation due to heat conduction, mass diffusion and viscosity effects. A new methodology is developed, termed the entropy filtered density function (En-FDF), to account for all individual entropy generation effects in turbulent flows. The En-FDF represents the joint probability density function of entropy, frequency, velocity and scalar fields within the SGS. An exact transport equation is developed for the En-FDF, which is modeled by a system of stochastic differential equations, incorporating the second law of thermodynamics. The modeled En-FDF transport equation is solved by a Lagrangian Monte Carlo method. The methodology is employed to simulate a turbulent mixing layer involving transport of passive scalars and entropy. Various modes of entropy generation are obtained from the En-FDF and analyzed. Predictions are assessed against data generated by direct numerical simulation (DNS). The En-FDF predictions are in good agreements with the DNS data.

Robust stochastic optimization for reservoir operation

NASA Astrophysics Data System (ADS)

Pan, Limeng; Housh, Mashor; Liu, Pan; Cai, Ximing; Chen, Xin

2015-01-01

Optimal reservoir operation under uncertainty is a challenging engineering problem. Application of classic stochastic optimization methods to large-scale problems is limited due to computational difficulty. Moreover, classic stochastic methods assume that the estimated distribution function or the sample inflow data accurately represents the true probability distribution, which may be invalid and the performance of the algorithms may be undermined. In this study, we introduce a robust optimization (RO) approach, Iterative Linear Decision Rule (ILDR), so as to provide a tractable approximation for a multiperiod hydropower generation problem. The proposed approach extends the existing LDR method by accommodating nonlinear objective functions. It also provides users with the flexibility of choosing the accuracy of ILDR approximations by assigning a desired number of piecewise linear segments to each uncertainty. The performance of the ILDR is compared with benchmark policies including the sampling stochastic dynamic programming (SSDP) policy derived from historical data. The ILDR solves both the single and multireservoir systems efficiently. The single reservoir case study results show that the RO method is as good as SSDP when implemented on the original historical inflows and it outperforms SSDP policy when tested on generated inflows with the same mean and covariance matrix as those in history. For the multireservoir case study, which considers water supply in addition to power generation, numerical results show that the proposed approach performs as well as in the single reservoir case study in terms of optimal value and distributional robustness.

Eddington's demon: inferring galaxy mass functions and other distributions from uncertain data

NASA Astrophysics Data System (ADS)

Obreschkow, D.; Murray, S. G.; Robotham, A. S. G.; Westmeier, T.

2018-03-01

We present a general modified maximum likelihood (MML) method for inferring generative distribution functions from uncertain and biased data. The MML estimator is identical to, but easier and many orders of magnitude faster to compute than the solution of the exact Bayesian hierarchical modelling of all measurement errors. As a key application, this method can accurately recover the mass function (MF) of galaxies, while simultaneously dealing with observational uncertainties (Eddington bias), complex selection functions and unknown cosmic large-scale structure. The MML method is free of binning and natively accounts for small number statistics and non-detections. Its fast implementation in the R-package dftools is equally applicable to other objects, such as haloes, groups, and clusters, as well as observables other than mass. The formalism readily extends to multidimensional distribution functions, e.g. a Choloniewski function for the galaxy mass-angular momentum distribution, also handled by dftools. The code provides uncertainties and covariances for the fitted model parameters and approximate Bayesian evidences. We use numerous mock surveys to illustrate and test the MML method, as well as to emphasize the necessity of accounting for observational uncertainties in MFs of modern galaxy surveys.

Adaptive grid methods for RLV environment assessment and nozzle analysis

NASA Technical Reports Server (NTRS)

Thornburg, Hugh J.

1996-01-01

Rapid access to highly accurate data about complex configurations is needed for multi-disciplinary optimization and design. In order to efficiently meet these requirements a closer coupling between the analysis algorithms and the discretization process is needed. In some cases, such as free surface, temporally varying geometries, and fluid structure interaction, the need is unavoidable. In other cases the need is to rapidly generate and modify high quality grids. Techniques such as unstructured and/or solution-adaptive methods can be used to speed the grid generation process and to automatically cluster mesh points in regions of interest. Global features of the flow can be significantly affected by isolated regions of inadequately resolved flow. These regions may not exhibit high gradients and can be difficult to detect. Thus excessive resolution in certain regions does not necessarily increase the accuracy of the overall solution. Several approaches have been employed for both structured and unstructured grid adaption. The most widely used involve grid point redistribution, local grid point enrichment/derefinement or local modification of the actual flow solver. However, the success of any one of these methods ultimately depends on the feature detection algorithm used to determine solution domain regions which require a fine mesh for their accurate representation. Typically, weight functions are constructed to mimic the local truncation error and may require substantial user input. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. These weight functions can then be used to construct blending functions for algebraic redistribution, interpolation functions for unstructured grid generation, forcing functions to attract/repel points in an elliptic system, or to trigger local refinement, based upon application of an equidistribution principle. The popularity of solution-adaptive techniques is growing in tandem with unstructured methods. The difficultly of precisely controlling mesh densities and orientations with current unstructured grid generation systems has driven the use of solution-adaptive meshing. Use of derivatives of density or pressure are widely used for construction of such weight functions, and have been proven very successful for inviscid flows with shocks. However, less success has been realized for flowfields with viscous layers, vortices or shocks of disparate strength. It is difficult to maintain the appropriate mesh point spacing in the various regions which require a fine spacing for adequate resolution. Mesh points often migrate from important regions due to refinement of dominant features. An example of this is the well know tendency of adaptive methods to increase the resolution of shocks in the flowfield around airfoils, but in the incorrect location due to inadequate resolution of the stagnation region. This problem has been the motivation for this research.

Nonlinear optical interactions in silicon waveguides

NASA Astrophysics Data System (ADS)

Kuyken, B.; Leo, F.; Clemmen, S.; Dave, U.; Van Laer, R.; Ideguchi, T.; Zhao, H.; Liu, X.; Safioui, J.; Coen, S.; Gorza, S. P.; Selvaraja, S. K.; Massar, S.; Osgood, R. M.; Verheyen, P.; Van Campenhout, J.; Baets, R.; Green, W. M. J.; Roelkens, G.

2017-03-01

The strong nonlinear response of silicon photonic nanowire waveguides allows for the integration of nonlinear optical functions on a chip. However, the detrimental nonlinear optical absorption in silicon at telecom wavelengths limits the efficiency of many such experiments. In this review, several approaches are proposed and demonstrated to overcome this fundamental issue. By using the proposed methods, we demonstrate amongst others supercontinuum generation, frequency comb generation, a parametric optical amplifier, and a parametric optical oscillator.

An architecture for efficient gravitational wave parameter estimation with multimodal linear surrogate models

NASA Astrophysics Data System (ADS)

O'Shaughnessy, Richard; Blackman, Jonathan; Field, Scott E.

2017-07-01

The recent direct observation of gravitational waves has further emphasized the desire for fast, low-cost, and accurate methods to infer the parameters of gravitational wave sources. Due to expense in waveform generation and data handling, the cost of evaluating the likelihood function limits the computational performance of these calculations. Building on recently developed surrogate models and a novel parameter estimation pipeline, we show how to quickly generate the likelihood function as an analytic, closed-form expression. Using a straightforward variant of a production-scale parameter estimation code, we demonstrate our method using surrogate models of effective-one-body and numerical relativity waveforms. Our study is the first time these models have been used for parameter estimation and one of the first ever parameter estimation calculations with multi-modal numerical relativity waveforms, which include all \\ell ≤slant 4 modes. Our grid-free method enables rapid parameter estimation for any waveform with a suitable reduced-order model. The methods described in this paper may also find use in other data analysis studies, such as vetting coincident events or the computation of the coalescing-compact-binary detection statistic.

Girsanov reweighting for path ensembles and Markov state models

NASA Astrophysics Data System (ADS)

Donati, L.; Hartmann, C.; Keller, B. G.

2017-06-01

The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor "on the fly" during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics.

AN ASSESSMENT OF MCNP WEIGHT WINDOWS

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

J. S. HENDRICKS; C. N. CULBERTSON

2000-01-01

The weight window variance reduction method in the general-purpose Monte Carlo N-Particle radiation transport code MCNPTM has recently been rewritten. In particular, it is now possible to generate weight window importance functions on a superimposed mesh, eliminating the need to subdivide geometries for variance reduction purposes. Our assessment addresses the following questions: (1) Does the new MCNP4C treatment utilize weight windows as well as the former MCNP4B treatment? (2) Does the new MCNP4C weight window generator generate importance functions as well as MCNP4B? (3) How do superimposed mesh weight windows compare to cell-based weight windows? (4) What are the shortcomingsmore » of the new MCNP4C weight window generator? Our assessment was carried out with five neutron and photon shielding problems chosen for their demanding variance reduction requirements. The problems were an oil well logging problem, the Oak Ridge fusion shielding benchmark problem, a photon skyshine problem, an air-over-ground problem, and a sample problem for variance reduction.« less

Generation of Leishmania Hybrids by Whole Genomic DNA Transformation

PubMed Central

Coelho, Adriano C.; Leprohon, Philippe; Ouellette, Marc

2012-01-01

Genetic exchange is a powerful tool to study gene function in microorganisms. Here, we tested the feasibility of generating Leishmania hybrids by electroporating genomic DNA of donor cells into recipient Leishmania parasites. The donor DNA was marked with a drug resistance marker facilitating the selection of DNA transfer into the recipient cells. The transferred DNA was integrated exclusively at homologous locus and was as large as 45 kb. The independent generation of L. infantum hybrids with L. major sequences was possible for several chromosomal regions. Interfering with the mismatch repair machinery by inactivating the MSH2 gene enabled an increased efficiency of recombination between divergent sequences, hence favouring the selection of hybrids between species. Hybrids were shown to acquire the phenotype derived from the donor cells, as demonstrated for the transfer of drug resistance genes from L. major into L. infantum. The described method is a first step allowing the generation of in vitro hybrids for testing gene functions in a natural genomic context in the parasite Leishmania. PMID:23029579

Statistical properties and correlation functions for drift waves

NASA Technical Reports Server (NTRS)

Horton, W.

1986-01-01

The dissipative one-field drift wave equation is solved using the pseudospectral method to generate steady-state fluctuations. The fluctuations are analyzed in terms of space-time correlation functions and modal probability distributions. Nearly Gaussian statistics and exponential decay of the two-time correlation functions occur in the presence of electron dissipation, while in the absence of electron dissipation long-lived vortical structures occur. Formulas from renormalized, Markovianized statistical turbulence theory are given in a local approximation to interpret the dissipative turbulence.

A Rapid Aerodynamic Design Procedure Based on Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2001-01-01

An aerodynamic design procedure that uses neural networks to model the functional behavior of the objective function in design space has been developed. This method incorporates several improvements to an earlier method that employed a strategy called parameter-based partitioning of the design space in order to reduce the computational costs associated with design optimization. As with the earlier method, the current method uses a sequence of response surfaces to traverse the design space in search of the optimal solution. The new method yields significant reductions in computational costs by using composite response surfaces with better generalization capabilities and by exploiting synergies between the optimization method and the simulation codes used to generate the training data. These reductions in design optimization costs are demonstrated for a turbine airfoil design study where a generic shape is evolved into an optimal airfoil.

Free boundary skin current magnetohydrodynamic equilibria

NASA Astrophysics Data System (ADS)

Reusch, Michael F.

1988-10-01

Function theoretic methods in the complex plane are used to develop simple parametric hodograph formulas that generate sharp boundary equilibria of arbitrary shape. The related method of Gorenflo [Z. Angew. Math. Phys. 16, 279 (1965)] and Merkel (Ph.D. thesis, University of Munich, 1965) is discussed. A numerical technique for the construction of solutions, based on one of the methods, is presented. A study is made of the bifurcations of an equilibrium of general form.

A genetic-algorithm approach for assessing the liquefaction potential of sandy soils

NASA Astrophysics Data System (ADS)

Sen, G.; Akyol, E.

2010-04-01

The determination of liquefaction potential is required to take into account a large number of parameters, which creates a complex nonlinear structure of the liquefaction phenomenon. The conventional methods rely on simple statistical and empirical relations or charts. However, they cannot characterise these complexities. Genetic algorithms are suited to solve these types of problems. A genetic algorithm-based model has been developed to determine the liquefaction potential by confirming Cone Penetration Test datasets derived from case studies of sandy soils. Software has been developed that uses genetic algorithms for the parameter selection and assessment of liquefaction potential. Then several estimation functions for the assessment of a Liquefaction Index have been generated from the dataset. The generated Liquefaction Index estimation functions were evaluated by assessing the training and test data. The suggested formulation estimates the liquefaction occurrence with significant accuracy. Besides, the parametric study on the liquefaction index curves shows a good relation with the physical behaviour. The total number of misestimated cases was only 7.8% for the proposed method, which is quite low when compared to another commonly used method.

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

Sequence-independent construction of ordered combinatorial libraries with predefined crossover points.

PubMed

Jézéquel, Laetitia; Loeper, Jacqueline; Pompon, Denis

2008-11-01

Combinatorial libraries coding for mosaic enzymes with predefined crossover points constitute useful tools to address and model structure-function relationships and for functional optimization of enzymes based on multivariate statistics. The presented method, called sequence-independent generation of a chimera-ordered library (SIGNAL), allows easy shuffling of any predefined amino acid segment between two or more proteins. This method is particularly well adapted to the exchange of protein structural modules. The procedure could also be well suited to generate ordered combinatorial libraries independent of sequence similarities in a robotized manner. Sequence segments to be recombined are first extracted by PCR from a single-stranded template coding for an enzyme of interest using a biotin-avidin-based method. This technique allows the reduction of parental template contamination in the final library. Specific PCR primers allow amplification of two complementary mosaic DNA fragments, overlapping in the region to be exchanged. Fragments are finally reassembled using a fusion PCR. The process is illustrated via the construction of a set of mosaic CYP2B enzymes using this highly modular approach.

Drawing Sensors with Ball-Milled Blends of Metal-Organic Frameworks and Graphite

PubMed Central

Ko, Michael; Aykanat, Aylin; Smith, Merry K.

2017-01-01

The synthetically tunable properties and intrinsic porosity of conductive metal-organic frameworks (MOFs) make them promising materials for transducing selective interactions with gaseous analytes in an electrically addressable platform. Consequently, conductive MOFs are valuable functional materials with high potential utility in chemical detection. The implementation of these materials, however, is limited by the available methods for device incorporation due to their poor solubility and moderate electrical conductivity. This manuscript describes a straightforward method for the integration of moderately conductive MOFs into chemiresistive sensors by mechanical abrasion. To improve electrical contacts, blends of MOFs with graphite were generated using a solvent-free ball-milling procedure. While most bulk powders of pure conductive MOFs were difficult to integrate into devices directly via mechanical abrasion, the compressed solid-state MOF/graphite blends were easily abraded onto the surface of paper substrates equipped with gold electrodes to generate functional sensors. This method was used to prepare an array of chemiresistors, from four conductive MOFs, capable of detecting and differentiating NH3, H2S and NO at parts-per-million concentrations. PMID:28946624

LINKING LUNG AIRWAY STRUCTURE TO PULMONARY FUNCTION VIA COMPOSITE BRIDGE REGRESSION

PubMed Central

Chen, Kun; Hoffman, Eric A.; Seetharaman, Indu; Jiao, Feiran; Lin, Ching-Long; Chan, Kung-Sik

2017-01-01

The human lung airway is a complex inverted tree-like structure. Detailed airway measurements can be extracted from MDCT-scanned lung images, such as segmental wall thickness, airway diameter, parent-child branch angles, etc. The wealth of lung airway data provides a unique opportunity for advancing our understanding of the fundamental structure-function relationships within the lung. An important problem is to construct and identify important lung airway features in normal subjects and connect these to standardized pulmonary function test results such as FEV1%. Among other things, the problem is complicated by the fact that a particular airway feature may be an important (relevant) predictor only when it pertains to segments of certain generations. Thus, the key is an efficient, consistent method for simultaneously conducting group selection (lung airway feature types) and within-group variable selection (airway generations), i.e., bi-level selection. Here we streamline a comprehensive procedure to process the lung airway data via imputation, normalization, transformation and groupwise principal component analysis, and then adopt a new composite penalized regression approach for conducting bi-level feature selection. As a prototype of composite penalization, the proposed composite bridge regression method is shown to admit an efficient algorithm, enjoy bi-level oracle properties, and outperform several existing methods. We analyze the MDCT lung image data from a cohort of 132 subjects with normal lung function. Our results show that, lung function in terms of FEV1% is promoted by having a less dense and more homogeneous lung comprising an airway whose segments enjoy more heterogeneity in wall thicknesses, larger mean diameters, lumen areas and branch angles. These data hold the potential of defining more accurately the “normal” subject population with borderline atypical lung functions that are clearly influenced by many genetic and environmental factors. PMID:28280520

An Application of Cartesian-Grid and Volume-of-Fluid Methods to Numerical Ship Hydrodynamics

DTIC Science & Technology

2007-10-01

water-particle ve- locity is discontinuous across the air-water interface, and where CiEA is the Levi - Civita function. rj is the moment the vertical...methods and volume-of- immersed- body and volume-of-fluid (VOF) methods. fluid methods is used to simulate breaking waves around The governing equations are...of a ship hull is used as input to automat- body -fitted grids. The sole geometric input into NFA ically generate an immersed-boundary representation of

Creating Fidelitious Climate Data Records from Meteosat First Generation Observations

NASA Astrophysics Data System (ADS)

Quast, Ralf; Govaerts, Yves; Ruthrich, Frank; Giering, Ralf; Roebeling, Rob

2016-08-01

A novel method for reconstructing the spectral response function of the Meteosat visible (VIS) channels is presented and applied to the Meteosat-10 Spinning Enhanced Visible and Infrared Imager (SEVIRI) high-resolution visible (HRV) channel as the first real-world benchmark. The method incorporates advanced radiative transfer modelling and inverse modelling techniques. Once established, EUMETSAT will use the reconstructed spectral response and uncertainty information to increase the calibration accuracy of Meteosat First Generation VIS observations, which will provide the basis for the Fidelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) Horizon 2020 project to produce new fundamental (reflectance) and thematic (albedo and aerosol) climate data records.

Multiplexed genome engineering and genotyping methods applications for synthetic biology and metabolic engineering.

PubMed

Wang, Harris H; Church, George M

2011-01-01

Engineering at the scale of whole genomes requires fundamentally new molecular biology tools. Recent advances in recombineering using synthetic oligonucleotides enable the rapid generation of mutants at high efficiency and specificity and can be implemented at the genome scale. With these techniques, libraries of mutants can be generated, from which individuals with functionally useful phenotypes can be isolated. Furthermore, populations of cells can be evolved in situ by directed evolution using complex pools of oligonucleotides. Here, we discuss ways to utilize these multiplexed genome engineering methods, with special emphasis on experimental design and implementation. Copyright © 2011 Elsevier Inc. All rights reserved.

Beyond the Divinyl Ketone: Innovations in the Generation and Nazarov Cyclization of Pentadienyl Cation Intermediates

PubMed Central

Spencer, William T.; Vaidya, Tulaza; Frontier, Alison J.

2013-01-01

The requirement for new strategies for synthesizing five-membered carbocycles has driven an expansion in the study of the Nazarov cyclization. This renewed interest in the reaction has led to the discovery of several interesting new methods for generating the pentadienyl cation intermediate central to the cyclization. Methods reviewed include carbon-heteroatom ionization, functionalization of a double bond, nucleophilic addition, or electrocyclic ring opening. Additional variations employ unconventional substrates to produce novel pentacycles, such as the iso- and imino-Nazarov. Herein, we provide an overview of these unconventional, yet highly useful versions of the Nazarov cyclization. PMID:24348092

Dynamic state estimation assisted power system monitoring and protection

NASA Astrophysics Data System (ADS)

Cui, Yinan

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the energy function for the system. This establishes a direct correspondence (or mapping) between an event and certain component(s) of the energy function. The last paper considers the dynamic latency effect when the measurements and estimated dynamics are transmitted from remote ends to a centralized location through the networks.

The ssWavelets package

Treesearch

Jeffrey H. Gove

2017-01-01

This package adds several classes, generics and associated methods as well as a few various functions to help with wavelet decomposition of sampling surfaces generated using sampSurf. As such, it can be thought of as an extension to sampSurf for wavelet analysis.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Numerical integration of discontinuous functions: moment fitting and smart octree

NASA Astrophysics Data System (ADS)

Hubrich, Simeon; Di Stolfo, Paolo; Kudela, László; Kollmannsberger, Stefan; Rank, Ernst; Schröder, Andreas; Düster, Alexander

2017-11-01

A fast and simple grid generation can be achieved by non-standard discretization methods where the mesh does not conform to the boundary or the internal interfaces of the problem. However, this simplification leads to discontinuous integrands for intersected elements and, therefore, standard quadrature rules do not perform well anymore. Consequently, special methods are required for the numerical integration. To this end, we present two approaches to obtain quadrature rules for arbitrary domains. The first approach is based on an extension of the moment fitting method combined with an optimization strategy for the position and weights of the quadrature points. In the second approach, we apply the smart octree, which generates curved sub-cells for the integration mesh. To demonstrate the performance of the proposed methods, we consider several numerical examples, showing that the methods lead to efficient quadrature rules, resulting in less integration points and in high accuracy.

Automatic transfer function generation for volume rendering of high-resolution x-ray 3D digital mammography images

NASA Astrophysics Data System (ADS)

Alyassin, Abdal M.

2002-05-01

3D Digital mammography (3DDM) is a new technology that provides high resolution X-ray breast tomographic data. Like any other tomographic medical imaging modalities, viewing a stack of tomographic images may require time especially if the images are of large matrix size. In addition, it may cause difficulty to conceptually construct 3D breast structures. Therefore, there is a need to readily visualize the data in 3D. However, one of the issues that hinder the usage of volume rendering (VR) is finding an automatic way to generate transfer functions that efficiently map the important diagnostic information in the data. We have developed a method that randomly samples the volume. Based on the mean and the standard deviation of these samples, the technique determines the lower limit and upper limit of a piecewise linear ramp transfer function. We have volume rendered several 3DDM data using this technique and compared visually the outcome with the result from a conventional automatic technique. The transfer function generated through the proposed technique provided superior VR images over the conventional technique. Furthermore, the improvement in the reproducibility of the transfer function correlated with the number of samples taken from the volume at the expense of the processing time.

Fast semi-analytical method for precise prediction of ion energy distribution functions and sheath electric field in multi-frequency capacitively coupled plasmas

NASA Astrophysics Data System (ADS)

Chen, Wencong; Zhang, Xi; Diao, Dongfeng

2018-05-01

We propose a fast semi-analytical method to predict ion energy distribution functions and sheath electric field in multi-frequency capacitively coupled plasmas, which are difficult to measure in commercial plasma reactors. In the intermediate frequency regime, the ion density within the sheath is strongly modulated by the low-frequency sheath electric field, making the time-independent ion density assumption employed in conventional models invalid. Our results are in a good agreement with experimental measurements and computer simulations. The application of this method will facilitate the understanding of ion–material interaction mechanisms and development of new-generation plasma etching devices.

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

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

Gao, H

2015-06-15

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “themore » test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

DFTB3: Extension of the self-consistent-charge density-functional tight-binding method (SCC-DFTB).

PubMed

Gaus, Michael; Cui, Qiang; Elstner, Marcus

2012-04-10

The self-consistent-charge density-functional tight-binding method (SCC-DFTB) is an approximate quantum chemical method derived from density functional theory (DFT) based on a second-order expansion of the DFT total energy around a reference density. In the present study we combine earlier extensions and improve them consistently with, first, an improved Coulomb interaction between atomic partial charges, and second, the complete third-order expansion of the DFT total energy. These modifications lead us to the next generation of the DFTB methodology called DFTB3, which substantially improves the description of charged systems containing elements C, H, N, O, and P, especially regarding hydrogen binding energies and proton affinities. As a result, DFTB3 is particularly applicable to biomolecular systems. Remaining challenges and possible solutions are also briefly discussed.

First-Principles Framework to Compute Sum-Frequency Generation Vibrational Spectra of Semiconductors and Insulators.

PubMed

Wan, Quan; Galli, Giulia

2015-12-11

We present a first-principles framework to compute sum-frequency generation (SFG) vibrational spectra of semiconductors and insulators. The method is based on density functional theory and the use of maximally localized Wannier functions to compute the response to electric fields, and it includes the effect of electric field gradients at surfaces. In addition, it includes quadrupole contributions to SFG spectra, thus enabling the verification of the dipole approximation, whose validity determines the surface specificity of SFG spectroscopy. We compute the SFG spectra of ice I_{h} basal surfaces and identify which spectra components are affected by bulk contributions. Our results are in good agreement with experiments at low temperature.

Adaptive sparsest narrow-band decomposition method and its applications to rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Junsheng; Peng, Yanfeng; Yang, Yu; Wu, Zhantao

2017-02-01

Enlightened by ASTFA method, adaptive sparsest narrow-band decomposition (ASNBD) method is proposed in this paper. In ASNBD method, an optimized filter must be established at first. The parameters of the filter are determined by solving a nonlinear optimization problem. A regulated differential operator is used as the objective function so that each component is constrained to be a local narrow-band signal. Afterwards, the signal is filtered by the optimized filter to generate an intrinsic narrow-band component (INBC). ASNBD is proposed aiming at solving the problems existed in ASTFA. Gauss-Newton type method, which is applied to solve the optimization problem in ASTFA, is irreplaceable and very sensitive to initial values. However, more appropriate optimization method such as genetic algorithm (GA) can be utilized to solve the optimization problem in ASNBD. Meanwhile, compared with ASTFA, the decomposition results generated by ASNBD have better physical meaning by constraining the components to be local narrow-band signals. Comparisons are made between ASNBD, ASTFA and EMD by analyzing simulation and experimental signals. The results indicate that ASNBD method is superior to the other two methods in generating more accurate components from noise signal, restraining the boundary effect, possessing better orthogonality and diagnosing rolling element bearing fault.

Experimental observation of acoustic emissions generated by a pulsed proton beam from a hospital-based clinical cyclotron.

PubMed

Jones, Kevin C; Vander Stappen, François; Bawiec, Christopher R; Janssens, Guillaume; Lewin, Peter A; Prieels, Damien; Solberg, Timothy D; Sehgal, Chandra M; Avery, Stephen

2015-12-01

To measure the acoustic signal generated by a pulsed proton spill from a hospital-based clinical cyclotron. An electronic function generator modulated the IBA C230 isochronous cyclotron to create a pulsed proton beam. The acoustic emissions generated by the proton beam were measured in water using a hydrophone. The acoustic measurements were repeated with increasing proton current and increasing distance between detector and beam. The cyclotron generated proton spills with rise times of 18 μs and a maximum measured instantaneous proton current of 790 nA. Acoustic emissions generated by the proton energy deposition were measured to be on the order of mPa. The origin of the acoustic wave was identified as the proton beam based on the correlation between acoustic emission arrival time and distance between the hydrophone and proton beam. The acoustic frequency spectrum peaked at 10 kHz, and the acoustic pressure amplitude increased monotonically with increasing proton current. The authors report the first observation of acoustic emissions generated by a proton beam from a hospital-based clinical cyclotron. When modulated by an electronic function generator, the cyclotron is capable of creating proton spills with fast rise times (18 μs) and high instantaneous currents (790 nA). Measurements of the proton-generated acoustic emissions in a clinical setting may provide a method for in vivo proton range verification and patient monitoring.

Release strategies for making transferable semiconductor structures, devices and device components

DOEpatents

Rogers, John A; Nuzzo, Ralph G; Meitl, Matthew; Ko, Heung Cho; Yoon, Jongseung; Menard, Etienne; Baca, Alfred J

2014-11-25

Provided are methods for making a device or device component by providing a multilayer structure having a plurality of functional layers and a plurality of release layers and releasing the functional layers from the multilayer structure by separating one or more of the release layers to generate a plurality of transferable structures. The transferable structures are printed onto a device substrate or device component supported by a device substrate. The methods and systems provide means for making high-quality and low-cost photovoltaic devices, transferable semiconductor structures, (opto-)electronic devices and device components.

Release strategies for making transferable semiconductor structures, devices and device components

DOEpatents

Rogers, John A [Champaign, IL; Nuzzo, Ralph G [Champaign, IL; Meitl, Matthew [Raleigh, NC; Ko, Heung Cho [Urbana, IL; Yoon, Jongseung [Urbana, IL; Menard, Etienne [Durham, NC; Baca, Alfred J [Urbana, IL

2011-04-26

Provided are methods for making a device or device component by providing a multilayer structure having a plurality of functional layers and a plurality of release layers and releasing the functional layers from the multilayer structure by separating one or more of the release layers to generate a plurality of transferable structures. The transferable structures are printed onto a device substrate or device component supported by a device substrate. The methods and systems provide means for making high-quality and low-cost photovoltaic devices, transferable semiconductor structures, (opto-)electronic devices and device components.

Application of the MNA design method to a nonlinear turbofan engine. [multivariable Nyquist array method

NASA Technical Reports Server (NTRS)

Leininger, G. G.

1981-01-01

Using nonlinear digital simulation as a representative model of the dynamic operation of the QCSEE turbofan engine, a feedback control system is designed by variable frequency design techniques. Transfer functions are generated for each of five power level settings covering the range of operation from approach power to full throttle (62.5% to 100% full power). These transfer functions are then used by an interactive control system design synthesis program to provide a closed loop feedback control using the multivariable Nyquist array and extensions to multivariable Bode diagrams and Nichols charts.