Endogenous Retroviruses in the Genomics Era.

PubMed

Johnson, Welkin E

2015-11-01

Endogenous retroviruses comprise millions of discrete genetic loci distributed within the genomes of extant vertebrates. These sequences, which are clearly related to exogenous retroviruses, represent retroviral infections of the deep past, and their abundance suggests that retroviruses were a near-constant presence throughout the evolutionary history of modern vertebrates. Endogenous retroviruses contribute in myriad ways to the evolution of host genomes, as mutagens and as sources of genetic novelty (both coding and regulatory) to be acted upon by the twin engines of random genetic drift and natural selection. Importantly, the richness and complexity of endogenous retrovirus data can be used to understand how viruses spread and adapt on evolutionary timescales by combining population genetics and evolutionary theory with a detailed understanding of retrovirus biology (gleaned from the study of extant retroviruses). In addition to revealing the impact of viruses on organismal evolution, such studies can help us better understand, by looking back in time, how life-history traits, as well as ecological and geological events, influence the movement of viruses within and between populations.

Robustness of quantum key distribution with discrete and continuous variables to channel noise

NASA Astrophysics Data System (ADS)

Lasota, Mikołaj; Filip, Radim; Usenko, Vladyslav C.

2017-06-01

We study the robustness of quantum key distribution protocols using discrete or continuous variables to the channel noise. We introduce the model of such noise based on coupling of the signal to a thermal reservoir, typical for continuous-variable quantum key distribution, to the discrete-variable case. Then we perform a comparison of the bounds on the tolerable channel noise between these two kinds of protocols using the same noise parametrization, in the case of implementation which is perfect otherwise. Obtained results show that continuous-variable protocols can exhibit similar robustness to the channel noise when the transmittance of the channel is relatively high. However, for strong loss discrete-variable protocols are superior and can overcome even the infinite-squeezing continuous-variable protocol while using limited nonclassical resources. The requirement on the probability of a single-photon production which would have to be fulfilled by a practical source of photons in order to demonstrate such superiority is feasible thanks to the recent rapid development in this field.

Antioxidant mediated response of Scoparia dulcis in noise-induced redox imbalance and immunohistochemical changes in rat brain.

PubMed

Wankhar, Wankupar; Srinivasan, Sakthivel; Rajan, Ravindran; Sheeladevi, Rathinasamy

2017-01-19

Noise has been regarded as an environmental/occupational stressor that causes damages to both auditory and non-auditory organs. Prolonged exposure to these mediators of stress has often resulted in detrimental effect, where oxidative/nitrosative stress plays a major role. Hence, it would be appropriate to examine the possible role of free radicals in brain discrete regions and the "antioxidants" mediated response of S. dulcis. Animals were subjected to noise stress for 15 days (100 dB/4 hours/day) and estimation of endogenous free radical and antioxidant activity were carried out on brain discrete regions (the cerebral cortex, cerebellum, brainstem, striatum, hippocampus and hypothalamus). The result showed that exposure to noise could alleviate endogenous free radical generation and altered antioxidant status in brain discrete regions when compared to that of the control groups. This alleviated free radical generation (H 2 O 2 and NO) is well supported by an upregulated protein expression on immunohistochemistry of both iNOS and nNOS in the cerebral cortex on exposure to noise stress. These findings suggest that increased free radical generation and altered anti-oxidative status can cause redox imbalance in the brain discrete regions. However, free radical scavenging activity of the plant was evident as the noise exposed group treated with S. dulcis[200 mg/(kg·b·w)] displayed a therapeutic effect by decreasing the free radical level and regulate the anti-oxidative status to that of control animals. Hence, it can be concluded that the efficacy of S. dulcis could be attributed to its free radical scavenging activity and anti-oxidative property.

Antioxidant mediated response of Scoparia dulcis in noise-induced redox imbalance and immunohistochemical changes in rat brain

PubMed Central

Wankhar, Wankupar; Srinivasan, Sakthivel; Rajan, Ravindran; Sheeladevi, Rathinasamy

2017-01-01

Noise has been regarded as an environmental/occupational stressor that causes damages to both auditory and non-auditory organs. Prolonged exposure to these mediators of stress has often resulted in detrimental effect, where oxidative/nitrosative stress plays a major role. Hence, it would be appropriate to examine the possible role of free radicals in brain discrete regions and the "antioxidants" mediated response of S. dulcis. Animals were subjected to noise stress for 15 days (100 dB/4 hours/day) and estimation of endogenous free radical and antioxidant activity were carried out on brain discrete regions (the cerebral cortex, cerebellum, brainstem, striatum, hippocampus and hypothalamus). The result showed that exposure to noise could alleviate endogenous free radical generation and altered antioxidant status in brain discrete regions when compared to that of the control groups. This alleviated free radical generation (H2O2 and NO) is well supported by an upregulated protein expression on immunohistochemistry of both iNOS and nNOS in the cerebral cortex on exposure to noise stress. These findings suggest that increased free radical generation and altered anti-oxidative status can cause redox imbalance in the brain discrete regions. However, free radical scavenging activity of the plant was evident as the noise exposed group treated with S. dulcis[200 mg/(kg·b·w)] displayed a therapeutic effect by decreasing the free radical level and regulate the anti-oxidative status to that of control animals. Hence, it can be concluded that the efficacy of S. dulcis could be attributed to its free radical scavenging activity and anti-oxidative property. PMID:28808196

An instrumental variable random-coefficients model for binary outcomes

PubMed Central

Chesher, Andrew; Rosen, Adam M

2014-01-01

In this paper, we study a random-coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be required for a control function approach. The model fits within the spectrum of generalized instrumental variable models, and we thus apply identification results from our previous studies of such models to the present context, demonstrating their use. Specifically, we characterize the identified set for the distribution of random coefficients in the binary response model with endogeneity via a collection of conditional moment inequalities, and we investigate the structure of these sets by way of numerical illustration. PMID:25798048

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory

PubMed Central

Pratte, Michael S.; Park, Young Eun; Rademaker, Rosanne L.; Tong, Frank

2016-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced “oblique effect”, with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. PMID:28004957

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

PubMed

Pratte, Michael S; Park, Young Eun; Rademaker, Rosanne L; Tong, Frank

2017-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced "oblique effect," with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Structural Equation Models in a Redundancy Analysis Framework With Covariates.

PubMed

Lovaglio, Pietro Giorgio; Vittadini, Giorgio

2014-01-01

A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.

Exogenic and endogenic albedo and color patterns on Europa

NASA Technical Reports Server (NTRS)

Mcewen, A. S.

1986-01-01

New global and high-resolution multispectral mosaics of Europa have been produced from the Voyager imaging data. Photometric normalizations are based on multiple-image techniques that explicitly account for intrinsic albedo variations through pixel-by-pixel solutions. The exogenic color and albedo pattern on Europa is described by a second-order function of the cosine of the angular distance from the apex of orbital motion. On the basis of this second-order function and of color trends that are different on the leading and trailing hemispheres, the exogenic pattern is interpreted as being due to equilibrium between two dominant processes: (1) impact gardening and (2) magnetospheric interactions, including sulfur-ion implantation and sputtering redistribution. Removal of the model exogenic pattern in the mosaics reveals the endogenic variations, consisting of only two major units: darker (redder) and bright materials. Therefore Europa's visual spectral reflectivity is simple, having one continuous exogenic pattern and two discrete endogenic units.

Maximum-entropy probability distributions under Lp-norm constraints

NASA Technical Reports Server (NTRS)

Dolinar, S.

1991-01-01

Continuous probability density functions and discrete probability mass functions are tabulated which maximize the differential entropy or absolute entropy, respectively, among all probability distributions with a given L sub p norm (i.e., a given pth absolute moment when p is a finite integer) and unconstrained or constrained value set. Expressions for the maximum entropy are evaluated as functions of the L sub p norm. The most interesting results are obtained and plotted for unconstrained (real valued) continuous random variables and for integer valued discrete random variables. The maximum entropy expressions are obtained in closed form for unconstrained continuous random variables, and in this case there is a simple straight line relationship between the maximum differential entropy and the logarithm of the L sub p norm. Corresponding expressions for arbitrary discrete and constrained continuous random variables are given parametrically; closed form expressions are available only for special cases. However, simpler alternative bounds on the maximum entropy of integer valued discrete random variables are obtained by applying the differential entropy results to continuous random variables which approximate the integer valued random variables in a natural manner. All the results are presented in an integrated framework that includes continuous and discrete random variables, constraints on the permissible value set, and all possible values of p. Understanding such as this is useful in evaluating the performance of data compression schemes.

An energy-stable method for solving the incompressible Navier-Stokes equations with non-slip boundary condition

NASA Astrophysics Data System (ADS)

Lee, Byungjoon; Min, Chohong

2018-05-01

We introduce a stable method for solving the incompressible Navier-Stokes equations with variable density and viscosity. Our method is stable in the sense that it does not increase the total energy of dynamics that is the sum of kinetic energy and potential energy. Instead of velocity, a new state variable is taken so that the kinetic energy is formulated by the L2 norm of the new variable. Navier-Stokes equations are rephrased with respect to the new variable, and a stable time discretization for the rephrased equations is presented. Taking into consideration the incompressibility in the Marker-And-Cell (MAC) grid, we present a modified Lax-Friedrich method that is L2 stable. Utilizing the discrete integration-by-parts in MAC grid and the modified Lax-Friedrich method, the time discretization is fully discretized. An explicit CFL condition for the stability of the full discretization is given and mathematically proved.

Structural Equations and Path Analysis for Discrete Data.

ERIC Educational Resources Information Center

Winship, Christopher; Mare, Robert D.

1983-01-01

Presented is an approach to causal models in which some or all variables are discretely measured, showing that path analytic methods permit quantification of causal relationships among variables with the same flexibility and power of interpretation as is feasible in models including only continuous variables. Examples are provided. (Author/IS)

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

ERIC Educational Resources Information Center

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids by Using Complex Variables

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Kleb, William L.

2005-01-01

A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids Using Complex Variables

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Kleb, William L.

2005-01-01

A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.

Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching

NASA Astrophysics Data System (ADS)

Shen, Kaiming; Yu, Wei

2018-05-01

This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multi-cell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Further, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.

Causal relationship model between variables using linear regression to improve professional commitment of lecturer

NASA Astrophysics Data System (ADS)

Setyaningsih, S.

2017-01-01

The main element to build a leading university requires lecturer commitment in a professional manner. Commitment is measured through willpower, loyalty, pride, loyalty, and integrity as a professional lecturer. A total of 135 from 337 university lecturers were sampled to collect data. Data were analyzed using validity and reliability test and multiple linear regression. Many studies have found a link on the commitment of lecturers, but the basic cause of the causal relationship is generally neglected. These results indicate that the professional commitment of lecturers affected by variables empowerment, academic culture, and trust. The relationship model between variables is composed of three substructures. The first substructure consists of endogenous variables professional commitment and exogenous three variables, namely the academic culture, empowerment and trust, as well as residue variable ɛ y . The second substructure consists of one endogenous variable that is trust and two exogenous variables, namely empowerment and academic culture and the residue variable ɛ 3. The third substructure consists of one endogenous variable, namely the academic culture and exogenous variables, namely empowerment as well as residue variable ɛ 2. Multiple linear regression was used in the path model for each substructure. The results showed that the hypothesis has been proved and these findings provide empirical evidence that increasing the variables will have an impact on increasing the professional commitment of the lecturers.

The discrete hungry Lotka Volterra system and a new algorithm for computing matrix eigenvalues

NASA Astrophysics Data System (ADS)

Fukuda, Akiko; Ishiwata, Emiko; Iwasaki, Masashi; Nakamura, Yoshimasa

2009-01-01

The discrete hungry Lotka-Volterra (dhLV) system is a generalization of the discrete Lotka-Volterra (dLV) system which stands for a prey-predator model in mathematical biology. In this paper, we show that (1) some invariants exist which are expressed by dhLV variables and are independent from the discrete time and (2) a dhLV variable converges to some positive constant or zero as the discrete time becomes sufficiently large. Some characteristic polynomial is then factorized with the help of the dhLV system. The asymptotic behaviour of the dhLV system enables us to design an algorithm for computing complex eigenvalues of a certain band matrix.

Some applications of uncertainty relations in quantum information

NASA Astrophysics Data System (ADS)

Majumdar, A. S.; Pramanik, T.

2016-08-01

We discuss some applications of various versions of uncertainty relations for both discrete and continuous variables in the context of quantum information theory. The Heisenberg uncertainty relation enables demonstration of the Einstein, Podolsky and Rosen (EPR) paradox. Entropic uncertainty relations (EURs) are used to reveal quantum steering for non-Gaussian continuous variable states. EURs for discrete variables are studied in the context of quantum memory where fine-graining yields the optimum lower bound of uncertainty. The fine-grained uncertainty relation is used to obtain connections between uncertainty and the nonlocality of retrieval games for bipartite and tripartite systems. The Robertson-Schrödinger (RS) uncertainty relation is applied for distinguishing pure and mixed states of discrete variables.

Discretization of 3d gravity in different polarizations

NASA Astrophysics Data System (ADS)

Dupuis, Maïté; Freidel, Laurent; Girelli, Florian

2017-10-01

We study the discretization of three-dimensional gravity with Λ =0 following the loop quantum gravity framework. In the process, we realize that different choices of polarization are possible. This allows us to introduce a new discretization based on the triad as opposed to the connection as in the standard loop quantum gravity framework. We also identify the classical nontrivial symmetries of discrete gravity, namely the Drinfeld double, given in terms of momentum maps. Another choice of polarization is given by the Chern-Simons formulation of gravity. Our framework also provides a new discretization scheme of Chern-Simons, which keeps track of the link between the continuum variables and the discrete ones. We show how the Poisson bracket we recover between the Chern-Simons holonomies allows us to recover the Goldman bracket. There is also a transparent link between the discrete Chern-Simons formulation and the discretization of gravity based on the connection (loop gravity) or triad variables (dual loop gravity).

Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables.

PubMed

Fagerland, Morten W; Sandvik, Leiv; Mowinckel, Petter

2011-04-13

The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables. Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure. The Welch U test (the T test with adjustment for unequal variances) and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group). The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily. The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.

A comparative study of human IgE binding to proteins of a genetically modified (GM) soybean and six non-GM soybeans grown in multiple locations.

PubMed

Lu, Mei; Jin, Yuan; Ballmer-Weber, Barbara; Goodman, Richard E

2018-02-01

Prior to commercialization, genetically modified (GM) crops are evaluated to determine the allergenicity of the newly expressed protein. Some regulators require an evaluation of endogenous allergens in commonly allergenic crops including soybean to determine if genetic transformation increased endogenous allergen concentrations, even asking for IgE testing using sera from individual sensitized subjects. Little is known about the variability of the expression of endogenous allergens among non-GM varieties or under different environmental conditions. We tested IgE binding to endogenous allergenic proteins in an experimental non-commercial GM line, a non-GM near-isoline control, and five non-GM commercial soybean lines replicated at three geographically separated locations. One-dimensional (1D) and two-dimensional (2D) immunoblotting and ELISA were performed using serum or plasma from eleven soybean allergic patients. The results of immunoblots and ELISA showed no significant differences in IgE binding between the GM line and its non-GM near-isoline control. However, some distinct differences in IgE binding patterns were observed among the non-GM commercial soybean lines and between different locations, highlighting the inherent variability in endogenous allergenic proteins. Understanding the potential variability in the levels of endogenous allergens is necessary to establish a standard of acceptance for GM soybeans compared to non-GM soybean events and lines. Copyright © 2018. Published by Elsevier Ltd.

Endogenous central amygdala mu-opioid receptor signaling promotes sodium appetite in mice.

PubMed

Smith, Craig M; Walker, Lesley L; Leeboonngam, Tanawan; McKinley, Michael J; Denton, Derek A; Lawrence, Andrew J

2016-11-29

Due to the importance of dietary sodium and its paucity within many inland environments, terrestrial animals have evolved an instinctive sodium appetite that is commensurate with sodium deficiency. Despite a well-established role for central opioid signaling in sodium appetite, the endogenous influence of specific opioid receptor subtypes within distinct brain regions remains to be elucidated. Using selective pharmacological antagonists of opioid receptor subtypes, we reveal that endogenous mu-opioid receptor (MOR) signaling strongly drives sodium appetite in sodium-depleted mice, whereas a role for kappa (KOR) and delta (DOR) opioid receptor signaling was not detected, at least in sodium-depleted mice. Fos immunohistochemistry revealed discrete regions of the mouse brain displaying an increased number of activated neurons during sodium gratification: the rostral portion of the nucleus of the solitary tract (rNTS), the lateral parabrachial nucleus (LPB), and the central amygdala (CeA). The CeA was subsequently targeted with bilateral infusions of the MOR antagonist naloxonazine, which significantly reduced sodium appetite in mice. The CeA is therefore identified as a key node in the circuit that contributes to sodium appetite. Moreover, endogenous opioids, acting via MOR, within the CeA promote this form of appetitive behavior.

Endogenous central amygdala mu-opioid receptor signaling promotes sodium appetite in mice

PubMed Central

Smith, Craig M.; Walker, Lesley L.; Leeboonngam, Tanawan; McKinley, Michael J.; Denton, Derek A.; Lawrence, Andrew J.

2016-01-01

Due to the importance of dietary sodium and its paucity within many inland environments, terrestrial animals have evolved an instinctive sodium appetite that is commensurate with sodium deficiency. Despite a well-established role for central opioid signaling in sodium appetite, the endogenous influence of specific opioid receptor subtypes within distinct brain regions remains to be elucidated. Using selective pharmacological antagonists of opioid receptor subtypes, we reveal that endogenous mu-opioid receptor (MOR) signaling strongly drives sodium appetite in sodium-depleted mice, whereas a role for kappa (KOR) and delta (DOR) opioid receptor signaling was not detected, at least in sodium-depleted mice. Fos immunohistochemistry revealed discrete regions of the mouse brain displaying an increased number of activated neurons during sodium gratification: the rostral portion of the nucleus of the solitary tract (rNTS), the lateral parabrachial nucleus (LPB), and the central amygdala (CeA). The CeA was subsequently targeted with bilateral infusions of the MOR antagonist naloxonazine, which significantly reduced sodium appetite in mice. The CeA is therefore identified as a key node in the circuit that contributes to sodium appetite. Moreover, endogenous opioids, acting via MOR, within the CeA promote this form of appetitive behavior. PMID:27849613

The variability puzzle in human memory.

PubMed

Kahana, Michael J; Aggarwal, Eash V; Phan, Tung D

2018-04-26

Memory performance exhibits a high level of variability from moment to moment. Much of this variability may reflect inadequately controlled experimental variables, such as word memorability, past practice and subject fatigue. Alternatively, stochastic variability in performance may largely reflect the efficiency of endogenous neural processes that govern memory function. To help adjudicate between these competing views, the authors conducted a multisession study in which subjects completed 552 trials of a delayed free-recall task. Applying a statistical model to predict variability in each subject's recall performance uncovered modest effects of word memorability, proactive interference, and other variables. In contrast to the limited explanatory power of these experimental variables, performance on the prior list strongly predicted current list recall. These findings suggest that endogenous factors underlying successful encoding and retrieval drive variability in performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A Stochastic Dynamic Programming Model With Fuzzy Storage States Applied to Reservoir Operation Optimization

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Jamshid; Mahdizadeh, Kourosh; Afshar, Abbas

2004-08-01

Application of stochastic dynamic programming (SDP) models to reservoir optimization calls for state variables discretization. As an important variable discretization of reservoir storage volume has a pronounced effect on the computational efforts. The error caused by storage volume discretization is examined by considering it as a fuzzy state variable. In this approach, the point-to-point transitions between storage volumes at the beginning and end of each period are replaced by transitions between storage intervals. This is achieved by using fuzzy arithmetic operations with fuzzy numbers. In this approach, instead of aggregating single-valued crisp numbers, the membership functions of fuzzy numbers are combined. Running a simulated model with optimal release policies derived from fuzzy and non-fuzzy SDP models shows that a fuzzy SDP with a coarse discretization scheme performs as well as a classical SDP having much finer discretized space. It is believed that this advantage in the fuzzy SDP model is due to the smooth transitions between storage intervals which benefit from soft boundaries.

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

2016-04-01

In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold modification. The metrics for the first time provides quantification of the routing relevant information loss due to discretization according to the relationship between in-channel routing length and flow velocity. Moreover, it identifies and counts the spatial pattern changes of dominant hydrological variables by overlaying candidate discretization schemes upon input data and accumulating variable changes in area-weighted way. The metrics are straightforward and applicable to any semi-distributed or fully distributed hydrological model with grid scales are greater than input data resolutions. The discretization metrics and decision-making approach are applied to the Grand River watershed located in southwestern Ontario, Canada where discretization decisions are required for a semi-distributed modelling application. Results show that discretization induced information loss monotonically increases as discretization gets rougher. With regards to routing information loss in subbasin discretization, multiple interesting points rather than just the watershed outlet should be considered. Moreover, subbasin and HRU discretization decisions should not be considered independently since subbasin input significantly influences the complexity of HRU discretization result. Finally, results show that the common and convenient approach of making uniform discretization decisions across the watershed domain performs worse compared to a metric informed non-uniform discretization approach as the later since is able to conserve more watershed heterogeneity under the same model complexity (number of computational units).

Dual Formulations of Mixed Finite Element Methods with Applications

PubMed Central

Gillette, Andrew; Bajaj, Chandrajit

2011-01-01

Mixed finite element methods solve a PDE using two or more variables. The theory of Discrete Exterior Calculus explains why the degrees of freedom associated to the different variables should be stored on both primal and dual domain meshes with a discrete Hodge star used to transfer information between the meshes. We show through analysis and examples that the choice of discrete Hodge star is essential to the numerical stability of the method. Additionally, we define interpolation functions and discrete Hodge stars on dual meshes which can be used to create previously unconsidered mixed methods. Examples from magnetostatics and Darcy flow are examined in detail. PMID:21984841

Characterization and Comprehensive Proteome Profiling of Exosomes Secreted by Hepatocytes

PubMed Central

Conde-Vancells, Javier; Rodriguez-Suarez, Eva; Embade, Nieves; Gil, David; Matthiesen, Rune; Valle, Mikel; Elortza, Felix; Lu, Shelly C.; Mato, Jose M.; Falcon-Perez, Juan M.

2009-01-01

Synopsis Exosomes constitute a discrete population of nanometer-sized (30-150 nm) vesicles formed in endocytic compartments and released to the extracellular environment by different cell types. In this work we demonstrated by electron microscopic, western blotting and proteomic analyses that primary hepatocytes secrete exosome-like vesicles containing proteins involved in metabolizing lipoproteins, endogenous compounds as well as xenobiotics. These new findings contribute to improve our knowledge about biology's hepatocyte and may have important diagnostic, prognosis and therapeutic implications in liver diseases Exosomes represent a discrete population of vesicles that are secreted from various cell types to the extracellular media. Their protein and lipid composition are a consequence of sorting events at the level of the multivesicular body, a central organelle which integrates endocytic and secretory pathways. Characterization of exosomes from different biological samples has shown the presence of common as well as cell-type specific proteins. Remarkably, the protein content of the exosomes is modified upon pathological or stress conditions. Hepatocytes play a central role in the body response to stress metabolizing potentially harmful endogenous substances as well as xenobiotics. In the present study we described and characterized for first time exosome secretion in non-tumoral hepatocytes, and using a systematic proteomic approach, we establish the first extensive proteome of a hepatocyte-derived exosome population which should be useful in furthering our understanding of the hepatic function and in the identification of components that may serve as biomarkers for hepatic alterations. Our analysis identifies a significant number of proteins previously described among exosomes derived from others cell types as well as proteins involved in metabolizing lipoproteins, endogenous compounds and xenobiotics, not previously described in exosomes. Furthermore, we demonstrated that exosomal membrane proteins can constitute an interesting tool to express non-exosomal proteins into exosomes with therapeutic purposes. PMID:19367702

Optimization of Operations Resources via Discrete Event Simulation Modeling

NASA Technical Reports Server (NTRS)

Joshi, B.; Morris, D.; White, N.; Unal, R.

1996-01-01

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

PHENOTYPIC VARIABILITY IN INDIVIDUALS WITH TYPE V OSTEOGENESIS IMPERFECTA WITH IDENTICAL IFITM5 MUTATIONS

PubMed Central

Fitzgerald, Jamie; Holden, Paul; Wright, Hollis; Wilmot, Beth; Hata, Abigail; Steiner, Robert D.; Basel, Don

2016-01-01

Background Osteogenesis imperfecta (OI) type V is a dominantly inherited skeletal dysplasia characterized by fractures and progressive deformity of long bones. In addition, patients often present with radial head dislocation, hyperplastic callus, and calcification of the forearm interosseous membrane. Recently, a specific mutation in the IFITM5 gene was found to be responsible for OI type V. This mutation, a C to T transition 14 nucleotides upstream from the endogenous start codon, creates a new start methionine that appears to be preferentially used by the translational machinery. However, the mechanism by which the lengthened protein results in a dominant type of OI is unknown. Methods and Results We report 7 ethnically diverse (African-American, Caucasian, Hispanic, and African) individuals with OI type V from 2 families and 2 sporadic cases. Exome sequencing failed to identify a causative mutation. Using Sanger sequencing, we found that all affected individuals in our cohort possess the c.−14 IFITM5 variant, further supporting the notion that OI type V is caused by a single, discrete mutation. Our patient cohort demonstrated inter-and intrafamilial phenotypic variability, including a father with classic OI type V whose daughter had a phenotype similar to OI type I. This clinical variability suggests that modifier genes influence the OI type V phenotype. We also confirm that the mutation creates an aberrant IFITM5 protein containing an additional 5 amino acids at the N-terminus. Conclusions The variable clinical signs in these cases illustrate the significant variability of the OI type V phenotype caused by the c.−14 IFITM5 mutation. The affected individuals are more ethnically diverse than previously reported. PMID:28824928

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Unconditional security proof of long-distance continuous-variable quantum key distribution with discrete modulation.

PubMed

Leverrier, Anthony; Grangier, Philippe

2009-05-08

We present a continuous-variable quantum key distribution protocol combining a discrete modulation and reverse reconciliation. This protocol is proven unconditionally secure and allows the distribution of secret keys over long distances, thanks to a reverse reconciliation scheme efficient at very low signal-to-noise ratio.

A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.

Discrete-time bidirectional associative memory neural networks with variable delays

NASA Astrophysics Data System (ADS)

Liang, variable delays [rapid communication] J.; Cao, J.; Ho, D. W. C.

2005-02-01

Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks.

Controllability of discrete bilinear systems with bounded control.

NASA Technical Reports Server (NTRS)

Tarn, T. J.; Elliott, D. L.; Goka, T.

1973-01-01

The subject of this paper is the controllability of time-invariant discrete-time bilinear systems. Bilinear systems are classified into two categories; homogeneous and inhomogeneous. Sufficient conditions which ensure the global controllability of discrete-time bilinear systems are obtained by localized analysis in control variables.

Clustering and variable selection in the presence of mixed variable types and missing data.

PubMed

Storlie, C B; Myers, S M; Katusic, S K; Weaver, A L; Voigt, R G; Croarkin, P E; Stoeckel, R E; Port, J D

2018-05-17

We consider the problem of model-based clustering in the presence of many correlated, mixed continuous, and discrete variables, some of which may have missing values. Discrete variables are treated with a latent continuous variable approach, and the Dirichlet process is used to construct a mixture model with an unknown number of components. Variable selection is also performed to identify the variables that are most influential for determining cluster membership. The work is motivated by the need to cluster patients thought to potentially have autism spectrum disorder on the basis of many cognitive and/or behavioral test scores. There are a modest number of patients (486) in the data set along with many (55) test score variables (many of which are discrete valued and/or missing). The goal of the work is to (1) cluster these patients into similar groups to help identify those with similar clinical presentation and (2) identify a sparse subset of tests that inform the clusters in order to eliminate unnecessary testing. The proposed approach compares very favorably with other methods via simulation of problems of this type. The results of the autism spectrum disorder analysis suggested 3 clusters to be most likely, while only 4 test scores had high (>0.5) posterior probability of being informative. This will result in much more efficient and informative testing. The need to cluster observations on the basis of many correlated, continuous/discrete variables with missing values is a common problem in the health sciences as well as in many other disciplines. Copyright © 2018 John Wiley & Sons, Ltd.

A novel dataset on legal traditions, their determinants, and their economic role in 155 transplants.

PubMed

Guerriero, Carmine

2016-09-01

The law and the economy are deeply influenced by the legal tradition or origin, which is the bundle of institutions shaping lawmaking and dispute adjudication. The two principal legal traditions, common law and civil law, have been transplanted through colonization and occupation to the vast majority of the jurisdictions in the world by a group of European countries. Here, I illustrate a novel dataset recording the lawmaking institution employed by 155 of these jurisdictions at independence and in 2000 and four discretion-curbing adjudication institutions adopted by 99 of these "transplants" at the same two points in time. Contrary to the "legal origins" scholars׳ assumption, 25 transplants changed the transplanted lawmaking institution and 95 modified at least one of the transplanted lawmaking and adjudication rules. In "Endogenous Legal Traditions" (Guerriero, 2016a) [12], I document that these reforms are consistent with a model of the design of legal institutions by societies heterogeneous in their endowment of both the extent of cultural heterogeneity and the quality of the political process. In "Endogenous Legal Traditions and Economic Outcomes" (Guerriero, 2016b) [13] moreover, I show the relevance of considering legal evolution and the endogeneity between legal traditions and economics outcomes. The data illustrated here also include the proxies for the determinants of legal evolution I use in "Endogenous Legal Traditions" (Guerriero, 2016a) [12] and the novel measure of economic outcomes I employ in "Endogenous Legal Traditions and Economic Outcomes" (Guerriero, 2016b) [13].

Discrete-time BAM neural networks with variable delays

NASA Astrophysics Data System (ADS)

Liu, Xin-Ge; Tang, Mei-Lan; Martin, Ralph; Liu, Xin-Bi

2007-07-01

This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development.

Modeling old-age wealth with endogenous early-life outcomes: The case of Mexico

PubMed Central

DeGraff, Deborah S.; Wong, Rebeca

2014-01-01

This paper contributes to the literature on the life course and aging by examining the association between early-life outcomes and late-life well being, using data from the Mexican Health and Aging Study. Empirical research in this area has been challenged by the potential endogeneity of the early-life outcomes of interest, an issue which most studies ignore or downplay. Our contribution takes two forms: (1) we examine in detail the potential importance of two key life-cycle outcomes, age at marriage (a measure of family formation) and years of educational attainment (a measure of human capital investment) for old-age wealth, and (2) we illustrate the empirical value of past context variables that could help model the association between early-life outcomes and late-life well being. Our illustrative approach, matching macro-level historical policy and census variables to individual records to use as instruments in modeling the endogeneity of early-life behaviors, yields a statistically identified two-stage model of old-age wealth with minimum bias. We use simulations to show that the results for the model of wealth in old age are meaningfully different when comparing the approach that accounts for endogeneity with an approach that assumes exogeneity of early-life outcomes. Furthermore, our results suggest that in the Mexican case, models which ignore the potential endogeneity of early-life outcomes are likely to under-estimate the effects of such variables on old-age wealth. PMID:25170434

Quantifying the time scales over which exogenous and endogenous conditions affect soil respiration

USDA-ARS?s Scientific Manuscript database

Understanding how exogenous and endogenous factors and aboveground-belowground linkages modulate carbon dynamics is difficult because of influences of antecedent conditions. For example, there are variable lags between aboveground assimilation and belowground efflux, and the duration of antecedent p...

Improved robustness and performance of discrete time sliding mode control systems.

PubMed

Chakrabarty, Sohom; Bartoszewicz, Andrzej

2016-11-01

This paper presents a theoretical analysis along with simulations to show that increased robustness can be achieved for discrete time sliding mode control systems by choosing the sliding variable, or the output, to be of relative degree two instead of relative degree one. In other words it successfully reduces the ultimate bound of the sliding variable compared to the ultimate bound for standard discrete time sliding mode control systems. It is also found out that for such a selection of relative degree two output of the discrete time system, the reduced order system during sliding becomes finite time stable in absence of disturbance. With disturbance, it becomes finite time ultimately bounded. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Uncertainty relation for the discrete Fourier transform.

PubMed

Massar, Serge; Spindel, Philippe

2008-05-16

We derive an uncertainty relation for two unitary operators which obey a commutation relation of the form UV=e(i phi) VU. Its most important application is to constrain how much a quantum state can be localized simultaneously in two mutually unbiased bases related by a discrete fourier transform. It provides an uncertainty relation which smoothly interpolates between the well-known cases of the Pauli operators in two dimensions and the continuous variables position and momentum. This work also provides an uncertainty relation for modular variables, and could find applications in signal processing. In the finite dimensional case the minimum uncertainty states, discrete analogues of coherent and squeezed states, are minimum energy solutions of Harper's equation, a discrete version of the harmonic oscillator equation.

A Polychoric Instrumental Variable (PIV) Estimator for Structural Equation Models with Categorical Variables

ERIC Educational Resources Information Center

Bollen, Kenneth A.; Maydeu-Olivares, Albert

2007-01-01

This paper presents a new polychoric instrumental variable (PIV) estimator to use in structural equation models (SEMs) with categorical observed variables. The PIV estimator is a generalization of Bollen's (Psychometrika 61:109-121, 1996) 2SLS/IV estimator for continuous variables to categorical endogenous variables. We derive the PIV estimator…

Genetic-evolution-based optimization methods for engineering design

NASA Technical Reports Server (NTRS)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Forest structure estimation and pattern exploration from discrete return lidar in subalpine forests of the Central Rockies

Treesearch

K. R. Sherrill; M. A. Lefsky; J. B. Bradford; M. G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Forest structure estimation and pattern exploration from discrete-return lidar in subalpine forests of the central Rockies

Treesearch

K.R. Sherrill; M.A. Lefsky; J.B. Bradford; M.G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Discrete Choice Modeling (DCM): An Exciting Marketing Research Survey Method for Educational Researchers.

ERIC Educational Resources Information Center

Berdie, Doug R.

Discrete Choice Marketing (DCM), a research technique that has become more popular in recent marketing research, is described. DCM is a method that forces people to look at the combination of relevant variables within each choice domain and, with each option fully defined in terms of the values for those variables, make a choice of options. DCM…

Endogenous circadian regulation of carbon dioxide exchange in terrestrial ecosystems

Treesearch

Victor Resco de Dios; Michael L. Goulden; Kiona Ogle; Andrew D. Richardson; David Y. Hollinger; Eric A. Davidson; Josu G. Alday; Greg A. Barron-Gafford; Arnaud Carrara; Andrew S. Kowalski; Walt C. Oechel; Borja R. Reverter; Russell L. Scott; Ruth K. Varner; Ruben Diaz-Sierra; Jose M. Moreno

2012-01-01

It is often assumed that daytime patterns of ecosystem carbon assimilation are mostly driven by direct physiological responses to exogenous environmental cues. Under limited environmental variability, little variation in carbon assimilation should thus be expected unless endogenous plant controls on carbon assimilation, which regulate photosynthesis in time, are active...

Interpreting Significant Discrete-Time Periods in Survival Analysis.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Denson, Kathleen B.

Discrete-time survival analysis is a new method for educational researchers to employ when looking at the timing of certain educational events. Previous continuous-time methods do not allow for the flexibility inherent in a discrete-time method. Because both time-invariant and time-varying predictor variables can now be used, the interaction of…

Development and Application of Methods for Estimating Operating Characteristics of Discrete Test Item Responses without Assuming any Mathematical Form.

ERIC Educational Resources Information Center

Samejima, Fumiko

In latent trait theory the latent space, or space of the hypothetical construct, is usually represented by some unidimensional or multi-dimensional continuum of real numbers. Like the latent space, the item response can either be treated as a discrete variable or as a continuous variable. Latent trait theory relates the item response to the latent…

Sentient Structures: Optimising Sensor Layouts for Direct Measurement of Discrete Variables

DTIC Science & Technology

2008-11-01

1 Sentient Structures Optimising Sensor Layouts for Direct Measurement of Discrete Variables Report to US Air Force...TITLE AND SUBTITLE Sentient Structures 5a. CONTRACT NUMBER FA48690714045 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Donald Price...optimal sensor placements is an important requirement for the development of sentient structures. An optimal sensor layout is attained when a limited

The Effects of Model Misspecification and Sample Size on LISREL Maximum Likelihood Estimates.

ERIC Educational Resources Information Center

Baldwin, Beatrice

The robustness of LISREL computer program maximum likelihood estimates under specific conditions of model misspecification and sample size was examined. The population model used in this study contains one exogenous variable; three endogenous variables; and eight indicator variables, two for each latent variable. Conditions of model…

Non-equilibrium Green's functions study of discrete dopants variability on an ultra-scaled FinFET

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

Valin, R., E-mail: r.valinferreiro@swansea.ac.uk; Martinez, A., E-mail: a.e.Martinez@swansea.ac.uk; Barker, J. R., E-mail: john.barker@glasgow.ac.uk

In this paper, we study the effect of random discrete dopants on the performance of a 6.6 nm channel length silicon FinFET. The discrete dopants have been distributed randomly in the source/drain region of the device. Due to the small dimensions of the FinFET, a quantum transport formalism based on the non-equilibrium Green's functions has been deployed. The transfer characteristics for several devices that differ in location and number of dopants have been calculated. Our results demonstrate that discrete dopants modify the effective channel length and the height of the source/drain barrier, consequently changing the channel control of the charge. Thismore » effect becomes more significant at high drain bias. As a consequence, there is a strong effect on the variability of the on-current, off-current, sub-threshold slope, and threshold voltage. Finally, we have also calculated the mean and standard deviation of these parameters to quantify their variability. The obtained results show that the variability at high drain bias is 1.75 larger than at low drain bias. However, the variability of the on-current, off-current, and sub-threshold slope remains independent of the drain bias. In addition, we have found that a large source to drain current by tunnelling current occurs at low gate bias.« less

Endogenous Inhibition of Somatic Pain is Impaired in Girls with Irritable Bowel Syndrome Compared with Healthy Girls

PubMed Central

Williams, Amy E.; Heitkemper, Margaret; Self, Mariella M.; Czyzewski, Danita I.; Shulman, Robert J.

2013-01-01

Endogenous pain-inhibition is often deficient in adults with chronic pain conditions including irritable bowel syndrome (IBS). It is unclear whether deficiencies in pain-inhibition are present in young children with IBS. The present study compared endogenous pain-inhibition, somatic pain threshold, and psychosocial distress in young girls with IBS versus controls. Girls with IBS did not show significant endogenous pain-inhibition of heat pain-threshold during a cold-pressor task in contrast to controls who had significant pain-inhibition. Girls with IBS did not differ from peers on measures of somatic pain but had more symptoms of depression, somatization, and anxiety than controls. When psychological variables were included as covariates the difference in pain-inhibition was no longer significant, although poor achieved power limits interpretation of these results. Higher-order cognitive processes including psychological variables may be contributing to observed pain-inhibition. In girls with IBS, pain-inhibition was positively related to the number of days without a bowel movement. To our knowledge, this is the first study to demonstrate deficiencies of endogenous pain-inhibition in young children with IBS. Findings have implications for better understanding of onset and maintenance of IBS and other chronic pain conditions. PMID:23685184

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

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

Dall-Anese, Emiliano; Zhou, Xinyang; Liu, Zhiyuan

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together withmore » pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Adjoint-Based Methodology for Time-Dependent Optimization

NASA Technical Reports Server (NTRS)

Yamaleev, N. K.; Diskin, B.; Nielsen, E. J.

2008-01-01

This paper presents a discrete adjoint method for a broad class of time-dependent optimization problems. The time-dependent adjoint equations are derived in terms of the discrete residual of an arbitrary finite volume scheme which approximates unsteady conservation law equations. Although only the 2-D unsteady Euler equations are considered in the present analysis, this time-dependent adjoint method is applicable to the 3-D unsteady Reynolds-averaged Navier-Stokes equations with minor modifications. The discrete adjoint operators involving the derivatives of the discrete residual and the cost functional with respect to the flow variables are computed using a complex-variable approach, which provides discrete consistency and drastically reduces the implementation and debugging cycle. The implementation of the time-dependent adjoint method is validated by comparing the sensitivity derivative with that obtained by forward mode differentiation. Our numerical results show that O(10) optimization iterations of the steepest descent method are needed to reduce the objective functional by 3-6 orders of magnitude for test problems considered.

Health and Wages: Panel Data Estimates Considering Selection and Endogeneity

ERIC Educational Resources Information Center

Jackle, Robert; Himmler, Oliver

2010-01-01

This paper complements previous studies on the effects of health on wages by addressing the problems of unobserved heterogeneity, sample selection, and endogeneity in one comprehensive framework. Using data from the German Socio-Economic Panel (GSOEP), we find the health variable to suffer from measurement error and a number of tests provide…

Health and labour force participation of older people in Europe: what do objective health indicators add to the analysis?

PubMed

Kalwij, Adriaan; Vermeulen, Frederic

2008-05-01

This paper studies labour force participation of older individuals in 11 European countries. The data are drawn from the new Survey of Health, Ageing and Retirement in Europe (SHARE). We examine the value added of objective health indicators in relation to potentially endogenous self-reported health. We approach the endogeneity of self-reported health as an omitted variables problem. In line with the literature on the reliability of self-reported health ambiguous results are obtained. In some countries self-reported health does a fairly good job and controlling for objective health indicators does not add much to the analysis. In other countries, however, the results show that objective health indicators add significantly to the analysis and that self-reported health is endogenous due to omitted objective health indicators. These latter results illustrate the multi-dimensional nature of health and the need to control for objective health indicators when analysing the relation between health status and labour force participation. This makes an instrumental variables approach to deal with the endogeneity of self-reported health less appropriate.

Neurobiological actions of cysteamine

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

Brown, M.; Fisher, L.; Mason, R.T.

1985-06-01

Somatostatin (SS)-related peptides act within discrete brain regions to inhibit adrenal epinephrine (E) secretion, to prevent hypothermia, and to produce hyperthermia. Depletion of brain concentrations of these SS-related peptides using cysteamine (CSH) or central administration of an SS receptor antagonist increases adrenal E secretion and impairs thermoregulation. These actions of CSH and the SS receptor antagonist are reversed by administration of SS into the central nervous system. These results support the hypothesis that endogenous brain SS-related peptides are involved in the regulation of adrenal E secretion and thermoregulation.

Functional entropy variables: A new methodology for deriving thermodynamically consistent algorithms for complex fluids, with particular reference to the isothermal Navier–Stokes–Korteweg equations

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

Liu, Ju, E-mail: jliu@ices.utexas.edu; Gomez, Hector; Evans, John A.

2013-09-01

We propose a new methodology for the numerical solution of the isothermal Navier–Stokes–Korteweg equations. Our methodology is based on a semi-discrete Galerkin method invoking functional entropy variables, a generalization of classical entropy variables, and a new time integration scheme. We show that the resulting fully discrete scheme is unconditionally stable-in-energy, second-order time-accurate, and mass-conservative. We utilize isogeometric analysis for spatial discretization and verify the aforementioned properties by adopting the method of manufactured solutions and comparing coarse mesh solutions with overkill solutions. Various problems are simulated to show the capability of the method. Our methodology provides a means of constructing unconditionallymore » stable numerical schemes for nonlinear non-convex hyperbolic systems of conservation laws.« less

Identification of suitable reference genes for hepatic microRNA quantitation.

PubMed

Lamba, Vishal; Ghodke-Puranik, Yogita; Guan, Weihua; Lamba, Jatinder K

2014-03-07

MicroRNAs (miRNAs) are short (~22 nt) endogenous RNAs that play important roles in regulating expression of a wide variety of genes involved in different cellular processes. Alterations in microRNA expression patterns have been associated with a number of human diseases. Accurate quantitation of microRNA levels is important for their use as biomarkers and in determining their functions. Real time PCR is the gold standard and the most frequently used technique for miRNA quantitation. Real time PCR data analysis includes normalizing the amplification data to suitable endogenous control/s to ensure that microRNA quantitation is not affected by the variability that is potentially introduced at different experimental steps. U6 (RNU6A) and RNU6B are two commonly used endogenous controls in microRNA quantitation. The present study was designed to investigate inter-individual variability and gender differences in hepatic microRNA expression as well as to identify the best endogenous control/s that could be used for normalization of real-time expression data in liver samples. We used Taqman based real time PCR to quantitate hepatic expression levels of 22 microRNAs along with U6 and RNU6B in 50 human livers samples (25 M, 25 F). To identify the best endogenous controls for use in data analysis, we evaluated the amplified candidates for their stability (least variability) in expression using two commonly used software programs: Normfinder and GeNormplus, Both Normfinder and GeNormplus identified U6 to be among the least stable of all the candidates analyzed, and RNU6B was also not among the top genes in stability. mir-152 and mir-23b were identified to be the two most stable candidates by both Normfinder and GeNormplus in our analysis, and were used as endogenous controls for normalization of hepatic miRNA levels. Measurements of microRNA stability indicate that U6 and RNU6B are not suitable for use as endogenous controls for normalizing microRNA relative quantitation data in hepatic tissue, and their use can led to possibly erroneous conclusions.

Affective norms of 875 Spanish words for five discrete emotional categories and two emotional dimensions.

PubMed

Hinojosa, J A; Martínez-García, N; Villalba-García, C; Fernández-Folgueiras, U; Sánchez-Carmona, A; Pozo, M A; Montoro, P R

2016-03-01

In the present study, we introduce affective norms for a new set of Spanish words, the Madrid Affective Database for Spanish (MADS), that were scored on two emotional dimensions (valence and arousal) and on five discrete emotional categories (happiness, anger, sadness, fear, and disgust), as well as on concreteness, by 660 Spanish native speakers. Measures of several objective psycholinguistic variables--grammatical class, word frequency, number of letters, and number of syllables--for the words are also included. We observed high split-half reliabilities for every emotional variable and a strong quadratic relationship between valence and arousal. Additional analyses revealed several associations between the affective dimensions and discrete emotions, as well as with some psycholinguistic variables. This new corpus complements and extends prior databases in Spanish and allows for designing new experiments investigating the influence of affective content in language processing under both dimensional and discrete theoretical conceptions of emotion. These norms can be downloaded as supplemental materials for this article from www.dropbox.com/s/o6dpw3irk6utfhy/Hinojosa%20et%20al_Supplementary%20materials.xlsx?dl=0 .

Characterization of digitalis-like factors in human plasma. Interactions with NaK-ATPase and cross-reactivity with cardiac glycoside-specific antibodies.

PubMed

Kelly, R A; O'Hara, D S; Canessa, M L; Mitch, W E; Smith, T W

1985-09-25

Much of the evidence for a physiologically important endogenous inhibitor of the sodium pump has been either contradictory or indirect. We have identified three discrete fractions in desalted deproteinized plasma from normal humans that resemble the digitalis glycosides in that they: are of low molecular weight; are resistant to acid and enzymatic proteolysis; inhibit NaK-ATPase activity; inhibit Na+ pump activity in human erythrocytes; displace [3H]ouabain bound to the enzyme; and cross-react with high-affinity polyclonal and monoclonal digoxin-specific antibodies but not with anti-ouabain or anti-digitoxin antibodies. An additional fraction cross-reacted with digoxin-specific antibodies but had no detectable activity against NaK-ATPase. The three inhibitory fractions differed from cardiac glycosides in that their concentration-effect curves in a NaK-ATPase inhibition and [3H]ouabain radioreceptor assays were steeper than unlabeled ouabain. This suggests that these inhibitors are not simple competitive ligands for binding to NaK-ATPase. In the presence of sodium, no fraction required ATP for binding to NaK-ATPase, and in the presence of potassium, only one fraction had the reduced affinity for the enzyme that is characteristic of cardiac glycosides. Unlike digitalis, all three NaK-ATPase inhibitory fractions stimulated the activity of skeletal muscle sarcoplasmic reticulum Ca-ATPase. The presence of at least three fractions in human plasma that inhibit NaK-ATPase and cross-react to a variable degree with different digoxin-specific antibody populations could explain much of the conflicting evidence for the existence of endogenous digitalis-like compounds in plasma.

A rhythmic modulatory gating system in the stomatogastric nervous system of Homarus gammarus. III. Rhythmic control of the pyloric CPG.

PubMed

Cardi, P; Nagy, F

1994-06-01

1. Two modulatory neurons, P and commissural pyloric (CP), known to be involved in the long-term maintenance of pyloric central pattern generator operation in the rock lobster Homarus gammarus, are members of the commissural pyloric oscillator (CPO), a higher-order oscillator influencing the pyloric network. 2. The CP neuron was endogenously oscillating in approximately 30% of the preparations in which its cell body was impaled. Rhythmic inhibitory feedback from the pyloric pacemaker anterior burster (AB) neuron stabilized the CP neuron's endogenous rhythm. 3. The organization of the CPO is described. Follower commissural neurons, the F cells, and the CP neuron receive a common excitatory postsynaptic potential from another commissural neuron, the large exciter (LE). When in oscillatory state, CP in turn excites the LE neuron. This positive feedback may maintain long episodes of CP oscillations. 4. The pyloric pacemaker neurons follow the CPO rhythm with variable coordination modes (i.e., 1:1, 1:2) and switch among these modes when their membrane potential is modified. The CPO inputs strongly constrain the pyloric period, which as a result may adopt only a few discrete values. This effect is based on mechanisms of entrainment between the CPO and the pyloric oscillator. 5. Pyloric constrictor neurons show differential sensitivity from the pyloric pacemaker neurons with respect to the CPO inputs. Consequently, their bursting period can be a shorter harmonic of the bursting period of the pyloric pacemakers neurons. 6. The CPO neurons seem to be the first example of modulatory gating neurons that also give timing cues to a rhythmic pattern generating network.

Functional Extended Redundancy Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop

2012-01-01

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

Models of multidimensional discrete distribution of probabilities of random variables in information systems

NASA Astrophysics Data System (ADS)

Gromov, Yu Yu; Minin, Yu V.; Ivanova, O. G.; Morozova, O. N.

2018-03-01

Multidimensional discrete distributions of probabilities of independent random values were received. Their one-dimensional distribution is widely used in probability theory. Producing functions of those multidimensional distributions were also received.

Nonautonomous discrete bright soliton solutions and interaction management for the Ablowitz-Ladik equation.

PubMed

Yu, Fajun

2015-03-01

We present the nonautonomous discrete bright soliton solutions and their interactions in the discrete Ablowitz-Ladik (DAL) equation with variable coefficients, which possesses complicated wave propagation in time and differs from the usual bright soliton waves. The differential-difference similarity transformation allows us to relate the discrete bright soliton solutions of the inhomogeneous DAL equation to the solutions of the homogeneous DAL equation. Propagation and interaction behaviors of the nonautonomous discrete solitons are analyzed through the one- and two-soliton solutions. We study the discrete snaking behaviors, parabolic behaviors, and interaction behaviors of the discrete solitons. In addition, the interaction management with free functions and dynamic behaviors of these solutions is investigated analytically, which have certain applications in electrical and optical systems.

Expression of endogenous proteins in maize hybrids in a multi-location field trial in India.

PubMed

Gutha, Linga R; Purushottam, Divakar; Veeramachaneni, Aruna; Tigulla, Sarita; Kodappully, Vikas; Enjala, Chandana; Rajput, Hitendrasinh; Anderson, Jennifer; Hong, Bonnie; Schmidt, Jean; Bagga, Shveta

2018-05-17

Genetically modified (GM) crops undergo large scale multi-location field trials to characterize agronomics, composition, and the concentration of newly expressed protein(s) [herein referred to as transgenic protein(s)]. The concentration of transgenic proteins in different plant tissues and across the developmental stages of the plant is considered in the safety assessment of GM crops. Reference or housekeeping proteins are expected to maintain a relatively stable expression pattern in healthy plants given their role in cellular functions. Understanding the effects of genotype, growth stage and location on the concentration of endogenous housekeeping proteins may provide insight into the contribution these factors could have on transgenic protein concentrations in GM crops. The concentrations of three endogenous proteins (actin, elongation factor 1-alpha, and glyceraldehyde 3-phosphate dehydrogenase) were measured in several different maize hybrids grown across multiple field locations over 2 years. Leaf samples were collected from healthy plants at three developmental stages across the growing seasons, and protein concentrations were quantified by indirect enzyme-linked immunosorbent assay (ELISA) for each protein. In general, the concentrations of these three endogenous proteins were relatively consistent across hybrid backgrounds, when compared within one growth stage and location (2-26%CV), whereas the concentrations of proteins in the same hybrid and growth stage across different locations were more variable (12-64%CV). In general, the protein concentrations in 2013 and 2014 show similar trends in variability. Some degree of variability in protein concentrations should be expected for both transgenic and endogenous plant-expressed proteins. In the case of GM crops, the potential variation in protein concentrations due to location effects is captured in the current model of multi-location field testing.

Demands, skill discretion, decision authority and social climate at work as determinants of major depression in a 3-year follow-up study.

PubMed

Fandiño-Losada, Andrés; Forsell, Yvonne; Lundberg, Ingvar

2013-07-01

The psychosocial work environment may be a determinant of the development and course of depressive disorders, but the literature shows inconsistent findings. Thus, the aim of this study is to determine longitudinal effects of the job demands-control-support model (JDCSM) variables on the occurrence of major depression among working men and women from the general population. The sample comprised 4,710 working women and men living in Stockholm, who answered the same questionnaire twice, 3 years apart, who were not depressed during the first wave and had the same job in both waves. The questionnaire included JDCSM variables (demands, skill discretion, decision authority and social climate) and other co-variables (income, education, occupational group, social support, help and small children at home, living with an adult and depressive symptoms at time 1; and negative life events at time 2). Multiple logistic regressions were run to calculate odds ratios of having major depression at time 2, after adjustment for other JDCSM variables and co-variables. Among women, inadequate work social climate was the only significant risk indicator for major depression. Surprisingly, among men, high job demands and low skill discretion appeared as protective factors against major depression. The results showed a strong relationship between inadequate social climate and major depression among women, while there were no certain effects for the remaining exposure variables. Among men, few cases of major depression hampered well-founded conclusions regarding our findings of low job demands and high skill discretion as related to major depression.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Evaluating the Effectiveness of Two Commonly Used Discrete Trial Procedures for Teaching Receptive Discrimination to Young Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Gutierrez, Anibal, Jr.; Hale, Melissa N.; O'Brien, Heather A.; Fischer, Aaron J.; Durocher, Jennifer S.; Alessandri, Michael

2009-01-01

Discrete trial teaching procedures have been demonstrated to be effective in teaching a variety of important skills for children with autism spectrum disorders (ASD). Although all discrete trial programs are based in the principles of applied behavior analysis, some variability exists between programs with regards to the precise teaching…

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.

PubMed

Schmid, Matthias; Küchenhoff, Helmut; Hoerauf, Achim; Tutz, Gerhard

2016-02-28

Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior. Copyright © 2015 John Wiley & Sons, Ltd.

Measurement Model Specification Error in LISREL Structural Equation Models.

ERIC Educational Resources Information Center

Baldwin, Beatrice; Lomax, Richard

This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of…

Security of a discretely signaled continuous variable quantum key distribution protocol for high rate systems.

PubMed

Zhang, Zheshen; Voss, Paul L

2009-07-06

We propose a continuous variable based quantum key distribution protocol that makes use of discretely signaled coherent light and reverse error reconciliation. We present a rigorous security proof against collective attacks with realistic lossy, noisy quantum channels, imperfect detector efficiency, and detector electronic noise. This protocol is promising for convenient, high-speed operation at link distances up to 50 km with the use of post-selection.

Comment on "Route from discreteness to the continuum for the Tsallis q -entropy"

NASA Astrophysics Data System (ADS)

Ou, Congjie; Abe, Sumiyoshi

2018-06-01

Several years ago, it had been discussed that nonlogarithmic entropies, such as the Tsallis q -entropy cannot be applied to systems with continuous variables. Now, in their recent paper [Phys. Rev. E 97, 012104 (2018), 10.1103/PhysRevE.97.012104], Oikonomou and Bagci have modified the form of the q -entropy for discrete variables in such a way that its continuum limit exists. Here, it is shown that this modification violates the expandability property of entropy, and their work is actually supporting evidence for the absence of the q -entropy for systems with continuous variables.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?

NASA Astrophysics Data System (ADS)

Penney, Mark D.; Enshan Koh, Dax; Spekkens, Robert W.

2017-07-01

It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits.

Discrete structures in continuum descriptions of defective crystals.

PubMed

Parry, G P

2016-04-28

I discuss various mathematical constructions that combine together to provide a natural setting for discrete and continuum geometric models of defective crystals. In particular, I provide a quite general list of 'plastic strain variables', which quantifies inelastic behaviour, and exhibit rigorous connections between discrete and continuous mathematical structures associated with crystalline materials that have a correspondingly general constitutive specification. © 2016 The Author(s).

On multiple orthogonal polynomials for discrete Meixner measures

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

Sorokin, Vladimir N

2010-12-07

The paper examines two examples of multiple orthogonal polynomials generalizing orthogonal polynomials of a discrete variable, meaning thereby the Meixner polynomials. One example is bound up with a discrete Nikishin system, and the other leads to essentially new effects. The limit distribution of the zeros of polynomials is obtained in terms of logarithmic equilibrium potentials and in terms of algebraic curves. Bibliography: 9 titles.

The Population History of Endogenous Retroviruses in Mule Deer (Odocoileus hemionus)

PubMed Central

2014-01-01

Mobile elements are powerful agents of genomic evolution and can be exceptionally informative markers for investigating species and population-level evolutionary history. While several studies have utilized retrotransposon-based insertional polymorphisms to resolve phylogenies, few population studies exist outside of humans. Endogenous retroviruses are LTR-retrotransposons derived from retroviruses that have become stably integrated in the host genome during past infections and transmitted vertically to subsequent generations. They offer valuable insight into host-virus co-evolution and a unique perspective on host evolutionary history because they integrate into the genome at a discrete point in time. We examined the evolutionary history of a cervid endogenous gammaretrovirus (CrERVγ) in mule deer (Odocoileus hemionus). We sequenced 14 CrERV proviruses (CrERV-in1 to -in14), and examined the prevalence and distribution of 13 proviruses in 262 deer among 15 populations from Montana, Wyoming, and Utah. CrERV absence in white-tailed deer (O. virginianus), identical 5′ and 3′ long terminal repeat (LTR) sequences, insertional polymorphism, and CrERV divergence time estimates indicated that most endogenization events occurred within the last 200000 years. Population structure inferred from CrERVs (F ST = 0.008) and microsatellites (θ = 0.01) was low, but significant, with Utah, northwestern Montana, and a Helena herd being particularly differentiated. Clustering analyses indicated regional structuring, and non-contiguous clustering could often be explained by known translocations. Cluster ensemble results indicated spatial localization of viruses, specifically in deer from northeastern and western Montana. This study demonstrates the utility of endogenous retroviruses to elucidate and provide novel insight into both ERV evolutionary history and the history of contemporary host populations. PMID:24336966

The population history of endogenous retroviruses in mule deer (Odocoileus heminous)

USGS Publications Warehouse

Kamath, Pauline L.; Elleder, Daniel; Bao, Le; Cross, Paul C.; Powell, John H.; Poss, Mary

2013-01-01

Mobile elements are powerful agents of genomic evolution and can be exceptionally informative markers for investigating species and population-level evolutionary history. While several studies have utilized retrotransposon-based insertional polymorphisms to resolve phylogenies, few population studies exist outside of humans. Endogenous retroviruses are LTR-retrotransposons derived from retroviruses that have become stably integrated in the host genome during past infections and transmitted vertically to subsequent generations. They offer valuable insight into host-virus co-evolution and a unique perspective on host evolutionary history because they integrate into the genome at a discrete point in time. We examined the evolutionary history of a cervid endogenous gammaretrovirus (CrERVγ) in mule deer (Odocoileus hemionus). We sequenced 14 CrERV proviruses (CrERV-in1 to -in14), and examined the prevalence and distribution of 13 proviruses in 262 deer among 15 populations from Montana, Wyoming, and Utah. CrERV absence in white-tailed deer (O. virginianus), identical 5′ and 3′ long terminal repeat (LTR) sequences, insertional polymorphism, and CrERV divergence time estimates indicated that most endogenization events occurred within the last 200000 years. Population structure inferred from CrERVs (F ST = 0.008) and microsatellites (θ = 0.01) was low, but significant, with Utah, northwestern Montana, and a Helena herd being particularly differentiated. Clustering analyses indicated regional structuring, and non-contiguous clustering could often be explained by known translocations. Cluster ensemble results indicated spatial localization of viruses, specifically in deer from northeastern and western Montana. This study demonstrates the utility of endogenous retroviruses to elucidate and provide novel insight into both ERV evolutionary history and the history of contemporary host populations.

Biomechanical symmetry in elite rugby union players during dynamic tasks: an investigation using discrete and continuous data analysis techniques.

PubMed

Marshall, Brendan; Franklyn-Miller, Andrew; Moran, Kieran; King, Enda; Richter, Chris; Gore, Shane; Strike, Siobhán; Falvey, Éanna

2015-01-01

While measures of asymmetry may provide a means of identifying individuals predisposed to injury, normative asymmetry values for challenging sport specific movements in elite athletes are currently lacking in the literature. In addition, previous studies have typically investigated symmetry using discrete point analyses alone. This study examined biomechanical symmetry in elite rugby union players using both discrete point and continuous data analysis techniques. Twenty elite injury free international rugby union players (mean ± SD: age 20.4 ± 1.0 years; height 1.86 ± 0.08 m; mass 98.4 ± 9.9 kg) underwent biomechanical assessment. A single leg drop landing, a single leg hurdle hop, and a running cut were analysed. Peak joint angles and moments were examined in the discrete point analysis while analysis of characterising phases (ACP) techniques were used to examine the continuous data. Dominant side was compared to non-dominant side using dependent t-tests for normally distributed data or Wilcoxon signed-rank test for non-normally distributed data. The significance level was set at α = 0.05. The majority of variables were found to be symmetrical with a total of 57/60 variables displaying symmetry in the discrete point analysis and 55/60 in the ACP. The five variables that were found to be asymmetrical were hip abductor moment in the drop landing (p = 0.02), pelvis lift/drop in the drop landing (p = 0.04) and hurdle hop (p = 0.02), ankle internal rotation moment in the cut (p = 0.04) and ankle dorsiflexion angle also in the cut (p = 0.01). The ACP identified two additional asymmetries not identified in the discrete point analysis. Elite injury free rugby union players tended to exhibit bi-lateral symmetry across a range of biomechanical variables in a drop landing, hurdle hop and cut. This study provides useful normative values for inter-limb symmetry in these movement tests. When examining symmetry it is recommended to incorporate continuous data analysis techniques rather than a discrete point analysis alone; a discrete point analysis was unable to detect two of the five asymmetries identified.

New preconditioning strategy for Jacobian-free solvers for variably saturated flows with Richards’ equation

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

Lipnikov, Konstantin; Moulton, David; Svyatskiy, Daniil

2016-04-29

We develop a new approach for solving the nonlinear Richards’ equation arising in variably saturated flow modeling. The growing complexity of geometric models for simulation of subsurface flows leads to the necessity of using unstructured meshes and advanced discretization methods. Typically, a numerical solution is obtained by first discretizing PDEs and then solving the resulting system of nonlinear discrete equations with a Newton-Raphson-type method. Efficiency and robustness of the existing solvers rely on many factors, including an empiric quality control of intermediate iterates, complexity of the employed discretization method and a customized preconditioner. We propose and analyze a new preconditioningmore » strategy that is based on a stable discretization of the continuum Jacobian. We will show with numerical experiments for challenging problems in subsurface hydrology that this new preconditioner improves convergence of the existing Jacobian-free solvers 3-20 times. Furthermore, we show that the Picard method with this preconditioner becomes a more efficient nonlinear solver than a few widely used Jacobian-free solvers.« less

Development of B cells expressing surface immunoglobulin molecules that lack V(D)J-encoded determinants in the avian embryo bursa of Fabricius

PubMed Central

Sayegh, Camil E.; Demaries, Sandra L.; Iacampo, Sandra; Ratcliffe, Michael J. H.

1999-01-01

Immunoglobulin gene rearrangement in avian B cell precursors generates surface Ig receptors of limited diversity. It has been proposed that specificities encoded by these receptors play a critical role in B lineage development by recognizing endogenous ligands within the bursa of Fabricius. To address this issue directly we have introduced a truncated surface IgM, lacking variable region domains, into developing B precursors by retroviral gene transfer in vivo. Cells expressing this truncated receptor lack endogenous surface IgM, and the low level of endogenous Ig rearrangements that have occurred within this population of cells has not been selected for having a productive reading frame. Such cells proliferate rapidly within bursal epithelial buds of normal morphology. In addition, despite reduced levels of endogenous light chain rearrangement, those light chain rearrangements that have occurred have undergone variable region diversification by gene conversion. Therefore, although surface expression of an Ig receptor is required for bursal colonization and the induction of gene conversion, the specificity encoded by the prediversified receptor is irrelevant and, consequently, there is no obligate ligand for V(D)J-encoded determinants of prediversified avian cell surface IgM receptor. PMID:10485907

The Wronskian solution of the constrained discrete Kadomtsev-Petviashvili hierarchy

NASA Astrophysics Data System (ADS)

Li, Maohua; He, Jingsong

2016-05-01

From the constrained discrete Kadomtsev-Petviashvili (cdKP) hierarchy, the discrete nonlinear Schrödinger (DNLS) equations have been derived. By means of the gauge transformation, the Wronskian solution of DNLS equations have been given. The u1 of the cdKP hierarchy is a Y-type soliton solution for odd times of the gauge transformation, but it becomes a dark-bright soliton solution for even times of the gauge transformation. The role of the discrete variable n in the profile of the u1 is discussed.

Endogenous Technology Adoption and Medical Costs.

PubMed

Lamiraud, Karine; Lhuillery, Stephane

2016-09-01

Despite the claim that technology has been one of the most important drivers of healthcare spending growth over the past decades, technology variables are rarely introduced explicitly in cost equations. Furthermore, technology is often considered exogenous. Using 1996-2007 panel data on Swiss geographical areas, we assessed the impact of technology availability on per capita healthcare spending covered by basic health insurance whilst controlling for the endogeneity of health technology availability variables. Our results suggest that medical research, patent intensity and the density of employees working in the medical device industry are influential factors for the adoption of technology and can be used as instruments for technology availability variables in the cost equation. These results are similar to previous findings: CT and PET scanner adoption is associated with increased healthcare spending, whilst increased availability of percutaneous transluminal coronary angioplasty facilities is associated with reductions in per capita spending. However, our results suggest that the magnitude of these relationships is much greater in absolute value than that suggested by previous studies that did not control for the possible endogeneity of the availability of technologies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Relation of Finite Element and Finite Difference Methods

NASA Technical Reports Server (NTRS)

Vinokur, M.

1976-01-01

Finite element and finite difference methods are examined in order to bring out their relationship. It is shown that both methods use two types of discrete representations of continuous functions. They differ in that finite difference methods emphasize the discretization of independent variable, while finite element methods emphasize the discretization of dependent variable (referred to as functional approximations). An important point is that finite element methods use global piecewise functional approximations, while finite difference methods normally use local functional approximations. A general conclusion is that finite element methods are best designed to handle complex boundaries, while finite difference methods are superior for complex equations. It is also shown that finite volume difference methods possess many of the advantages attributed to finite element methods.

Discrete optimal control approach to a four-dimensional guidance problem near terminal areas

NASA Technical Reports Server (NTRS)

Nagarajan, N.

1974-01-01

Description of a computer-oriented technique to generate the necessary control inputs to guide an aircraft in a given time from a given initial state to a prescribed final state subject to the constraints on airspeed, acceleration, and pitch and bank angles of the aircraft. A discrete-time mathematical model requiring five state variables and three control variables is obtained, assuming steady wind and zero sideslip. The guidance problem is posed as a discrete nonlinear optimal control problem with a cost functional of Bolza form. A solution technique for the control problem is investigated, and numerical examples are presented. It is believed that this approach should prove to be useful in automated air traffic control schemes near large terminal areas.

Low energy physical activity recognition system on smartphones.

PubMed

Soria Morillo, Luis Miguel; Gonzalez-Abril, Luis; Ortega Ramirez, Juan Antonio; de la Concepcion, Miguel Angel Alvarez

2015-03-03

An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy.

Evaluation of the Navys Sea/Shore Flow Policy

DTIC Science & Technology

2016-06-01

Std. Z39.18 i Abstract CNA developed an independent Discrete -Event Simulation model to evaluate and assess the effect of...a more steady manning level, but the variability remains, even if the system is optimized. In building a Discrete -Event Simulation model, we...steady-state model. In FY 2014, CNA developed a Discrete -Event Simulation model to evaluate the impact of sea/shore flow policy (the DES-SSF model

Antecedent Moisture and Biological Inertia as Predictors of Plant and Ecosystem Productivity in Arid and Semiarid Systems

NASA Astrophysics Data System (ADS)

Ogle, K.

2011-12-01

Many plant and ecosystem processes in arid and semiarid systems may be affected by antecedent environmental conditions (e.g., precipitation patterns, soil water availability, temperature) that integrate over past days, weeks, months, seasons, or years. However, the importance of such antecedent exogenous effects relative to conditions occurring at the time of the observed process is relatively unexplored. Even less is known about the potential importance of antecedent endogenous effects that describe the influence of past ecosystem states on the current ecosystem state; e.g., how is current ecosystem productivity related to past productivity patterns? We hypothesize that incorporation of antecedent exogenous and endogenous factors can improve our predictive understanding of many plant and ecosystem processes, especially in arid and semiarid ecosystems. Furthermore, the common approach to quantifying the effects of antecedent (exogenous) variables relies on arbitrary, deterministic definitions of antecedent variables that (1) may not accurately describe the role of antecedent conditions and (2) ignore uncertainty associated with applying deterministic definitions. In this study, we employ a stochastic framework for (1) computing the antecedent variables that estimates the relative importance of conditions experienced each time unit into the past, also providing insight into potential lag responses, and (2) estimating the effect of antecedent factors on the response variable of interest. We employ this approach to explore the potential roles of antecedent exogenous and endogenous influences in three settings that illustrate the: (1) importance of antecedent precipitation for net primary productivity in the shortgrass steppe in northern Colorado, (2) dependency of tree growth on antecedent precipitation and past growth states for pinyon growing in western Colorado, and (3) influence of antecedent soil water and prior root status on observed root growth in the Mojave Desert FACE experiment. All three examples suggest that antecedent conditions are critical to predicting different indices of productivity such that the incorporation of antecedent effects explained an additional 20-40% of the variation in the productivity responses. Antecedent endogenous factors were important for understanding tree and root growth, suggesting a potential biological inertia effect that is likely linked to labile carbon storage and allocation strategies. The role of antecedent exogenous (water) variables suggests a lag response whose duration and timing differs according to the time scale of the response variable. In summary, antecedent water availability and past endogenous states appear critical to understanding plant and ecosystem productivity in arid and semiarid systems, and this study describes a stochastic framework for quantifying the potential influence of such antecedent conditions.

A study of renal blood flow regulation using the discrete wavelet transform

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Pavlova, Olga N.; Mosekilde, Erik; Sosnovtseva, Olga V.

2010-02-01

In this paper we provide a way to distinguish features of renal blood flow autoregulation mechanisms in normotensive and hypertensive rats based on the discrete wavelet transform. Using the variability of the wavelet coefficients we show distinctions that occur between the normal and pathological states. A reduction of this variability in hypertension is observed on the microscopic level of the blood flow in efferent arteriole of single nephrons. This reduction is probably associated with higher flexibility of healthy cardiovascular system.

A 24 km fiber-based discretely signaled continuous variable quantum key distribution system.

PubMed

Dinh Xuan, Quyen; Zhang, Zheshen; Voss, Paul L

2009-12-21

We report a continuous variable key distribution system that achieves a final secure key rate of 3.45 kilobits/s over a distance of 24.2 km of optical fiber. The protocol uses discrete signaling and post-selection to improve reconciliation speed and quantifies security by means of quantum state tomography. Polarization multiplexing and a frequency translation scheme permit transmission of a continuous wave local oscillator and suppression of noise from guided acoustic wave Brillouin scattering by more than 27 dB.

The effect of prenatal care on birthweight: a full-information maximum likelihood approach.

PubMed

Rous, Jeffrey J; Jewell, R Todd; Brown, Robert W

2004-03-01

This paper uses a full-information maximum likelihood estimation procedure, the Discrete Factor Method, to estimate the relationship between birthweight and prenatal care. This technique controls for the potential biases surrounding both the sample selection of the pregnancy-resolution decision and the endogeneity of prenatal care. In addition, we use the actual number of prenatal care visits; other studies have normally measured prenatal care as the month care is initiated. We estimate a birthweight production function using 1993 data from the US state of Texas. The results underscore the importance of correcting for estimation problems. Specifically, a model that does not control for sample selection and endogeneity overestimates the benefit of an additional visit for women who have relatively few visits. This overestimation may indicate 'positive fetal selection,' i.e., women who did not abort may have healthier babies. Also, a model that does not control for self-selection and endogenity predicts that past 17 visits, an additional visit leads to lower birthweight, while a model that corrects for these estimation problems predicts a positive effect for additional visits. This result shows the effect of mothers with less healthy fetuses making more prenatal care visits, known as 'adverse selection' in prenatal care. Copyright 2003 John Wiley & Sons, Ltd.

Control approach development for variable recruitment artificial muscles

NASA Astrophysics Data System (ADS)

Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

2016-04-01

This study characterizes hybrid control approaches for the variable recruitment of fluidic artificial muscles with double acting (antagonistic) actuation. Fluidic artificial muscle actuators have been explored by researchers due to their natural compliance, high force-to-weight ratio, and low cost of fabrication. Previous studies have attempted to improve system efficiency of the actuators through variable recruitment, i.e. using discrete changes in the number of active actuators. While current variable recruitment research utilizes manual valve switching, this paper details the current development of an online variable recruitment control scheme. By continuously controlling applied pressure and discretely controlling the number of active actuators, operation in the lowest possible recruitment state is ensured and working fluid consumption is minimized. Results provide insight into switching control scheme effects on working fluids, fabrication material choices, actuator modeling, and controller development decisions.

Stability with large step sizes for multistep discretizations of stiff ordinary differential equations

NASA Technical Reports Server (NTRS)

Majda, George

1986-01-01

One-leg and multistep discretizations of variable-coefficient linear systems of ODEs having both slow and fast time scales are investigated analytically. The stability properties of these discretizations are obtained independent of ODE stiffness and compared. The results of numerical computations are presented in tables, and it is shown that for large step sizes the stability of one-leg methods is better than that of the corresponding linear multistep methods.

Discrete cosine and sine transforms generalized to honeycomb lattice

NASA Astrophysics Data System (ADS)

Hrivnák, Jiří; Motlochová, Lenka

2018-06-01

The discrete cosine and sine transforms are generalized to a triangular fragment of the honeycomb lattice. The honeycomb point sets are constructed by subtracting the root lattice from the weight lattice points of the crystallographic root system A2. The two-variable orbit functions of the Weyl group of A2, discretized simultaneously on the weight and root lattices, induce a novel parametric family of extended Weyl orbit functions. The periodicity and von Neumann and Dirichlet boundary properties of the extended Weyl orbit functions are detailed. Three types of discrete complex Fourier-Weyl transforms and real-valued Hartley-Weyl transforms are described. Unitary transform matrices and interpolating behavior of the discrete transforms are exemplified. Consequences of the developed discrete transforms for transversal eigenvibrations of the mechanical graphene model are discussed.

The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom.

PubMed

Krüger, Melanie; Straube, Andreas; Eggert, Thomas

2017-01-01

In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.

Optodynamic simulation of β-adrenergic receptor signalling

PubMed Central

Siuda, Edward R.; McCall, Jordan G.; Al-Hasani, Ream; Shin, Gunchul; Il Park, Sung; Schmidt, Martin J.; Anderson, Sonya L.; Planer, William J.; Rogers, John A.; Bruchas, Michael R.

2015-01-01

Optogenetics has provided a revolutionary approach to dissecting biological phenomena. However, the generation and use of optically active GPCRs in these contexts is limited and it is unclear how well an opsin-chimera GPCR might mimic endogenous receptor activity. Here we show that a chimeric rhodopsin/β2 adrenergic receptor (opto-β2AR) is similar in dynamics to endogenous β2AR in terms of: cAMP generation, MAP kinase activation and receptor internalization. In addition, we develop and characterize a novel toolset of optically active, functionally selective GPCRs that can bias intracellular signalling cascades towards either G-protein or arrestin-mediated cAMP and MAP kinase pathways. Finally, we show how photoactivation of opto-β2AR in vivo modulates neuronal activity and induces anxiety-like behavioural states in both fiber-tethered and wireless, freely moving animals when expressed in brain regions known to contain β2ARs. These new GPCR approaches enhance the utility of optogenetics and allow for discrete spatiotemporal control of GPCR signalling in vitro and in vivo. PMID:26412387

Optodynamic simulation of β-adrenergic receptor signalling.

PubMed

Siuda, Edward R; McCall, Jordan G; Al-Hasani, Ream; Shin, Gunchul; Il Park, Sung; Schmidt, Martin J; Anderson, Sonya L; Planer, William J; Rogers, John A; Bruchas, Michael R

2015-09-28

Optogenetics has provided a revolutionary approach to dissecting biological phenomena. However, the generation and use of optically active GPCRs in these contexts is limited and it is unclear how well an opsin-chimera GPCR might mimic endogenous receptor activity. Here we show that a chimeric rhodopsin/β2 adrenergic receptor (opto-β2AR) is similar in dynamics to endogenous β2AR in terms of: cAMP generation, MAP kinase activation and receptor internalization. In addition, we develop and characterize a novel toolset of optically active, functionally selective GPCRs that can bias intracellular signalling cascades towards either G-protein or arrestin-mediated cAMP and MAP kinase pathways. Finally, we show how photoactivation of opto-β2AR in vivo modulates neuronal activity and induces anxiety-like behavioural states in both fiber-tethered and wireless, freely moving animals when expressed in brain regions known to contain β2ARs. These new GPCR approaches enhance the utility of optogenetics and allow for discrete spatiotemporal control of GPCR signalling in vitro and in vivo.

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

DOT National Transportation Integrated Search

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Numerical simulation of freshwater/seawater interaction in a dual-permeability karst system with conduits: the development of discrete-continuum VDFST-CFP model

NASA Astrophysics Data System (ADS)

Xu, Zexuan; Hu, Bill

2016-04-01

Dual-permeability karst aquifers of porous media and conduit networks with significant different hydrological characteristics are widely distributed in the world. Discrete-continuum numerical models, such as MODFLOW-CFP and CFPv2, have been verified as appropriate approaches to simulate groundwater flow and solute transport in numerical modeling of karst hydrogeology. On the other hand, seawater intrusion associated with fresh groundwater resources contamination has been observed and investigated in numbers of coastal aquifers, especially under conditions of sea level rise. Density-dependent numerical models including SEAWAT are able to quantitatively evaluate the seawater/freshwater interaction processes. A numerical model of variable-density flow and solute transport - conduit flow process (VDFST-CFP) is developed to provide a better description of seawater intrusion and submarine groundwater discharge in a coastal karst aquifer with conduits. The coupling discrete-continuum VDFST-CFP model applies Darcy-Weisbach equation to simulate non-laminar groundwater flow in the conduit system in which is conceptualized and discretized as pipes, while Darcy equation is still used in continuum porous media. Density-dependent groundwater flow and solute transport equations with appropriate density terms in both conduit and porous media systems are derived and numerically solved using standard finite difference method with an implicit iteration procedure. Synthetic horizontal and vertical benchmarks are created to validate the newly developed VDFST-CFP model by comparing with other numerical models such as variable density SEAWAT, couplings of constant density groundwater flow and solute transport MODFLOW/MT3DMS and discrete-continuum CFPv2/UMT3D models. VDFST-CFP model improves the simulation of density dependent seawater/freshwater mixing processes and exchanges between conduit and matrix. Continuum numerical models greatly overestimated the flow rate under turbulent flow condition but discrete-continuum models provide more accurate results. Parameters sensitivities analysis indicates that conduit diameter and friction factor, matrix hydraulic conductivity and porosity are important parameters that significantly affect variable-density flow and solute transport simulation. The pros and cons of model assumptions, conceptual simplifications and numerical techniques in VDFST-CFP are discussed. In general, the development of VDFST-CFP model is an innovation in numerical modeling methodology and could be applied to quantitatively evaluate the seawater/freshwater interaction in coastal karst aquifers. Keywords: Discrete-continuum numerical model; Variable density flow and transport; Coastal karst aquifer; Non-laminar flow

School system evaluation by value added analysis under endogeneity.

PubMed

Manzi, Jorge; San Martín, Ernesto; Van Bellegem, Sébastien

2014-01-01

Value added is a common tool in educational research on effectiveness. It is often modeled as a (prediction of a) random effect in a specific hierarchical linear model. This paper shows that this modeling strategy is not valid when endogeneity is present. Endogeneity stems, for instance, from a correlation between the random effect in the hierarchical model and some of its covariates. This paper shows that this phenomenon is far from exceptional and can even be a generic problem when the covariates contain the prior score attainments, a typical situation in value added modeling. Starting from a general, model-free definition of value added, the paper derives an explicit expression of the value added in an endogeneous hierarchical linear Gaussian model. Inference on value added is proposed using an instrumental variable approach. The impact of endogeneity on the value added and the estimated value added is calculated accurately. This is also illustrated on a large data set of individual scores of about 200,000 students in Chile.

Sniffer patch laser uncaging response (SPLURgE): an assay of regional differences in allosteric receptor modulation and neurotransmitter clearance

PubMed Central

Christian, Catherine A.

2013-01-01

Allosteric modulators exert actions on neurotransmitter receptors by positively or negatively altering the effective response of these receptors to their respective neurotransmitter. γ-Aminobutyric acid (GABA) type A ionotropic receptors (GABAARs) are major targets for allosteric modulators such as benzodiazepines, neurosteroids, and barbiturates. Analysis of substances that produce similar effects has been hampered by the lack of techniques to assess the localization and function of such agents in brain slices. Here we describe measurement of the sniffer patch laser uncaging response (SPLURgE), which combines the sniffer patch recording configuration with laser photolysis of caged GABA. This methodology enables the detection of allosteric GABAAR modulators endogenously present in discrete areas of the brain slice and allows for the application of exogenous GABA with spatiotemporal control without altering the release and localization of endogenous modulators within the slice. Here we demonstrate the development and use of this technique for the measurement of allosteric modulation in different areas of the thalamus. Application of this technique will be useful in determining whether a lack of modulatory effect on a particular category of neurons or receptors is due to insensitivity to allosteric modulation or a lack of local release of endogenous ligand. We also demonstrate that this technique can be used to investigate GABA diffusion and uptake. This method thus provides a biosensor assay for rapid detection of endogenous GABAAR modulators and has the potential to aid studies of allosteric modulators that exert effects on other classes of neurotransmitter receptors, such as glutamate, acetylcholine, or glycine receptors. PMID:23843428

Sniffer patch laser uncaging response (SPLURgE): an assay of regional differences in allosteric receptor modulation and neurotransmitter clearance.

PubMed

Christian, Catherine A; Huguenard, John R

2013-10-01

Allosteric modulators exert actions on neurotransmitter receptors by positively or negatively altering the effective response of these receptors to their respective neurotransmitter. γ-Aminobutyric acid (GABA) type A ionotropic receptors (GABAARs) are major targets for allosteric modulators such as benzodiazepines, neurosteroids, and barbiturates. Analysis of substances that produce similar effects has been hampered by the lack of techniques to assess the localization and function of such agents in brain slices. Here we describe measurement of the sniffer patch laser uncaging response (SPLURgE), which combines the sniffer patch recording configuration with laser photolysis of caged GABA. This methodology enables the detection of allosteric GABAAR modulators endogenously present in discrete areas of the brain slice and allows for the application of exogenous GABA with spatiotemporal control without altering the release and localization of endogenous modulators within the slice. Here we demonstrate the development and use of this technique for the measurement of allosteric modulation in different areas of the thalamus. Application of this technique will be useful in determining whether a lack of modulatory effect on a particular category of neurons or receptors is due to insensitivity to allosteric modulation or a lack of local release of endogenous ligand. We also demonstrate that this technique can be used to investigate GABA diffusion and uptake. This method thus provides a biosensor assay for rapid detection of endogenous GABAAR modulators and has the potential to aid studies of allosteric modulators that exert effects on other classes of neurotransmitter receptors, such as glutamate, acetylcholine, or glycine receptors.

Introduced T cell receptor variable region gene segments recombine in pre-B cells: evidence that B and T cells use a common recombinase.

PubMed

Yancopoulos, G D; Blackwell, T K; Suh, H; Hood, L; Alt, F W

1986-01-31

We have recently proposed that a common recombinase performs all of the many variable region gene assembly events in B and T cells, and that the specificity of these joining events is mediated by regulating the "accessibility" of the involved gene segments. To test this possibility, we have introduced "accessible" T cell receptor (TCR) variable region gene segments into a pre-B cell line capable of recombining endogenous and transfected immunoglobulin (Ig) variable region gene segments. Although the corresponding "inaccessible" endogenous TCR gene segments do not rearrange in this line or in B cells in general, the introduced TCR gene segments join very frequently and, in fact, closely resemble introduced Ig gene segments in their recombination characteristics. These observations suggest a new role for conventional Ig transcriptional enhancers--recombinational enhancement. Our studies provide insight into additional aspects of the joining mechanism such as N region insertion, aberrant joining, and recombination-recognition sequence requirements for joining.

Generalized chaos synchronization theorems for bidirectional differential equations and discrete systems with applications

NASA Astrophysics Data System (ADS)

Ji, Ye; Liu, Ting; Min, Lequan

2008-05-01

Two constructive generalized chaos synchronization (GCS) theorems for bidirectional differential equations and discrete systems are introduced. Using the two theorems, one can construct new chaos systems to make the system variables be in GCS. Five examples are presented to illustrate the effectiveness of the theoretical results.

A coherent discrete variable representation method on a sphere

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

Yu, Hua -Gen

Here, the coherent discrete variable representation (ZDVR) has been extended for construct- ing a multidimensional potential-optimized DVR basis on a sphere. In order to deal with the non-constant Jacobian in spherical angles, two direct product primitive basis methods are proposed so that the original ZDVR technique can be properly implemented. The method has been demonstrated by computing the lowest states of a two dimensional (2D) vibrational model. Results show that the extended ZDVR method gives accurate eigenval- ues and exponential convergence with increasing ZDVR basis size.

A coherent discrete variable representation method on a sphere

DOE PAGES

Yu, Hua -Gen

2017-09-05

Here, the coherent discrete variable representation (ZDVR) has been extended for construct- ing a multidimensional potential-optimized DVR basis on a sphere. In order to deal with the non-constant Jacobian in spherical angles, two direct product primitive basis methods are proposed so that the original ZDVR technique can be properly implemented. The method has been demonstrated by computing the lowest states of a two dimensional (2D) vibrational model. Results show that the extended ZDVR method gives accurate eigenval- ues and exponential convergence with increasing ZDVR basis size.

Students' Misconceptions about Random Variables

ERIC Educational Resources Information Center

Kachapova, Farida; Kachapov, Ilias

2012-01-01

This article describes some misconceptions about random variables and related counter-examples, and makes suggestions about teaching initial topics on random variables in general form instead of doing it separately for discrete and continuous cases. The focus is on post-calculus probability courses. (Contains 2 figures.)

Heterogeneity of rabbit endogenous pyrogens is not attributable to glycosylated variants of a single polypeptide chain.

PubMed

Murphy, P A; Cebula, T A; Windle, B E

1981-10-01

Rabbit endogenous pyrogens were of about the same molecular size, but showed considerable heterogeneity of their isoelectric points. We attempted to show that this heterogeneity was attributable to variable glycosylation of a single polypeptide chain. When peritoneal exudate cells were stimulated to make pyrogens in the presence of 2-deoxy-D-glucose, there was a relatively trivial suppression of pyrogen release, and analysis by isoelectric focusing showed parallel inhibition of secretion of all the forms of endogenous pyrogen. When cells were stimulated in the presence of 3H-labeled amino acids and 14C-labeled glucosamine or glucose, the purified pyrogens were labeled with 3H but not with 14C. Macrophage membrane preparations were made which contained glycosyl transferases and could transfer sugar residues from sugar nucleotides to deglycosylated fetuin. These macrophage membrane preparations did not transfer sugars to the pI 7.3 endogenous pyrogen. Treatment of endogenous pyrogens with neuraminidase or with periodate produced no evidence suggesting that the pyrogens were glycosylated. Last, endogenous pyrogens did not bind to any of four lectins with different carbohydrate specificities. This evidence suggests that the heterogeneity of rabbit endogenous pyrogens is not attributable to glycosylation and must have some other cause.

Heterogeneity of rabbit endogenous pyrogens is not attributable to glycosylated variants of a single polypeptide chain.

PubMed Central

Murphy, P A; Cebula, T A; Windle, B E

1981-01-01

Rabbit endogenous pyrogens were of about the same molecular size, but showed considerable heterogeneity of their isoelectric points. We attempted to show that this heterogeneity was attributable to variable glycosylation of a single polypeptide chain. When peritoneal exudate cells were stimulated to make pyrogens in the presence of 2-deoxy-D-glucose, there was a relatively trivial suppression of pyrogen release, and analysis by isoelectric focusing showed parallel inhibition of secretion of all the forms of endogenous pyrogen. When cells were stimulated in the presence of 3H-labeled amino acids and 14C-labeled glucosamine or glucose, the purified pyrogens were labeled with 3H but not with 14C. Macrophage membrane preparations were made which contained glycosyl transferases and could transfer sugar residues from sugar nucleotides to deglycosylated fetuin. These macrophage membrane preparations did not transfer sugars to the pI 7.3 endogenous pyrogen. Treatment of endogenous pyrogens with neuraminidase or with periodate produced no evidence suggesting that the pyrogens were glycosylated. Last, endogenous pyrogens did not bind to any of four lectins with different carbohydrate specificities. This evidence suggests that the heterogeneity of rabbit endogenous pyrogens is not attributable to glycosylation and must have some other cause. PMID:6271680

Biomechanical contributions of the trunk and upper extremity in discrete versus cyclic reaching in survivors of stroke.

PubMed

Massie, Crystal L; Malcolm, Matthew P; Greene, David P; Browning, Raymond C

2014-01-01

Stroke rehabilitation interventions and assessments incorporate discrete and/or cyclic reaching tasks, yet no biomechanical comparison exists between these 2 movements in survivors of stroke. To characterize the differences between discrete (movements bounded by stationary periods) and cyclic (continuous repetitive movements) reaching in survivors of stroke. Seventeen survivors of stroke underwent kinematic motion analysis of discrete and cyclic reaching movements. Outcomes collected for each side included shoulder, elbow, and trunk range of motion (ROM); peak velocity; movement time; and spatial variability at target contact. Participants used significantly less shoulder and elbow ROM and significantly more trunk flexion ROM when reaching with the stroke-affected side compared with the less-affected side (P < .001). Participants used significantly more trunk rotation during cyclic reaching than discrete reaching with the stroke-affected side (P = .01). No post hoc differences were observed between tasks within the stroke-affected side for elbow, shoulder, and trunk flexion ROM. Peak velocity, movement time, and spatial variability were not different between discrete and cyclic reaching in the stroke-affected side. Survivors of stroke reached with altered kinematics when the stroke-affected side was compared with the less-affected side, yet there were few differences between discrete and cyclic reaching within the stroke-affected side. The greater trunk rotation during cyclic reaching represents a unique segmental strategy when using the stroke-affected side without consequences to end-point kinematics. These findings suggest that clinicians should consider the type of reaching required in therapeutic activities because of the continuous movement demands required with cyclic reaching.

An improved switching converter model using discrete and average techniques

NASA Technical Reports Server (NTRS)

Shortt, D. J.; Lee, F. C.

1982-01-01

The nonlinear modeling and analysis of dc-dc converters has been done by averaging and discrete-sampling techniques. The averaging technique is simple, but inaccurate as the modulation frequencies approach the theoretical limit of one-half the switching frequency. The discrete technique is accurate even at high frequencies, but is very complex and cumbersome. An improved model is developed by combining the aforementioned techniques. This new model is easy to implement in circuit and state variable forms and is accurate to the theoretical limit.

Quadratic Finite Element Method for 1D Deterministic Transport

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

Tolar, Jr., D R; Ferguson, J M

2004-01-06

In the discrete ordinates, or SN, numerical solution of the transport equation, both the spatial ({und r}) and angular ({und {Omega}}) dependences on the angular flux {psi}{und r},{und {Omega}}are modeled discretely. While significant effort has been devoted toward improving the spatial discretization of the angular flux, we focus on improving the angular discretization of {psi}{und r},{und {Omega}}. Specifically, we employ a Petrov-Galerkin quadratic finite element approximation for the differencing of the angular variable ({mu}) in developing the one-dimensional (1D) spherical geometry S{sub N} equations. We develop an algorithm that shows faster convergence with angular resolution than conventional S{sub N} algorithms.

Exactly and quasi-exactly solvable 'discrete' quantum mechanics.

PubMed

Sasaki, Ryu

2011-03-28

A brief introduction to discrete quantum mechanics is given together with the main results on various exactly solvable systems. Namely, the intertwining relations, shape invariance, Heisenberg operator solutions, annihilation/creation operators and dynamical symmetry algebras, including the q-oscillator algebra and the Askey-Wilson algebra. A simple recipe to construct exactly and quasi-exactly solvable (QES) Hamiltonians in one-dimensional 'discrete' quantum mechanics is presented. It reproduces all the known Hamiltonians whose eigenfunctions consist of the Askey scheme of hypergeometric orthogonal polynomials of a continuous or a discrete variable. Several new exactly and QES Hamiltonians are constructed. The sinusoidal coordinate plays an essential role.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Evidence for a Stable Intermediate in Leukemia Virus Activation in AKR Mouse Embryo Cells

PubMed Central

Ihle, James N.; Kenney, Francis T.; Tennant, Raymond W.

1974-01-01

Analysis of the requirement for serum in the activation of the endogenous leukemia virus expression in AKR mouse embryo cells by 5-iododeoxyuridine shows that activation can be dissociated into two discrete serum-dependent events. The first involves incorporation of 5-iododeoxyuridine into DNA and results in the formation of a stable “activation intermediate” resembling the provirus formed during infection of stationary mouse embryo cells with exogenous leukemia virus. The second event, resulting in expression of the activation intermediate as synthesis of virus proteins, requires DNA replication but not 5-iododeoxyuridine. PMID:4604455

MEDICAL EXPENDITURE RISK AND HOUSEHOLD PORTFOLIO CHOICE

PubMed Central

Goldman, Dana

2013-01-01

Medical expenses are an increasingly important contributor to household financial risk. We examine the effect of medical expenditure risk on the willingness of Medicare beneficiaries to hold risky assets. Using a discrete factor maximum likelihood method to address the endogeneity of insurance choices, we find that having a moderately protective Medigap or employer supplemental policy increases risky asset holding by 7.1 percentage points relative to those without supplemental coverage, while participation in a highly protective Medicare HMO increases risky asset holding by 13.0 percentage points. Our results highlight an important link between the availability of health insurance and financial behavior. PMID:23997424

Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

PubMed

Verdam, Mathilde G E; Oort, Frans J; Sprangers, Mirjam A G

2016-06-01

The structural equation modeling (SEM) approach for detection of response shift (Oort in Qual Life Res 14:587-598, 2005. doi: 10.1007/s11136-004-0830-y ) is especially suited for continuous data, e.g., questionnaire scales. The present objective is to explain how the SEM approach can be applied to discrete data and to illustrate response shift detection in items measuring health-related quality of life (HRQL) of cancer patients. The SEM approach for discrete data includes two stages: (1) establishing a model of underlying continuous variables that represent the observed discrete variables, (2) using these underlying continuous variables to establish a common factor model for the detection of response shift and to assess true change. The proposed SEM approach was illustrated with data of 485 cancer patients whose HRQL was measured with the SF-36, before and after start of antineoplastic treatment. Response shift effects were detected in items of the subscales mental health, physical functioning, role limitations due to physical health, and bodily pain. Recalibration response shifts indicated that patients experienced relatively fewer limitations with "bathing or dressing yourself" (effect size d = 0.51) and less "nervousness" (d = 0.30), but more "pain" (d = -0.23) and less "happiness" (d = -0.16) after antineoplastic treatment as compared to the other symptoms of the same subscale. Overall, patients' mental health improved, while their physical health, vitality, and social functioning deteriorated. No change was found for the other subscales of the SF-36. The proposed SEM approach to discrete data enables response shift detection at the item level. This will lead to a better understanding of the response shift phenomena at the item level and therefore enhances interpretation of change in the area of HRQL.

Application of variable-gain output feedback for high-alpha control

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.

1990-01-01

A variable-gain, optimal, discrete, output feedback design approach that is applied to a nonlinear flight regime is described. The flight regime covers a wide angle-of-attack range that includes stall and post stall. The paper includes brief descriptions of the variable-gain formulation, the discrete-control structure and flight equations used to apply the design approach, and the high performance airplane model used in the application. Both linear and nonlinear analysis are shown for a longitudinal four-model design case with angles of attack of 5, 15, 35, and 60 deg. Linear and nonlinear simulations are compared for a single-point longitudinal design at 60 deg angle of attack. Nonlinear simulations for the four-model, multi-mode, variable-gain design include a longitudinal pitch-up and pitch-down maneuver and high angle-of-attack regulation during a lateral maneuver.

Development toward School Readiness: A Holistic Model

ERIC Educational Resources Information Center

Gaynor, Alan Kibbe

2015-01-01

A systemic analysis of early childhood development factors explains the variance in school readiness among representative U.S. 5-year-olds. The underlying theory incorporates a set of causally interactive endogenous variables that are hypothesized to be driven by the effects of three exogenous variables: parental education, immigrant status and…

Leaping from Discrete to Continuous Independent Variables: Sixth Graders' Science Line Graph Interpretations

ERIC Educational Resources Information Center

Boote, Stacy K.; Boote, David N.

2017-01-01

Students often struggle to interpret graphs correctly, despite emphasis on graphic literacy in U.S. education standards documents. The purpose of this study was to describe challenges sixth graders with varying levels of science and mathematics achievement encounter when transitioning from interpreting graphs having discrete independent variables…

Discrete-Trial Functional Analysis and Functional Communication Training with Three Individuals with Autism and Severe Problem Behavior

ERIC Educational Resources Information Center

Schmidt, Jonathan D.; Drasgow, Erik; Halle, James W.; Martin, Christian A.; Bliss, Sacha A.

2014-01-01

Discrete-trial functional analysis (DTFA) is an experimental method for determining the variables maintaining problem behavior in the context of natural routines. Functional communication training (FCT) is an effective method for replacing problem behavior, once identified, with a functionally equivalent response. We implemented these procedures…

Lens elliptic gamma function solution of the Yang-Baxter equation at roots of unity

NASA Astrophysics Data System (ADS)

Kels, Andrew P.; Yamazaki, Masahito

2018-02-01

We study the root of unity limit of the lens elliptic gamma function solution of the star-triangle relation, for an integrable model with continuous and discrete spin variables. This limit involves taking an elliptic nome to a primitive rNth root of unity, where r is an existing integer parameter of the lens elliptic gamma function, and N is an additional integer parameter. This is a singular limit of the star-triangle relation, and at subleading order of an asymptotic expansion, another star-triangle relation is obtained for a model with discrete spin variables in {Z}rN . Some special choices of solutions of equation of motion are shown to result in well-known discrete spin solutions of the star-triangle relation. The saddle point equations themselves are identified with three-leg forms of ‘3D-consistent’ classical discrete integrable equations, known as Q4 and Q3(δ=0) . We also comment on the implications for supersymmetric gauge theories, and in particular comment on a close parallel with the works of Nekrasov and Shatashvili.

Air Cargo Transportation Route Choice Analysis

NASA Technical Reports Server (NTRS)

Obashi, Hiroshi; Kim, Tae-Seung; Oum, Tae Hoon

2003-01-01

Using a unique feature of air cargo transshipment data in the Northeast Asian region, this paper identifies the critical factors that determine the transshipment route choice. Taking advantage of the variations in the transport characteristics in each origin-destination airports pair, the paper uses a discrete choice model to describe the transshipping route choice decision made by an agent (i.e., freight forwarder, consolidator, and large shipper). The analysis incorporates two major factors, monetary cost (such as line-haul cost and landing fee) and time cost (i.e., aircraft turnaround time, including loading and unloading time, custom clearance time, and expected scheduled delay), along with other controls. The estimation method considers the presence of unobserved attributes, and corrects for resulting endogeneity by use of appropriate instrumental variables. Estimation results find that transshipment volumes are more sensitive to time cost, and that the reduction in aircraft turnaround time by 1 hour would be worth the increase in airport charges by more than $1000. Simulation exercises measures the impacts of alternative policy scenarios for a Korean airport, which has recently declared their intention to be a future regional hub in the Northeast Asian region. The results suggest that reducing aircraft turnaround time at the airport be an effective strategy, rather than subsidizing to reduce airport charges.

Light and dark adaptation mechanisms in the compound eyes of Myrmecia ants that occupy discrete temporal niches.

PubMed

Narendra, Ajay; Greiner, Birgit; Ribi, Willi A; Zeil, Jochen

2016-08-15

Ants of the Australian genus Myrmecia partition their foraging niche temporally, allowing them to be sympatric with overlapping foraging requirements. We used histological techniques to study the light and dark adaptation mechanisms in the compound eyes of diurnal (Myrmecia croslandi), crepuscular (M. tarsata, M. nigriceps) and nocturnal ants (M. pyriformis). We found that, except in the day-active species, all ants have a variable primary pigment cell pupil that constricts the crystalline cone in bright light to control for light flux. We show for the nocturnal M. pyriformis that the constriction of the crystalline cone by the primary pigment cells is light dependent whereas the opening of the aperture is regulated by an endogenous rhythm. In addition, in the light-adapted eyes of all species, the retinular cell pigment granules radially migrate towards the rhabdom, a process that in both the day-active M. croslandi and the night-active M. pyriformis is driven by ambient light intensity. Visual system properties thus do not restrict crepuscular and night-active ants to their temporal foraging niche, while day-active ants require high light intensities to operate. We discuss the ecological significance of these adaptation mechanisms and their role in temporal niche partitioning. © 2016. Published by The Company of Biologists Ltd.

The Effect of Private Insurance on the Health of Older, Working Age Adults: Evidence from the Health and Retirement Study

PubMed Central

Dor, Avi; Sudano, Joseph; Baker, David W

2006-01-01

Objective Primarily, to determine if the presence of private insurance leads to improved health status, as measured by a survey-based health score. Secondarily, to explore sensitivity of estimates to adjustments for endogeneity. The study focuses on adults in late middle age who are nearing entry into Medicare. Data Sources The analysis file is drawn from the Health and Retirement Study, a national survey of relatively older adults in the labor force. The dependent variable, an index of 5 health outcome items, was obtained from the 1996 survey. Independent variables were obtained from the 1992 survey. State-level instrumental variables were obtained from the Area Resources File and the TAXSIM file. The final sample consists of 9,034 individuals of which 1,540 were uninsured. Study Design Estimation addresses endogeneity of the insurance participation decision in health score regressions. In addition to ordinary least squares (OLS), two models are tested: an instrumental variables (IV) model, and a model with endogenous treatment effects due to Heckman (1978). Insurance participation and health behaviors enter with a lag to allow their effects to dissipate over time. Separate regressions were run for groupings of chronic conditions. Principal Findings The OLS model results in statistically significant albeit small effects of insurance on the computed health score, but the results may be downward biased. Adjusting for endogeneity using state-level instrumental variables yields up to a six-fold increase in the insurance effect. Results are consistent across IV and treatment effects models, and for major groupings of medical conditions. The insurance effect appears to be in the range of about 2–11 percent. There appear to be no significant differences in the insurance effect for subgroups with and without major chronic conditions. Conclusions Extending insurance coverage to working age adults may result in improved health. By conjecture, policies aimed at expanding coverage to this population may lead to improved health at retirement and entry to Medicare, potentially leading to savings. However, further research is needed to determine whether similar results are found when alternative measures of overall health or health scores are used. Future research should also explore the use of alternative instrumental variables. Preliminary results provide no justification for targeting certain subgroups with susceptibility to certain chronic conditions rather than broad policy interventions. PMID:16704511

Multilayer shallow water models with locally variable number of layers and semi-implicit time discretization

NASA Astrophysics Data System (ADS)

Bonaventura, Luca; Fernández-Nieto, Enrique D.; Garres-Díaz, José; Narbona-Reina, Gladys

2018-07-01

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in which the number of vertical layers and their distribution are allowed to change in different regions of the computational domain. Furthermore, semi-implicit schemes are employed for the time discretization, leading to a significant efficiency improvement for subcritical regimes. We show that, in the typical regimes in which the application of multilayer shallow water models is justified, the resulting discretization does not introduce any major spurious feature and allows again to reduce substantially the computational cost in areas with complex bathymetry. As an example of the potential of the proposed technique, an application to a sediment transport problem is presented, showing a remarkable improvement with respect to standard discretization approaches.

Comparative dynamic analysis of the full Grossman model.

PubMed

Ried, W

1998-08-01

The paper applies the method of comparative dynamic analysis to the full Grossman model. For a particular class of solutions, it derives the equations implicitly defining the complete trajectories of the endogenous variables. Relying on the concept of Frisch decision functions, the impact of any parametric change on an endogenous variable can be decomposed into a direct and an indirect effect. The focus of the paper is on marginal changes in the rate of health capital depreciation. It also analyses the impact of either initial financial wealth or the initial stock of health capital. While the direction of most effects remains ambiguous in the full model, the assumption of a zero consumption benefit of health is sufficient to obtain a definite for any direct or indirect effect.

THAT INSTRUMENT IS LOUSY! IN SEARCH OF AGREEMENT WHEN USING INSTRUMENTAL VARIABLES ESTIMATION IN SUBSTANCE USE RESEARCH

PubMed Central

Popovici, Ioana

2009-01-01

SUMMARY The primary statistical challenge that must be addressed when using cross-sectional data to estimate the consequences of consuming addictive substances is the likely endogeneity of substance use. While economists are in agreement on the need to consider potential endogeneity bias and the value of instrumental variables estimation, the selection of credible instruments is a topic of heated debate in the field. Rather than attempt to resolve this debate, our paper highlights the diversity of judgments about what constitutes appropriate instruments for substance use based on a comprehensive review of the economics literature since 1990. We then offer recommendations related to the selection of reliable instruments in future studies. PMID:20029936

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

PubMed Central

Weiss, Scott T.

2014-01-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com. PMID:24922310

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

PubMed

McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

2014-06-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

Two-Stage Bayesian Model Averaging in Endogenous Variable Models*

PubMed Central

Lenkoski, Alex; Eicher, Theo S.; Raftery, Adrian E.

2013-01-01

Economic modeling in the presence of endogeneity is subject to model uncertainty at both the instrument and covariate level. We propose a Two-Stage Bayesian Model Averaging (2SBMA) methodology that extends the Two-Stage Least Squares (2SLS) estimator. By constructing a Two-Stage Unit Information Prior in the endogenous variable model, we are able to efficiently combine established methods for addressing model uncertainty in regression models with the classic technique of 2SLS. To assess the validity of instruments in the 2SBMA context, we develop Bayesian tests of the identification restriction that are based on model averaged posterior predictive p-values. A simulation study showed that 2SBMA has the ability to recover structure in both the instrument and covariate set, and substantially improves the sharpness of resulting coefficient estimates in comparison to 2SLS using the full specification in an automatic fashion. Due to the increased parsimony of the 2SBMA estimate, the Bayesian Sargan test had a power of 50 percent in detecting a violation of the exogeneity assumption, while the method based on 2SLS using the full specification had negligible power. We apply our approach to the problem of development accounting, and find support not only for institutions, but also for geography and integration as development determinants, once both model uncertainty and endogeneity have been jointly addressed. PMID:24223471

Investigations into the differential reactivity of endogenous and exogenous mercury species in coastal sediments.

PubMed

Bouchet, S; Rodriguez-Gonzalez, P; Bridou, R; Monperrus, M; Tessier, E; Anschutz, P; Guyoneaud, R; Amouroux, D

2013-03-01

Stable isotopic tracer methodologies now allow the evaluation of the reactivity of the endogenous (ambient) and exogenous (added) Hg to further predict the potential effect of Hg inputs in ecosystems. The differential reactivity of endogenous and exogenous Hg was compared in superficial sediments collected in a coastal lagoon (Arcachon Bay) and in an estuary (Adour River) from the Bay of Biscay (SW France). All Hg species (gaseous, aqueous, and solid fraction) and ancillary data were measured during time course slurry experiments under variable redox conditions. The average endogenous methylation yield was higher in the estuarine (1.2 %) than in the lagoonal sediment (0.5 %), although both methylation and demethylation rates were higher in the lagoonal sediment in relation with a higher sulfate-reducing activity. Demethylation was overall more consistent than methylation in both sediments. The endogenous and exogenous Hg behaviors were always correlated but the exogenous inorganic Hg (IHg) partitioning into water was 2.0-4.3 times higher than the endogenous one. Its methylation was just slightly higher (1.4) in the estuarine sediment while the difference in the lagoonal sediment was much larger (3.6). The relative endogenous and exogenous methylation yields were not correlated to IHg partitioning, demonstrating that the bioavailable species distributions were different for the two IHg pools. In both sediments, the exogenous IHg partitioning equaled the endogenous one within a week, while its higher methylation lasted for months. Such results provide an original assessment approach to compare coastal sediment response to Hg inputs.

Rational Ruijsenaars Schneider hierarchy and bispectral difference operators

NASA Astrophysics Data System (ADS)

Iliev, Plamen

2007-05-01

We show that a monic polynomial in a discrete variable n, with coefficients depending on time variables t1,t2,…, is a τ-function for the discrete Kadomtsev-Petviashvili hierarchy if and only if the motion of its zeros is governed by a hierarchy of Ruijsenaars-Schneider systems. These τ-functions were considered in [L. Haine, P. Iliev, Commutative rings of difference operators and an adelic flag manifold, Int. Math. Res. Not. 2000 (6) (2000) 281-323], where it was proved that they parametrize rank one solutions to a difference-differential version of the bispectral problem.

Interesting examples of supervised continuous variable systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joe; Ramadge, Peter

1990-01-01

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

DOE PAGES

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.; ...

2017-01-01

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution.

PubMed

Cai, Hong; Long, Christopher M; DeRose, Christopher T; Boynton, Nicholas; Urayama, Junji; Camacho, Ryan; Pomerene, Andrew; Starbuck, Andrew L; Trotter, Douglas C; Davids, Paul S; Lentine, Anthony L

2017-05-29

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

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

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Heterogeneous impact of the "Seguro Popular" program on the utilization of obstetrical services in Mexico, 2001-2006: a multinomial probit model with a discrete endogenous variable.

PubMed

Sosa-Rubí, Sandra G; Galárraga, Omar; Harris, Jeffrey E

2009-01-01

We evaluated the impact of Seguro Popular (SP), a program introduced in 2001 in Mexico primarily to finance health care for the poor. We focused on the effect of household enrollment in SP on pregnant women's access to obstetrical services, an important outcome measure of both maternal and infant health. We relied upon data from the cross-sectional 2006 National Health and Nutrition Survey (ENSANUT) in Mexico. We analyzed the responses of 3890 women who delivered babies during 2001-2006 and whose households lacked employer-based health care coverage. We formulated a multinomial probit model that distinguished between three mutually exclusive sites for delivering a baby: a health unit specifically accredited by SP; a non-SP-accredited clinic run by the Department of Health (Secretaría de Salud, or SSA); and private obstetrical care. Our model accounted for the endogeneity of the household's binary decision to enroll in the SP program. Women in households that participated in the SP program had a much stronger preference for having a baby in a SP-sponsored unit rather than paying out of pocket for a private delivery. At the same time, participation in SP was associated with a stronger preference for delivering in the private sector rather than at a state-run SSA clinic. On balance, the Seguro Popular program reduced pregnant women's attendance at an SSA clinic much more than it reduced the probability of delivering a baby in the private sector. The quantitative impact of the SP program varied with the woman's education and health, as well as the assets and location (rural vs. urban) of the household. The SP program had a robust, significantly positive impact on access to obstetrical services. Our finding that women enrolled in SP switched from non-SP state-run facilities, rather than from out-of-pocket private services, is important for public policy and requires further exploration.

Entanglement transfer from two-mode continuous variable SU(2) cat states to discrete qubits systems in Jaynes-Cummings Dimers

PubMed Central

Ran, Du; Hu, Chang-Sheng; Yang, Zhen-Biao

2016-01-01

We study the entanglement transfer from a two-mode continuous variable system (initially in the two-mode SU(2) cat states) to a couple of discrete two-state systems (initially in an arbitrary mixed state), by use of the resonant Jaynes-Cummings (JC) interaction. We first quantitatively connect the entanglement transfer to non-Gaussianity of the two-mode SU(2) cat states and find a positive correlation between them. We then investigate the behaviors of the entanglement transfer and find that it is dependent on the initial state of the discrete systems. We also find that the largest possible value of the transferred entanglement exhibits a variety of behaviors for different photon number as well as for the phase angle of the two-mode SU(2) cat states. We finally consider the influences of the noise on the transferred entanglement. PMID:27553881

On Studying Common Factor Dominance and Approximate Unidimensionality in Multicomponent Measuring Instruments with Discrete Items

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2018-01-01

This article outlines a procedure for examining the degree to which a common factor may be dominating additional factors in a multicomponent measuring instrument consisting of binary items. The procedure rests on an application of the latent variable modeling methodology and accounts for the discrete nature of the manifest indicators. The method…

Modular architecture for robotics and teleoperation

DOEpatents

Anderson, Robert J.

1996-12-03

Systems and methods for modularization and discretization of real-time robot, telerobot and teleoperation systems using passive, network based control laws. Modules consist of network one-ports and two-ports. Wave variables and position information are passed between modules. The behavior of each module is decomposed into uncoupled linear-time-invariant, and coupled, nonlinear memoryless elements and then are separately discretized.

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Discrete variable representation in electronic structure theory: quadrature grids for least-squares tensor hypercontraction.

PubMed

Parrish, Robert M; Hohenstein, Edward G; Martínez, Todd J; Sherrill, C David

2013-05-21

We investigate the application of molecular quadratures obtained from either standard Becke-type grids or discrete variable representation (DVR) techniques to the recently developed least-squares tensor hypercontraction (LS-THC) representation of the electron repulsion integral (ERI) tensor. LS-THC uses least-squares fitting to renormalize a two-sided pseudospectral decomposition of the ERI, over a physical-space quadrature grid. While this procedure is technically applicable with any choice of grid, the best efficiency is obtained when the quadrature is tuned to accurately reproduce the overlap metric for quadratic products of the primary orbital basis. Properly selected Becke DFT grids can roughly attain this property. Additionally, we provide algorithms for adopting the DVR techniques of the dynamics community to produce two different classes of grids which approximately attain this property. The simplest algorithm is radial discrete variable representation (R-DVR), which diagonalizes the finite auxiliary-basis representation of the radial coordinate for each atom, and then combines Lebedev-Laikov spherical quadratures and Becke atomic partitioning to produce the full molecular quadrature grid. The other algorithm is full discrete variable representation (F-DVR), which uses approximate simultaneous diagonalization of the finite auxiliary-basis representation of the full position operator to produce non-direct-product quadrature grids. The qualitative features of all three grid classes are discussed, and then the relative efficiencies of these grids are compared in the context of LS-THC-DF-MP2. Coarse Becke grids are found to give essentially the same accuracy and efficiency as R-DVR grids; however, the latter are built from explicit knowledge of the basis set and may guide future development of atom-centered grids. F-DVR is found to provide reasonable accuracy with markedly fewer points than either Becke or R-DVR schemes.

Adaptive feedback synchronisation of complex dynamical network with discrete-time communications and delayed nodes

NASA Astrophysics Data System (ADS)

Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong

2016-08-01

This paper considered the synchronisation of continuous complex dynamical networks with discrete-time communications and delayed nodes. The nodes in the dynamical networks act in the continuous manner, while the communications between nodes are discrete-time; that is, they communicate with others only at discrete time instants. The communication intervals in communication period can be uncertain and variable. By using a piecewise Lyapunov-Krasovskii function to govern the characteristics of the discrete communication instants, we investigate the adaptive feedback synchronisation and a criterion is derived to guarantee the existence of the desired controllers. The globally exponential synchronisation can be achieved by the controllers under the updating laws. Finally, two numerical examples including globally coupled network and nearest-neighbour coupled networks are presented to demonstrate the validity and effectiveness of the proposed control scheme.

Body temperature variability (Part 2): masking influences of body temperature variability and a review of body temperature variability in disease.

PubMed

Kelly, Gregory S

2007-03-01

This is the second of a two-part review on body temperature variability. Part 1 discussed historical and modern findings on average body temperatures. It also discussed endogenous sources of temperature variability, including variations caused by site of measurement; circadian, menstrual, and annual biological rhythms; fitness; and aging. Part 2 reviews the effects of exogenous masking agents - external factors in the environment, diet, or lifestyle that can be a significant source of body temperature variability. Body temperature variability findings in disease states are also reviewed.

Single step optimization of manipulator maneuvers with variable structure control

NASA Technical Reports Server (NTRS)

Chen, N.; Dwyer, T. A. W., III

1987-01-01

One step ahead optimization has been recently proposed for spacecraft attitude maneuvers as well as for robot manipulator maneuvers. Such a technique yields a discrete time control algorithm implementable as a sequence of state-dependent, quadratic programming problems for acceleration optimization. Its sensitivity to model accuracy, for the required inversion of the system dynamics, is shown in this paper to be alleviated by a fast variable structure control correction, acting between the sampling intervals of the slow one step ahead discrete time acceleration command generation algorithm. The slow and fast looping concept chosen follows that recently proposed for optimal aiming strategies with variable structure control. Accelerations required by the VSC correction are reserved during the slow one step ahead command generation so that the ability to overshoot the sliding surface is guaranteed.

Natural Scales in Geographical Patterns

NASA Astrophysics Data System (ADS)

Menezes, Telmo; Roth, Camille

2017-04-01

Human mobility is known to be distributed across several orders of magnitude of physical distances, which makes it generally difficult to endogenously find or define typical and meaningful scales. Relevant analyses, from movements to geographical partitions, seem to be relative to some ad-hoc scale, or no scale at all. Relying on geotagged data collected from photo-sharing social media, we apply community detection to movement networks constrained by increasing percentiles of the distance distribution. Using a simple parameter-free discontinuity detection algorithm, we discover clear phase transitions in the community partition space. The detection of these phases constitutes the first objective method of characterising endogenous, natural scales of human movement. Our study covers nine regions, ranging from cities to countries of various sizes and a transnational area. For all regions, the number of natural scales is remarkably low (2 or 3). Further, our results hint at scale-related behaviours rather than scale-related users. The partitions of the natural scales allow us to draw discrete multi-scale geographical boundaries, potentially capable of providing key insights in fields such as epidemiology or cultural contagion where the introduction of spatial boundaries is pivotal.

Precise integration of inducible transcriptional elements (PrIITE) enables absolute control of gene expression.

PubMed

Pinto, Rita; Hansen, Lars; Hintze, John; Almeida, Raquel; Larsen, Sylvester; Coskun, Mehmet; Davidsen, Johanne; Mitchelmore, Cathy; David, Leonor; Troelsen, Jesper Thorvald; Bennett, Eric Paul

2017-07-27

Tetracycline-based inducible systems provide powerful methods for functional studies where gene expression can be controlled. However, the lack of tight control of the inducible system, leading to leakiness and adverse effects caused by undesirable tetracycline dosage requirements, has proven to be a limitation. Here, we report that the combined use of genome editing tools and last generation Tet-On systems can resolve these issues. Our principle is based on precise integration of inducible transcriptional elements (coined PrIITE) targeted to: (i) exons of an endogenous gene of interest (GOI) and (ii) a safe harbor locus. Using PrIITE cells harboring a GFP reporter or CDX2 transcription factor, we demonstrate discrete inducibility of gene expression with complete abrogation of leakiness. CDX2 PrIITE cells generated by this approach uncovered novel CDX2 downstream effector genes. Our results provide a strategy for characterization of dose-dependent effector functions of essential genes that require absence of endogenous gene expression. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Enhanced attention-dependent activity in the auditory cortex of older musicians.

PubMed

Zendel, Benjamin Rich; Alain, Claude

2014-01-01

Musical training improves auditory processing abilities, which correlates with neuro-plastic changes in exogenous (input-driven) and endogenous (attention-dependent) components of auditory event-related potentials (ERPs). Evidence suggests that musicians, compared to non-musicians, experience less age-related decline in auditory processing abilities. Here, we investigated whether lifelong musicianship mitigates exogenous or endogenous processing by measuring auditory ERPs in younger and older musicians and non-musicians while they either attended to auditory stimuli or watched a muted subtitled movie of their choice. Both age and musical training-related differences were observed in the exogenous components; however, the differences between musicians and non-musicians were similar across the lifespan. These results suggest that exogenous auditory ERPs are enhanced in musicians, but decline with age at the same rate. On the other hand, attention-related activity, modeled in the right auditory cortex using a discrete spatiotemporal source analysis, was selectively enhanced in older musicians. This suggests that older musicians use a compensatory strategy to overcome age-related decline in peripheral and exogenous processing of acoustic information. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Guo, Z.; Department of Applied Mathematics and Mechanics, University of Science and Technology Beijing, Beijing 100083; Lin, P.

In this paper, we investigate numerically a diffuse interface model for the Navier–Stokes equation with fluid–fluid interface when the fluids have different densities [48]. Under minor reformulation of the system, we show that there is a continuous energy law underlying the system, assuming that all variables have reasonable regularities. It is shown in the literature that an energy law preserving method will perform better for multiphase problems. Thus for the reformulated system, we design a C{sup 0} finite element method and a special temporal scheme where the energy law is preserved at the discrete level. Such a discrete energy lawmore » (almost the same as the continuous energy law) for this variable density two-phase flow model has never been established before with C{sup 0} finite element. A Newton method is introduced to linearise the highly non-linear system of our discretization scheme. Some numerical experiments are carried out using the adaptive mesh to investigate the scenario of coalescing and rising drops with differing density ratio. The snapshots for the evolution of the interface together with the adaptive mesh at different times are presented to show that the evolution, including the break-up/pinch-off of the drop, can be handled smoothly by our numerical scheme. The discrete energy functional for the system is examined to show that the energy law at the discrete level is preserved by our scheme.« less

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners

PubMed Central

Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

2014-01-01

In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. PMID:24663061

Measurement of discrete vertical in-shoe stress with piezoelectric transducers.

PubMed

Gross, T S; Bunch, R P

1988-05-01

The purpose of this investigation was to design and validate a system suitable for non-invasive measurement of discrete in-shoe vertical plantar stress during dynamic activities. Eight transducers were constructed, with small piezoelectric ceramic squares (4.83 x 4.83 x 1.3 mm) used to generate a charge output proportional to vertical plantar stress. The mechanical properties of the transducers included 2.3% linearity and 3.7% hysteresis for stresses up to 2000 kPa and loading times up to 200 ms. System design efficacy was analysed by means of a multiple day, multiple trial data collection. With the transducers placed beneath plantar landmarks, the footstrike of one subject was recorded ten times on each of five days while running at 3.58 m/s on a treadmill. Within-day and between-day proportional error (PE) was used to estimate the error contained in the mean peak stress during foot contact. Within-day PE focused on trial to trial variability associated with the subject and equipment, and averaged 3.1% (range 2.5-4.0%) across transducer location. Between-day PE provided a cumulative estimate of subject, transducer placement, and random equipment variability, but excluded trial to trial variability. It ranged from 4.9 to 15.8%, with a mean of 9.9%. Peak stress, impulse, and sequence of loading data were examined to identify discrete foot function patterns and highlight the value of discrete stress analysis.

The discrete and localized nature of the variable emission from active regions

NASA Technical Reports Server (NTRS)

Arndt, Martina Belz; Habbal, Shadia Rifai; Karovska, Margarita

1994-01-01

Using data from the Extreme Ultraviolet (EUV) Spectroheliometer on Skylab, we study the empirical characteristics of the variable emission in active regions. These simultaneous multi-wavelength observations clearly confirm that active regions consist of a complex of loops at different temperatures. The variable emission from this complex has very well-defined properties that can be quantitatively summarized as follows: (1) It is localized predominantly around the footpoints where it occurs at discrete locations. (2) The strongest variability does not necessarily coincide with the most intense emission. (3) The fraction of the area of the footpoints, (delta n)/N, that exhibits variable emission, varies by +/- 15% as a function of time, at any of the wavelengths measured. It also varies very little from footpoint to footpoint. (4) This fractional variation is temperature dependent with a maximum around 10(exp 5) K. (5) The ratio of the intensity of the variable to the average background emission, (delta I)/(bar-I), also changes with temperature. In addition, we find that these distinctive characteristics persist even when flares occur within the active region.

Continuous-variable quantum network coding for coherent states

NASA Astrophysics Data System (ADS)

Shang, Tao; Li, Ke; Liu, Jian-wei

2017-04-01

As far as the spectral characteristic of quantum information is concerned, the existing quantum network coding schemes can be looked on as the discrete-variable quantum network coding schemes. Considering the practical advantage of continuous variables, in this paper, we explore two feasible continuous-variable quantum network coding (CVQNC) schemes. Basic operations and CVQNC schemes are both provided. The first scheme is based on Gaussian cloning and ADD/SUB operators and can transmit two coherent states across with a fidelity of 1/2, while the second scheme utilizes continuous-variable quantum teleportation and can transmit two coherent states perfectly. By encoding classical information on quantum states, quantum network coding schemes can be utilized to transmit classical information. Scheme analysis shows that compared with the discrete-variable paradigms, the proposed CVQNC schemes provide better network throughput from the viewpoint of classical information transmission. By modulating the amplitude and phase quadratures of coherent states with classical characters, the first scheme and the second scheme can transmit 4{log _2}N and 2{log _2}N bits of information by a single network use, respectively.

Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research.

PubMed

Wu, Hulin; Xue, Hongqi; Kumar, Arun

2012-06-01

Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches. © 2012, The International Biometric Society.

On the dynamic rounding-off in analogue and RF optimal circuit sizing

NASA Astrophysics Data System (ADS)

Kotti, Mouna; Fakhfakh, Mourad; Fino, Maria Helena

2014-04-01

Frequently used approaches to solve discrete multivariable optimisation problems consist of computing solutions using a continuous optimisation technique. Then, using heuristics, the variables are rounded-off to their nearest available discrete values to obtain a discrete solution. Indeed, in many engineering problems, and particularly in analogue circuit design, component values, such as the geometric dimensions of the transistors, the number of fingers in an integrated capacitor or the number of turns in an integrated inductor, cannot be chosen arbitrarily since they have to obey to some technology sizing constraints. However, rounding-off the variables values a posteriori and can lead to infeasible solutions (solutions that are located too close to the feasible solution frontier) or degradation of the obtained results (expulsion from the neighbourhood of a 'sharp' optimum) depending on how the added perturbation affects the solution. Discrete optimisation techniques, such as the dynamic rounding-off technique (DRO) are, therefore, needed to overcome the previously mentioned situation. In this paper, we deal with an improvement of the DRO technique. We propose a particle swarm optimisation (PSO)-based DRO technique, and we show, via some analog and RF-examples, the necessity to implement such a routine into continuous optimisation algorithms.

Gaussian-modulated coherent-state measurement-device-independent quantum key distribution

NASA Astrophysics Data System (ADS)

Ma, Xiang-Chun; Sun, Shi-Hai; Jiang, Mu-Sheng; Gui, Ming; Liang, Lin-Mei

2014-04-01

Measurement-device-independent quantum key distribution (MDI-QKD), leaving the detection procedure to the third partner and thus being immune to all detector side-channel attacks, is very promising for the construction of high-security quantum information networks. We propose a scheme to implement MDI-QKD, but with continuous variables instead of discrete ones, i.e., with the source of Gaussian-modulated coherent states, based on the principle of continuous-variable entanglement swapping. This protocol not only can be implemented with current telecom components but also has high key rates compared to its discrete counterpart; thus it will be highly compatible with quantum networks.

A boundary value approach for solving three-dimensional elliptic and hyperbolic partial differential equations.

PubMed

Biala, T A; Jator, S N

2015-01-01

In this article, the boundary value method is applied to solve three dimensional elliptic and hyperbolic partial differential equations. The partial derivatives with respect to two of the spatial variables (y, z) are discretized using finite difference approximations to obtain a large system of ordinary differential equations (ODEs) in the third spatial variable (x). Using interpolation and collocation techniques, a continuous scheme is developed and used to obtain discrete methods which are applied via the Block unification approach to obtain approximations to the resulting large system of ODEs. Several test problems are investigated to elucidate the solution process.

Bounds for the price of discrete arithmetic Asian options

NASA Astrophysics Data System (ADS)

Vanmaele, M.; Deelstra, G.; Liinev, J.; Dhaene, J.; Goovaerts, M. J.

2006-01-01

In this paper the pricing of European-style discrete arithmetic Asian options with fixed and floating strike is studied by deriving analytical lower and upper bounds. In our approach we use a general technique for deriving upper (and lower) bounds for stop-loss premiums of sums of dependent random variables, as explained in Kaas et al. (Ins. Math. Econom. 27 (2000) 151-168), and additionally, the ideas of Rogers and Shi (J. Appl. Probab. 32 (1995) 1077-1088) and of Nielsen and Sandmann (J. Financial Quant. Anal. 38(2) (2003) 449-473). We are able to create a unifying framework for European-style discrete arithmetic Asian options through these bounds, that generalizes several approaches in the literature as well as improves the existing results. We obtain analytical and easily computable bounds. The aim of the paper is to formulate an advice of the appropriate choice of the bounds given the parameters, investigate the effect of different conditioning variables and compare their efficiency numerically. Several sets of numerical results are included. We also discuss hedging using these bounds. Moreover, our methods are applicable to a wide range of (pricing) problems involving a sum of dependent random variables.

The discrete adjoint method for parameter identification in multibody system dynamics.

PubMed

Lauß, Thomas; Oberpeilsteiner, Stefan; Steiner, Wolfgang; Nachbagauer, Karin

2018-01-01

The adjoint method is an elegant approach for the computation of the gradient of a cost function to identify a set of parameters. An additional set of differential equations has to be solved to compute the adjoint variables, which are further used for the gradient computation. However, the accuracy of the numerical solution of the adjoint differential equation has a great impact on the gradient. Hence, an alternative approach is the discrete adjoint method , where the adjoint differential equations are replaced by algebraic equations. Therefore, a finite difference scheme is constructed for the adjoint system directly from the numerical time integration method. The method provides the exact gradient of the discretized cost function subjected to the discretized equations of motion.

Detecting Mixtures from Structural Model Differences Using Latent Variable Mixture Modeling: A Comparison of Relative Model Fit Statistics

ERIC Educational Resources Information Center

Henson, James M.; Reise, Steven P.; Kim, Kevin H.

2007-01-01

The accuracy of structural model parameter estimates in latent variable mixture modeling was explored with a 3 (sample size) [times] 3 (exogenous latent mean difference) [times] 3 (endogenous latent mean difference) [times] 3 (correlation between factors) [times] 3 (mixture proportions) factorial design. In addition, the efficacy of several…

Accommodating Binary and Count Variables in Mediation: A Case for Conditional Indirect Effects

ERIC Educational Resources Information Center

Geldhof, G. John; Anthony, Katherine P.; Selig, James P.; Mendez-Luck, Carolyn A.

2018-01-01

The existence of several accessible sources has led to a proliferation of mediation models in the applied research literature. Most of these sources assume endogenous variables (e.g., M, and Y) have normally distributed residuals, precluding models of binary and/or count data. Although a growing body of literature has expanded mediation models to…

Empirical Modeling of Information Communication Technology Usage Behaviour among Business Education Teachers in Tertiary Colleges of a Developing Country

ERIC Educational Resources Information Center

Isiyaku, Dauda Dansarki; Ayub, Ahmad Fauzi Mohd; Abdulkadir, Suhaida

2015-01-01

This study has empirically tested the fitness of a structural model in explaining the influence of two exogenous variables (perceived enjoyment and attitude towards ICTs) on two endogenous variables (behavioural intention and teachers' Information Communication Technology (ICT) usage behavior), based on the proposition of Technology Acceptance…

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Bayesian estimation of the discrete coefficient of determination.

PubMed

Chen, Ting; Braga-Neto, Ulisses M

2016-12-01

The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.

Joint modeling of longitudinal data and discrete-time survival outcome.

PubMed

Qiu, Feiyou; Stein, Catherine M; Elston, Robert C

2016-08-01

A predictive joint shared parameter model is proposed for discrete time-to-event and longitudinal data. A discrete survival model with frailty and a generalized linear mixed model for the longitudinal data are joined to predict the probability of events. This joint model focuses on predicting discrete time-to-event outcome, taking advantage of repeated measurements. We show that the probability of an event in a time window can be more precisely predicted by incorporating the longitudinal measurements. The model was investigated by comparison with a two-step model and a discrete-time survival model. Results from both a study on the occurrence of tuberculosis and simulated data show that the joint model is superior to the other models in discrimination ability, especially as the latent variables related to both survival times and the longitudinal measurements depart from 0. © The Author(s) 2013.

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

USGS Publications Warehouse

Cade, Brian S.; Noon, Barry R.; Scherer, Rick D.; Keane, John J.

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

Ring-Opening Copolymerization of Epoxides and Cyclic Anhydrides with Discrete Metal Complexes: Structure-Property Relationships.

PubMed

Longo, Julie M; Sanford, Maria J; Coates, Geoffrey W

2016-12-28

Polyesters synthesized through the alternating copolymerization of epoxides and cyclic anhydrides compose a growing class of polymers that exhibit an impressive array of chemical and physical properties. Because they are synthesized through the chain-growth polymerization of two variable monomers, their syntheses can be controlled by discrete metal complexes, and the resulting materials vary widely in their functionality and physical properties. This polymer-focused review gives a perspective on the current state of the field of epoxide/anhydride copolymerization mediated by discrete catalysts and the relationships between the structures and properties of these polyesters.

Dynamic characteristics of a two-stage variable-mass flexible missile with internal flow

NASA Technical Reports Server (NTRS)

Meirovitch, L.; Bankovskis, J.

1972-01-01

A general formulation of the dynamical problems associated with powered flight of a two stage flexible, variable-mass missile with internal flow, discrete masses, and aerodynamic forces is presented. The formulation comprises six ordinary differential equations for the rigid body motion, 3n ordinary differential equations for the n discrete masses and three partial differential equations with the appropriate boundary conditions for the elastic motion. This set of equations is modified to represent a single stage flexible, variable-mass missile with internal flow and aerodynamic forces. The rigid-body motion consists then of three translations and three rotations, whereas the elastic motion is defined by one longitudinal and two flexural displacements, the latter about two orthogonal transverse axes. The differential equations are nonlinear and, in addition, they possess time-dependent coefficients due to the mass variation.

Discrete approach to stochastic parametrization and dimension reduction in nonlinear dynamics.

PubMed

Chorin, Alexandre J; Lu, Fei

2015-08-11

Many physical systems are described by nonlinear differential equations that are too complicated to solve in full. A natural way to proceed is to divide the variables into those that are of direct interest and those that are not, formulate solvable approximate equations for the variables of greater interest, and use data and statistical methods to account for the impact of the other variables. In the present paper we consider time-dependent problems and introduce a fully discrete solution method, which simplifies both the analysis of the data and the numerical algorithms. The resulting time series are identified by a NARMAX (nonlinear autoregression moving average with exogenous input) representation familiar from engineering practice. The connections with the Mori-Zwanzig formalism of statistical physics are discussed, as well as an application to the Lorenz 96 system.

Elementary exact calculations of degree growth and entropy for discrete equations.

PubMed

Halburd, R G

2017-05-01

Second-order discrete equations are studied over the field of rational functions [Formula: see text], where z is a variable not appearing in the equation. The exact degree of each iterate as a function of z can be calculated easily using the standard calculations that arise in singularity confinement analysis, even when the singularities are not confined. This produces elementary yet rigorous entropy calculations.

Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

Treesearch

Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

2006-01-01

We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

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

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

Diurnal variations in metal concentrations in the Alamosa River and Wightman Fork, southwestern Colorado, 1995-97

USGS Publications Warehouse

Ortiz, Roderick F.; Stogner, Sr., Robert W.

2001-01-01

A comprehensive sampling network was implemented in the Alamosa River Basin from 1995 to 1997 to address data gaps identified as part of the ecological risk assessment of the Summitville Superfund site. Aluminum, copper, iron, and zinc were identified as the constituents of concern for the risk assessment. Water-quality samples were collected at six sites on the Alamosa River and Wightman Fork by automatic samplers. Several discrete (instantaneous) samples were collected over 24 hours at each site during periods of high diurnal variations in streamflow (May through September). The discrete samples were analyzed individually and duplicate samples were composited to produce a single sample that represented the daily-mean concentration. The diurnal variations in concentration with respect to the theoretical daily-mean concentration (maximum minus minimum divided by daily mean) are presented. Diurnal metal concentrations were highly variable in the Alamosa River and Wightman Fork. The concentration of a metal at a single site could change by several hundred percent during one diurnal cycle. The largest percent change in metal concentrations was observed for aluminum and iron. Zinc concentrations varied the least of the four metals. No discernible or predictable pattern was indicated in the timing of the daily mean, maximum, or minimum concentrations. The percentage of discrete sample concentrations that varied from the daily-mean concentration by thresholds of plus or minus 10, 25, and 50 percent was evaluated. Between 50 and 75 percent of discrete-sample concentrations varied from the daily-mean concentration by more than plus or minus 10 percent. The percentage of samples exceeding given thresholds generally was smaller during the summer period than the snowmelt period. Sampling strategies are critical to accurately define variability in constituent concentration, and conversely, understanding constituent variability is important in determining appropriate sampling strategies. During nonsteady-state periods, considerable errors in estimates of daily-mean concentration are possible if based on one discrete sample. Flow-weighting multiple discrete samples collected over a diurnal cycle provides a better estimate of daily-mean concentrations during nonsteady-state periods.

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

PubMed

Zhang, Jian-Hua; Xia, Jia-Jun; Garibaldi, Jonathan M; Groumpos, Petros P; Wang, Ru-Bin

2017-06-01

In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2008-12-30

Discrete bounded outcome scores (BOS), i.e. discrete measurements that are restricted on a finite interval, often occur in practice. Examples are compliance measures, quality of life measures, etc. In this paper we examine three related random effects approaches to analyze longitudinal studies with a BOS as response: (1) a linear mixed effects (LM) model applied to a logistic transformed modified BOS; (2) a model assuming that the discrete BOS is a coarsened version of a latent random variable, which after a logistic-normal transformation, satisfies an LM model; and (3) a random effects probit model. We consider also the extension whereby the variability of the BOS is allowed to depend on covariates. The methods are contrasted using a simulation study and on a longitudinal project, which documents stroke rehabilitation in four European countries using measures of motor and functional recovery. Copyright 2008 John Wiley & Sons, Ltd.

A Discrete Constraint for Entropy Conservation and Sound Waves in Cloud-Resolving Modeling

NASA Technical Reports Server (NTRS)

Zeng, Xi-Ping; Tao, Wei-Kuo; Simpson, Joanne

2003-01-01

Ideal cloud-resolving models contain little-accumulative errors. When their domain is so large that synoptic large-scale circulations are accommodated, they can be used for the simulation of the interaction between convective clouds and the large-scale circulations. This paper sets up a framework for the models, using moist entropy as a prognostic variable and employing conservative numerical schemes. The models possess no accumulative errors of thermodynamic variables when they comply with a discrete constraint on entropy conservation and sound waves. Alternatively speaking, the discrete constraint is related to the correct representation of the large-scale convergence and advection of moist entropy. Since air density is involved in entropy conservation and sound waves, the challenge is how to compute sound waves efficiently under the constraint. To address the challenge, a compensation method is introduced on the basis of a reference isothermal atmosphere whose governing equations are solved analytically. Stability analysis and numerical experiments show that the method allows the models to integrate efficiently with a large time step.

Bayesian Estimation of Panel Data Fractional Response Models with Endogeneity: An Application to Standardized Test Rates

ERIC Educational Resources Information Center

Kessler, Lawrence M.

2013-01-01

In this paper I propose Bayesian estimation of a nonlinear panel data model with a fractional dependent variable (bounded between 0 and 1). Specifically, I estimate a panel data fractional probit model which takes into account the bounded nature of the fractional response variable. I outline estimation under the assumption of strict exogeneity as…

Sources of Biased Inference in Alcohol and Drug Services Research: An Instrumental Variable Approach

PubMed Central

Schmidt, Laura A.; Tam, Tammy W.; Larson, Mary Jo

2012-01-01

Objective: This study examined the potential for biased inference due to endogeneity when using standard approaches for modeling the utilization of alcohol and drug treatment. Method: Results from standard regression analysis were compared with those that controlled for endogeneity using instrumental variables estimation. Comparable models predicted the likelihood of receiving alcohol treatment based on the widely used Aday and Andersen medical care–seeking model. Data were from the National Epidemiologic Survey on Alcohol and Related Conditions and included a representative sample of adults in households and group quarters throughout the contiguous United States. Results: Findings suggested that standard approaches for modeling treatment utilization are prone to bias because of uncontrolled reverse causation and omitted variables. Compared with instrumental variables estimation, standard regression analyses produced downwardly biased estimates of the impact of alcohol problem severity on the likelihood of receiving care. Conclusions: Standard approaches for modeling service utilization are prone to underestimating the true effects of problem severity on service use. Biased inference could lead to inaccurate policy recommendations, for example, by suggesting that people with milder forms of substance use disorder are more likely to receive care than is actually the case. PMID:22152672

General phase spaces: from discrete variables to rotor and continuum limits

NASA Astrophysics Data System (ADS)

Albert, Victor V.; Pascazio, Saverio; Devoret, Michel H.

2017-12-01

We provide a basic introduction to discrete-variable, rotor, and continuous-variable quantum phase spaces, explaining how the latter two can be understood as limiting cases of the first. We extend the limit-taking procedures used to travel between phase spaces to a general class of Hamiltonians (including many local stabilizer codes) and provide six examples: the Harper equation, the Baxter parafermionic spin chain, the Rabi model, the Kitaev toric code, the Haah cubic code (which we generalize to qudits), and the Kitaev honeycomb model. We obtain continuous-variable generalizations of all models, some of which are novel. The Baxter model is mapped to a chain of coupled oscillators and the Rabi model to the optomechanical radiation pressure Hamiltonian. The procedures also yield rotor versions of all models, five of which are novel many-body extensions of the almost Mathieu equation. The toric and cubic codes are mapped to lattice models of rotors, with the toric code case related to U(1) lattice gauge theory.

Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

Dynamics of nonautonomous discrete rogue wave solutions for an Ablowitz-Musslimani equation with PT-symmetric potential.

PubMed

Yu, Fajun

2017-02-01

Starting from a discrete spectral problem, we derive a hierarchy of nonlinear discrete equations which include the Ablowitz-Ladik (AL) equation. We analytically study the discrete rogue-wave (DRW) solutions of AL equation with three free parameters. The trajectories of peaks and depressions of profiles for the first- and second-order DRWs are produced by means of analytical and numerical methods. In particular, we study the solutions with dispersion in parity-time ( PT) symmetric potential for Ablowitz-Musslimani equation. And we consider the non-autonomous DRW solutions, parameters controlling and their interactions with variable coefficients, and predict the long-living rogue wave solutions. Our results might provide useful information for potential applications of synthetic PT symmetric systems in nonlinear optics and condensed matter physics.

A Noachian/Hesperian Hiatus and Erosive Reactivation of Martian Valley Networks

NASA Technical Reports Server (NTRS)

Irwin, R. P., III.; Maxwell, T. A.; Howard, A. D.; Craddock, R. A.; Moore, J. M.

2005-01-01

Despite new evidence for persistent flow and sedimentation on early Mars, it remains unclear whether valley networks were active over long geologic timescales (10(exp 5)-10(exp 8) yr), or if flows were persistent only during multiple discrete episodes of moderate (approx. 10(exp 4) yr) to short (<10 yr) duration. Understanding the long-term stability/variability of valley network hydrology would provide an important control on paleoclimate and groundwater models. Here we describe geologic evidence for a hiatus in highland valley network activity while the fretted terrain formed, followed by a discrete reactivation of persistent (but possibly variable) erosive flows. Additional information is included in the original extended abstract.

Violation of continuous-variable Einstein-Podolsky-Rosen steering with discrete measurements.

PubMed

Schneeloch, James; Dixon, P Ben; Howland, Gregory A; Broadbent, Curtis J; Howell, John C

2013-03-29

In this Letter, we derive an entropic Einstein-Podolsky-Rosen (EPR) steering inequality for continuous-variable systems using only experimentally measured discrete probability distributions and details of the measurement apparatus. We use this inequality to witness EPR steering between the positions and momenta of photon pairs generated in spontaneous parametric down-conversion. We examine the asymmetry between parties in this inequality, and show that this asymmetry can be used to reduce the technical requirements of experimental setups intended to demonstrate the EPR paradox. Furthermore, we develop a more stringent steering inequality that is symmetric between parties, and use it to show that the down-converted photon pairs also exhibit symmetric EPR steering.

Violation of Continuous-Variable Einstein-Podolsky-Rosen Steering with Discrete Measurements

NASA Astrophysics Data System (ADS)

Schneeloch, James; Dixon, P. Ben; Howland, Gregory A.; Broadbent, Curtis J.; Howell, John C.

2013-03-01

In this Letter, we derive an entropic Einstein-Podolsky-Rosen (EPR) steering inequality for continuous-variable systems using only experimentally measured discrete probability distributions and details of the measurement apparatus. We use this inequality to witness EPR steering between the positions and momenta of photon pairs generated in spontaneous parametric down-conversion. We examine the asymmetry between parties in this inequality, and show that this asymmetry can be used to reduce the technical requirements of experimental setups intended to demonstrate the EPR paradox. Furthermore, we develop a more stringent steering inequality that is symmetric between parties, and use it to show that the down-converted photon pairs also exhibit symmetric EPR steering.

Fast and Accurate Learning When Making Discrete Numerical Estimates.

PubMed

Sanborn, Adam N; Beierholm, Ulrik R

2016-04-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

Fast and Accurate Learning When Making Discrete Numerical Estimates

PubMed Central

Sanborn, Adam N.; Beierholm, Ulrik R.

2016-01-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

On discrete control of nonlinear systems with applications to robotics

NASA Technical Reports Server (NTRS)

Eslami, Mansour

1989-01-01

Much progress has been reported in the areas of modeling and control of nonlinear dynamic systems in a continuous-time framework. From implementation point of view, however, it is essential to study these nonlinear systems directly in a discrete setting that is amenable for interfacing with digital computers. But to develop discrete models and discrete controllers for a nonlinear system such as robot is a nontrivial task. Robot is also inherently a variable-inertia dynamic system involving additional complications. Not only the computer-oriented models of these systems must satisfy the usual requirements for such models, but these must also be compatible with the inherent capabilities of computers and must preserve the fundamental physical characteristics of continuous-time systems such as the conservation of energy and/or momentum. Preliminary issues regarding discrete systems in general and discrete models of a typical industrial robot that is developed with full consideration of the principle of conservation of energy are presented. Some research on the pertinent tactile information processing is reviewed. Finally, system control methods and how to integrate these issues in order to complete the task of discrete control of a robot manipulator are also reviewed.

Distributed Relaxation for Conservative Discretizations

NASA Technical Reports Server (NTRS)

Diskin, Boris; Thomas, James L.

2001-01-01

A multigrid method is defined as having textbook multigrid efficiency (TME) if the solutions to the governing system of equations are attained in a computational work that is a small (less than 10) multiple of the operation count in one target-grid residual evaluation. The way to achieve this efficiency is the distributed relaxation approach. TME solvers employing distributed relaxation have already been demonstrated for nonconservative formulations of high-Reynolds-number viscous incompressible and subsonic compressible flow regimes. The purpose of this paper is to provide foundations for applications of distributed relaxation to conservative discretizations. A direct correspondence between the primitive variable interpolations for calculating fluxes in conservative finite-volume discretizations and stencils of the discretized derivatives in the nonconservative formulation has been established. Based on this correspondence, one can arrive at a conservative discretization which is very efficiently solved with a nonconservative relaxation scheme and this is demonstrated for conservative discretization of the quasi one-dimensional Euler equations. Formulations for both staggered and collocated grid arrangements are considered and extensions of the general procedure to multiple dimensions are discussed.

Spectral collocation method with a flexible angular discretization scheme for radiative transfer in multi-layer graded index medium

NASA Astrophysics Data System (ADS)

Wei, Linyang; Qi, Hong; Sun, Jianping; Ren, Yatao; Ruan, Liming

2017-05-01

The spectral collocation method (SCM) is employed to solve the radiative transfer in multi-layer semitransparent medium with graded index. A new flexible angular discretization scheme is employed to discretize the solid angle domain freely to overcome the limit of the number of discrete radiative direction when adopting traditional SN discrete ordinate scheme. Three radial basis function interpolation approaches, named as multi-quadric (MQ), inverse multi-quadric (IMQ) and inverse quadratic (IQ) interpolation, are employed to couple the radiative intensity at the interface between two adjacent layers and numerical experiments show that MQ interpolation has the highest accuracy and best stability. Variable radiative transfer problems in double-layer semitransparent media with different thermophysical properties are investigated and the influence of these thermophysical properties on the radiative transfer procedure in double-layer semitransparent media is also analyzed. All the simulated results show that the present SCM with the new angular discretization scheme can predict the radiative transfer in multi-layer semitransparent medium with graded index efficiently and accurately.

The Livingstone Model of a Main Propulsion System

NASA Technical Reports Server (NTRS)

Bajwa, Anupa; Sweet, Adam; Korsmeyer, David (Technical Monitor)

2003-01-01

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

NASA Astrophysics Data System (ADS)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

Transparent lattices and their solitary waves.

PubMed

Sadurní, E

2014-09-01

We provide a family of transparent tight-binding models with nontrivial potentials and site-dependent hopping parameters. Their feasibility is discussed in electromagnetic resonators, dielectric slabs, and quantum-mechanical traps. In the second part of the paper, the arrays are obtained through a generalization of supersymmetric quantum mechanics in discrete variables. The formalism includes a finite-difference Darboux transformation applied to the scattering matrix of a periodic array. A procedure for constructing a hierarchy of discrete Hamiltonians is indicated and a particular biparametric family is given. The corresponding potentials and hopping functions are identified as solitary waves, pointing to a discrete spinorial generalization of the Korteweg-deVries family.

Quantum information processing in phase space: A modular variables approach

NASA Astrophysics Data System (ADS)

Ketterer, A.; Keller, A.; Walborn, S. P.; Coudreau, T.; Milman, P.

2016-08-01

Binary quantum information can be fault-tolerantly encoded in states defined in infinite-dimensional Hilbert spaces. Such states define a computational basis, and permit a perfect equivalence between continuous and discrete universal operations. The drawback of this encoding is that the corresponding logical states are unphysical, meaning infinitely localized in phase space. We use the modular variables formalism to show that, in a number of protocols relevant for quantum information and for the realization of fundamental tests of quantum mechanics, it is possible to loosen the requirements on the logical subspace without jeopardizing their usefulness or their successful implementation. Such protocols involve measurements of appropriately chosen modular variables that permit the readout of the encoded discrete quantum information from the corresponding logical states. Finally, we demonstrate the experimental feasibility of our approach by applying it to the transverse degrees of freedom of single photons.

Probabilistic finite elements for transient analysis in nonlinear continua

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Mani, A.

1985-01-01

The probabilistic finite element method (PFEM), which is a combination of finite element methods and second-moment analysis, is formulated for linear and nonlinear continua with inhomogeneous random fields. Analogous to the discretization of the displacement field in finite element methods, the random field is also discretized. The formulation is simplified by transforming the correlated variables to a set of uncorrelated variables through an eigenvalue orthogonalization. Furthermore, it is shown that a reduced set of the uncorrelated variables is sufficient for the second-moment analysis. Based on the linear formulation of the PFEM, the method is then extended to transient analysis in nonlinear continua. The accuracy and efficiency of the method is demonstrated by application to a one-dimensional, elastic/plastic wave propagation problem. The moments calculated compare favorably with those obtained by Monte Carlo simulation. Also, the procedure is amenable to implementation in deterministic FEM based computer programs.

The arbitrary order mixed mimetic finite difference method for the diffusion equation

DOE PAGES

Gyrya, Vitaliy; Lipnikov, Konstantin; Manzini, Gianmarco

2016-05-01

Here, we propose an arbitrary-order accurate mimetic finite difference (MFD) method for the approximation of diffusion problems in mixed form on unstructured polygonal and polyhedral meshes. As usual in the mimetic numerical technology, the method satisfies local consistency and stability conditions, which determines the accuracy and the well-posedness of the resulting approximation. The method also requires the definition of a high-order discrete divergence operator that is the discrete analog of the divergence operator and is acting on the degrees of freedom. The new family of mimetic methods is proved theoretically to be convergent and optimal error estimates for flux andmore » scalar variable are derived from the convergence analysis. A numerical experiment confirms the high-order accuracy of the method in solving diffusion problems with variable diffusion tensor. It is worth mentioning that the approximation of the scalar variable presents a superconvergence effect.« less

Continuous-Variable Instantaneous Quantum Computing is Hard to Sample.

PubMed

Douce, T; Markham, D; Kashefi, E; Diamanti, E; Coudreau, T; Milman, P; van Loock, P; Ferrini, G

2017-02-17

Instantaneous quantum computing is a subuniversal quantum complexity class, whose circuits have proven to be hard to simulate classically in the discrete-variable realm. We extend this proof to the continuous-variable (CV) domain by using squeezed states and homodyne detection, and by exploring the properties of postselected circuits. In order to treat postselection in CVs, we consider finitely resolved homodyne detectors, corresponding to a realistic scheme based on discrete probability distributions of the measurement outcomes. The unavoidable errors stemming from the use of finitely squeezed states are suppressed through a qubit-into-oscillator Gottesman-Kitaev-Preskill encoding of quantum information, which was previously shown to enable fault-tolerant CV quantum computation. Finally, we show that, in order to render postselected computational classes in CVs meaningful, a logarithmic scaling of the squeezing parameter with the circuit size is necessary, translating into a polynomial scaling of the input energy.

Impact of random discrete dopant in extension induced fluctuation in gate-source/drain underlap FinFET

NASA Astrophysics Data System (ADS)

Wang, Yijiao; Huang, Peng; Xin, Zheng; Zeng, Lang; Liu, Xiaoyan; Du, Gang; Kang, Jinfeng

2014-01-01

In this work, three dimensional technology computer-aided design (TCAD) simulations are performed to investigate the impact of random discrete dopant (RDD) including extension induced fluctuation in 14 nm silicon-on-insulator (SOI) gate-source/drain (G-S/D) underlap fin field effect transistor (FinFET). To fully understand the RDD impact in extension, RDD effect is evaluated in channel and extension separately and together. The statistical variability of FinFET performance parameters including threshold voltage (Vth), subthreshold slope (SS), drain induced barrier lowering (DIBL), drive current (Ion), and leakage current (Ioff) are analyzed. The results indicate that RDD in extension can lead to substantial variability, especially for SS, DIBL, and Ion and should be taken into account together with that in channel to get an accurate estimation on RDF. Meanwhile, higher doping concentration of extension region is suggested from the perspective of overall variability control.

Remote creation of hybrid entanglement between particle-like and wave-like optical qubits

NASA Astrophysics Data System (ADS)

Morin, Olivier; Huang, Kun; Liu, Jianli; Le Jeannic, Hanna; Fabre, Claude; Laurat, Julien

2014-07-01

The wave-particle duality of light has led to two different encodings for optical quantum information processing. Several approaches have emerged based either on particle-like discrete-variable states (that is, finite-dimensional quantum systems) or on wave-like continuous-variable states (that is, infinite-dimensional systems). Here, we demonstrate the generation of entanglement between optical qubits of these different types, located at distant places and connected by a lossy channel. Such hybrid entanglement, which is a key resource for a variety of recently proposed schemes, including quantum cryptography and computing, enables information to be converted from one Hilbert space to the other via teleportation and therefore the connection of remote quantum processors based upon different encodings. Beyond its fundamental significance for the exploration of entanglement and its possible instantiations, our optical circuit holds promise for implementations of heterogeneous network, where discrete- and continuous-variable operations and techniques can be efficiently combined.

Self-dual form of Ruijsenaars-Schneider models and ILW equation with discrete Laplacian

NASA Astrophysics Data System (ADS)

Zabrodin, A.; Zotov, A.

2018-02-01

We discuss a self-dual form or the Bäcklund transformations for the continuous (in time variable) glN Ruijsenaars-Schneider model. It is based on the first order equations in N + M complex variables which include N positions of particles and M dual variables. The latter satisfy equations of motion of the glM Ruijsenaars-Schneider model. In the elliptic case it holds M = N while for the rational and trigonometric models M is not necessarily equal to N. Our consideration is similar to the previously obtained results for the Calogero-Moser models which are recovered in the non-relativistic limit. We also show that the self-dual description of the Ruijsenaars-Schneider models can be derived from complexified intermediate long wave equation with discrete Laplacian by means of the simple pole ansatz likewise the Calogero-Moser models arise from ordinary intermediate long wave and Benjamin-Ono equations.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Does job insecurity deteriorate health?

PubMed

Caroli, Eve; Godard, Mathilde

2016-02-01

This paper estimates the causal effect of perceived job insecurity - that is, the fear of involuntary job loss - on health in a sample of men from 22 European countries. We rely on an original instrumental variable approach on the basis of the idea that workers perceive greater job security in countries where employment is strongly protected by the law and more so if employed in industries where employment protection legislation is more binding; that is, in induastries with a higher natural rate of dismissals. Using cross-country data from the 2010 European Working Conditions Survey, we show that, when the potential endogeneity of job insecurity is not accounted for, the latter appears to deteriorate almost all health outcomes. When tackling the endogeneity issue by estimating an instrumental variable model and dealing with potential weak-instrument issues, the health-damaging effect of job insecurity is confirmed for a limited subgroup of health outcomes; namely, suffering from headaches or eyestrain and skin problems. As for other health variables, the impact of job insecurity appears to be insignificant at conventional levels. Copyright © 2014 John Wiley & Sons, Ltd.

KOALA RETROVIRUS: A REVIEW.

PubMed

Kinney, Matthew E; Pye, Geoffrey W

2016-06-01

Koala retrovirus (KoRV) is a gammaretrovirus that has been identified in both captive and free-ranging koalas ( Phascolarctos cinereus ) with variable geographic distribution in Australia. KoRV is capable of both exogenous and endogenous transmission, which provides an interesting research platform for scientists to study active retrovirus endogenization into a host genome and offers veterinary scientists an opportunity to examine the clinical consequences of KoRV infection in koalas. Causation between KoRV and frequently recognized clinical conditions associated with immune suppression and neoplasia in koalas has not been definitively established, however research continues to evaluate a potential association. Three KoRV variants, KoRV-A, KoRV-B, and KoRV-J, have been the most thoroughly described and preliminary evidence suggests KoRV variability may be fundamental in host pathogenicity. In addition to reviewing what is currently known about KoRV, this article discusses treatment, management, and future research directions.

A Structural Examination of Academic Integration, Perceived Stress, Academic Performance, and Goal Commitment from an Elaborated Model of Adult Student Persistence.

ERIC Educational Resources Information Center

Sandler, Martin E.

The effects of selected variables on the academic persistence of adult students were examined in a study of a random sample of 469 adult students aged 24 years or older enrolled in a four-year college. The survey questionnaire, the Adult Student Experiences Survey, collected data regarding 12 endogenous variables and 13 exogenous variables…

GY SAMPLING THEORY AND GEOSTATISTICS: ALTERNATE MODELS OF VARIABILITY IN CONTINUOUS MEDIA

EPA Science Inventory

In the sampling theory developed by Pierre Gy, sample variability is modeled as the sum of a set of seven discrete error components. The variogram used in geostatisties provides an alternate model in which several of Gy's error components are combined in a continuous mode...

A Unifying Probability Example.

ERIC Educational Resources Information Center

Maruszewski, Richard F., Jr.

2002-01-01

Presents an example from probability and statistics that ties together several topics including the mean and variance of a discrete random variable, the binomial distribution and its particular mean and variance, the sum of independent random variables, the mean and variance of the sum, and the central limit theorem. Uses Excel to illustrate these…

Discrete Emotion Effects on Lexical Decision Response Times

PubMed Central

Briesemeister, Benny B.; Kuchinke, Lars; Jacobs, Arthur M.

2011-01-01

Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account. PMID:21887307

Discrete emotion effects on lexical decision response times.

PubMed

Briesemeister, Benny B; Kuchinke, Lars; Jacobs, Arthur M

2011-01-01

Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2006-01-01

Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.

The Use of Linear Instrumental Variables Methods in Health Services Research and Health Economics: A Cautionary Note

PubMed Central

Terza, Joseph V; Bradford, W David; Dismuke, Clara E

2008-01-01

Objective To investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings. Data Sources Smoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data. Study Design Potential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor. Principle Findings The simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods. Conclusions We offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity. PMID:18546544

Improved result on stability analysis of discrete stochastic neural networks with time delay

NASA Astrophysics Data System (ADS)

Wu, Zhengguang; Su, Hongye; Chu, Jian; Zhou, Wuneng

2009-04-01

This Letter investigates the problem of exponential stability for discrete stochastic time-delay neural networks. By defining a novel Lyapunov functional, an improved delay-dependent exponential stability criterion is established in terms of linear matrix inequality (LMI) approach. Meanwhile, the computational complexity of the newly established stability condition is reduced because less variables are involved. Numerical example is given to illustrate the effectiveness and the benefits of the proposed method.

New Discrete Fibonacci Charge Pump Design, Evaluation and Measurement

NASA Astrophysics Data System (ADS)

Matoušek, David; Hospodka, Jiří; Šubrt, Ondřej

2017-06-01

This paper focuses on the practical aspects of the realisation of Dickson and Fibonacci charge pumps. Standard Dickson charge pump circuit solution and new Fibonacci charge pump implementation are compared. Both charge pumps were designed and then evaluated by LTspice XVII simulations and realised in a discrete form on printed circuit board (PCB). Finally, the key parameters as the output voltage, efficiency, rise time, variable power supply and clock frequency effects were measured.

Short-term variability in QT interval and ventricular arrhythmias induced by dofetilide are dependent on high-frequency autonomic oscillations

PubMed Central

Champeroux, P; Thireau, J; Judé, S; Laigot-Barbé, C; Maurin, A; Sola, M L; Fowler, J S L; Richard, S; Le Guennec, J Y

2015-01-01

Background and Purpose The present study was undertaken to investigate an effect of dofetilide, a potent arrhythmic blocker of the voltage-gated K+ channel, hERG, on cardiac autonomic control. Combined with effects on ardiomyocytes, these properties could influence its arrhythmic potency. Experimental Approach The short-term variability of beat-to-beat QT interval (STVQT), induced by dofetilide is a strong surrogate of Torsades de pointes liability. Involvement of autonomic modulation in STVQT was investigated in healthy cynomolgus monkeys and beagle dogs by power spectral analysis under conditions of autonomic blockade with hexamethonium. Key Results Increase in STVQT induced by dofetilide in monkeys and dogs was closely associated with an enhancement of endogenous heart rate and QT interval high-frequency (HF) oscillations. These effects were fully suppressed under conditions of autonomic blockade with hexamethonium. Ventricular arrhythmias, including Torsades de pointes in monkeys, were prevented in both species when HF oscillations were suppressed by autonomic blockade. Similar enhancements of heart rate HF oscillations were found in dogs with other hERG blockers described as causing Torsades de pointes in humans. Conclusions and Implications These results demonstrate for the first time that beat-to-beat ventricular repolarization variability and ventricular arrhythmias induced by dofetilide are dependent on endogenous HF autonomic oscillations in heart rate. When combined with evidence of hERG-blocking properties, enhancement of endogenous HF oscillations in heart rate could constitute an earlier and more sensitive biomarker than STVQT for Torsades de pointes liability, applicable to preclinical regulatory studies conducted in healthy animals. PMID:25625756

Development of a real-time PCR method for the differential detection and quantification of four solanaceae in GMO analysis: potato (Solanum tuberosum), tomato (Solanum lycopersicum), eggplant (Solanum melongena), and pepper (Capsicum annuum).

PubMed

Chaouachi, Maher; El Malki, Redouane; Berard, Aurélie; Romaniuk, Marcel; Laval, Valérie; Brunel, Dominique; Bertheau, Yves

2008-03-26

The labeling of products containing genetically modified organisms (GMO) is linked to their quantification since a threshold for the presence of fortuitous GMOs in food has been established. This threshold is calculated from a combination of two absolute quantification values: one for the specific GMO target and the second for an endogenous reference gene specific to the taxon. Thus, the development of reliable methods to quantify GMOs using endogenous reference genes in complex matrixes such as food and feed is needed. Plant identification can be difficult in the case of closely related taxa, which moreover are subject to introgression events. Based on the homology of beta-fructosidase sequences obtained from public databases, two couples of consensus primers were designed for the detection, quantification, and differentiation of four Solanaceae: potato (Solanum tuberosum), tomato (Solanum lycopersicum), pepper (Capsicum annuum), and eggplant (Solanum melongena). Sequence variability was studied first using lines and cultivars (intraspecies sequence variability), then using taxa involved in gene introgressions, and finally, using taxonomically close taxa (interspecies sequence variability). This study allowed us to design four highly specific TaqMan-MGB probes. A duplex real time PCR assay was developed for simultaneous quantification of tomato and potato. For eggplant and pepper, only simplex real time PCR tests were developed. The results demonstrated the high specificity and sensitivity of the assays. We therefore conclude that beta-fructosidase can be used as an endogenous reference gene for GMO analysis.

Short-term variability in QT interval and ventricular arrhythmias induced by dofetilide are dependent on high-frequency autonomic oscillations.

PubMed

Champeroux, P; Thireau, J; Judé, S; Laigot-Barbé, C; Maurin, A; Sola, M L; Fowler, J S L; Richard, S; Le Guennec, J Y

2015-06-01

The present study was undertaken to investigate an effect of dofetilide, a potent arrhythmic blocker of the voltage-gated K(+) channel, hERG, on cardiac autonomic control. Combined with effects on ardiomyocytes, these properties could influence its arrhythmic potency. The short-term variability of beat-to-beat QT interval (STVQT ), induced by dofetilide is a strong surrogate of Torsades de pointes liability. Involvement of autonomic modulation in STVQT was investigated in healthy cynomolgus monkeys and beagle dogs by power spectral analysis under conditions of autonomic blockade with hexamethonium. Increase in STVQT induced by dofetilide in monkeys and dogs was closely associated with an enhancement of endogenous heart rate and QT interval high-frequency (HF) oscillations. These effects were fully suppressed under conditions of autonomic blockade with hexamethonium. Ventricular arrhythmias, including Torsades de pointes in monkeys, were prevented in both species when HF oscillations were suppressed by autonomic blockade. Similar enhancements of heart rate HF oscillations were found in dogs with other hERG blockers described as causing Torsades de pointes in humans. These results demonstrate for the first time that beat-to-beat ventricular repolarization variability and ventricular arrhythmias induced by dofetilide are dependent on endogenous HF autonomic oscillations in heart rate. When combined with evidence of hERG-blocking properties, enhancement of endogenous HF oscillations in heart rate could constitute an earlier and more sensitive biomarker than STVQT for Torsades de pointes liability, applicable to preclinical regulatory studies conducted in healthy animals. © 2015 The British Pharmacological Society.

Quantum cryptography with finite resources: unconditional security bound for discrete-variable protocols with one-way postprocessing.

PubMed

Scarani, Valerio; Renner, Renato

2008-05-23

We derive a bound for the security of quantum key distribution with finite resources under one-way postprocessing, based on a definition of security that is composable and has an operational meaning. While our proof relies on the assumption of collective attacks, unconditional security follows immediately for standard protocols such as Bennett-Brassard 1984 and six-states protocol. For single-qubit implementations of such protocols, we find that the secret key rate becomes positive when at least N approximately 10(5) signals are exchanged and processed. For any other discrete-variable protocol, unconditional security can be obtained using the exponential de Finetti theorem, but the additional overhead leads to very pessimistic estimates.

Topology and layout optimization of discrete and continuum structures

NASA Technical Reports Server (NTRS)

Bendsoe, Martin P.; Kikuchi, Noboru

1993-01-01

The basic features of the ground structure method for truss structure an continuum problems are described. Problems with a large number of potential structural elements are considered using the compliance of the structure as the objective function. The design problem is the minimization of compliance for a given structural weight, and the design variables for truss problems are the cross-sectional areas of the individual truss members, while for continuum problems they are the variable densities of material in each of the elements of the FEM discretization. It is shown how homogenization theory can be applied to provide a relation between material density and the effective material properties of a periodic medium with a known microstructure of material and voids.

On the convergence of a fully discrete scheme of LES type to physically relevant solutions of the incompressible Navier-Stokes

NASA Astrophysics Data System (ADS)

Berselli, Luigi C.; Spirito, Stefano

2018-06-01

Obtaining reliable numerical simulations of turbulent fluids is a challenging problem in computational fluid mechanics. The large eddy simulation (LES) models are efficient tools to approximate turbulent fluids, and an important step in the validation of these models is the ability to reproduce relevant properties of the flow. In this paper, we consider a fully discrete approximation of the Navier-Stokes-Voigt model by an implicit Euler algorithm (with respect to the time variable) and a Fourier-Galerkin method (in the space variables). We prove the convergence to weak solutions of the incompressible Navier-Stokes equations satisfying the natural local entropy condition, hence selecting the so-called physically relevant solutions.

Experimental study on discretely modulated continuous-variable quantum key distribution

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

Shen Yong; Zou Hongxin; Chen Pingxing

2010-08-15

We present a discretely modulated continuous-variable quantum key distribution system in free space by using strong coherent states. The amplitude noise in the laser source is suppressed to the shot-noise limit by using a mode cleaner combined with a frequency shift technique. Also, it is proven that the phase noise in the source has no impact on the final secret key rate. In order to increase the encoding rate, we use broadband homodyne detectors and the no-switching protocol. In a realistic model, we establish a secret key rate of 46.8 kbits/s against collective attacks at an encoding rate of 10more » MHz for a 90% channel loss when the modulation variance is optimal.« less

DiscML: an R package for estimating evolutionary rates of discrete characters using maximum likelihood.

PubMed

Kim, Tane; Hao, Weilong

2014-09-27

The study of discrete characters is crucial for the understanding of evolutionary processes. Even though great advances have been made in the analysis of nucleotide sequences, computer programs for non-DNA discrete characters are often dedicated to specific analyses and lack flexibility. Discrete characters often have different transition rate matrices, variable rates among sites and sometimes contain unobservable states. To obtain the ability to accurately estimate a variety of discrete characters, programs with sophisticated methodologies and flexible settings are desired. DiscML performs maximum likelihood estimation for evolutionary rates of discrete characters on a provided phylogeny with the options that correct for unobservable data, rate variations, and unknown prior root probabilities from the empirical data. It gives users options to customize the instantaneous transition rate matrices, or to choose pre-determined matrices from models such as birth-and-death (BD), birth-death-and-innovation (BDI), equal rates (ER), symmetric (SYM), general time-reversible (GTR) and all rates different (ARD). Moreover, we show application examples of DiscML on gene family data and on intron presence/absence data. DiscML was developed as a unified R program for estimating evolutionary rates of discrete characters with no restriction on the number of character states, and with flexibility to use different transition models. DiscML is ideal for the analyses of binary (1s/0s) patterns, multi-gene families, and multistate discrete morphological characteristics.

Is processing of symbols and words influenced by writing system? Evidence from Chinese, Korean, English, and Greek.

PubMed

Altani, Angeliki; Georgiou, George K; Deng, Ciping; Cho, Jeung-Ryeul; Katopodi, Katerina; Wei, Wei; Protopapas, Athanassios

2017-12-01

We examined cross-linguistic effects in the relationship between serial and discrete versions of digit naming and word reading. In total, 113 Mandarin-speaking Chinese children, 100 Korean children, 112 English-speaking Canadian children, and 108 Greek children in Grade 3 were administered tasks of serial and discrete naming of words and digits. Interrelations among tasks indicated that the link between rapid naming and reading is largely determined by the format of the tasks across orthographies. Multigroup path analyses with discrete and serial word reading as dependent variables revealed commonalities as well as significant differences between writing systems. The path coefficient from discrete digits to discrete words was greater for the more transparent orthographies, consistent with more efficient sight-word processing. The effect of discrete word reading on serial word reading was stronger in alphabetic languages, where there was also a suppressive effect of discrete digit naming. However, the effect of serial digit naming on serial word reading did not differ among the four language groups. This pattern of relationships challenges a universal account of reading fluency acquisition while upholding a universal role of rapid serial naming, further distinguishing between multi-element interword and intraword processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Diagnosis of delay-deadline failures in real time discrete event models.

PubMed

Biswas, Santosh; Sarkar, Dipankar; Bhowal, Prodip; Mukhopadhyay, Siddhartha

2007-10-01

In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

Synchronous Parallel Emulation and Discrete Event Simulation System with Self-Contained Simulation Objects and Active Event Objects

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1998-01-01

The present invention is embodied in a method of performing object-oriented simulation and a system having inter-connected processor nodes operating in parallel to simulate mutual interactions of a set of discrete simulation objects distributed among the nodes as a sequence of discrete events changing state variables of respective simulation objects so as to generate new event-defining messages addressed to respective ones of the nodes. The object-oriented simulation is performed at each one of the nodes by assigning passive self-contained simulation objects to each one of the nodes, responding to messages received at one node by generating corresponding active event objects having user-defined inherent capabilities and individual time stamps and corresponding to respective events affecting one of the passive self-contained simulation objects of the one node, restricting the respective passive self-contained simulation objects to only providing and receiving information from die respective active event objects, requesting information and changing variables within a passive self-contained simulation object by the active event object, and producing corresponding messages specifying events resulting therefrom by the active event objects.

The Role of Emotion in Global Warming Policy Support and Opposition

PubMed Central

Smith, Nicholas; Leiserowitz, Anthony

2014-01-01

Prior research has found that affect and affective imagery strongly influence public support for global warming. This article extends this literature by exploring the separate influence of discrete emotions. Utilizing a nationally representative survey in the United States, this study found that discrete emotions were stronger predictors of global warming policy support than cultural worldviews, negative affect, image associations, or sociodemographic variables. In particular, worry, interest, and hope were strongly associated with increased policy support. The results contribute to experiential theories of risk information processing and suggest that discrete emotions play a significant role in public support for climate change policy. Implications for climate change communication are also discussed. PMID:24219420

The role of emotion in global warming policy support and opposition.

PubMed

Smith, Nicholas; Leiserowitz, Anthony

2014-05-01

Prior research has found that affect and affective imagery strongly influence public support for global warming. This article extends this literature by exploring the separate influence of discrete emotions. Utilizing a nationally representative survey in the United States, this study found that discrete emotions were stronger predictors of global warming policy support than cultural worldviews, negative affect, image associations, or sociodemographic variables. In particular, worry, interest, and hope were strongly associated with increased policy support. The results contribute to experiential theories of risk information processing and suggest that discrete emotions play a significant role in public support for climate change policy. Implications for climate change communication are also discussed. © 2013 Society for Risk Analysis.

[The theory of the demographic transition as a reference for demo-economic models].

PubMed

Genne, M

1981-01-01

The aim of the theory of demographic transition (TTD) is to better understand the behavior and interrelationship of economic and demographic variables. There are 2 types of demo-economic models: 1) the malthusian models, which consider demographic variables as pure exogenous variables, and 2) the neoclassical models, which consider demographic variables as strictly endogenous. If TTD can explore the behavior of exogenous and endogenous demographic variables, it cannot demonstrate neither the relation nor the order of causality among the various demographic and economic variables, but it is simply the theoretical framework of a complex social and economic phenomenon which started in Europe in the 19th Century, and which today can be extended to developing countries. There are 4 stages in the TTD; the 1st stage is characterized by high levels of fecundity and mortality; the 2nd stage is characterized by high fecundity levels and declining mortality levels; the 3rd stage is characterized by declining fecundity levels and low mortality levels; the 4th stage is characterized by low fertility and mortality levels. The impact of economic variables over mortality and birth rates is evident for mortality rates, which decline earlier and at a greater speed than birth rates. According to reliable mathematical predictions, around the year 1987 mortality rates in developing countries will have reached the low level of European countries, and growth rate will be only 1.5%. If the validity of demo-economic models has not yet been established, TTD has clearly shown that social and economic development is the factor which influences demographic expansion.

Bayesian Analysis of Structural Equation Models with Nonlinear Covariates and Latent Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2006-01-01

In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…

Evaluation of Scale Reliability with Binary Measures Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Dimitrov, Dimiter M.; Asparouhov, Tihomir

2010-01-01

A method for interval estimation of scale reliability with discrete data is outlined. The approach is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology. The procedure is useful for evaluation of consistency of single measures and of sum scores from item sets…

Path integrals and large deviations in stochastic hybrid systems.

PubMed

Bressloff, Paul C; Newby, Jay M

2014-04-01

We construct a path-integral representation of solutions to a stochastic hybrid system, consisting of one or more continuous variables evolving according to a piecewise-deterministic dynamics. The differential equations for the continuous variables are coupled to a set of discrete variables that satisfy a continuous-time Markov process, which means that the differential equations are only valid between jumps in the discrete variables. Examples of stochastic hybrid systems arise in biophysical models of stochastic ion channels, motor-driven intracellular transport, gene networks, and stochastic neural networks. We use the path-integral representation to derive a large deviation action principle for a stochastic hybrid system. Minimizing the associated action functional with respect to the set of all trajectories emanating from a metastable state (assuming that such a minimization scheme exists) then determines the most probable paths of escape. Moreover, evaluating the action functional along a most probable path generates the so-called quasipotential used in the calculation of mean first passage times. We illustrate the theory by considering the optimal paths of escape from a metastable state in a bistable neural network.

A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes

NASA Astrophysics Data System (ADS)

Le-Duc, Thang; Ho-Huu, Vinh; Nguyen-Thoi, Trung; Nguyen-Quoc, Hung

2016-12-01

In recent years, various types of magnetorheological brakes (MRBs) have been proposed and optimized by different optimization algorithms that are integrated in commercial software such as ANSYS and Comsol Multiphysics. However, many of these optimization algorithms often possess some noteworthy shortcomings such as the trap of solutions at local extremes, or the limited number of design variables or the difficulty of dealing with discrete design variables. Thus, to overcome these limitations and develop an efficient computation tool for optimal design of the MRBs, an optimization procedure that combines differential evolution (DE), a gradient-free global optimization method with finite element analysis (FEA) is proposed in this paper. The proposed approach is then applied to the optimal design of MRBs with different configurations including conventional MRBs and MRBs with coils placed on the side housings. Moreover, to approach a real-life design, some necessary design variables of MRBs are considered as discrete variables in the optimization process. The obtained optimal design results are compared with those of available optimal designs in the literature. The results reveal that the proposed method outperforms some traditional approaches.

Norms for 10,491 Spanish words for five discrete emotions: Happiness, disgust, anger, fear, and sadness.

PubMed

Stadthagen-González, Hans; Ferré, Pilar; Pérez-Sánchez, Miguel A; Imbault, Constance; Hinojosa, José Antonio

2017-09-18

The discrete emotion theory proposes that affective experiences can be reduced to a limited set of universal "basic" emotions, most commonly identified as happiness, sadness, anger, fear, and disgust. Here we present norms for 10,491 Spanish words for those five discrete emotions collected from a total of 2,010 native speakers, making it the largest set of norms for discrete emotions in any language to date. When used in conjunction with the norms from Hinojosa, Martínez-García et al. (Behavior Research Methods, 48, 272-284, 2016) and Ferré, Guasch, Martínez-García, Fraga, & Hinojosa (Behavior Research Methods, 49, 1082-1094, 2017), researchers now have access to ratings of discrete emotions for 13,633 Spanish words. Our norms show a high degree of inter-rater reliability and correlate highly with those from Ferré et al. (2017). Our exploration of the relationship between the five discrete emotions and relevant lexical and emotional variables confirmed findings of previous studies conducted with smaller datasets. The availability of such large set of norms will greatly facilitate the study of emotion, language and related fields. The norms are available as supplementary materials to this article.

The Semigeostrophic Equations Discretized in Reference and Dual Variables

NASA Astrophysics Data System (ADS)

Cullen, Mike; Gangbo, Wilfrid; Pisante, Giovanni

2007-08-01

We study the evolution of a system of n particles {\\{(x_i, v_i)\\}_{i=1}n} in {mathbb{R}^{2d}} . That system is a conservative system with a Hamiltonian of the form {H[μ]=W22(μ, νn)} , where W 2 is the Wasserstein distance and μ is a discrete measure concentrated on the set {\\{(x_i, v_i)\\}_{i=1}n} . Typically, μ(0) is a discrete measure approximating an initial L ∞ density and can be chosen randomly. When d = 1, our results prove convergence of the discrete system to a variant of the semigeostrophic equations. We obtain that the limiting densities are absolutely continuous with respect to the Lebesgue measure. When {\\{ν^n\\}_{n=1}^infty} converges to a measure concentrated on a special d-dimensional set, we obtain the Vlasov-Monge-Ampère (VMA) system. When, d = 1 the VMA system coincides with the standard Vlasov-Poisson system.

Mediterranean climate since the Middle Pleistocene: a 640 ka stable isotope record from Lake Ohrid (Albania/Macedonia)

NASA Astrophysics Data System (ADS)

Lacey, J. H.; Leng, M. J.; Francke, A.; Sloane, H. J.; Milodowski, A.; Vogel, H.; Baumgarten, H.; Wagner, B.

2015-08-01

Lake Ohrid (Macedonia/Albania) is an ancient lake with a unique biodiversity and a site of global significance for investigating the influence of climate, geological and tectonic events on the generation of endemic populations. Here, we present oxygen (δ18O) and carbon (δ13C) isotope data on carbonate from the upper ca. 248 m of sediment cores recovered as part of the Scientific Collaboration on Past Speciation Conditions in Lake Ohrid (SCOPSCO) project, covering the past 640 ka. Previous studies on short cores from the lake (up to 15 m, < 140 ka) have indicated the Total Inorganic Carbon (TIC) content of sediments to be highly sensitive to climate change over the last glacial-interglacial cycle, comprising abundant endogenic calcite through interglacials and being almost absent in glacials, apart from discrete bands of early diagenetic authigenic siderite. Isotope measurements on endogenic calcite (δ18Oc and δ13Cc) reveal variations both between and within interglacials that suggest the lake has been subject to hydroclimate fluctuations on orbital and millennial timescales. We also measured isotopes on authigenic siderite (δ18Os and δ13Cs) and, with the δ18OCc and δ18Os, reconstruct δ18O of lakewater (δ18Olw) through the 640 ka. Overall, glacials have lower δ18Olw when compared to interglacials, most likely due to cooler summer temperatures, a higher proportion of winter precipitation (snowfall), and a reduced inflow from adjacent Lake Prespa. The isotope stratigraphy suggests Lake Ohrid experienced a period of general stability through Marine Isotope Stage (MIS) 15 to MIS 13, highlighting MIS 14 as a particularly warm glacial, and was isotopically freshest during MIS 9. After MIS 9, the variability between glacial and interglacial δ18Olw is enhanced and the lake became increasingly evaporated through to present day with MIS 5 having the highest average δ18Olw. Our results provide new evidence for long-term climate change in the northern Mediterranean region, which will form the basis to better understand the influence of major environmental events on biological evolution within the lake.

Heterogeneous Impact of the “Seguro Popular” Program on the Utilization of Obstetrical Services in Mexico, 2001–2006: A Multinomial Probit Model with a Discrete Endogenous Variable

PubMed Central

Sosa-Rubi, Sandra G.; Galárraga, Omar

2009-01-01

Objective We evaluated the impact of Seguro Popular (SP), a program introduced in 2001 in Mexico primarily to finance health care for the poor. We focused on the effect of household enrollment in SP on pregnant women’s access to obstetrical services, an important outcome measure of both maternal and infant health. Data We relied upon data from the cross-sectional 2006 National Health and Nutrition Survey (ENSANUT) in Mexico. We analyzed the responses of 3,890 women who delivered babies during 2001–2006 and whose households lacked employer-based health care coverage. Methods We formulated a multinomial probit model that distinguished between three mutually exclusive sites for delivering a baby: a health unit specifically accredited by SP; a non-SP-accredited clinic run by the Department of Health (Secretaría de Salud, or SSA); and private obstetrical care. Our model accounted for the endogeneity of the household’s binary decision to enroll in the SP program. Results Women in households that participated in the SP program had a much stronger preference for having a baby in a SP-sponsored unit rather than paying out of pocket for a private delivery. At the same time, participation in SP was associated with a stronger preference for delivering in the private sector rather than at a state-run SSA clinic. On balance, the Seguro Popular program reduced pregnant women’s attendance at an SSA clinic much more than it reduced the probability of delivering a baby in the private sector. The quantitative impact of the SP program varied with the woman’s education and health, as well as the assets and location (rural versus urban) of the household. Conclusions The SP program had a robust, significantly positive impact on access to obstetrical services. Our finding that women enrolled in SP switched from non-SP state-run facilities, rather than from out-of-pocket private services, is important for public policy and requires further exploration. PMID:18824268

Ascertainment-adjusted parameter estimation approach to improve robustness against misspecification of health monitoring methods

NASA Astrophysics Data System (ADS)

Juesas, P.; Ramasso, E.

2016-12-01

Condition monitoring aims at ensuring system safety which is a fundamental requirement for industrial applications and that has become an inescapable social demand. This objective is attained by instrumenting the system and developing data analytics methods such as statistical models able to turn data into relevant knowledge. One difficulty is to be able to correctly estimate the parameters of those methods based on time-series data. This paper suggests the use of the Weighted Distribution Theory together with the Expectation-Maximization algorithm to improve parameter estimation in statistical models with latent variables with an application to health monotonic under uncertainty. The improvement of estimates is made possible by incorporating uncertain and possibly noisy prior knowledge on latent variables in a sound manner. The latent variables are exploited to build a degradation model of dynamical system represented as a sequence of discrete states. Examples on Gaussian Mixture Models, Hidden Markov Models (HMM) with discrete and continuous outputs are presented on both simulated data and benchmarks using the turbofan engine datasets. A focus on the application of a discrete HMM to health monitoring under uncertainty allows to emphasize the interest of the proposed approach in presence of different operating conditions and fault modes. It is shown that the proposed model depicts high robustness in presence of noisy and uncertain prior.

Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics.

PubMed

Harris, Kenneth D; Hochgerner, Hannah; Skene, Nathan G; Magno, Lorenza; Katona, Linda; Bengtsson Gonzales, Carolina; Somogyi, Peter; Kessaris, Nicoletta; Linnarsson, Sten; Hjerling-Leffler, Jens

2018-06-18

Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.

Field comparison of analytical results from discrete-depth ground water samplers

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

Zemo, D.A.; Delfino, T.A.; Gallinatti, J.D.

1995-07-01

Discrete-depth ground water samplers are used during environmental screening investigations to collect ground water samples in lieu of installing and sampling monitoring wells. Two of the most commonly used samplers are the BAT Enviroprobe and the QED HydroPunch I, which rely on differing sample collection mechanics. Although these devices have been on the market for several years, it was unknown what, if any, effect the differences would have on analytical results for ground water samples containing low to moderate concentrations of chlorinated volatile organic compounds (VOCs). This study investigated whether the discrete-depth ground water sampler used introduces statistically significant differencesmore » in analytical results. The goal was to provide a technical basis for allowing the two devices to be used interchangeably during screening investigations. Because this study was based on field samples, it included several sources of potential variability. It was necessary to separate differences due to sampler type from variability due to sampling location, sample handling, and laboratory analytical error. To statistically evaluate these sources of variability, the experiment was arranged in a nested design. Sixteen ground water samples were collected from eight random locations within a 15-foot by 15-foot grid. The grid was located in an area where shallow ground water was believed to be uniformly affected by VOCs. The data were evaluated using analysis of variance.« less

An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems

NASA Astrophysics Data System (ADS)

Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri

2018-01-01

The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.

Violation of Bell's Inequality Using Continuous Variable Measurements

NASA Astrophysics Data System (ADS)

Thearle, Oliver; Janousek, Jiri; Armstrong, Seiji; Hosseini, Sara; Schünemann Mraz, Melanie; Assad, Syed; Symul, Thomas; James, Matthew R.; Huntington, Elanor; Ralph, Timothy C.; Lam, Ping Koy

2018-01-01

A Bell inequality is a fundamental test to rule out local hidden variable model descriptions of correlations between two physically separated systems. There have been a number of experiments in which a Bell inequality has been violated using discrete-variable systems. We demonstrate a violation of Bell's inequality using continuous variable quadrature measurements. By creating a four-mode entangled state with homodyne detection, we recorded a clear violation with a Bell value of B =2.31 ±0.02 . This opens new possibilities for using continuous variable states for device independent quantum protocols.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

Heralded processes on continuous-variable spaces as quantum maps

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

Ferreyrol, Franck; Spagnolo, Nicolò; Blandino, Rémi

2014-12-04

Heralding processes, which only work when a measurement on a part of the system give the good result, are particularly interesting for continuous-variables. They permit non-Gaussian transformations that are necessary for several continuous-variable quantum information tasks. However if maps and quantum process tomography are commonly used to describe quantum transformations in discrete-variable space, they are much rarer in the continuous-variable domain. Also, no convenient tool for representing maps in a way more adapted to the particularities of continuous variables have yet been explored. In this paper we try to fill this gap by presenting such a tool.

Discrete emotions predict changes in cognition, judgment, experience, behavior, and physiology: a meta-analysis of experimental emotion elicitations.

PubMed

Lench, Heather C; Flores, Sarah A; Bench, Shane W

2011-09-01

Our purpose in the present meta-analysis was to examine the extent to which discrete emotions elicit changes in cognition, judgment, experience, behavior, and physiology; whether these changes are correlated as would be expected if emotions organize responses across these systems; and which factors moderate the magnitude of these effects. Studies (687; 4,946 effects, 49,473 participants) were included that elicited the discrete emotions of happiness, sadness, anger, and anxiety as independent variables with adults. Consistent with discrete emotion theory, there were (a) moderate differences among discrete emotions; (b) differences among discrete negative emotions; and (c) correlated changes in behavior, experience, and physiology (cognition and judgment were mostly not correlated with other changes). Valence, valence-arousal, and approach-avoidance models of emotion were not as clearly supported. There was evidence that these factors are likely important components of emotion but that they could not fully account for the pattern of results. Most emotion elicitations were effective, although the efficacy varied with the emotions being compared. Picture presentations were overall the most effective elicitor of discrete emotions. Stronger effects of emotion elicitations were associated with happiness versus negative emotions, self-reported experience, a greater proportion of women (for elicitations of happiness and sadness), omission of a cover story, and participants alone versus in groups. Conclusions are limited by the inclusion of only some discrete emotions, exclusion of studies that did not elicit discrete emotions, few available effect sizes for some contrasts and moderators, and the methodological rigor of included studies. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

Analysis of a mesoscale infiltration and water seepage test in unsaturated fractured rock: Spatial variabilities and discrete fracture patterns

USGS Publications Warehouse

Zhou, Q.; Salve, R.; Liu, H.-H.; Wang, J.S.Y.; Hudson, D.

2006-01-01

A mesoscale (21??m in flow distance) infiltration and seepage test was recently conducted in a deep, unsaturated fractured rock system at the crossover point of two underground tunnels. Water was released from a 3??m ?? 4??m infiltration plot on the floor of an alcove in the upper tunnel, and seepage was collected from the ceiling of a niche in the lower tunnel. Significant temporal and (particularly) spatial variabilities were observed in both measured infiltration and seepage rates. To analyze the test results, a three-dimensional unsaturated flow model was used. A column-based scheme was developed to capture heterogeneous hydraulic properties reflected by these spatial variabilities observed. Fracture permeability and van Genuchten ?? parameter [van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892-898] were calibrated for each rock column in the upper and lower hydrogeologic units in the test bed. The calibrated fracture properties for the infiltration and seepage zone enabled a good match between simulated and measured (spatially varying) seepage rates. The numerical model was also able to capture the general trend of the highly transient seepage processes through a discrete fracture network. The calibrated properties and measured infiltration/seepage rates were further compared with mapped discrete fracture patterns at the top and bottom boundaries. The measured infiltration rates and calibrated fracture permeability of the upper unit were found to be partially controlled by the fracture patterns on the infiltration plot (as indicated by their positive correlations with fracture density). However, no correlation could be established between measured seepage rates and density of fractures mapped on the niche ceiling. This lack of correlation indicates the complexity of (preferential) unsaturated flow within the discrete fracture network. This also indicates that continuum-based modeling of unsaturated flow in fractured rock at mesoscale or a larger scale is not necessarily conditional explicitly on discrete fracture patterns. ?? 2006 Elsevier B.V. All rights reserved.

Dual methods and approximation concepts in structural synthesis

NASA Technical Reports Server (NTRS)

Fleury, C.; Schmit, L. A., Jr.

1980-01-01

Approximation concepts and dual method algorithms are combined to create a method for minimum weight design of structural systems. Approximation concepts convert the basic mathematical programming statement of the structural synthesis problem into a sequence of explicit primal problems of separable form. These problems are solved by constructing explicit dual functions, which are maximized subject to nonnegativity constraints on the dual variables. It is shown that the joining together of approximation concepts and dual methods can be viewed as a generalized optimality criteria approach. The dual method is successfully extended to deal with pure discrete and mixed continuous-discrete design variable problems. The power of the method presented is illustrated with numerical results for example problems, including a metallic swept wing and a thin delta wing with fiber composite skins.

Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation

PubMed Central

Müller, Eike H.; Scheichl, Rob; Shardlow, Tony

2015-01-01

This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy. PMID:27547075

Continuous-time discrete-space models for animal movement

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.

2015-01-01

The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.

A discrete decentralized variable structure robotic controller

NASA Technical Reports Server (NTRS)

Tumeh, Zuheir S.

1989-01-01

A decentralized trajectory controller for robotic manipulators is designed and tested using a multiprocessor architecture and a PUMA 560 robot arm. The controller is made up of a nominal model-based component and a correction component based on a variable structure suction control approach. The second control component is designed using bounds on the difference between the used and actual values of the model parameters. Since the continuous manipulator system is digitally controlled along a trajectory, a discretized equivalent model of the manipulator is used to derive the controller. The motivation for decentralized control is that the derived algorithms can be executed in parallel using a distributed, relatively inexpensive, architecture where each joint is assigned a microprocessor. Nonlinear interaction and coupling between joints is treated as a disturbance torque that is estimated and compensated for.

Further Results on Sufficient LMI Conditions for H∞ Static Output Feedback Control of Discrete-Time Systems

NASA Astrophysics Data System (ADS)

Feng, Zhi-Yong; Xu, Li; Matsushita, Shin-Ya; Wu, Min

Further results on sufficient LMI conditions for H∞ static output feedback (SOF) control of discrete-time systems are presented in this paper, which provide some new insights into this issue. First, by introducing a slack variable with block-triangular structure and choosing the coordinate transformation matrix properly, the conservativeness of one kind of existing sufficient LMI condition is further reduced. Then, by introducing a slack variable with linear matrix equality constraint, another kind of sufficient LMI condition is proposed. Furthermore, the relation of these two kinds of LMI conditions are revealed for the first time through analyzing the effect of different choices of coordinate transformation matrices. Finally, a numerical example is provided to demonstrate the effectiveness and merits of the proposed methods.

Exponential synchronization of neural networks with discrete and distributed delays under time-varying sampling.

PubMed

Wu, Zheng-Guang; Shi, Peng; Su, Hongye; Chu, Jian

2012-09-01

This paper investigates the problem of master-slave synchronization for neural networks with discrete and distributed delays under variable sampling with a known upper bound on the sampling intervals. An improved method is proposed, which captures the characteristic of sampled-data systems. Some delay-dependent criteria are derived to ensure the exponential stability of the error systems, and thus the master systems synchronize with the slave systems. The desired sampled-data controller can be achieved by solving a set of linear matrix inequalitys, which depend upon the maximum sampling interval and the decay rate. The obtained conditions not only have less conservatism but also have less decision variables than existing results. Simulation results are given to show the effectiveness and benefits of the proposed methods.

Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation.

PubMed

Müller, Eike H; Scheichl, Rob; Shardlow, Tony

2015-04-08

This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and especially the Langevin equation. We use modified equations analysis as an alternative to strong-approximation theory for the integrator, and we apply this to introduce MLMC for Langevin-type equations with integrators based on operator splitting. We combine this with extrapolation and investigate the use of discrete random variables in place of the Gaussian increments, which is a well-known technique for the weak approximation of SDEs. We show that, for small-noise problems, discrete random variables can lead to an increase in efficiency of almost two orders of magnitude for practical levels of accuracy.

Synchronous parallel system for emulation and discrete event simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

1992-01-01

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to state variables of the simulation object attributable to the event object, and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring the events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Multigrid one shot methods for optimal control problems: Infinite dimensional control

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.

Synchronous Parallel System for Emulation and Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor)

2001-01-01

A synchronous parallel system for emulation and discrete event simulation having parallel nodes responds to received messages at each node by generating event objects having individual time stamps, stores only the changes to the state variables of the simulation object attributable to the event object and produces corresponding messages. The system refrains from transmitting the messages and changing the state variables while it determines whether the changes are superseded, and then stores the unchanged state variables in the event object for later restoral to the simulation object if called for. This determination preferably includes sensing the time stamp of each new event object and determining which new event object has the earliest time stamp as the local event horizon, determining the earliest local event horizon of the nodes as the global event horizon, and ignoring events whose time stamps are less than the global event horizon. Host processing between the system and external terminals enables such a terminal to query, monitor, command or participate with a simulation object during the simulation process.

Discrete and continuous variables for measurement-device-independent quantum cryptography

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

Xu, Feihu; Curty, Marcos; Qi, Bing

In a recent Article in Nature Photonics, Pirandola et al.1 claim that the achievable secret key rates of discrete-variable (DV) measurementdevice- independent (MDI) quantum key distribution (QKD) (refs 2,3) are “typically very low, unsuitable for the demands of a metropolitan network” and introduce a continuous-variable (CV) MDI QKD protocol capable of providing key rates which, they claim, are “three orders of magnitude higher” than those of DV MDI QKD. We believe, however, that the claims regarding low key rates of DV MDI QKD made by Pirandola et al.1 are too pessimistic. Here in this paper, we show that the secretmore » key rate of DV MDI QKD with commercially available high-efficiency single-photon detectors (SPDs) (for example, see http://www.photonspot.com/detectors and http://www.singlequantum.com) and good system alignment is typically rather high and thus highly suitable for not only long-distance communication but also metropolitan networks.« less

Discrete and continuous variables for measurement-device-independent quantum cryptography

DOE PAGES

Xu, Feihu; Curty, Marcos; Qi, Bing; ...

2015-11-16

In a recent Article in Nature Photonics, Pirandola et al.1 claim that the achievable secret key rates of discrete-variable (DV) measurementdevice- independent (MDI) quantum key distribution (QKD) (refs 2,3) are “typically very low, unsuitable for the demands of a metropolitan network” and introduce a continuous-variable (CV) MDI QKD protocol capable of providing key rates which, they claim, are “three orders of magnitude higher” than those of DV MDI QKD. We believe, however, that the claims regarding low key rates of DV MDI QKD made by Pirandola et al.1 are too pessimistic. Here in this paper, we show that the secretmore » key rate of DV MDI QKD with commercially available high-efficiency single-photon detectors (SPDs) (for example, see http://www.photonspot.com/detectors and http://www.singlequantum.com) and good system alignment is typically rather high and thus highly suitable for not only long-distance communication but also metropolitan networks.« less

A mass-conserving mixed Fourier-Galerkin B-Spline-collocation method for Direct Numerical Simulation of the variable-density Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Reuter, Bryan; Oliver, Todd; Lee, M. K.; Moser, Robert

2017-11-01

We present an algorithm for a Direct Numerical Simulation of the variable-density Navier-Stokes equations based on the velocity-vorticity approach introduced by Kim, Moin, and Moser (1987). In the current work, a Helmholtz decomposition of the momentum is performed. Evolution equations for the curl and the Laplacian of the divergence-free portion are formulated by manipulation of the momentum equations and the curl-free portion is reconstructed by enforcing continuity. The solution is expanded in Fourier bases in the homogeneous directions and B-Spline bases in the inhomogeneous directions. Discrete equations are obtained through a mixed Fourier-Galerkin and collocation weighted residual method. The scheme is designed such that the numerical solution conserves mass locally and globally by ensuring the discrete divergence projection is exact through the use of higher order splines in the inhomogeneous directions. The formulation is tested on multiple variable-density flow problems.

Numerical solution of the two-dimensional time-dependent incompressible Euler equations

NASA Technical Reports Server (NTRS)

Whitfield, David L.; Taylor, Lafayette K.

1994-01-01

A numerical method is presented for solving the artificial compressibility form of the 2D time-dependent incompressible Euler equations. The approach is based on using an approximate Riemann solver for the cell face numerical flux of a finite volume discretization. Characteristic variable boundary conditions are developed and presented for all boundaries and in-flow out-flow situations. The system of algebraic equations is solved using the discretized Newton-relaxation (DNR) implicit method. Numerical results are presented for both steady and unsteady flow.

Iterative spectral methods and spectral solutions to compressible flows

NASA Technical Reports Server (NTRS)

Hussaini, M. Y.; Zang, T. A.

1982-01-01

A spectral multigrid scheme is described which can solve pseudospectral discretizations of self-adjoint elliptic problems in O(N log N) operations. An iterative technique for efficiently implementing semi-implicit time-stepping for pseudospectral discretizations of Navier-Stokes equations is discussed. This approach can handle variable coefficient terms in an effective manner. Pseudospectral solutions of compressible flow problems are presented. These include one dimensional problems and two dimensional Euler solutions. Results are given both for shock-capturing approaches and for shock-fitting ones.

Automatic Methods and Tools for the Verification of Real Time Systems

DTIC Science & Technology

1997-07-31

real - time systems . This was accomplished by extending techniques, based on automata theory and temporal logic, that have been successful for the verification of time-independent reactive systems. As system specification lanmaage for embedded real - time systems , we introduced hybrid automata, which equip traditional discrete automata with real-numbered clock variables and continuous environment variables. As requirements specification languages, we introduced temporal logics with clock variables for expressing timing constraints.

Achieving a physiological cortisol profile with once-daily dual-release hydrocortisone: a pharmacokinetic study.

PubMed

Johannsson, Gudmundur; Lennernäs, Hans; Marelli, Claudio; Rockich, Kevin; Skrtic, Stanko

2016-07-01

Oral once-daily dual-release hydrocortisone (DR-HC) replacement therapy was developed to provide a cortisol exposure-time profile that closely resembles the physiological cortisol profile. This study aimed to characterize single-dose pharmacokinetics (PK) of DR-HC 5-20mg and assess intrasubject variability. Thirty-one healthy Japanese or non-Hispanic Caucasian volunteers aged 20-55 years participated in this randomized, open-label, PK study. Single doses of DR-HC 5, 15 (3×5), and 20mg were administered orally after an overnight fast and suppression of endogenous cortisol secretion. After estimating the endogenous cortisol profile, PK of DR-HC over 24h were evaluated to assess dose proportionality and impact of ethnicity. Plasma cortisol concentrations were analyzed using liquid chromatography-tandem mass spectrometry. PK parameters were calculated from individual cortisol concentration-time profiles. DR-HC 20mg provided higher than endogenous cortisol plasma concentrations 0-4h post-dose but similar concentrations later in the profile. Cortisol concentrations and PK exposure parameters increased with increasing doses. Mean maximal serum concentration (Cmax) was 82.0 and 178.1ng/mL, while mean area under the concentration-time curve (AUC)0-∞ was 562.8 and 1180.8h×ng/mL with DR-HC 5 and 20mg respectively. Within-subject PK variability was low (<15%) for DR-HC 20mg. All exposure PK parameters were less than dose proportional (slope <1). PK differences between ethnicities were explained by body weight differences. DR-HC replacement resembles the daily normal cortisol profile. Within-subject day-to-day PK variability was low, underpinning the safety of DR-HC for replacement therapy. DR-HC PK were less than dose proportional - an important consideration when managing intercurrent illness in patients with adrenal insufficiency. © 2016 The authors.

Graph-cut based discrete-valued image reconstruction.

PubMed

Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

2015-05-01

Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care.

PubMed

Kowalski, Amanda

2016-01-02

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to induce variation in an individual's own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -0.76 to -1.49, which are an order of magnitude larger than previous estimates.

An improved switching converter model. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Shortt, D. J.

1982-01-01

The nonlinear modeling and analysis of dc-dc converters in the continuous mode and discontinuous mode was done by averaging and discrete sampling techniques. A model was developed by combining these two techniques. This model, the discrete average model, accurately predicts the envelope of the output voltage and is easy to implement in circuit and state variable forms. The proposed model is shown to be dependent on the type of duty cycle control. The proper selection of the power stage model, between average and discrete average, is largely a function of the error processor in the feedback loop. The accuracy of the measurement data taken by a conventional technique is affected by the conditions at which the data is collected.

On Reductions of the Hirota-Miwa Equation

NASA Astrophysics Data System (ADS)

Hone, Andrew N. W.; Kouloukas, Theodoros E.; Ward, Chloe

2017-07-01

The Hirota-Miwa equation (also known as the discrete KP equation, or the octahedron recurrence) is a bilinear partial difference equation in three independent variables. It is integrable in the sense that it arises as the compatibility condition of a linear system (Lax pair). The Hirota-Miwa equation has infinitely many reductions of plane wave type (including a quadratic exponential gauge transformation), defined by a triple of integers or half-integers, which produce bilinear ordinary difference equations of Somos/Gale-Robinson type. Here it is explained how to obtain Lax pairs and presymplectic structures for these reductions, in order to demonstrate Liouville integrability of some associated maps, certain of which are related to reductions of discrete Toda and discrete KdV equations.

A study of the variability in the febrile responses of rabbits to endogenous pyrogen.

PubMed

Stitt, J T

1985-10-01

The range of body temperature increases elicited by a standard dose of endogenous pyrogen (0.5 ml/kg iv) was examined in a population of 26 male New Zealand White rabbits. Although the mean maximum increase in rectal temperature was 0.88 +/- 0.06 degree C (SE), individual responses varied from 0.4 degree to 1.5 degree C. Three representative animals that responded to the standard dose of pyrogen with small, intermediate, and large febrile responses were selected and challenged with the same dose of pyrogen on eight separate occasions, and the variability of these responses was examined. There was little variability within the characteristic responses of any particular animal to the repeated challenges. The variability of the febrile responses elicited by both intravenous and intracerebroventricular administration of the same pyrogen was examined and compared using another group of 11 rabbits. The variability in response to the intravenous route was similar to that found in the larger population, whereas the variation in response to the intracerebroventricular route was smaller, and all 11 animals had fevers that were greater than 1 degrees C. It is concluded that the variability of the febrile responses of rabbits to intravenous pyrogen was due to differences between individual sensitivities of animals to the intravenously administered pyrogen. This difference in sensitivity may be due to a difference in the amount of pyrogen that reaches the putative receptor sites, or to a difference in the density or effectiveness of receptor sites in translating the pyrogenic stimulus into a fever response.

Menaquinones content of human serum and feces

USDA-ARS?s Scientific Manuscript database

Bacterially-synthesized menaquinones (MKn) may contribute to vitamin K (VK) nutriture. There are limited data on interindividual variability in endogenous MK synthesis and its relation to circulating forms of VK. Serum and fecal VK concentrations were assessed in 13 healthy adults (45-65 yr) consumi...

Quantitative Multispectral Analysis Of Discrete Subcellular Particles By Digital Imaging Fluorescence Microscopy (DIFM)

NASA Astrophysics Data System (ADS)

Dorey, C. K.; Ebenstein, David B.

1988-10-01

Subcellular localization of multiple biochemical markers is readily achieved through their characteristic autofluorescence or through use of appropriately labelled antibodies. Recent development of specific probes has permitted elegant studies in calcium and pH in living cells. However, each of these methods measured fluorescence at one wavelength; precise quantitation of multiple fluorophores at individual sites within a cell has not been possible. Using DIFM, we have achieved spectral analysis of discrete subcellular particles 1-2 gm in diameter. The fluorescence emission is broken into narrow bands by an interference monochromator and visualized through the combined use of a silicon intensified target (SIT) camera, a microcomputer based framegrabber with 8 bit resolution, and a color video monitor. Image acquisition, processing, analysis and display are under software control. The digitized image can be corrected for the spectral distortions induced by the wavelength dependent sensitivity of the camera, and the displayed image can be enhanced or presented in pseudocolor to facilitate discrimination of variation in pixel intensity of individual particles. For rapid comparison of the fluorophore composition of granules, a ratio image is produced by dividing the image captured at one wavelength by that captured at another. In the resultant ratio image, a granule which has a fluorophore composition different from the majority is selectively colored. This powerful system has been utilized to obtain spectra of endogenous autofluorescent compounds in discrete cellular organelles of human retinal pigment epithelium, and to measure immunohistochemically labelled components of the extracellular matrix associated with the human optic nerve.

Variable-Domain Displacement Transfer Functions for Converting Surface Strains into Deflections for Structural Deformed Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2015-01-01

Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions

WavePacket: A Matlab package for numerical quantum dynamics. I: Closed quantum systems and discrete variable representations

NASA Astrophysics Data System (ADS)

Schmidt, Burkhard; Lorenz, Ulf

2017-04-01

WavePacket is an open-source program package for the numerical simulation of quantum-mechanical dynamics. It can be used to solve time-independent or time-dependent linear Schrödinger and Liouville-von Neumann-equations in one or more dimensions. Also coupled equations can be treated, which allows to simulate molecular quantum dynamics beyond the Born-Oppenheimer approximation. Optionally accounting for the interaction with external electric fields within the semiclassical dipole approximation, WavePacket can be used to simulate experiments involving tailored light pulses in photo-induced physics or chemistry. The graphical capabilities allow visualization of quantum dynamics 'on the fly', including Wigner phase space representations. Being easy to use and highly versatile, WavePacket is well suited for the teaching of quantum mechanics as well as for research projects in atomic, molecular and optical physics or in physical or theoretical chemistry. The present Part I deals with the description of closed quantum systems in terms of Schrödinger equations. The emphasis is on discrete variable representations for spatial discretization as well as various techniques for temporal discretization. The upcoming Part II will focus on open quantum systems and dimension reduction; it also describes the codes for optimal control of quantum dynamics. The present work introduces the MATLAB version of WavePacket 5.2.1 which is hosted at the Sourceforge platform, where extensive Wiki-documentation as well as worked-out demonstration examples can be found.

3D ductile crack propagation within a polycrystalline microstructure using XFEM

NASA Astrophysics Data System (ADS)

Beese, Steffen; Loehnert, Stefan; Wriggers, Peter

2018-02-01

In this contribution we present a gradient enhanced damage based method to simulate discrete crack propagation in 3D polycrystalline microstructures. Discrete cracks are represented using the eXtended finite element method. The crack propagation criterion and the crack propagation direction for each point along the crack front line is based on the gradient enhanced damage variable. This approach requires the solution of a coupled problem for the balance of momentum and the additional global equation for the gradient enhanced damage field. To capture the discontinuity of the displacements as well as the gradient enhanced damage along the discrete crack, both fields are enriched using the XFEM in combination with level sets. Knowing the crack front velocity, level set methods are used to compute the updated crack geometry after each crack propagation step. The applied material model is a crystal plasticity model often used for polycrystalline microstructures of metals in combination with the gradient enhanced damage model. Due to the inelastic material behaviour after each discrete crack propagation step a projection of the internal variables from the old to the new crack configuration is required. Since for arbitrary crack geometries ill-conditioning of the equation system may occur due to (near) linear dependencies between standard and enriched degrees of freedom, an XFEM stabilisation technique based on a singular value decomposition of the element stiffness matrix is proposed. The performance of the presented methodology to capture crack propagation in polycrystalline microstructures is demonstrated with a number of numerical examples.

Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks.

PubMed

Adalsteinsson, David; McMillen, David; Elston, Timothy C

2004-03-08

Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA) molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. We have developed the software package Biochemical Network Stochastic Simulator (BioNetS) for efficiently and accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous) for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solves the appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://www.biospice.org. BioNetS also can be run as a stand alone package. All the required files are accessible from http://x.amath.unc.edu/BioNetS. We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.

A Descriptive Study Comparing GPA, Retention and Graduation of First-Time, Full-Time, Provisionally Admitted First-Generation College Students and Their Peers

ERIC Educational Resources Information Center

Lodhavia, Rajalakshmi

2009-01-01

This quantitative research study used ex post facto data to analyze possible relationships between a discrete set of independent variables and academic achievement among provisionally admitted students at a public, four-year historically black university located in the mid-Atlantic United States. The independent variables were first-generation…

Building Coherent Validation Arguments for the Measurement of Latent Constructs with Unified Statistical Frameworks

ERIC Educational Resources Information Center

Rupp, Andre A.

2012-01-01

In the focus article of this issue, von Davier, Naemi, and Roberts essentially coupled: (1) a short methodological review of structural similarities of latent variable models with discrete and continuous latent variables; and (2) 2 short empirical case studies that show how these models can be applied to real, rather than simulated, large-scale…

Assessing Fit of Models with Discrete Proficiency Variable in Educational Assessment. Research Report. RR-04-07

ERIC Educational Resources Information Center

Sinharay, Sandip; Almond, Russell; Yan, Duanli

2004-01-01

Model checking is a crucial part of any statistical analysis. As educators tie models for testing to cognitive theory of the domains, there is a natural tendency to represent participant proficiencies with latent variables representing the presence or absence of the knowledge, skills, and proficiencies to be tested (Mislevy, Almond, Yan, &…

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

Schnack, D.D.; Lottati, I.; Mikic, Z.

The authors describe TRIM, a MHD code which uses finite volume discretization of the MHD equations on an unstructured adaptive grid of triangles in the poloidal plane. They apply it to problems related to modeling tokamak toroidal plasmas. The toroidal direction is treated by a pseudospectral method. Care was taken to center variables appropriately on the mesh and to construct a self adjoint diffusion operator for cell centered variables.

The Effect of Varying Teacher Presentation Rates on Responding during Discrete Trial Training for Two Children with Autism

ERIC Educational Resources Information Center

Roxburgh, Carole A.; Carbone, Vincent J.

2013-01-01

Recent research has emphasized the importance of manipulating antecedent variables to reduce interfering behaviors when teaching persons with autism. Few studies have focused on the effects of the rate of teacher-presented instructional demands as an independent variable. In this study, an alternating treatment design was used to evaluate the…

Implementation of continuous-variable quantum key distribution with discrete modulation

NASA Astrophysics Data System (ADS)

Hirano, Takuya; Ichikawa, Tsubasa; Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Namiki, Ryo; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2017-06-01

We have developed a continuous-variable quantum key distribution (CV-QKD) system that employs discrete quadrature-amplitude modulation and homodyne detection of coherent states of light. We experimentally demonstrated automated secure key generation with a rate of 50 kbps when a quantum channel is a 10 km optical fibre. The CV-QKD system utilises a four-state and post-selection protocol and generates a secure key against the entangling cloner attack. We used a pulsed light source of 1550 nm wavelength with a repetition rate of 10 MHz. A commercially available balanced receiver is used to realise shot-noise-limited pulsed homodyne detection. We used a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification. A graphical processing unit card is used to accelerate the software-based post-processing.

FDTD modelling of induced polarization phenomena in transient electromagnetics

NASA Astrophysics Data System (ADS)

Commer, Michael; Petrov, Peter V.; Newman, Gregory A.

2017-04-01

The finite-difference time-domain scheme is augmented in order to treat the modelling of transient electromagnetic signals containing induced polarization effects from 3-D distributions of polarizable media. Compared to the non-dispersive problem, the discrete dispersive Maxwell system contains costly convolution operators. Key components to our solution for highly digitized model meshes are Debye decomposition and composite memory variables. We revert to the popular Cole-Cole model of dispersion to describe the frequency-dependent behaviour of electrical conductivity. Its inversely Laplace-transformed Debye decomposition results in a series of time convolutions between electric field and exponential decay functions, with the latter reflecting each Debye constituents' individual relaxation time. These function types in the discrete-time convolution allow for their substitution by memory variables, annihilating the otherwise prohibitive computing demands. Numerical examples demonstrate the efficiency and practicality of our algorithm.

Variable speed wind turbine control by discrete-time sliding mode approach.

PubMed

Torchani, Borhen; Sellami, Anis; Garcia, Germain

2016-05-01

The aim of this paper is to propose a new design variable speed wind turbine control by discrete-time sliding mode approach. This methodology is designed for linear saturated system. The saturation constraint is reported on inputs vector. To this end, the back stepping design procedure is followed to construct a suitable sliding manifold that guarantees the attainment of a stabilization control objective. It is well known that the mechanisms are investigated in term of the most proposed assumptions to deal with the damping, shaft stiffness and inertia effect of the gear. The objectives are to synthesize robust controllers that maximize the energy extracted from wind, while reducing mechanical loads and rotor speed tracking combined with an electromagnetic torque. Simulation results of the proposed scheme are presented. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Six-component semi-discrete integrable nonlinear Schrödinger system

NASA Astrophysics Data System (ADS)

Vakhnenko, Oleksiy O.

2018-01-01

We suggest the six-component integrable nonlinear system on a quasi-one-dimensional lattice. Due to its symmetrical form, the general system permits a number of reductions; one of which treated as the semi-discrete integrable nonlinear Schrödinger system on a lattice with three structural elements in the unit cell is considered in considerable details. Besides six truly independent basic field variables, the system is characterized by four concomitant fields whose background values produce three additional types of inter-site resonant interactions between the basic fields. As a result, the system dynamics becomes associated with the highly nonstandard form of Poisson structure. The elementary Poisson brackets between all field variables are calculated and presented explicitly. The richness of system dynamics is demonstrated on the multi-component soliton solution written in terms of properly parameterized soliton characteristics.

TESTOSTERONE AND SPORT: CURRENT PERSPECTIVES

PubMed Central

Wood, Ruth I.; Stanton, Steven J.

2011-01-01

Testosterone and other anabolic-androgenic steroids enhance athletic performance in men and women. As a result, exogenous androgen is banned from most competitive sports. However, due to variability in endogenous secretion, and similarities with exogenous testosterone, it has been challenging to establish allowable limits for testosterone in competition. Endogenous androgen production is dynamically regulated by both exercise and winning in competition. Furthermore, testosterone may promote athletic performance, not only through its long-term anabolic actions, but also through rapid effects on behavior. In women, excess production of endogenous testosterone due to inborn disorders of sexual development (DSD) may convey a competitive advantage. For many years, female competitors have been subject to tests of sexual genotype and phenotype known as gender verification. Although gender verification has not identified any normal man competing as a woman, this process has identified women athletes with DSD. As understanding of DSD has expanded in recent years, women with DSD are increasingly able to continue athletic competition. PMID:21983229

Failure of self-consistency in the discrete resource model of visual working memory.

PubMed

Bays, Paul M

2018-06-03

The discrete resource model of working memory proposes that each individual has a fixed upper limit on the number of items they can store at one time, due to division of memory into a few independent "slots". According to this model, responses on short-term memory tasks consist of a mixture of noisy recall (when the tested item is in memory) and random guessing (when the item is not in memory). This provides two opportunities to estimate capacity for each observer: first, based on their frequency of random guesses, and second, based on the set size at which the variability of stored items reaches a plateau. The discrete resource model makes the simple prediction that these two estimates will coincide. Data from eight published visual working memory experiments provide strong evidence against such a correspondence. These results present a challenge for discrete models of working memory that impose a fixed capacity limit. Copyright © 2018 The Author. Published by Elsevier Inc. All rights reserved.

Evaluation of endogenous control gene(s) for gene expression studies in human blood exposed to 60Co γ-rays ex vivo.

PubMed

Vaiphei, S Thangminlal; Keppen, Joshua; Nongrum, Saibadaiahun; Chaubey, R C; Kma, L; Sharan, R N

2015-01-01

In gene expression studies, it is critical to normalize data using a stably expressed endogenous control gene in order to obtain accurate and reliable results. However, we currently do not have a universally applied endogenous control gene for normalization of data for gene expression studies, particularly those involving (60)Co γ-ray-exposed human blood samples. In this study, a comparative assessment of the gene expression of six widely used housekeeping endogenous control genes, namely 18S, ACTB, B2M, GAPDH, MT-ATP6 and CDKN1A, was undertaken for a range of (60)Co γ-ray doses (0.5, 1.0, 2.0 and 4.0 Gy) at 8.4 Gy min(-1) at 0 and 24 h post-irradiation time intervals. Using the NormFinder algorithm, real-time PCR data obtained from six individuals (three males and three females) were analyzed with respect to the threshold cycle (Ct) value and abundance, ΔCt pair-wise comparison, intra- and inter-group variability assessments, etc. GAPDH, either alone or in combination with 18S, was found to be the most suitable endogenous control gene and should be used in gene expression studies, especially those involving qPCR of γ-ray-exposed human blood samples. © The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Efficient numerical method for investigating diatomic molecules with single active electron subjected to intense and ultrashort laser fields

NASA Astrophysics Data System (ADS)

Kiss, Gellért Zsolt; Borbély, Sándor; Nagy, Ladislau

2017-12-01

We have presented here an efficient numerical approach for the ab initio numerical solution of the time-dependent Schrödinger Equation describing diatomic molecules, which interact with ultrafast laser pulses. During the construction of the model we have assumed a frozen nuclear configuration and a single active electron. In order to increase efficiency our system was described using prolate spheroidal coordinates, where the wave function was discretized using the finite-element discrete variable representation (FE-DVR) method. The discretized wave functions were efficiently propagated in time using the short-iterative Lanczos algorithm. As a first test we have studied here how the laser induced bound state dynamics in H2+ is influenced by the strength of the driving laser field.

The partition function of the Bures ensemble as the τ-function of BKP and DKP hierarchies: continuous and discrete

NASA Astrophysics Data System (ADS)

Hu, Xing-Biao; Li, Shi-Hao

2017-07-01

The relationship between matrix integrals and integrable systems was revealed more than 20 years ago. As is known, matrix integrals over a Gaussian ensemble used in random matrix theory could act as the τ-function of several hierarchies of integrable systems. In this article, we will show that the time-dependent partition function of the Bures ensemble, whose measure has many interesting geometric properties, could act as the τ-function of BKP and DKP hierarchies. In addition, if discrete time variables are introduced, then this partition function could act as the τ-function of discrete BKP and DKP hierarchies. In particular, there are some links between the partition function of the Bures ensemble and Toda-type equations.

Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System

PubMed Central

Zhen, Chen; Finkelstein, Eric A.; Nonnemaker, James; Karns, Shawn; Todd, Jessica E.

2013-01-01

A censored Exact Affine Stone Index incomplete demand system is estimated for 23 packaged foods and beverages and a numéraire good. Instrumental variables are used to control for endogenous prices. A half-cent per ounce increase in sugar-sweetened beverage prices is predicted to reduce total calories from the 23 foods and beverages but increase sodium and fat intakes as a result of product substitution. The predicted decline in calories is larger for low-income households than for high-income households, although welfare loss is also higher for low-income households. Neglecting price endogeneity or estimating a conditional demand model significantly overestimates the calorie reduction. PMID:24839299

Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System.

PubMed

Zhen, Chen; Finkelstein, Eric A; Nonnemaker, James; Karns, Shawn; Todd, Jessica E

2014-01-01

A censored Exact Affine Stone Index incomplete demand system is estimated for 23 packaged foods and beverages and a numéraire good. Instrumental variables are used to control for endogenous prices. A half-cent per ounce increase in sugar-sweetened beverage prices is predicted to reduce total calories from the 23 foods and beverages but increase sodium and fat intakes as a result of product substitution. The predicted decline in calories is larger for low-income households than for high-income households, although welfare loss is also higher for low-income households. Neglecting price endogeneity or estimating a conditional demand model significantly overestimates the calorie reduction.

Performance on perceptual word identification is mediated by discrete states.

PubMed

Swagman, April R; Province, Jordan M; Rouder, Jeffrey N

2015-02-01

We contrast predictions from discrete-state models of all-or-none information loss with signal-detection models of graded strength for the identification of briefly flashed English words. Previous assessments have focused on whether ROC curves are straight or not, which is a test of a discrete-state model where detection leads to the highest confidence response with certainty. We along with many others argue this certainty assumption is too constraining, and, consequently, the straight-line ROC test is too stringent. Instead, we assess a core property of discrete-state models, conditional independence, where the pattern of responses depends only on which state is entered. The conditional independence property implies that confidence ratings are a mixture of detect and guess state responses, and that stimulus strength factors, the duration of the flashed word in this report, affect only the probability of entering a state and not responses conditional on a state. To assess this mixture property, 50 participants saw words presented briefly on a computer screen at three variable flash durations followed by either a two-alternative confidence ratings task or a yes-no confidence ratings task. Comparable discrete-state and signal-detection models were fit to the data for each participant and task. The discrete-state models outperformed the signal detection models for 90 % of participants in the two-alternative task and for 68 % of participants in the yes-no task. We conclude discrete-state models are viable for predicting performance across stimulus conditions in a perceptual word identification task.

Periodicity and chaos from switched flow systems - Contrasting examples of discretely controlled continuous systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joseph; Ramadge, Peter J.

1993-01-01

We analyze two examples of the discrete control of a continuous variable system. These examples exhibit what may be regarded as the two extremes of complexity of the closed-loop behavior: one is eventually periodic, the other is chaotic. Our examples are derived from sampled deterministic flow models. These are of interest in their own right but have also been used as models for certain aspects of manufacturing systems. In each case, we give a precise characterization of the closed-loop behavior.

Angular Distributions of Discrete Mesoscale Mapping Functions

NASA Astrophysics Data System (ADS)

Kroszczyński, Krzysztof

2015-08-01

The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.

Hybrid Methods in Quantum Information

NASA Astrophysics Data System (ADS)

Marshall, Kevin

Today, the potential power of quantum information processing comes as no surprise to physicist or science-fiction writer alike. However, the grand promises of this field remain unrealized, despite significant strides forward, due to the inherent difficulties of manipulating quantum systems. Simply put, it turns out that it is incredibly difficult to interact, in a controllable way, with the quantum realm when we seem to live our day to day lives in a classical world. In an effort to solve this challenge, people are exploring a variety of different physical platforms, each with their strengths and weaknesses, in hopes of developing new experimental methods that one day might allow us to control a quantum system. One path forward rests in combining different quantum systems in novel ways to exploit the benefits of different systems while circumventing their respective weaknesses. In particular, quantum systems come in two different flavours: either discrete-variable systems or continuous-variable ones. The field of hybrid quantum information seeks to combine these systems, in clever ways, to help overcome the challenges blocking the path between what is theoretically possible and what is achievable in a laboratory. In this thesis we explore four topics in the context of hybrid methods in quantum information, in an effort to contribute to the resolution of existing challenges and to stimulate new avenues of research. First, we explore the manipulation of a continuous-variable quantum system consisting of phonons in a linear chain of trapped ions where we use the discretized internal levels to mediate interactions. Using our proposed interaction we are able to implement, for example, the acoustic equivalent of a beam splitter with modest experimental resources. Next we propose an experimentally feasible implementation of the cubic phase gate, a primitive non-Gaussian gate required for universal continuous-variable quantum computation, based off sequential photon subtraction. We then discuss the notion of embedding a finite dimensional state into a continuous-variable system, and propose a method of performing quantum computations on encrypted continuous-variable states. This protocol allows for a client, of limited quantum ability, to outsource a computation while hiding their information. Next, we discuss the possibility of performing universal quantum computation on discrete-variable logical states encoded in mixed continuous-variable quantum states. Finally, we present an account of open problems related to our results, and possible future avenues of research.

A Note on Verification of Computer Simulation Models

ERIC Educational Resources Information Center

Aigner, Dennis J.

1972-01-01

Establishes an argument that questions the validity of one test'' of goodness-of-fit (the extent to which a series of obtained measures agrees with a series of theoretical measures) for the simulated time path of a simple endogenous (internally developed) variable in a simultaneous, perhaps dynamic econometric model. (Author)

Determinants of Students' Outcome: A Full-Fledged Structural Equation Modelling Approach

ERIC Educational Resources Information Center

Musah, Mohammed Borhandden; Ali, Hairuddin Bin Mohd; Al-Hudawi, Shafeeq Hussain Vazhathodi; Tahir, Lokman Mohd; Daud, Khadijah Binti; Hamdan, Abdul Rahim

2015-01-01

The vibrant demand for academic excellence in the twenty-first century has brought diverse determinants of students' outcome into play. However, few studies have validated the instruments and examined the mediating effect between exogenous and endogenous variables of the student outcome model. This study, therefore, investigates the psychometric…

Estimation and Model Selection for Finite Mixtures of Latent Interaction Models

ERIC Educational Resources Information Center

Hsu, Jui-Chen

2011-01-01

Latent interaction models and mixture models have received considerable attention in social science research recently, but little is known about how to handle if unobserved population heterogeneity exists in the endogenous latent variables of the nonlinear structural equation models. The current study estimates a mixture of latent interaction…

Similarity Attraction in Learning Contexts: An Empirical Study

ERIC Educational Resources Information Center

Varela, Otmar E.; Cater, John James, III; Michel, Norbert

2011-01-01

This study tests a process model of learning in which trainer and trainee traits are simultaneously considered as endogenous variables of learning outcomes. The article builds on a social view of training and similarity-attraction paradigms. In this context, the authors hypothesize that trainer-trainee similarity in personality (agreeableness)…

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care

PubMed Central

Kowalski, Amanda

2015-01-01

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member’s injury to induce variation in an individual’s own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from −0.76 to −1.49, which are an order of magnitude larger than previous estimates. PMID:26977117

Discrete Gust Model for Launch Vehicle Assessments

NASA Technical Reports Server (NTRS)

Leahy, Frank B.

2008-01-01

Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.

Software For Integer Programming

NASA Technical Reports Server (NTRS)

Fogle, F. R.

1992-01-01

Improved Exploratory Search Technique for Pure Integer Linear Programming Problems (IESIP) program optimizes objective function of variables subject to confining functions or constraints, using discrete optimization or integer programming. Enables rapid solution of problems up to 10 variables in size. Integer programming required for accuracy in modeling systems containing small number of components, distribution of goods, scheduling operations on machine tools, and scheduling production in general. Written in Borland's TURBO Pascal.

The combined effects of exogenous and endogenous variability on the spatial distribution of ant communities in a forested ecosystem (Hymenoptera: Formicidae).

PubMed

Yitbarek, Senay; Vandermeer, John H; Allen, David

2011-10-01

Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.

Elimination of endogenous aberrant kappa chain transcripts from sp2/0-derived hybridoma cells by specific ribozyme cleavage: utility in genetic therapy of HIV-1 infections.

PubMed Central

Duan, L; Pomerantz, R J

1994-01-01

The pooled degenerate-primer polymerase chain reaction (PCR) technology is now widely used in the amplification and cloning of murine hybridoma-specific immunoglobulin gene cDNAs. The design of primers is mainly based on the highly conserved 5' terminus of immunoglobulin gene variable regions and the constant region in the 3' terminus. Of note, most murine hybridoma cell lines are derived from the Sp2/0 cell line, which is demonstrated to express endogenous aberrant kappa chains (abV kappa). This high-level endogenous abV kappa mixes with specific kappa chains in the hybridomas and interferes with the efficiency of the reverse transcriptase (RT)-PCR cloning strategy. In this report, during the cloning of murine anti-human immunodeficiency virus type I (HIV-1) hybridoma immunoglobulin cDNAs, a specific primer-PCR screening system was developed, based on the abV kappa complementarity-defining region (CDR), to eliminate abV kappa-carrying plasmids. Furthermore, an abV kappa sequence-specific derived ribozyme was developed and packaged in a retroviral expression vector system. This abV kappa ribozyme can be transduced into different murine hybridomas, and expressed intracellularly to potently eliminate endogenous abV kappa RNA. Images PMID:7816635

Fashion cycle dynamics in a model with endogenous discrete evolution of heterogeneous preferences

NASA Astrophysics Data System (ADS)

Naimzada, A. K.; Pireddu, M.

2018-05-01

We propose a discrete-time exchange economy evolutionary model, in which two groups of agents are characterized by different preference structures. The reproduction level of a group is related to its attractiveness degree, which depends on the social visibility level, determined by the consumption choices of the agents in that group. The attractiveness of a group is initially increasing with its visibility level, but it becomes decreasing when its visibility exceeds a given threshold value, due to a congestion effect. Thanks to the combined action of the price mechanism and of the share updating rule, the model is able to reproduce the recurrent dynamic behavior typical of the fashion cycle, presenting booms and busts both in the agents' consumption choices and in the population shares. More precisely, we investigate the existence of equilibria and their stability, and we perform a qualitative bifurcation analysis on varying the parameter describing the group's heterogeneity degree. From a global viewpoint, we detect, among others, multistability phenomena in which the group coexistence is dynamic, either regular or irregular, and the fashion cycle occurs. The existence of complex dynamics is proven via the method of the turbulent maps, working with homoclinic orbits. Finally, we provide a social and economic interpretation of the main scenarios.

Diurnal rhythms in psychological reward functioning in healthy young men: 'Wanting', liking, and learning.

PubMed

Byrne, Jamie E M; Murray, Greg

2017-01-01

A range of evidence suggests that human reward functioning is partly driven by the endogenous circadian system, generating 24-hour rhythms in behavioural measures of reward activation. Reward functioning is multifaceted but literature to date is largely limited to measures of self-reported positive mood states. The aim of this study was to advance the field by testing for hypothesised diurnal variation in previously unexplored components of psychological reward: 'wanting', liking, and learning using subjective and behavioural measures. Risky decision making (automatic Balloon Analogue Risk Task), affective responsivity to positive images (International Affective Pictures System), uncued self-reported discrete emotions, and learning-contingent reward (Iowa Gambling Task) were measured at 10.00 hours, 14.00 hours, and 19.00 hours in a counterbalanced repeated measures design with 50 healthy male participants (aged 18-30). As hypothesised, risky decision making (unconscious 'wanting') and ratings of arousal towards positive images (conscious wanting) exhibited a diurnal waveform with indices highest at 14.00 hours. No diurnal rhythm was observed for liking (pleasure ratings to positive images, discrete uncued positive emotions) or in a learning-contingent reward task. Findings reaffirm that diurnal variation in human reward functioning is most pronounced in the motivational 'wanting' components of reward.

Fashion cycle dynamics in a model with endogenous discrete evolution of heterogeneous preferences.

PubMed

Naimzada, A K; Pireddu, M

2018-05-01

We propose a discrete-time exchange economy evolutionary model, in which two groups of agents are characterized by different preference structures. The reproduction level of a group is related to its attractiveness degree, which depends on the social visibility level, determined by the consumption choices of the agents in that group. The attractiveness of a group is initially increasing with its visibility level, but it becomes decreasing when its visibility exceeds a given threshold value, due to a congestion effect. Thanks to the combined action of the price mechanism and of the share updating rule, the model is able to reproduce the recurrent dynamic behavior typical of the fashion cycle, presenting booms and busts both in the agents' consumption choices and in the population shares. More precisely, we investigate the existence of equilibria and their stability, and we perform a qualitative bifurcation analysis on varying the parameter describing the group's heterogeneity degree. From a global viewpoint, we detect, among others, multistability phenomena in which the group coexistence is dynamic, either regular or irregular, and the fashion cycle occurs. The existence of complex dynamics is proven via the method of the turbulent maps, working with homoclinic orbits. Finally, we provide a social and economic interpretation of the main scenarios.

Force-Time Entropy of Isometric Impulse.

PubMed

Hsieh, Tsung-Yu; Newell, Karl M

2016-01-01

The relation between force and temporal variability in discrete impulse production has been viewed as independent (R. A. Schmidt, H. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979 ) or dependent on the rate of force (L. G. Carlton & K. M. Newell, 1993 ). Two experiments in an isometric single finger force task investigated the joint force-time entropy with (a) fixed time to peak force and different percentages of force level and (b) fixed percentage of force level and different times to peak force. The results showed that the peak force variability increased either with the increment of force level or through a shorter time to peak force that also reduced timing error variability. The peak force entropy and entropy of time to peak force increased on the respective dimension as the parameter conditions approached either maximum force or a minimum rate of force production. The findings show that force error and timing error are dependent but complementary when considered in the same framework with the joint force-time entropy at a minimum in the middle parameter range of discrete impulse.

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive.

PubMed

Ameid, Tarek; Menacer, Arezki; Talhaoui, Hicham; Azzoug, Youness

2018-05-03

This paper presents a methodology for the broken rotor bars fault detection is considered when the rotor speed varies continuously and the induction machine is controlled by Field-Oriented Control (FOC). The rotor fault detection is obtained by analyzing a several mechanical and electrical quantities (i.e., rotor speed, stator phase current and output signal of the speed regulator) by the Discrete Wavelet Transform (DWT) in variable speed drives. The severity of the fault is obtained by stored energy calculation for active power signal. Hence, it can be a useful solution as fault indicator. The FOC is implemented in order to preserve a good performance speed control; to compensate the broken rotor bars effect in the mechanical speed and to ensure the operation continuity and to investigate the fault effect in the variable speed. The effectiveness of the technique is evaluated in simulation and in a real-time implementation by using Matlab/Simulink with the real-time interface (RTI) based on dSpace 1104 board. Copyright © 2018. Published by Elsevier Ltd.

Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data

PubMed Central

DiPrete, Thomas A.; Burik, Casper A. P.; Koellinger, Philipp D.

2018-01-01

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA. PMID:29686100

Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data.

PubMed

DiPrete, Thomas A; Burik, Casper A P; Koellinger, Philipp D

2018-05-29

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA. Copyright © 2018 the Author(s). Published by PNAS.

Comparison of Classifiers for Decoding Sensory and Cognitive Information from Prefrontal Neuronal Populations

PubMed Central

Astrand, Elaine; Enel, Pierre; Ibos, Guilhem; Dominey, Peter Ford; Baraduc, Pierre; Ben Hamed, Suliann

2014-01-01

Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fields (FEF): the spatial position of a visual cue, and the instructed orientation of the animal's attention. While the first variable is exogenously driven by the environment, the second variable corresponds to the interpretation of the instruction conveyed by the cue; it is endogenously driven and corresponds to the output of internal cognitive operations performed on the visual attributes of the cue. These two variables were decoded using either a regularized optimal linear estimator in its explicit formulation, an optimal linear artificial neural network estimator, a non-linear artificial neural network estimator, a non-linear naïve Bayesian estimator, a non-linear Reservoir recurrent network classifier or a non-linear Support Vector Machine classifier. Our results suggest that endogenous information such as the orientation of attention can be decoded from the FEF with the same accuracy as exogenous visual information. All classifiers did not behave equally in the face of population size and heterogeneity, the available training and testing trials, the subject's behavior and the temporal structure of the variable of interest. In most situations, the regularized optimal linear estimator and the non-linear Support Vector Machine classifiers outperformed the other tested decoders. PMID:24466019

Stronger steerability criterion for more uncertain continuous-variable systems

NASA Astrophysics Data System (ADS)

Chowdhury, Priyanka; Pramanik, Tanumoy; Majumdar, A. S.

2015-10-01

We derive a fine-grained uncertainty relation for the measurement of two incompatible observables on a single quantum system of continuous variables, and show that continuous-variable systems are more uncertain than discrete-variable systems. Using the derived fine-grained uncertainty relation, we formulate a stronger steering criterion that is able to reveal the steerability of NOON states that has hitherto not been possible using other criteria. We further obtain a monogamy relation for our steering inequality which leads to an, in principle, improved lower bound on the secret key rate of a one-sided device independent quantum key distribution protocol for continuous variables.

Implementation Strategies for Large-Scale Transport Simulations Using Time Domain Particle Tracking

NASA Astrophysics Data System (ADS)

Painter, S.; Cvetkovic, V.; Mancillas, J.; Selroos, J.

2008-12-01

Time domain particle tracking is an emerging alternative to the conventional random walk particle tracking algorithm. With time domain particle tracking, particles are moved from node to node on one-dimensional pathways defined by streamlines of the groundwater flow field or by discrete subsurface features. The time to complete each deterministic segment is sampled from residence time distributions that include the effects of advection, longitudinal dispersion, a variety of kinetically controlled retention (sorption) processes, linear transformation, and temporal changes in groundwater velocities and sorption parameters. The simulation results in a set of arrival times at a monitoring location that can be post-processed with a kernel method to construct mass discharge (breakthrough) versus time. Implementation strategies differ for discrete flow (fractured media) systems and continuous porous media systems. The implementation strategy also depends on the scale at which hydraulic property heterogeneity is represented in the supporting flow model. For flow models that explicitly represent discrete features (e.g., discrete fracture networks), the sampling of residence times along segments is conceptually straightforward. For continuous porous media, such sampling needs to be related to the Lagrangian velocity field. Analytical or semi-analytical methods may be used to approximate the Lagrangian segment velocity distributions in aquifers with low-to-moderate variability, thereby capturing transport effects of subgrid velocity variability. If variability in hydraulic properties is large, however, Lagrangian velocity distributions are difficult to characterize and numerical simulations are required; in particular, numerical simulations are likely to be required for estimating the velocity integral scale as a basis for advective segment distributions. Aquifers with evolving heterogeneity scales present additional challenges. Large-scale simulations of radionuclide transport at two potential repository sites for high-level radioactive waste will be used to demonstrate the potential of the method. The simulations considered approximately 1000 source locations, multiple radionuclides with contrasting sorption properties, and abrupt changes in groundwater velocity associated with future glacial scenarios. Transport pathways linking the source locations to the accessible environment were extracted from discrete feature flow models that include detailed representations of the repository construction (tunnels, shafts, and emplacement boreholes) embedded in stochastically generated fracture networks. Acknowledgment The authors are grateful to SwRI Advisory Committee for Research, the Swedish Nuclear Fuel and Waste Management Company, and Posiva Oy for financial support.

Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera

NASA Astrophysics Data System (ADS)

Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.

2017-12-01

The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth's climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO variability.

78 FR 75942 - Certain Mobile Phones and Tablet Computers, and Components Thereof; Commission Determination To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-13

... implemented using a variable voltage source'' is an appropriate modifier of the corresponding structure for... the Nokia-Qualcomm agreement. The parties have been invited to brief only the discrete issues...

Approximation of state variables for discrete-time stochastic genetic regulatory networks with leakage, distributed, and probabilistic measurement delays: a robust stability problem.

PubMed

Pandiselvi, S; Raja, R; Cao, Jinde; Rajchakit, G; Ahmad, Bashir

2018-01-01

This work predominantly labels the problem of approximation of state variables for discrete-time stochastic genetic regulatory networks with leakage, distributed, and probabilistic measurement delays. Here we design a linear estimator in such a way that the absorption of mRNA and protein can be approximated via known measurement outputs. By utilizing a Lyapunov-Krasovskii functional and some stochastic analysis execution, we obtain the stability formula of the estimation error systems in the structure of linear matrix inequalities under which the estimation error dynamics is robustly exponentially stable. Further, the obtained conditions (in the form of LMIs) can be effortlessly solved by some available software packages. Moreover, the specific expression of the desired estimator is also shown in the main section. Finally, two mathematical illustrative examples are accorded to show the advantage of the proposed conceptual results.

A novel approach to piecewise analytic agricultural machinery path reconstruction

NASA Astrophysics Data System (ADS)

Wörz, Sascha; Mederle, Michael; Heizinger, Valentin; Bernhardt, Heinz

2017-12-01

Before analysing machinery operation in fields, it has to be coped with the problem that the GPS signals of GPS receivers located on the machines contain measurement noise, are time-discrete, and the underlying physical system describing the positions, axial and absolute velocities, angular rates and angular orientation of the operating machines during the whole working time are unknown. This research work presents a new three-dimensional mathematical approach using kinematic relations based on control variables as Euler angular velocities and angles and a discrete target control problem, such that the state control function is given by the sum of squared residuals involving the state and control variables to get such a physical system, which yields a noise-free and piecewise analytic representation of the positions, velocities, angular rates and angular orientation. It can be used for a further detailed study and analysis of the problem of why agricultural vehicles operate in practice as they do.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1977-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1978-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Multidisciplinary Optimization of a Transport Aircraft Wing using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Venter, Gerhard

2002-01-01

The purpose of this paper is to demonstrate the application of particle swarm optimization to a realistic multidisciplinary optimization test problem. The paper's new contributions to multidisciplinary optimization is the application of a new algorithm for dealing with the unique challenges associated with multidisciplinary optimization problems, and recommendations as to the utility of the algorithm in future multidisciplinary optimization applications. The selected example is a bi-level optimization problem that demonstrates severe numerical noise and has a combination of continuous and truly discrete design variables. The use of traditional gradient-based optimization algorithms is thus not practical. The numerical results presented indicate that the particle swarm optimization algorithm is able to reliably find the optimum design for the problem presented here. The algorithm is capable of dealing with the unique challenges posed by multidisciplinary optimization as well as the numerical noise and truly discrete variables present in the current example problem.

An opinion-driven behavioral dynamics model for addictive behaviors

NASA Astrophysics Data System (ADS)

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

2015-04-01

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

A PDE Pricing Framework for Cross-Currency Interest Rate Derivatives with Target Redemption Features

NASA Astrophysics Data System (ADS)

Christara, Christina C.; Minh Dang, Duy; Jackson, Kenneth R.; Lakhany, Asif

2010-09-01

We propose a general framework for efficient pricing via a partial differential equation (PDE) approach for exotic cross-currency interest rate (IR) derivatives, with strong emphasis on long-dated foreign exchange (FX) IR hybrids, namely Power Reverse Dual Currency (PRDC) swaps with a FX Target Redemption (FX-TARN) provision. The FX-TARN provision provides a cap on the FX-linked PRDC coupon amounts, and once the accumulated coupon amount reaches this cap, the underlying PRDC swap terminates. Our PDE pricing framework is based on an auxiliary state variable to keep track of the total accumulated PRDC coupon amount. Finite differences on uniform grids and the Alternating Direction Implicit (ADI) method are used for the spatial and time discretizations, respectively, of the model-dependent PDE corresponding to each discretized value of the auxiliary variable. Numerical examples illustrating the convergence properties of the numerical methods are provided.

Continuous-variable quantum homomorphic signature

NASA Astrophysics Data System (ADS)

Li, Ke; Shang, Tao; Liu, Jian-wei

2017-10-01

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.

Hybrid stochastic simplifications for multiscale gene networks.

PubMed

Crudu, Alina; Debussche, Arnaud; Radulescu, Ovidiu

2009-09-07

Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion [1-3] which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

Hybrid finite difference/finite element immersed boundary method.

PubMed

E Griffith, Boyce; Luo, Xiaoyu

2017-12-01

The immersed boundary method is an approach to fluid-structure interaction that uses a Lagrangian description of the structural deformations, stresses, and forces along with an Eulerian description of the momentum, viscosity, and incompressibility of the fluid-structure system. The original immersed boundary methods described immersed elastic structures using systems of flexible fibers, and even now, most immersed boundary methods still require Lagrangian meshes that are finer than the Eulerian grid. This work introduces a coupling scheme for the immersed boundary method to link the Lagrangian and Eulerian variables that facilitates independent spatial discretizations for the structure and background grid. This approach uses a finite element discretization of the structure while retaining a finite difference scheme for the Eulerian variables. We apply this method to benchmark problems involving elastic, rigid, and actively contracting structures, including an idealized model of the left ventricle of the heart. Our tests include cases in which, for a fixed Eulerian grid spacing, coarser Lagrangian structural meshes yield discretization errors that are as much as several orders of magnitude smaller than errors obtained using finer structural meshes. The Lagrangian-Eulerian coupling approach developed in this work enables the effective use of these coarse structural meshes with the immersed boundary method. This work also contrasts two different weak forms of the equations, one of which is demonstrated to be more effective for the coarse structural discretizations facilitated by our coupling approach. © 2017 The Authors International  Journal  for  Numerical  Methods  in  Biomedical  Engineering Published by John Wiley & Sons Ltd.

Epigenetic modification of the oxytocin receptor gene influences the perception of anger and fear in the human brain

PubMed Central

Puglia, Meghan H.; Lillard, Travis S.; Morris, James P.; Connelly, Jessica J.

2015-01-01

In humans, the neuropeptide oxytocin plays a critical role in social and emotional behavior. The actions of this molecule are dependent on a protein that acts as its receptor, which is encoded by the oxytocin receptor gene (OXTR). DNA methylation of OXTR, an epigenetic modification, directly influences gene transcription and is variable in humans. However, the impact of this variability on specific social behaviors is unknown. We hypothesized that variability in OXTR methylation impacts social perceptual processes often linked with oxytocin, such as perception of facial emotions. Using an imaging epigenetic approach, we established a relationship between OXTR methylation and neural activity in response to emotional face processing. Specifically, high levels of OXTR methylation were associated with greater amounts of activity in regions associated with face and emotion processing including amygdala, fusiform, and insula. Importantly, we found that these higher levels of OXTR methylation were also associated with decreased functional coupling of amygdala with regions involved in affect appraisal and emotion regulation. These data indicate that the human endogenous oxytocin system is involved in attenuation of the fear response, corroborating research implicating intranasal oxytocin in the same processes. Our findings highlight the importance of including epigenetic mechanisms in the description of the endogenous oxytocin system and further support a central role for oxytocin in social cognition. This approach linking epigenetic variability with neural endophenotypes may broadly explain individual differences in phenotype including susceptibility or resilience to disease. PMID:25675509

Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.

2009-01-01

An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and dynamic grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.

Non-verbal numerical cognition: from reals to integers.

PubMed

Gallistel; Gelman

2000-02-01

Data on numerical processing by verbal (human) and non-verbal (animal and human) subjects are integrated by the hypothesis that a non-verbal counting process represents discrete (countable) quantities by means of magnitudes with scalar variability. These appear to be identical to the magnitudes that represent continuous (uncountable) quantities such as duration. The magnitudes representing countable quantity are generated by a discrete incrementing process, which defines next magnitudes and yields a discrete ordering. In the case of continuous quantities, the continuous accumulation process does not define next magnitudes, so the ordering is also continuous ('dense'). The magnitudes representing both countable and uncountable quantity are arithmetically combined in, for example, the computation of the income to be expected from a foraging patch. Thus, on the hypothesis presented here, the primitive machinery for arithmetic processing works with real numbers (magnitudes).

Variationally consistent discretization schemes and numerical algorithms for contact problems

NASA Astrophysics Data System (ADS)

Wohlmuth, Barbara

We consider variationally consistent discretization schemes for mechanical contact problems. Most of the results can also be applied to other variational inequalities, such as those for phase transition problems in porous media, for plasticity or for option pricing applications from finance. The starting point is to weakly incorporate the constraint into the setting and to reformulate the inequality in the displacement in terms of a saddle-point problem. Here, the Lagrange multiplier represents the surface forces, and the constraints are restricted to the boundary of the simulation domain. Having a uniform inf-sup bound, one can then establish optimal low-order a priori convergence rates for the discretization error in the primal and dual variables. In addition to the abstract framework of linear saddle-point theory, complementarity terms have to be taken into account. The resulting inequality system is solved by rewriting it equivalently by means of the non-linear complementarity function as a system of equations. Although it is not differentiable in the classical sense, semi-smooth Newton methods, yielding super-linear convergence rates, can be applied and easily implemented in terms of a primal-dual active set strategy. Quite often the solution of contact problems has a low regularity, and the efficiency of the approach can be improved by using adaptive refinement techniques. Different standard types, such as residual- and equilibrated-based a posteriori error estimators, can be designed based on the interpretation of the dual variable as Neumann boundary condition. For the fully dynamic setting it is of interest to apply energy-preserving time-integration schemes. However, the differential algebraic character of the system can result in high oscillations if standard methods are applied. A possible remedy is to modify the fully discretized system by a local redistribution of the mass. Numerical results in two and three dimensions illustrate the wide range of possible applications and show the performance of the space discretization scheme, non-linear solver, adaptive refinement process and time integration.

Forecast Verification: Identification of small changes in weather forecasting skill

NASA Astrophysics Data System (ADS)

Weatherhead, E. C.; Jensen, T. L.

2017-12-01

Global and regonal weather forecasts have improved over the past seven decades most often because of small, incrmental improvements. The identificaiton and verification of forecast improvement due to proposed small changes in forecasting can be expensive and, if not carried out efficiently, can slow progress in forecasting development. This presentation will look at the skill of commonly used verification techniques and show how the ability to detect improvements can depend on the magnitude of the improvement, the number of runs used to test the improvement, the location on the Earth and the statistical techniques used. For continuous variables, such as temperture, wind and humidity, the skill of a forecast can be directly compared using a pair-wise statistical test that accommodates the natural autocorrelation and magnitude of variability. For discrete variables, such as tornado outbreaks, or icing events, the challenges is to reduce the false alarm rate while improving the rate of correctly identifying th discrete event. For both continuus and discrete verification results, proper statistical approaches can reduce the number of runs needed to identify a small improvement in forecasting skill. Verification within the Next Generation Global Prediction System is an important component to the many small decisions needed to make stat-of-the-art improvements to weather forecasting capabilities. The comparison of multiple skill scores with often conflicting results requires not only appropriate testing, but also scientific judgment to assure that the choices are appropriate not only for improvements in today's forecasting capabilities, but allow improvements that will come in the future.

Effects of the design of environmental disclosure regulation on information provision: the case of Israeli securities regulation.

PubMed

Kerret, Dorit; Menahem, Gila; Sagi, Rinat

2010-11-01

Focusing on the potential of information regulations, this article aims to contribute to ongoing efforts of policymakers to improve policy tools, in light of the increasing complexity of assessing the environmental impacts of new technologies and industrial corporations. Using the annual reports of corporations and performance data from the Ministry of Environmental Protection, the study analyzed the quality of responses to the amendments of Israel's Securities Regulations by major, publicly traded, polluting industrial corporations in Israel. The main theoretical claim of this paper is that within mandatory regulations there may be a large variability in the degree of specification of requirements. When considerable discretion is left to corporations, the result is a mixed mandatory-voluntary regulation regime. Our findings suggest that such variability impacts the implementation outcomes, as responses to environmental requirements depend on the level of discretion. Facilities increased their reported information, including the negative aspects, when specific mandatory prescriptions were stipulated. However, voluntary motivations did not result in the provision of information when corporations were allowed a high level of discretion. The authors recommend the delineation of exact stipulations of prescriptive requirements for the provision of comparative environmental information in order to obtain the environmental information deemed necessary.

Persistence of non-Markovian Gaussian stationary processes in discrete time

NASA Astrophysics Data System (ADS)

Nyberg, Markus; Lizana, Ludvig

2018-04-01

The persistence of a stochastic variable is the probability that it does not cross a given level during a fixed time interval. Although persistence is a simple concept to understand, it is in general hard to calculate. Here we consider zero mean Gaussian stationary processes in discrete time n . Few results are known for the persistence P0(n ) in discrete time, except the large time behavior which is characterized by the nontrivial constant θ through P0(n ) ˜θn . Using a modified version of the independent interval approximation (IIA) that we developed before, we are able to calculate P0(n ) analytically in z -transform space in terms of the autocorrelation function A (n ) . If A (n )→0 as n →∞ , we extract θ numerically, while if A (n )=0 , for finite n >N , we find θ exactly (within the IIA). We apply our results to three special cases: the nearest-neighbor-correlated "first order moving average process", where A (n )=0 for n >1 , the double exponential-correlated "second order autoregressive process", where A (n ) =c1λ1n+c2λ2n , and power-law-correlated variables, where A (n ) ˜n-μ . Apart from the power-law case when μ <5 , we find excellent agreement with simulations.

Self-reported psychological demands, skill discretion and decision authority at work: A twin study.

PubMed

Theorell, Töres; De Manzano, Örjan; Lennartsson, Anna-Karin; Pedersen, Nancy L; Ullén, Fredrik

2016-06-01

To examine the contribution of genetic factors to self-reported psychological demands (PD), skill discretion (SD) and decision authority (DA) and the possible importance of such influence on the association between these work variables and depressive symptoms. 11,543 participants aged 27-54 in the Swedish Twin Registry participated in a web survey. First of all, in multiple regressions, phenotypic associations between each one of the three work environment variables and depressive symptoms were analysed. Secondly, by means of classical twin analysis, the genetic contribution to PD, SD and DA was assessed. After this, cross-twin cross-trait correlations were computed between PD, SD and DA, on the one hand, and depressive symptom score, on the other hand. The genetic contribution to self-reported PD, DS and DA ranged from 18% for decision authority to 30% for skill discretion. Cross-twin cross-trait correlations were very weak (r values < .1) and non-significant for dizygotic twins, and we lacked power to analyse the genetic architecture of the phenotypic associations using bivariate twin modelling. However, substantial genetic contribution to these associations seems unlikely. CONCLUSIONS GENETIC CONTRIBUTIONS TO THE SELF-REPORTED WORK ENVIRONMENT SCORES WERE 18-30%. © 2016 the Nordic Societies of Public Health.

Evaluating the effect of internal aperture variability on transport in kilometer scale discrete fracture networks

DOE PAGES

Makedonska, Nataliia; Hyman, Jeffrey D.; Karra, Satish; ...

2016-08-01

The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale fracture networks has been under debate for a long time, since the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We addressmore » this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P 32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. The recently developed discrete fracture network (DFN) simulation capability, dfnWorks, is used to generate kilometer scale DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time, , and cumulative retention, , are calculated along particles streamlines. As a result, it is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture aperture variability than the tails of travel time distributions, where no significant effect of the in-fracture aperture variations and spatial correlation length is observed.« less

Evaluating the effect of internal aperture variability on transport in kilometer scale discrete fracture networks

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

Makedonska, Nataliia; Hyman, Jeffrey D.; Karra, Satish

The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale fracture networks has been under debate for a long time, since the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We addressmore » this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P 32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. The recently developed discrete fracture network (DFN) simulation capability, dfnWorks, is used to generate kilometer scale DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time, , and cumulative retention, , are calculated along particles streamlines. As a result, it is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture aperture variability than the tails of travel time distributions, where no significant effect of the in-fracture aperture variations and spatial correlation length is observed.« less

Birth Spacing and Sibling Outcomes

ERIC Educational Resources Information Center

Buckles, Kasey S.; Munnich, Elizabeth L.

2012-01-01

Using the NLSY79 and NLSY79 Child and Young Adult Surveys, we investigate the effect of the age difference between siblings (spacing) on educational achievement. Because spacing may be endogenous, we use an instrumental variables strategy that exploits variation in spacing driven by miscarriages. The IV results indicate that a one-year increase in…

VARIATION OF THE EXPRESSION OF ENDOGENOUS "HOUSEKEEPING" GENES IN B[A]P TREATED MOUSE LUNGS MEASURED BY qRT-PCR

EPA Science Inventory

Quantitative RT-PCR is frequently used to analyze gene expression in different experimental systems. In this assay, housekeeping genes are frequently used to normalize for the variability between samples (relative quantification). We have examined the utility of using qRT-PCR and...

Organizational Commitment of Teachers in Urban Schools: Examining the Effects of Team Structures

ERIC Educational Resources Information Center

Dee, Jay R.; Henkin, Alan B.; Singleton, Carole A.

2006-01-01

This study examines the effects of four team-based structures on the organizational commitment of elementary teachers in an urban school district. The study model focuses on organizational commitment and includes three intervening, endogenous variables: teacher empowerment, school communication, and work autonomy. Team teaching had both direct and…

Properties of Endogenous Post-Stratified Estimation using remote sensing data

Treesearch

John Tipton; Jean Opsomer; Gretchen Moisen

2013-01-01

Post-stratification is commonly used to improve the precision of survey estimates. In traditional poststratification methods, the stratification variable must be known at the population level. When suitable covariates are available at the population level, an alternative approach consists of fitting a model on the covariates, making predictions for the population and...

Athletics, Athletic Leadership, and Academic Achievement

ERIC Educational Resources Information Center

Yeung, Ryan

2015-01-01

This study examines the relationship between athletics, athletic leadership, and academic achievement. This is likely to be a tricky issue as athletes and athletic leaders are not likely to be a random group of students. To address this issue I control for school fixed effects and instrument the endogenous variables with height. I find that…

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors.

PubMed

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-04-16

Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. © 2015 by Kerman University of Medical Sciences.

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors

PubMed Central

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-01-01

Background: Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods: Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education, residence in metropolitan areas, and so on). As the results of the Wald test carried out after the estimations did not allow to reject the null hypothesis of endogeneity, a probit model was run too. Results: Overall, women tend to develop depression more frequently than men. There is an inverse effect of education on depressed mood (probability of -24.6% to report a depressed mood due to high school education, as it emerges from the probit model marginal effects), while marital status and the number of family members may act as protective factors (probability to report a depressed mood of -1.0% for each family member). Depression is significantly associated with socio-economic conditions, such as work and income. Living in metropolitan areas is inversely correlated with depression (probability of -4.1% to report a depressed mood estimated through the probit model): this could be explained considering that, in rural areas, people rarely have immediate access to high-quality health services. Conclusion: This study outlines the factors that are more likely to impact on depression, and applies an IVP model to take into account the potential endogeneity of some of the predictors of depressive mood, such as female participation to workforce and health status. A probit model has been estimated too. Depression is associated with a wide range of socio-economic factors, although the strength and direction of the association can differ by gender. Prevention approaches to contrast depressive symptoms might take into consideration the evidence offered by the present study. PMID:26340392

Biases in the subjective timing of perceptual events: Libet et al. (1983) revisited.

PubMed

Danquah, Adam N; Farrell, Martin J; O'Boyle, Donald J

2008-09-01

We report two experiments in which participants had to judge the time of occurrence of a stimulus relative to a clock. The experiments were based on the control condition used by Libet, Gleason, Wright, and Pearl [Libet, B., Gleason, C. A., Wright, E. W., & Pearl, D. K. (1983). Time of conscious intention to act in relation to onset of cerebral activities (readiness-potential): The unconscious initiation of a freely voluntary act. Brain 106, 623-642] to correct for any bias in the estimation of the time at which an endogenous event, the conscious intention to perform a movement, occurred. Participants' responses were affected systematically by the sensory modality of the stimulus and by the speed of the clock. Such findings demonstrate the variability in judging the time at which an exogenous event occurs and, by extension, suggest that such variability may also apply to the judging the time of occurrence of endogenous events. The reliability of participants' estimations of when they formed the conscious intention to perform a movement in Libet et al.'s (1983) study is therefore questionable.

Confounding factors in determining causal soil moisture-precipitation feedback

NASA Astrophysics Data System (ADS)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

Encoding dependence in Bayesian causal networks

USDA-ARS?s Scientific Manuscript database

Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...

17 CFR 270.6e-3(T) - Temporary exemptions for flexible premium variable life insurance separate accounts.

Code of Federal Regulations, 2012 CFR

2012-04-01

... contracts, including, but not limited to, premium rate structure and premium processing, insurance... discrete cash values that may vary in amount in accordance with the investment experience of the separate...

17 CFR 270.6e-3(T) - Temporary exemptions for flexible premium variable life insurance separate accounts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... contracts, including, but not limited to, premium rate structure and premium processing, insurance... discrete cash values that may vary in amount in accordance with the investment experience of the separate...

17 CFR 270.6e-3(T) - Temporary exemptions for flexible premium variable life insurance separate accounts.

Code of Federal Regulations, 2014 CFR

2014-04-01

... contracts, including, but not limited to, premium rate structure and premium processing, insurance... discrete cash values that may vary in amount in accordance with the investment experience of the separate...

17 CFR 270.6e-3(T) - Temporary exemptions for flexible premium variable life insurance separate accounts.

Code of Federal Regulations, 2013 CFR

2013-04-01

... contracts, including, but not limited to, premium rate structure and premium processing, insurance... discrete cash values that may vary in amount in accordance with the investment experience of the separate...

17 CFR 270.6e-3(T) - Temporary exemptions for flexible premium variable life insurance separate accounts.

Code of Federal Regulations, 2011 CFR

2011-04-01

... contracts, including, but not limited to, premium rate structure and premium processing, insurance... discrete cash values that may vary in amount in accordance with the investment experience of the separate...

NEPTUNE'S DYNAMIC ATMOSPHERE FROM KEPLER K2 OBSERVATIONS: IMPLICATIONS FOR BROWN DWARF LIGHT CURVE ANALYSES.

PubMed

Simon, Amy A; Rowe, Jason F; Gaulme, Patrick; Hammel, Heidi B; Casewell, Sarah L; Fortney, Jonathan J; Gizis, John E; Lissauer, Jack J; Morales-Juberias, Raul; Orton, Glenn S; Wong, Michael H; Marley, Mark S

2016-02-01

Observations of Neptune with the Kepler Space Telescope yield a 49 day light curve with 98% coverage at a 1 minute cadence. A significant signature in the light curve comes from discrete cloud features. We compare results extracted from the light curve data with contemporaneous disk-resolved imaging of Neptune from the Keck 10-m telescope at 1.65 microns and Hubble Space Telescope visible imaging acquired nine months later. This direct comparison validates the feature latitudes assigned to the K2 light curve periods based on Neptune's zonal wind profile, and confirms observed cloud feature variability. Although Neptune's clouds vary in location and intensity on short and long timescales, a single large discrete storm seen in Keck imaging dominates the K2 and Hubble light curves; smaller or fainter clouds likely contribute to short-term brightness variability. The K2 Neptune light curve, in conjunction with our imaging data, provides context for the interpretation of current and future brown dwarf and extrasolar planet variability measurements. In particular we suggest that the balance between large, relatively stable, atmospheric features and smaller, more transient, clouds controls the character of substellar atmospheric variability. Atmospheres dominated by a few large spots may show inherently greater light curve stability than those which exhibit a greater number of smaller features.

Coexistence of unlimited bipartite and genuine multipartite entanglement: Promiscuous quantum correlations arising from discrete to continuous-variable systems

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

Adesso, Gerardo; CNR-INFM Coherentia , Naples; Grup d'Informacio Quantica, Universitat Autonoma de Barcelona, E-08193 Bellaterra

2007-08-15

Quantum mechanics imposes 'monogamy' constraints on the sharing of entanglement. We show that, despite these limitations, entanglement can be fully 'promiscuous', i.e., simultaneously present in unlimited two-body and many-body forms in states living in an infinite-dimensional Hilbert space. Monogamy just bounds the divergence rate of the various entanglement contributions. This is demonstrated in simple families of N-mode (N{>=}4) Gaussian states of light fields or atomic ensembles, which therefore enable infinitely more freedom in the distribution of information, as opposed to systems of individual qubits. Such a finding is of importance for the quantification, understanding, and potential exploitation of shared quantummore » correlations in continuous variable systems. We discuss how promiscuity gradually arises when considering simple families of discrete variable states, with increasing Hilbert space dimension towards the continuous variable limit. Such models are somehow analogous to Gaussian states with asymptotically diverging, but finite, squeezing. In this respect, we find that non-Gaussian states (which in general are more entangled than Gaussian states) exhibit also the interesting feature that their entanglement is more shareable: in the non-Gaussian multipartite arena, unlimited promiscuity can be already achieved among three entangled parties, while this is impossible for Gaussian, even infinitely squeezed states.« less

Genotyping of feline leukemia virus in Mexican housecats.

PubMed

Ramírez, Hugo; Autran, Marcela; García, M Martha; Carmona, M Ángel; Rodríguez, Cecilia; Martínez, H Alejandro

2016-04-01

Feline leukemia virus (FeLV) is a retrovirus with variable rates of infection globally. DNA was obtained from cats' peripheral blood mononuclear cells, and proviral DNA of pol and env genes was detected using PCR. Seventy-six percent of cats scored positive for FeLV using env-PCR; and 54 %, by pol-PCR. Phylogenetic analysis of both regions identified sequences that correspond to a group that includes endogenous retroviruses. They form an independent branch and, therefore, a new group of endogenous viruses. Cat gender, age, outdoor access, and cohabitation with other cats were found to be significant risk factors associated with the disease. This strongly suggests that these FeLV genotypes are widely distributed in the studied feline population in Mexico.

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

USGS Publications Warehouse

Muller, Benjamin J.; Cade, Brian S.; Schwarzkoph, Lin

2018-01-01

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads (Rhinella marina) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

Modelling discrete choice variables in assessment of teaching staff work satisfaction.

PubMed

Mieilă, Mihai; Popescu, Constanţa; Tudorache, Ana-Maria; Toplicianu, Valerică

2015-01-01

Levels of self-reported job satisfaction and motivation were measured by survey in a sample of 286 teachers. Using the discrete choice framework, the paper tries to assess the relevance of the considered indicators (demographic, social, motivational) in overall teaching work satisfaction. The findings provide evidence that job satisfaction is correlated significantly with level of university degree held by the teacher, type of secondary school where the teacher is enrolled, revenues, and salary-tasks adequacy. This is important for the Romanian economy, since the education system is expected to provide future human resources with enhanced skills and abilities.

Modelling Discrete Choice Variables in Assessment of Teaching Staff Work Satisfaction

PubMed Central

2015-01-01

Levels of self-reported job satisfaction and motivation were measured by survey in a sample of 286 teachers. Using the discrete choice framework, the paper tries to assess the relevance of the considered indicators (demographic, social, motivational) in overall teaching work satisfaction. The findings provide evidence that job satisfaction is correlated significantly with level of university degree held by the teacher, type of secondary school where the teacher is enrolled, revenues, and salary-tasks adequacy. This is important for the Romanian economy, since the education system is expected to provide future human resources with enhanced skills and abilities. PMID:25849295

Discrete-Event Simulation Models of Plasmodium falciparum Malaria

PubMed Central

McKenzie, F. Ellis; Wong, Roger C.; Bossert, William H.

2008-01-01

We develop discrete-event simulation models using a single “timeline” variable to represent the Plasmodium falciparum lifecycle in individual hosts and vectors within interacting host and vector populations. Where they are comparable our conclusions regarding the relative importance of vector mortality and the durations of host immunity and parasite development are congruent with those of classic differential-equation models of malaria, epidemiology. However, our results also imply that in regions with intense perennial transmission, the influence of mosquito mortality on malaria prevalence in humans may be rivaled by that of the duration of host infectivity. PMID:18668185

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

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

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

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

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Electro-impulse de-icing electrodynamic solution by discrete elements

NASA Technical Reports Server (NTRS)

Bernhart, W. D.; Schrag, R. L.

1988-01-01

This paper describes a technique for analyzing the electrodynamic phenomena associated with electro-impulse deicing. The analysis is done in the time domain and utilizes a discrete element formulation concept expressed in state variable form. Calculated results include coil current, eddy currents in the target (aircraft leading edge skin), pressure distribution on the target, and total force and impulse on the target. Typical results are presented and described. Some comparisons are made between calculated and experimental results, and also between calculated values from other theoretical approaches. Application to the problem of a nonrigid target is treated briefly.

Conservation of wave action. [in discrete oscillating system

NASA Technical Reports Server (NTRS)

Hayes, W. D.

1974-01-01

It is pointed out that two basic principles appear in the theory of wave propagation, including the existence of a phase variable and a law governing the intensity, in terms of a conservation law. The concepts underlying such a conservation law are explored. The waves treated are conservative in the sense that they obey equations derivable from a variational principle applied to a Lagrangian functional. A discrete oscillating system is considered. The approach employed also permits in a natural way the definition of a local action density and flux in problems in which the waves are modal or general.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Achieving a physiological cortisol profile with once-daily dual-release hydrocortisone: a pharmacokinetic study

PubMed Central

Lennernäs, Hans; Marelli, Claudio; Rockich, Kevin; Skrtic, Stanko

2016-01-01

Objective Oral once-daily dual-release hydrocortisone (DR-HC) replacement therapy was developed to provide a cortisol exposure−time profile that closely resembles the physiological cortisol profile. This study aimed to characterize single-dose pharmacokinetics (PK) of DR-HC 5–20mg and assess intrasubject variability. Methods Thirty-one healthy Japanese or non-Hispanic Caucasian volunteers aged 20−55 years participated in this randomized, open-label, PK study. Single doses of DR-HC 5, 15 (3×5), and 20mg were administered orally after an overnight fast and suppression of endogenous cortisol secretion. After estimating the endogenous cortisol profile, PK of DR-HC over 24h were evaluated to assess dose proportionality and impact of ethnicity. Plasma cortisol concentrations were analyzed using liquid chromatography−tandem mass spectrometry. PK parameters were calculated from individual cortisol concentration−time profiles. Results DR-HC 20mg provided higher than endogenous cortisol plasma concentrations 0−4h post-dose but similar concentrations later in the profile. Cortisol concentrations and PK exposure parameters increased with increasing doses. Mean maximal serum concentration (Cmax) was 82.0 and 178.1ng/mL, while mean area under the concentration−time curve (AUC)0−∞ was 562.8 and 1180.8h×ng/mL with DR-HC 5 and 20mg respectively. Within-subject PK variability was low (<15%) for DR-HC 20mg. All exposure PK parameters were less than dose proportional (slope <1). PK differences between ethnicities were explained by body weight differences. Conclusions DR-HC replacement resembles the daily normal cortisol profile. Within-subject day-to-day PK variability was low, underpinning the safety of DR-HC for replacement therapy. DR-HC PK were less than dose proportional – an important consideration when managing intercurrent illness in patients with adrenal insufficiency. PMID:27129362

Algorithms for Maneuvering Spacecraft Around Small Bodies

NASA Technical Reports Server (NTRS)

Acikmese, A. Bechet; Bayard, David

2006-01-01

A document describes mathematical derivations and applications of autonomous guidance algorithms for maneuvering spacecraft in the vicinities of small astronomical bodies like comets or asteroids. These algorithms compute fuel- or energy-optimal trajectories for typical maneuvers by solving the associated optimal-control problems with relevant control and state constraints. In the derivations, these problems are converted from their original continuous (infinite-dimensional) forms to finite-dimensional forms through (1) discretization of the time axis and (2) spectral discretization of control inputs via a finite number of Chebyshev basis functions. In these doubly discretized problems, the Chebyshev coefficients are the variables. These problems are, variously, either convex programming problems or programming problems that can be convexified. The resulting discrete problems are convex parameter-optimization problems; this is desirable because one can take advantage of very efficient and robust algorithms that have been developed previously and are well established for solving such problems. These algorithms are fast, do not require initial guesses, and always converge to global optima. Following the derivations, the algorithms are demonstrated by applying them to numerical examples of flyby, descent-to-hover, and ascent-from-hover maneuvers.

Optimal control of a hybrid rhythmic-discrete task: the bouncing ball revisited.

PubMed

Ronsse, Renaud; Wei, Kunlin; Sternad, Dagmar

2010-05-01

Rhythmically bouncing a ball with a racket is a hybrid task that combines continuous rhythmic actuation of the racket with the control of discrete impact events between racket and ball. This study presents experimental data and a two-layered modeling framework that explicitly addresses the hybrid nature of control: a first discrete layer calculates the state to reach at impact and the second continuous layer smoothly drives the racket to this desired state, based on optimality principles. The testbed for this hybrid model is task performance at a range of increasingly slower tempos. When slowing the rhythm of the bouncing actions, the continuous cycles become separated into a sequence of discrete movements interspersed by dwell times and directed to achieve the desired impact. Analyses of human performance show increasing variability of performance measures with slower tempi, associated with a change in racket trajectories from approximately sinusoidal to less symmetrical velocity profiles. Matching results of model simulations give support to a hybrid control model based on optimality, and therefore suggest that optimality principles are applicable to the sensorimotor control of complex movements such as ball bouncing.

Electrical Connector Mechanical Seating Sensor

NASA Technical Reports Server (NTRS)

Arens, Ellen; Captain, Janine; Youngquist, Robert

2011-01-01

A sensor provides a measurement of the degree of seating of an electrical connector. This sensor provides a number of discrete distances that a plug is inserted into a socket or receptacle. The number of measurements is equal to the number of pins available in the connector for sensing. On at least two occasions, the Shuttle Program has suffered serious time delays and incurred excessive costs simply because a plug was not seated well within a receptacle. Two methods were designed to address this problem: (1) the resistive pin technique and (2) the discrete length pins technique. In the resistive pin approach, a standard pin in a male connector is replaced with a pin that has a uniform resistivity along its length. This provides a variable resistance on that pin that is dependent on how far the pin is inserted into a socket. This is essentially a linear potentiometer. The discrete approach uses a pin (or a few pins) in the connector as a displacement indicator by truncating the pin length so it sits shorter in the connector than the other pins. A loss of signal on this pin would indicate a discrete amount of displacement of the connector. This approach would only give discrete values of connector displacement, and at least one pin would be needed for each displacement value that would be of interest.

Stochastic thermodynamics across scales: Emergent inter-attractoral discrete Markov jump process and its underlying continuous diffusion

NASA Astrophysics Data System (ADS)

Santillán, Moisés; Qian, Hong

2013-01-01

We investigate the internal consistency of a recently developed mathematical thermodynamic structure across scales, between a continuous stochastic nonlinear dynamical system, i.e., a diffusion process with Langevin and Fokker-Planck equations, and its emergent discrete, inter-attractoral Markov jump process. We analyze how the system’s thermodynamic state functions, e.g. free energy F, entropy S, entropy production ep, free energy dissipation Ḟ, etc., are related when the continuous system is described with coarse-grained discrete variables. It is shown that the thermodynamics derived from the underlying, detailed continuous dynamics gives rise to exactly the free-energy representation of Gibbs and Helmholtz. That is, the system’s thermodynamic structure is the same as if one only takes a middle road and starts with the natural discrete description, with the corresponding transition rates empirically determined. By natural we mean in the thermodynamic limit of a large system, with an inherent separation of time scales between inter- and intra-attractoral dynamics. This result generalizes a fundamental idea from chemistry, and the theory of Kramers, by incorporating thermodynamics: while a mechanical description of a molecule is in terms of continuous bond lengths and angles, chemical reactions are phenomenologically described by a discrete representation, in terms of exponential rate laws and a stochastic thermodynamics.

Relocalization of STIM1 in mouse oocytes at fertilization: early involvement of store-operated calcium entry.

PubMed

Gómez-Fernández, Carolina; Pozo-Guisado, Eulalia; Gañán-Parra, Miguel; Perianes, Mario J; Alvarez, Ignacio S; Martín-Romero, Francisco Javier

2009-08-01

Calcium waves represent one of the most important intracellular signaling events in oocytes at fertilization required for the exit from metaphase arrest and the resumption of the cell cycle. The molecular mechanism ruling this signaling has been described in terms of the contribution of intracellular calcium stores to calcium spikes. In this work, we considered the possible contribution of store-operated calcium entry (SOCE) to this signaling, by studying the localization of the protein STIM1 in oocytes. STIM1 has been suggested to play a key role in the recruitment and activation of plasma membrane calcium channels, and we show here that mature mouse oocytes express this protein distributed in discrete clusters throughout their periphery in resting cells, colocalizing with the endoplasmic reticulum marker calreticulin. However, immunolocalization of the endogenous STIM1 showed considerable redistribution over larger areas or patches covering the entire periphery of the oocyte during Ca(2+) store depletion induced with thapsigargin or ionomycin. Furthermore, pharmacological activation of endogenous phospholipase C induced a similar pattern of redistribution of STIM1 in the oocyte. Finally, fertilization of mouse oocytes revealed a significant and rapid relocalization of STIM1, similar to that found after pharmacological Ca(2+) store depletion. This particular relocalization supports a role for STIM1 and SOCE in the calcium signaling during early stages of fertilization.

The importance of individual frequencies of endogenous brain oscillations for auditory cognition - A short review.

PubMed

Baltus, Alina; Herrmann, Christoph Siegfried

2016-06-01

Oscillatory EEG activity in the human brain with frequencies in the gamma range (approx. 30-80Hz) is known to be relevant for a large number of cognitive processes. Interestingly, each subject reveals an individual frequency of the auditory gamma-band response (GBR) that coincides with the peak in the auditory steady state response (ASSR). A common resonance frequency of auditory cortex seems to underlie both the individual frequency of the GBR and the peak of the ASSR. This review sheds light on the functional role of oscillatory gamma activity for auditory processing. For successful processing, the auditory system has to track changes in auditory input over time and store information about past events in memory which allows the construction of auditory objects. Recent findings support the idea of gamma oscillations being involved in the partitioning of auditory input into discrete samples to facilitate higher order processing. We review experiments that seem to suggest that inter-individual differences in the resonance frequency are behaviorally relevant for gap detection and speech processing. A possible application of these resonance frequencies for brain computer interfaces is illustrated with regard to optimized individual presentation rates for auditory input to correspond with endogenous oscillatory activity. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

Long-distance continuous-variable quantum key distribution by controlling excess noise

NASA Astrophysics Data System (ADS)

Huang, Duan; Huang, Peng; Lin, Dakai; Zeng, Guihua

2016-01-01

Quantum cryptography founded on the laws of physics could revolutionize the way in which communication information is protected. Significant progresses in long-distance quantum key distribution based on discrete variables have led to the secure quantum communication in real-world conditions being available. However, the alternative approach implemented with continuous variables has not yet reached the secure distance beyond 100 km. Here, we overcome the previous range limitation by controlling system excess noise and report such a long distance continuous-variable quantum key distribution experiment. Our result paves the road to the large-scale secure quantum communication with continuous variables and serves as a stepping stone in the quest for quantum network.

Long-distance continuous-variable quantum key distribution by controlling excess noise.

PubMed

Huang, Duan; Huang, Peng; Lin, Dakai; Zeng, Guihua

2016-01-13

Quantum cryptography founded on the laws of physics could revolutionize the way in which communication information is protected. Significant progresses in long-distance quantum key distribution based on discrete variables have led to the secure quantum communication in real-world conditions being available. However, the alternative approach implemented with continuous variables has not yet reached the secure distance beyond 100 km. Here, we overcome the previous range limitation by controlling system excess noise and report such a long distance continuous-variable quantum key distribution experiment. Our result paves the road to the large-scale secure quantum communication with continuous variables and serves as a stepping stone in the quest for quantum network.

Long-distance continuous-variable quantum key distribution by controlling excess noise

PubMed Central

Huang, Duan; Huang, Peng; Lin, Dakai; Zeng, Guihua

2016-01-01

Quantum cryptography founded on the laws of physics could revolutionize the way in which communication information is protected. Significant progresses in long-distance quantum key distribution based on discrete variables have led to the secure quantum communication in real-world conditions being available. However, the alternative approach implemented with continuous variables has not yet reached the secure distance beyond 100 km. Here, we overcome the previous range limitation by controlling system excess noise and report such a long distance continuous-variable quantum key distribution experiment. Our result paves the road to the large-scale secure quantum communication with continuous variables and serves as a stepping stone in the quest for quantum network. PMID:26758727

Possible Origin of Stagnation and Variability of Earth's Biodiversity

NASA Astrophysics Data System (ADS)

Stollmeier, Frank; Geisel, Theo; Nagler, Jan

2014-06-01

The magnitude and variability of Earth's biodiversity have puzzled scientists ever since paleontologic fossil databases became available. We identify and study a model of interdependent species where both endogenous and exogenous impacts determine the nonstationary extinction dynamics. The framework provides an explanation for the qualitative difference of marine and continental biodiversity growth. In particular, the stagnation of marine biodiversity may result from a global transition from an imbalanced to a balanced state of the species dependency network. The predictions of our framework are in agreement with paleontologic databases.

Comparative estrogenicity of endogenous, environmental and dietary estrogens in pregnant women I: Serum levels, variability and the basis for urinary biomonitoring of serum estrogenicity

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

Fleck, Stefanie C.; Twaddle, Nathan C.; Churchwell, Mona I.

Biomonitoring of human exposure to estrogens most frequently focuses on environmental and dietary estrogens, and infrequently includes measures of exposure to potent endogenous estrogens present in serum. Pregnancy is a developmentally sensitive period during which “added” serum estrogenicity exceeding normal intra-individual daily variability may be of particular relevance. Here, we made repeated measurements of serum concentrations of estrone (E1), estradiol (E2), estriol (E3), estetrol (E4), daidzein (DDZ), genistein (GEN) and bisphenol A (BPA) in thirty pregnant women using ultra-performance liquid chromatography coupled with tandem mass spectrometry detection (UPLC-MS/MS) and electrospray ionization (ESI). Serum E1, E2, and E3 concentrations varied significantlymore » (coefficients of variation 9–10%) with broad ranges across the cohort: 1.61–85.1 nM, 9.09–69.7 nM, and 1.5–36.3 nM respectively. BPA (undetected, estimated from total exposure), DDZ and GEN concentrations were 1-5 orders of magnitude lower. The 24-h urinary elimination profiles of endogenous estrogens were each strongly correlated with their corresponding serum concentrations (Pearson's Correlation Coefficients of 0.83 (E1), 0.84 (E2) and 0.94 (E3)). Lastly, a multivariate regression analysis produced equations for estimating serum concentrations of E1, E2, E3, E4, GEN and DDZ from urinary elimination rates and gestation period, an important step towards non-invasive biomonitoring for assessment of “added” estrogenicity during pregnancy.« less

Comparative estrogenicity of endogenous, environmental and dietary estrogens in pregnant women I: Serum levels, variability and the basis for urinary biomonitoring of serum estrogenicity

DOE PAGES

Fleck, Stefanie C.; Twaddle, Nathan C.; Churchwell, Mona I.; ...

2018-03-13

Biomonitoring of human exposure to estrogens most frequently focuses on environmental and dietary estrogens, and infrequently includes measures of exposure to potent endogenous estrogens present in serum. Pregnancy is a developmentally sensitive period during which “added” serum estrogenicity exceeding normal intra-individual daily variability may be of particular relevance. Here, we made repeated measurements of serum concentrations of estrone (E1), estradiol (E2), estriol (E3), estetrol (E4), daidzein (DDZ), genistein (GEN) and bisphenol A (BPA) in thirty pregnant women using ultra-performance liquid chromatography coupled with tandem mass spectrometry detection (UPLC-MS/MS) and electrospray ionization (ESI). Serum E1, E2, and E3 concentrations varied significantlymore » (coefficients of variation 9–10%) with broad ranges across the cohort: 1.61–85.1 nM, 9.09–69.7 nM, and 1.5–36.3 nM respectively. BPA (undetected, estimated from total exposure), DDZ and GEN concentrations were 1-5 orders of magnitude lower. The 24-h urinary elimination profiles of endogenous estrogens were each strongly correlated with their corresponding serum concentrations (Pearson's Correlation Coefficients of 0.83 (E1), 0.84 (E2) and 0.94 (E3)). Lastly, a multivariate regression analysis produced equations for estimating serum concentrations of E1, E2, E3, E4, GEN and DDZ from urinary elimination rates and gestation period, an important step towards non-invasive biomonitoring for assessment of “added” estrogenicity during pregnancy.« less

F8 haplotype and inhibitor risk: results from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort

PubMed Central

Schwarz, John; Astermark, Jan; Menius, Erika D.; Carrington, Mary; Donfield, Sharyne M.; Gomperts, Edward D.; Nelson, George W.; Oldenburg, Johannes; Pavlova, Anna; Shapiro, Amy D.; Winkler, Cheryl A.; Berntorp, Erik

2012-01-01

Background Ancestral background, specifically African descent, confers higher risk for development of inhibitory antibodies to factor VIII (FVIII) in hemophilia A. It has been suggested that differences in the distribution of factor VIII gene (F8) haplotypes, and mismatch between endogenous F8 haplotypes and those comprising products used for treatment could contribute to risk. Design and Methods Data from the HIGS Combined Cohort were used to determine the association between F8 haplotype 3 (H3) vs. haplotypes 1 and 2 (H1+H2) and inhibitor risk among individuals of genetically-determined African descent. Other variables known to affect inhibitor risk including type of F8 mutation and HLA were included in the analysis. A second research question regarding risk related to mismatch in endogenous F8 haplotype and recombinant FVIII products used for treatment was addressed. Results H3 was associated with higher inhibitor risk among those genetically-identified (N=49) as of African ancestry, but the association did not remain significant after adjustment for F8 mutation type and the HLA variables. Among subjects of all racial ancestries enrolled in HIGS who reported early use of recombinant products (N=223), mismatch in endogenous haplotype and the FVIII proteins constituting the products used did not confer greater risk for inhibitor development. Conclusion H3 was not an independent predictor of inhibitor risk. Further, our findings did not support a higher risk of inhibitors in the presence of a haplotype mismatch between the FVIII molecule infused and that of the individual. PMID:22958194

Enabling the extended compact genetic algorithm for real-parameter optimization by using adaptive discretization.

PubMed

Chen, Ying-ping; Chen, Chao-Hong

2010-01-01

An adaptive discretization method, called split-on-demand (SoD), enables estimation of distribution algorithms (EDAs) for discrete variables to solve continuous optimization problems. SoD randomly splits a continuous interval if the number of search points within the interval exceeds a threshold, which is decreased at every iteration. After the split operation, the nonempty intervals are assigned integer codes, and the search points are discretized accordingly. As an example of using SoD with EDAs, the integration of SoD and the extended compact genetic algorithm (ECGA) is presented and numerically examined. In this integration, we adopt a local search mechanism as an optional component of our back end optimization engine. As a result, the proposed framework can be considered as a memetic algorithm, and SoD can potentially be applied to other memetic algorithms. The numerical experiments consist of two parts: (1) a set of benchmark functions on which ECGA with SoD and ECGA with two well-known discretization methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH) are compared; (2) a real-world application, the economic dispatch problem, on which ECGA with SoD is compared to other methods. The experimental results indicate that SoD is a better discretization method to work with ECGA. Moreover, ECGA with SoD works quite well on the economic dispatch problem and delivers solutions better than the best known results obtained by other methods in existence.

Development of discrete gas kinetic scheme for simulation of 3D viscous incompressible and compressible flows

NASA Astrophysics Data System (ADS)

Yang, L. M.; Shu, C.; Wang, Y.; Sun, Y.

2016-08-01

The sphere function-based gas kinetic scheme (GKS), which was presented by Shu and his coworkers [23] for simulation of inviscid compressible flows, is extended to simulate 3D viscous incompressible and compressible flows in this work. Firstly, we use certain discrete points to represent the spherical surface in the phase velocity space. Then, integrals along the spherical surface for conservation forms of moments, which are needed to recover 3D Navier-Stokes equations, are approximated by integral quadrature. The basic requirement is that these conservation forms of moments can be exactly satisfied by weighted summation of distribution functions at discrete points. It was found that the integral quadrature by eight discrete points on the spherical surface, which forms the D3Q8 discrete velocity model, can exactly match the integral. In this way, the conservative variables and numerical fluxes can be computed by weighted summation of distribution functions at eight discrete points. That is, the application of complicated formulations resultant from integrals can be replaced by a simple solution process. Several numerical examples including laminar flat plate boundary layer, 3D lid-driven cavity flow, steady flow through a 90° bending square duct, transonic flow around DPW-W1 wing and supersonic flow around NACA0012 airfoil are chosen to validate the proposed scheme. Numerical results demonstrate that the present scheme can provide reasonable numerical results for 3D viscous flows.

Development of a discrete gas-kinetic scheme for simulation of two-dimensional viscous incompressible and compressible flows.

PubMed

Yang, L M; Shu, C; Wang, Y

2016-03-01

In this work, a discrete gas-kinetic scheme (DGKS) is presented for simulation of two-dimensional viscous incompressible and compressible flows. This scheme is developed from the circular function-based GKS, which was recently proposed by Shu and his co-workers [L. M. Yang, C. Shu, and J. Wu, J. Comput. Phys. 274, 611 (2014)]. For the circular function-based GKS, the integrals for conservation forms of moments in the infinity domain for the Maxwellian function-based GKS are simplified to those integrals along the circle. As a result, the explicit formulations of conservative variables and fluxes are derived. However, these explicit formulations of circular function-based GKS for viscous flows are still complicated, which may not be easy for the application by new users. By using certain discrete points to represent the circle in the phase velocity space, the complicated formulations can be replaced by a simple solution process. The basic requirement is that the conservation forms of moments for the circular function-based GKS can be accurately satisfied by weighted summation of distribution functions at discrete points. In this work, it is shown that integral quadrature by four discrete points on the circle, which forms the D2Q4 discrete velocity model, can exactly match the integrals. Numerical results showed that the present scheme can provide accurate numerical results for incompressible and compressible viscous flows with roughly the same computational cost as that needed by the Roe scheme.

The coupling hypothesis: why genome scans may fail to map local adaptation genes.

PubMed

Bierne, Nicolas; Welch, John; Loire, Etienne; Bonhomme, François; David, Patrice

2011-05-01

Genomic scans of multiple populations often reveal marker loci with greatly increased differentiation between populations. Often this differentiation coincides in space with contrasts in ecological factors, forming a genetic-environment association (GEA). GEAs imply a role for local adaptation, and so it is tempting to conclude that the strongly differentiated markers are themselves under ecologically based divergent selection, or are closely linked to loci under such selection. Here, we highlight an alternative and neglected explanation: intrinsic (i.e. environment-independent) pre- or post-zygotic genetic incompatibilities rather than local adaptation can be responsible for increased differentiation. Intrinsic genetic incompatibilities create endogenous barriers to gene flow, also known as tension zones, whose location can shift over time. However, tension zones have a tendency to become trapped by, and therefore to coincide with, exogenous barriers due to ecological selection. This coupling of endogenous and exogenous barriers can occur easily in spatially subdivided populations, even if the loci involved are unlinked. The result is that local adaptation explains where genetic breaks are positioned, but not necessarily their existence, which can be best explained by endogenous incompatibilities. More precisely, we show that (i) the coupling of endogenous and exogenous barriers can easily occur even when ecological selection is weak; (ii) when environmental heterogeneity is fine-grained, GEAs can emerge at incompatibility loci, but only locally, in places where habitats and gene pools are sufficiently intermingled to maintain linkage disequilibria between genetic incompatibilities, local-adaptation genes and neutral loci. Furthermore, the association between the locally adapted and intrinsically incompatible alleles (i.e. the sign of linkage disequilibrium between endogenous and exogenous loci) is arbitrary and can form in either direction. Reviewing results from the literature, we find that many predictions of our model are supported, including endogenous genetic barriers that coincide with environmental boundaries, local GEA in mosaic hybrid zones, and inverted or modified GEAs at distant locations. We argue that endogenous genetic barriers are often more likely than local adaptation to explain the majority of Fst-outlying loci observed in genome scan approaches - even when these are correlated to environmental variables. © 2011 Blackwell Publishing Ltd.

Free Vibrations of Nonthin Elliptic Cylindrical Shells of Variable Thickness

NASA Astrophysics Data System (ADS)

Grigorenko, A. Ya.; Efimova, T. L.; Korotkikh, Yu. A.

2017-11-01

The problem of the free vibrations of nonthin elliptic cylindrical shells of variable thickness under various boundary conditions is solved using the refined Timoshenko-Mindlin theory. To solve the problem, an effective numerical approach based on the spline-approximation and discrete-orthogonalization methods is used. The effect of the cross-sectional shape, thickness variation law, material properties, and boundary conditions on the natural frequency spectrum of the shells is analyzed.

Significance of the impact of motion compensation on the variability of PET image features

NASA Astrophysics Data System (ADS)

Carles, M.; Bach, T.; Torres-Espallardo, I.; Baltas, D.; Nestle, U.; Martí-Bonmatí, L.

2018-03-01

In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40% of SUVmax and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40% contours, despite the values not being interchangeable, all image features showed strong linear correlations (r  >  0.91, p\\ll 0.001 ). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the compensation of tumor motion did not have a significant impact on the quantitative PET parameters. The variability of PET parameters due to voxel size in image reconstruction was more significant than variability due to voxel size in image post-resampling. In conclusion, most of the parameters (apart from the contrast of neighborhood matrix) were robust to the motion compensation implied by 4D-PET/CT. The impact on parameter variability due to the voxel size in image reconstruction and in image post-resampling could not be assumed to be equivalent.

Dynamic mortar finite element method for modeling of shear rupture on frictional rough surfaces

NASA Astrophysics Data System (ADS)

Tal, Yuval; Hager, Bradford H.

2017-09-01

This paper presents a mortar-based finite element formulation for modeling the dynamics of shear rupture on rough interfaces governed by slip-weakening and rate and state (RS) friction laws, focusing on the dynamics of earthquakes. The method utilizes the dual Lagrange multipliers and the primal-dual active set strategy concepts, together with a consistent discretization and linearization of the contact forces and constraints, and the friction laws to obtain a semi-smooth Newton method. The discretization of the RS friction law involves a procedure to condense out the state variables, thus eliminating the addition of another set of unknowns into the system. Several numerical examples of shear rupture on frictional rough interfaces demonstrate the efficiency of the method and examine the effects of the different time discretization schemes on the convergence, energy conservation, and the time evolution of shear traction and slip rate.

Pseudo spectral collocation with Maxwell polynomials for kinetic equations with energy diffusion

NASA Astrophysics Data System (ADS)

Sánchez-Vizuet, Tonatiuh; Cerfon, Antoine J.

2018-02-01

We study the approximation and stability properties of a recently popularized discretization strategy for the speed variable in kinetic equations, based on pseudo-spectral collocation on a grid defined by the zeros of a non-standard family of orthogonal polynomials called Maxwell polynomials. Taking a one-dimensional equation describing energy diffusion due to Fokker-Planck collisions with a Maxwell-Boltzmann background distribution as the test bench for the performance of the scheme, we find that Maxwell based discretizations outperform other commonly used schemes in most situations, often by orders of magnitude. This provides a strong motivation for their use in high-dimensional gyrokinetic simulations. However, we also show that Maxwell based schemes are subject to a non-modal time stepping instability in their most straightforward implementation, so that special care must be given to the discrete representation of the linear operators in order to benefit from the advantages provided by Maxwell polynomials.

Discrete Adjoint-Based Design for Unsteady Turbulent Flows On Dynamic Overset Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Diskin, Boris

2012-01-01

A discrete adjoint-based design methodology for unsteady turbulent flows on three-dimensional dynamic overset unstructured grids is formulated, implemented, and verified. The methodology supports both compressible and incompressible flows and is amenable to massively parallel computing environments. The approach provides a general framework for performing highly efficient and discretely consistent sensitivity analysis for problems involving arbitrary combinations of overset unstructured grids which may be static, undergoing rigid or deforming motions, or any combination thereof. General parent-child motions are also accommodated, and the accuracy of the implementation is established using an independent verification based on a complex-variable approach. The methodology is used to demonstrate aerodynamic optimizations of a wind turbine geometry, a biologically-inspired flapping wing, and a complex helicopter configuration subject to trimming constraints. The objective function for each problem is successfully reduced and all specified constraints are satisfied.

Solving ill-posed control problems by stabilized finite element methods: an alternative to Tikhonov regularization

NASA Astrophysics Data System (ADS)

Burman, Erik; Hansbo, Peter; Larson, Mats G.

2018-03-01

Tikhonov regularization is one of the most commonly used methods for the regularization of ill-posed problems. In the setting of finite element solutions of elliptic partial differential control problems, Tikhonov regularization amounts to adding suitably weighted least squares terms of the control variable, or derivatives thereof, to the Lagrangian determining the optimality system. In this note we show that the stabilization methods for discretely ill-posed problems developed in the setting of convection-dominated convection-diffusion problems, can be highly suitable for stabilizing optimal control problems, and that Tikhonov regularization will lead to less accurate discrete solutions. We consider some inverse problems for Poisson’s equation as an illustration and derive new error estimates both for the reconstruction of the solution from the measured data and reconstruction of the source term from the measured data. These estimates include both the effect of the discretization error and error in the measurements.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Dissecting components of population-level variation in seed production and the evolution of masting behavior.

Treesearch

W. D. Koenig; D. Kelly; V. L. Sork; R. P. Duncan; J. S. Elkinton; M.S. Peltonen; R. D. Westfall

2003-01-01

Mast-fruiting or masting behavior is the cumulative result of the reproductive patterns of individuals within a population and thus involves components of individual variability, between-individual synchrony, and endogenous cycles of temporal autocorrelation. Extending prior work by Herrera, we explore the interrelationships of these components using data on individual...

Effects of College Educational Debt on Graduate School Attendance and Early Career and Lifestyle Choices

ERIC Educational Resources Information Center

Zhang, Lei

2013-01-01

This paper examines how college educational debt affects various post-baccalaureate decisions of bachelor's degree recipients. I employ the Baccalaureate and Beyond 93/97 survey data. Using college-aid policies as instrumental variables to correct for the endogeneity of student college debt level, I find that for public college graduates, college…

Hybrid stochastic simplifications for multiscale gene networks

PubMed Central

Crudu, Alina; Debussche, Arnaud; Radulescu, Ovidiu

2009-01-01

Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion [1-3] which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach. PMID:19735554

Bayesian functional integral method for inferring continuous data from discrete measurements.

PubMed

Heuett, William J; Miller, Bernard V; Racette, Susan B; Holloszy, John O; Chow, Carson C; Periwal, Vipul

2012-02-08

Inference of the insulin secretion rate (ISR) from C-peptide measurements as a quantification of pancreatic β-cell function is clinically important in diseases related to reduced insulin sensitivity and insulin action. ISR derived from C-peptide concentration is an example of nonparametric Bayesian model selection where a proposed ISR time-course is considered to be a "model". An inferred value of inaccessible continuous variables from discrete observable data is often problematic in biology and medicine, because it is a priori unclear how robust the inference is to the deletion of data points, and a closely related question, how much smoothness or continuity the data actually support. Predictions weighted by the posterior distribution can be cast as functional integrals as used in statistical field theory. Functional integrals are generally difficult to evaluate, especially for nonanalytic constraints such as positivity of the estimated parameters. We propose a computationally tractable method that uses the exact solution of an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo evaluation of the posterior for the full model. As a concrete application of our method, we calculate the ISR from actual clinical C-peptide measurements in human subjects with varying degrees of insulin sensitivity. Our method demonstrates the feasibility of functional integral Bayesian model selection as a practical method for such data-driven inference, allowing the data to determine the smoothing timescale and the width of the prior probability distribution on the space of models. In particular, our model comparison method determines the discrete time-step for interpolation of the unobservable continuous variable that is supported by the data. Attempts to go to finer discrete time-steps lead to less likely models. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The effects of competition on premiums: using United Healthcare's 2015 entry into Affordable Care Act's marketplaces as an instrumental variable.

PubMed

Agirdas, Cagdas; Krebs, Robert J; Yano, Masato

2018-01-08

One goal of the Affordable Care Act is to increase insurance coverage by improving competition and lowering premiums. To facilitate this goal, the federal government enacted online marketplaces in the 395 rating areas spanning 34 states that chose not to establish their own state-run marketplaces. Few multivariate regression studies analyzing the effects of competition on premiums suffer from endogeneity, due to simultaneity and omitted variable biases. However, United Healthcare's decision to enter these marketplaces in 2015 provides the researcher with an opportunity to address this endogeneity problem. Exploiting the variation caused by United Healthcare's entry decision as an instrument for competition, we study the impact of competition on premiums during the first 2 years of these marketplaces. Combining panel data from five different sources and controlling for 12 variables, we find that one more insurer in a rating area leads to a 6.97% reduction in the second-lowest-priced silver plan premium, which is larger than the estimated effects in existing literature. Furthermore, we run a threshold analysis and find that competition's effects on premiums become statistically insignificant if there are four or more insurers in a rating area. These findings are robust to alternative measures of premiums, inclusion of a non-linear term in the regression models and a county-level analysis.

Sensitivity and diagnosticity of NASA-TLX and simplified SWAT to assess the mental workload associated with operating an agricultural sprayer.

PubMed

Dey, Asit; Mann, Danny D

2010-07-01

The objectives of the present study were: a) to investigate three continuous variants of the NASA-Task Load Index (TLX) (standard NASA (CNASA), average NASA (C1NASA) and principal component NASA (PCNASA)) and five different variants of the simplified subjective workload assessment technique (SSWAT) (continuous standard SSWAT (CSSWAT), continuous average SSWAT (C1SSWAT), continuous principal component SSWAT (PCSSWAT), discrete event-based SSWAT (D1SSWAT) and discrete standard SSWAT (DSSWAT)) in terms of their sensitivity and diagnosticity to assess the mental workload associated with agricultural spraying; b) to compare and select the best variants of NASA-TLX and SSWAT for future mental workload research in the agricultural domain. A total of 16 male university students (mean 30.4 +/- 12.5 years) participated in this study. All the participants were trained to drive an agricultural spraying simulator. Sensitivity was assessed by the ability of the scales to report the maximum change in workload ratings due to the change in illumination and difficulty levels. In addition, the factor loading method was used to quantify sensitivity. The diagnosticity was assessed by the ability of the scale to diagnose the change in task levels from single to dual. Among all the variants of NASA-TLX and SSWAT, PCNASA and discrete variants of SSWAT showed the highest sensitivity and diagnosticity. Moreover, among all the variants of NASA and SSWAT, the discrete variants of SSWAT showed the highest sensitivity and diagnosticity but also high between-subject variability. The continuous variants of both scales had relatively low sensitivity and diagnosticity and also low between-subject variability. Hence, when selecting a scale for future mental workload research in the agricultural domain, a researcher should decide what to compromise: 1) between-subject variability or 2) sensitivity and diagnosticity. STATEMENT OF RELEVANCE: The use of subjective workload scales is very popular in mental workload research. The present study investigated the different variants of two popular workload rating scales (i.e. NASA-TLX and SSWAT) in terms of their sensitivity and diagnositicity and selected the best variants of each scale for future mental workload research.

Review of literature on the finite-element solution of the equations of two-dimensional surface-water flow in the horizontal plane

USGS Publications Warehouse

Lee, Jonathan K.; Froehlich, David C.

1987-01-01

Published literature on the application of the finite-element method to solving the equations of two-dimensional surface-water flow in the horizontal plane is reviewed in this report. The finite-element method is ideally suited to modeling two-dimensional flow over complex topography with spatially variable resistance. A two-dimensional finite-element surface-water flow model with depth and vertically averaged velocity components as dependent variables allows the user great flexibility in defining geometric features such as the boundaries of a water body, channels, islands, dikes, and embankments. The following topics are reviewed in this report: alternative formulations of the equations of two-dimensional surface-water flow in the horizontal plane; basic concepts of the finite-element method; discretization of the flow domain and representation of the dependent flow variables; treatment of boundary conditions; discretization of the time domain; methods for modeling bottom, surface, and lateral stresses; approaches to solving systems of nonlinear equations; techniques for solving systems of linear equations; finite-element alternatives to Galerkin's method of weighted residuals; techniques of model validation; and preparation of model input data. References are listed in the final chapter.

An Algorithm for Integrated Subsystem Embodiment and System Synthesis

NASA Technical Reports Server (NTRS)

Lewis, Kemper

1997-01-01

Consider the statement,'A system has two coupled subsystems, one of which dominates the design process. Each subsystem consists of discrete and continuous variables, and is solved using sequential analysis and solution.' To address this type of statement in the design of complex systems, three steps are required, namely, the embodiment of the statement in terms of entities on a computer, the mathematical formulation of subsystem models, and the resulting solution and system synthesis. In complex system decomposition, the subsystems are not isolated, self-supporting entities. Information such as constraints, goals, and design variables may be shared between entities. But many times in engineering problems, full communication and cooperation does not exist, information is incomplete, or one subsystem may dominate the design. Additionally, these engineering problems give rise to mathematical models involving nonlinear functions of both discrete and continuous design variables. In this dissertation an algorithm is developed to handle these types of scenarios for the domain-independent integration of subsystem embodiment, coordination, and system synthesis using constructs from Decision-Based Design, Game Theory, and Multidisciplinary Design Optimization. Implementation of the concept in this dissertation involves testing of the hypotheses using example problems and a motivating case study involving the design of a subsonic passenger aircraft.

On-chip continuous-variable quantum entanglement

NASA Astrophysics Data System (ADS)

Masada, Genta; Furusawa, Akira

2016-09-01

Entanglement is an essential feature of quantum theory and the core of the majority of quantum information science and technologies. Quantum computing is one of the most important fruits of quantum entanglement and requires not only a bipartite entangled state but also more complicated multipartite entanglement. In previous experimental works to demonstrate various entanglement-based quantum information processing, light has been extensively used. Experiments utilizing such a complicated state need highly complex optical circuits to propagate optical beams and a high level of spatial interference between different light beams to generate quantum entanglement or to efficiently perform balanced homodyne measurement. Current experiments have been performed in conventional free-space optics with large numbers of optical components and a relatively large-sized optical setup. Therefore, they are limited in stability and scalability. Integrated photonics offer new tools and additional capabilities for manipulating light in quantum information technology. Owing to integrated waveguide circuits, it is possible to stabilize and miniaturize complex optical circuits and achieve high interference of light beams. The integrated circuits have been firstly developed for discrete-variable systems and then applied to continuous-variable systems. In this article, we review the currently developed scheme for generation and verification of continuous-variable quantum entanglement such as Einstein-Podolsky-Rosen beams using a photonic chip where waveguide circuits are integrated. This includes balanced homodyne measurement of a squeezed state of light. As a simple example, we also review an experiment for generating discrete-variable quantum entanglement using integrated waveguide circuits.

Family of columns isospectral to gravity-loaded columns with tip force: A discrete approach

NASA Astrophysics Data System (ADS)

Ramachandran, Nirmal; Ganguli, Ranjan

2018-06-01

A discrete model is introduced to analyze transverse vibration of straight, clamped-free (CF) columns of variable cross-sectional geometry under the influence of gravity and a constant axial force at the tip. The discrete model is used to determine critical combinations of loading parameters - a gravity parameter and a tip force parameter - that cause onset of dynamic instability in the CF column. A methodology, based on matrix-factorization, is described to transform the discrete model into a family of models corresponding to weightless and unloaded clamped-free (WUCF) columns, each with a transverse vibration spectrum isospectral to the original model. Characteristics of models in this isospectral family are dependent on three transformation parameters. A procedure is discussed to convert the isospectral discrete model description into geometric description of realistic columns i.e. from the discrete model, we construct isospectral WUCF columns with rectangular cross-sections varying in width and depth. As part of numerical studies to demonstrate efficacy of techniques presented, frequency parameters of a uniform column and three types of tapered CF columns under different combinations of loading parameters are obtained from the discrete model. Critical combinations of these parameters for a typical tapered column are derived. These results match with published results. Example CF columns, under arbitrarily-chosen combinations of loading parameters are considered and for each combination, isospectral WUCF columns are constructed. Role of transformation parameters in determining characteristics of isospectral columns is discussed and optimum values are deduced. Natural frequencies of these WUCF columns computed using Finite Element Method (FEM) match well with those of the given gravity-loaded CF column with tip force, hence confirming isospectrality.

Discrete Sparse Coding.

PubMed

Exarchakis, Georgios; Lücke, Jörg

2017-11-01

Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.

Continuous and difficult discrete cognitive tasks promote improved stability in older adults.

PubMed

Lajoie, Yves; Jehu, Deborah A; Richer, Natalie; Chan, Alan

2017-06-01

Directing attention away from postural control and onto a cognitive task affords the emergence of automatic control processes. Perhaps the continuous withdrawal of attention from the postural task facilitates an automatization of posture as opposed to only intermittent withdrawal; however this is unknown in the aging population. Twenty older adults (69.9±3.5years) stood with feet together on a force platform for 60s while performing randomly assigned discrete and continuous cognitive tasks. Participants were instructed to stand comfortably with their arms by their sides while verbally responding to the auditory stimuli as fast as possible during the discrete tasks, or mentally performing the continuous cognitive tasks. Participants also performed single-task standing. Results demonstrate significant reductions in sway amplitude and sway variability for the difficult discrete task as well as the continuous tasks relative to single-task standing. The continuous cognitive tasks also prompted greater frequency of sway in the anterior-posterior direction compared to single-standing and discrete tasks, and greater velocity in both directions compared to single-task standing, which could suggest ankle stiffening. No differences in the simple discrete condition were shown compared to single-task standing, perhaps due to the simplicity of the task. Therefore, we propose that the level of difficulty of the task, the specific neuropsychological process engaged during the cognitive task, and the type of task (discrete vs. continuous) influence postural control in older adults. Dual-tasking is a common activity of daily living; this work provides insight into the age-related changes in postural stability and attention demand. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic variability in the human cannabinoid receptor 1 is associated with resting state EEG theta power in humans.

PubMed

Heitland, I; Kenemans, J L; Böcker, K B E; Baas, J M P

2014-11-01

It has long been postulated that exogenous cannabinoids have a profound effect on human cognitive functioning. These cannabinoid effects are thought to depend, at least in parts, on alterations of phase-locking of local field potential neuronal firing. The latter can be measured as activity in the theta frequency band (4-7Hz) by electroencephalogram. Theta oscillations are supposed to serve as a mechanism in neural representations of behaviorally relevant information. However, it remains unknown whether variability in endogenous cannabinoid activity is involved in theta rhythms and therefore, may serve as an individual differences index of human cognitive functioning. To clarify this issue, we recorded resting state EEG activity in 164 healthy human subjects and extracted EEG power across frequency bands (δ, θ, α, and β). To assess variability in the endocannabinoid system, two genetic polymorphisms (rs1049353, rs2180619) within the cannabinoid receptor 1 (CB1) were determined in all participants. As expected, we observed significant effects of rs1049353 on EEG power in the theta band at frontal, central and parietal electrode regions. Crucially, these effects were specific for the theta band, with no effects on activity in the other frequency bands. Rs2180619 showed no significant associations with theta power after Bonferroni correction. Taken together, we provide novel evidence in humans showing that genetic variability in the cannabinoid receptor 1 is associated with resting state EEG power in the theta frequency band. This extends prior findings of exogenous cannabinoid effects on theta power to the endogenous cannabinoid system. Copyright © 2014 Elsevier B.V. All rights reserved.

Longitudinal evaluation of the isotope ratio mass spectrometric data: towards the 'isotopic module' of the athlete biological passport?

PubMed

Jardines, Daniel; Botrè, Francesco; Colamonici, Cristiana; Curcio, Davide; Procida, Gemma; de la Torre, Xavier

2016-11-01

The detection of the abuse of pseudo-endogenous steroids (testosterone and/or its precursors) is currently based on the application of the steroid module of the World Anti-Doping Agency (WADA) Athletes' Biological Passport (ABP), implemented through ADAMS. Diagnostic metabolites are monitored for every athlete and statistically evaluated with a predictive Bayesian approach. In the case of suspicious samples, the data of the ABP are confirmed and the isotope ratio mass spectrometry (IRMS) test is activated. We have previously demonstrated that IRMS enables confirmation of the non-endogenous origin of pseudo-endogenous steroids in otherwise non-suspicious samples, after a longitudinal evaluation of the ABP, even after the inclusion of additional long-term diagnostic hydroxylated metabolites, and that the delta values of the parameters obtained during the IRMS confirmation process presented much less variability compared to the parameters of the ABP. The aim of the present work is to evaluate the application of the same methodology used for the evaluation of the ABP, on the delta values of the pseudo-endogenous steroids monitored. The effectiveness of the proposed model has been assessed on samples obtained after controlled administrations of oral androstenedione and transdermal testosterone. The results support the conclusion that, if applied, the longitudinal evaluation of the IRMS data allows the detection of positive samples that otherwise will be reported as atypical findings (ATF), improving the efficacy of the fight against doping in sport. This approach, by narrowing the individual acceptable range, could possibly improve the detection of the intake of preparations of synthetic origin with delta values close to or overlapping those of endogenously produced steroids. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site-Working towards a toolbox for better assessment.

PubMed

Wroble, Julie; Frederick, Timothy; Frame, Alicia; Vallero, Daniel

2017-01-01

Established soil sampling methods for asbestos are inadequate to support risk assessment and risk-based decision making at Superfund sites due to difficulties in detecting asbestos at low concentrations and difficulty in extrapolating soil concentrations to air concentrations. Environmental Protection Agency (EPA)'s Office of Land and Emergency Management (OLEM) currently recommends the rigorous process of Activity Based Sampling (ABS) to characterize site exposures. The purpose of this study was to compare three soil analytical methods and two soil sampling methods to determine whether one method, or combination of methods, would yield more reliable soil asbestos data than other methods. Samples were collected using both traditional discrete ("grab") samples and incremental sampling methodology (ISM). Analyses were conducted using polarized light microscopy (PLM), transmission electron microscopy (TEM) methods or a combination of these two methods. Data show that the fluidized bed asbestos segregator (FBAS) followed by TEM analysis could detect asbestos at locations that were not detected using other analytical methods; however, this method exhibited high relative standard deviations, indicating the results may be more variable than other soil asbestos methods. The comparison of samples collected using ISM versus discrete techniques for asbestos resulted in no clear conclusions regarding preferred sampling method. However, analytical results for metals clearly showed that measured concentrations in ISM samples were less variable than discrete samples.

Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site—Working towards a toolbox for better assessment

PubMed Central

2017-01-01

Established soil sampling methods for asbestos are inadequate to support risk assessment and risk-based decision making at Superfund sites due to difficulties in detecting asbestos at low concentrations and difficulty in extrapolating soil concentrations to air concentrations. Environmental Protection Agency (EPA)’s Office of Land and Emergency Management (OLEM) currently recommends the rigorous process of Activity Based Sampling (ABS) to characterize site exposures. The purpose of this study was to compare three soil analytical methods and two soil sampling methods to determine whether one method, or combination of methods, would yield more reliable soil asbestos data than other methods. Samples were collected using both traditional discrete (“grab”) samples and incremental sampling methodology (ISM). Analyses were conducted using polarized light microscopy (PLM), transmission electron microscopy (TEM) methods or a combination of these two methods. Data show that the fluidized bed asbestos segregator (FBAS) followed by TEM analysis could detect asbestos at locations that were not detected using other analytical methods; however, this method exhibited high relative standard deviations, indicating the results may be more variable than other soil asbestos methods. The comparison of samples collected using ISM versus discrete techniques for asbestos resulted in no clear conclusions regarding preferred sampling method. However, analytical results for metals clearly showed that measured concentrations in ISM samples were less variable than discrete samples. PMID:28759607

An Algorithm for the Mixed Transportation Network Design Problem

PubMed Central

Liu, Xinyu; Chen, Qun

2016-01-01

This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems.

PubMed

Sadowski, Krzysztof L; Thierens, Dirk; Bosman, Peter A N

2018-01-01

Learning and exploiting problem structure is one of the key challenges in optimization. This is especially important for black-box optimization (BBO) where prior structural knowledge of a problem is not available. Existing model-based Evolutionary Algorithms (EAs) are very efficient at learning structure in both the discrete, and in the continuous domain. In this article, discrete and continuous model-building mechanisms are integrated for the Mixed-Integer (MI) domain, comprising discrete and continuous variables. We revisit a recently introduced model-based evolutionary algorithm for the MI domain, the Genetic Algorithm for Model-Based mixed-Integer opTimization (GAMBIT). We extend GAMBIT with a parameterless scheme that allows for practical use of the algorithm without the need to explicitly specify any parameters. We furthermore contrast GAMBIT with other model-based alternatives. The ultimate goal of processing mixed dependences explicitly in GAMBIT is also addressed by introducing a new mechanism for the explicit exploitation of mixed dependences. We find that processing mixed dependences with this novel mechanism allows for more efficient optimization. We further contrast the parameterless GAMBIT with Mixed-Integer Evolution Strategies (MIES) and other state-of-the-art MI optimization algorithms from the General Algebraic Modeling System (GAMS) commercial algorithm suite on problems with and without constraints, and show that GAMBIT is capable of solving problems where variable dependences prevent many algorithms from successfully optimizing them.

Self-adaptive difference method for the effective solution of computationally complex problems of boundary layer theory

NASA Technical Reports Server (NTRS)

Schoenauer, W.; Daeubler, H. G.; Glotz, G.; Gruening, J.

1986-01-01

An implicit difference procedure for the solution of equations for a chemically reacting hypersonic boundary layer is described. Difference forms of arbitrary error order in the x and y coordinate plane were used to derive estimates for discretization error. Computational complexity and time were minimized by the use of this difference method and the iteration of the nonlinear boundary layer equations was regulated by discretization error. Velocity and temperature profiles are presented for Mach 20.14 and Mach 18.5; variables are velocity profiles, temperature profiles, mass flow factor, Stanton number, and friction drag coefficient; three figures include numeric data.

Global stabilization analysis of inertial memristive recurrent neural networks with discrete and distributed delays.

PubMed

Wang, Leimin; Zeng, Zhigang; Ge, Ming-Feng; Hu, Junhao

2018-05-02

This paper deals with the stabilization problem of memristive recurrent neural networks with inertial items, discrete delays, bounded and unbounded distributed delays. First, for inertial memristive recurrent neural networks (IMRNNs) with second-order derivatives of states, an appropriate variable substitution method is invoked to transfer IMRNNs into a first-order differential form. Then, based on nonsmooth analysis theory, several algebraic criteria are established for the global stabilizability of IMRNNs under proposed feedback control, where the cases with both bounded and unbounded distributed delays are successfully addressed. Finally, the theoretical results are illustrated via the numerical simulations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sensitivity analysis of discrete structural systems: A survey

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.

1984-01-01

Methods for calculating sensitivity derivatives for discrete structural systems are surveyed, primarily covering literature published during the past two decades. Methods are described for calculating derivatives of static displacements and stresses, eigenvalues and eigenvectors, transient structural response, and derivatives of optimum structural designs with respect to problem parameters. The survey is focused on publications addressed to structural analysis, but also includes a number of methods developed in nonstructural fields such as electronics, controls, and physical chemistry which are directly applicable to structural problems. Most notable among the nonstructural-based methods are the adjoint variable technique from control theory, and the Green's function and FAST methods from physical chemistry.

Nonintegrable Schrodinger discrete breathers.

PubMed

Gómez-Gardeñes, J; Floría, L M; Peyrard, M; Bishop, A R

2004-12-01

In an extensive numerical investigation of nonintegrable translational motion of discrete breathers in nonlinear Schrödinger lattices, we have used a regularized Newton algorithm to continue these solutions from the limit of the integrable Ablowitz-Ladik lattice. These solutions are shown to be a superposition of a localized moving core and an excited extended state (background) to which the localized moving pulse is spatially asymptotic. The background is a linear combination of small amplitude nonlinear resonant plane waves and it plays an essential role in the energy balance governing the translational motion of the localized core. Perturbative collective variable theory predictions are critically analyzed in the light of the numerical results.

An opinion-driven behavioral dynamics model for addictive behaviors

DOE PAGES

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

2015-04-08

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

Heat transfer at microscopic level in a MHD fractional inertial flow confined between non-isothermal boundaries

NASA Astrophysics Data System (ADS)

Shoaib Anwar, Muhammad; Rasheed, Amer

2017-07-01

Heat transfer through a Forchheimer medium in an unsteady magnetohydrodynamic (MHD) developed differential-type fluid flow is analyzed numerically in this study. The boundary layer flow is modeled with the help of the fractional calculus approach. The fluid is confined between infinite parallel plates and flows by motion of the plates in their own plane. Both the plates have variable surface temperature. Governing partial differential equations with appropriate initial and boundary conditions are solved by employing a finite-difference scheme to discretize the fractional time derivative and finite-element discretization for spatial variables. Coefficients of skin friction and local Nusselt numbers are computed for the fractional model. The flow behavior is presented for various values of the involved parameters. The influence of different dimensionless numbers on skin friction and Nusselt number is discussed by tabular results. Forchheimer medium flows that involve catalytic converters and gas turbines can be modeled in a similar manner.

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

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

Collins, Benjamin, E-mail: collinsbs@ornl.gov; Stimpson, Shane, E-mail: stimpsonsg@ornl.gov; Kelley, Blake W., E-mail: kelleybl@umich.edu

2016-12-01

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-classmore » computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.« less

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

DOE PAGES

Collins, Benjamin; Stimpson, Shane; Kelley, Blake W.; ...

2016-08-25

We derived a consistent “2D/1D” neutron transport method from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. Our paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. We also performed several applications on both leadership-class and industry-classmore » computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.« less

Interior and exterior sound field control using general two-dimensional first-order sources.

PubMed

Poletti, M A; Abhayapala, T D

2011-01-01

Reproduction of a given sound field interior to a circular loudspeaker array without producing an undesirable exterior sound field is an unsolved problem over a broadband of frequencies. At low frequencies, by implementing the Kirchhoff-Helmholtz integral using a circular discrete array of line-source loudspeakers, a sound field can be recreated within the array and produce no exterior sound field, provided that the loudspeakers have azimuthal polar responses with variable first-order responses which are a combination of a two-dimensional (2D) monopole and a radially oriented 2D dipole. This paper examines the performance of circular discrete arrays of line-source loudspeakers which also include a tangential dipole, providing general variable-directivity responses in azimuth. It is shown that at low frequencies, the tangential dipoles are not required, but that near and above the Nyquist frequency, the tangential dipoles can both improve the interior accuracy and reduce the exterior sound field. The additional dipoles extend the useful range of the array by around an octave.

Performance improvement of eight-state continuous-variable quantum key distribution with an optical amplifier

NASA Astrophysics Data System (ADS)

Guo, Ying; Li, Renjie; Liao, Qin; Zhou, Jian; Huang, Duan

2018-02-01

Discrete modulation is proven to be beneficial to improving the performance of continuous-variable quantum key distribution (CVQKD) in long-distance transmission. In this paper, we suggest a construct to improve the maximal generated secret key rate of discretely modulated eight-state CVQKD using an optical amplifier (OA) with a slight cost of transmission distance. In the proposed scheme, an optical amplifier is exploited to compensate imperfection of Bob's apparatus, so that the generated secret key rate of eight-state protocol is enhanced. Specifically, we investigate two types of optical amplifiers, phase-insensitive amplifier (PIA) and phase-sensitive amplifier (PSA), and thereby obtain approximately equivalent improved performance for eight-state CVQKD system when applying these two different amplifiers. Numeric simulation shows that the proposed scheme can well improve the generated secret key rate of eight-state CVQKD in both asymptotic limit and finite-size regime. We also show that the proposed scheme can achieve the relatively high-rate transmission at long-distance communication system.

Down-hole periodic seismic generator

DOEpatents

Hardee, H.C.; Hills, R.G.; Striker, R.P.

1982-10-28

A down hole periodic seismic generator system is disclosed for transmitting variable frequency, predominantly shear-wave vibration into earth strata surrounding a borehole. The system comprises a unitary housing operably connected to a well head by support and electrical cabling and contains clamping apparatus for selectively clamping the housing to the walls of the borehole. The system further comprises a variable speed pneumatic oscillator and a self-contained pneumatic reservoir for producing a frequency-swept seismic output over a discrete frequency range.

Advanced downhole periodic seismic generator

DOEpatents

Hardee, Harry C.; Hills, Richard G.; Striker, Richard P.

1991-07-16

An advanced downhole periodic seismic generator system for transmitting variable frequency, predominantly shear-wave vibration into earth strata surrounding a borehole. The system comprises a unitary housing operably connected to a well head by support and electrical cabling and contains clamping apparatus for selectively clamping the housing to the walls of the borehole. The system further comprises a variable speed pneumatic oscillator and a self-contained pneumatic reservoir for producing a frequency-swept seismic output over a discrete frequency range.

Down hole periodic seismic generator

DOEpatents

Hardee, Harry C.; Hills, Richard G.; Striker, Richard P.

1989-01-01

A down hole periodic seismic generator system for transmitting variable frequency, predominantly shear-wave vibration into earth strata surrounding a borehole. The system comprises a unitary housing operably connected to a well head by support and electrical cabling and contains clamping apparatus for selectively clamping the housing to the walls of the borehole. The system further comprises a variable speed pneumatic oscillator and a self-contained pneumatic reservoir for producing a frequency-swept seismic output over a discrete frequency range.

NEPTUNE’S DYNAMIC ATMOSPHERE FROM KEPLER K2 OBSERVATIONS: IMPLICATIONS FOR BROWN DWARF LIGHT CURVE ANALYSES

PubMed Central

Rowe, Jason F.; Gaulme, Patrick; Hammel, Heidi B.; Casewell, Sarah L.; Fortney, Jonathan J.; Gizis, John E.; Lissauer, Jack J.; Morales-Juberias, Raul; Orton, Glenn S.; Wong, Michael H.; Marley, Mark S.

2017-01-01

Observations of Neptune with the Kepler Space Telescope yield a 49 day light curve with 98% coverage at a 1 minute cadence. A significant signature in the light curve comes from discrete cloud features. We compare results extracted from the light curve data with contemporaneous disk-resolved imaging of Neptune from the Keck 10-m telescope at 1.65 microns and Hubble Space Telescope visible imaging acquired nine months later. This direct comparison validates the feature latitudes assigned to the K2 light curve periods based on Neptune’s zonal wind profile, and confirms observed cloud feature variability. Although Neptune’s clouds vary in location and intensity on short and long timescales, a single large discrete storm seen in Keck imaging dominates the K2 and Hubble light curves; smaller or fainter clouds likely contribute to short-term brightness variability. The K2 Neptune light curve, in conjunction with our imaging data, provides context for the interpretation of current and future brown dwarf and extrasolar planet variability measurements. In particular we suggest that the balance between large, relatively stable, atmospheric features and smaller, more transient, clouds controls the character of substellar atmospheric variability. Atmospheres dominated by a few large spots may show inherently greater light curve stability than those which exhibit a greater number of smaller features. PMID:28127087

Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

NASA Astrophysics Data System (ADS)

Carter, Jeffrey R.; Simon, Wayne E.

1990-08-01

Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

ACCURATE SOLUTION AND GRADIENT COMPUTATION FOR ELLIPTIC INTERFACE PROBLEMS WITH VARIABLE COEFFICIENTS

PubMed Central

LI, ZHILIN; JI, HAIFENG; CHEN, XIAOHONG

2016-01-01

A new augmented method is proposed for elliptic interface problems with a piecewise variable coefficient that has a finite jump across a smooth interface. The main motivation is not only to get a second order accurate solution but also a second order accurate gradient from each side of the interface. The key of the new method is to introduce the jump in the normal derivative of the solution as an augmented variable and re-write the interface problem as a new PDE that consists of a leading Laplacian operator plus lower order derivative terms near the interface. In this way, the leading second order derivatives jump relations are independent of the jump in the coefficient that appears only in the lower order terms after the scaling. An upwind type discretization is used for the finite difference discretization at the irregular grid points near or on the interface so that the resulting coefficient matrix is an M-matrix. A multi-grid solver is used to solve the linear system of equations and the GMRES iterative method is used to solve the augmented variable. Second order convergence for the solution and the gradient from each side of the interface has also been proved in this paper. Numerical examples for general elliptic interface problems have confirmed the theoretical analysis and efficiency of the new method. PMID:28983130

First-Order System Least-Squares for the Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Bochev, P.; Cai, Z.; Manteuffel, T. A.; McCormick, S. F.

1996-01-01

This paper develops a least-squares approach to the solution of the incompressible Navier-Stokes equations in primitive variables. As with our earlier work on Stokes equations, we recast the Navier-Stokes equations as a first-order system by introducing a velocity flux variable and associated curl and trace equations. We show that the resulting system is well-posed, and that an associated least-squares principle yields optimal discretization error estimates in the H(sup 1) norm in each variable (including the velocity flux) and optimal multigrid convergence estimates for the resulting algebraic system.

Numerical uncertainty in computational engineering and physics

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

Hemez, Francois M

2009-01-01

Obtaining a solution that approximates ordinary or partial differential equations on a computational mesh or grid does not necessarily mean that the solution is accurate or even 'correct'. Unfortunately assessing the quality of discrete solutions by questioning the role played by spatial and temporal discretizations generally comes as a distant third to test-analysis comparison and model calibration. This publication is contributed to raise awareness of the fact that discrete solutions introduce numerical uncertainty. This uncertainty may, in some cases, overwhelm in complexity and magnitude other sources of uncertainty that include experimental variability, parametric uncertainty and modeling assumptions. The concepts ofmore » consistency, convergence and truncation error are overviewed to explain the articulation between the exact solution of continuous equations, the solution of modified equations and discrete solutions computed by a code. The current state-of-the-practice of code and solution verification activities is discussed. An example in the discipline of hydro-dynamics illustrates the significant effect that meshing can have on the quality of code predictions. A simple method is proposed to derive bounds of solution uncertainty in cases where the exact solution of the continuous equations, or its modified equations, is unknown. It is argued that numerical uncertainty originating from mesh discretization should always be quantified and accounted for in the overall uncertainty 'budget' that supports decision-making for applications in computational physics and engineering.« less

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

PubMed

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2018-03-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.

Inferring network structure in non-normal and mixed discrete-continuous genomic data

PubMed Central

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2017-01-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. PMID:28437848

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach.

PubMed

Burns, Darren K; Jones, Andrew P; Goryakin, Yevgeniy; Suhrcke, Marc

2017-05-01

There is a scarcity of quantitative research into the effect of FDI on population health in low and middle income countries (LMICs). This paper investigates the relationship using annual panel data from 85 LMICs between 1974 and 2012. When controlling for time trends, country fixed effects, correlation between repeated observations, relevant covariates, and endogeneity via a novel instrumental variable approach, we find FDI to have a beneficial effect on overall health, proxied by life expectancy. When investigating age-specific mortality rates, we find a stronger beneficial effect of FDI on adult mortality, yet no association with either infant or child mortality. Notably, FDI effects on health remain undetected in all models which do not control for endogeneity. Exploring the effect of sector-specific FDI on health in LMICs, we provide preliminary evidence of a weak inverse association between secondary (i.e. manufacturing) sector FDI and overall life expectancy. Our results thus suggest that FDI has provided an overall benefit to population health in LMICs, particularly in adults, yet investments into the secondary sector could be harmful to health. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pheromones enhance somatosensory processing in newt brains through a vasotocin-dependent mechanism.

PubMed

Thompson, R R; Dickinson, P S; Rose, J D; Dakin, K A; Civiello, G M; Segerdahl, A; Bartlett, R

2008-07-22

We tested whether the sex pheromones that stimulate courtship clasping in male roughskin newts do so, at least in part, by amplifying the somatosensory signals that directly trigger the motor pattern associated with clasping and, if so, whether that amplification is dependent on endogenous vasotocin (VT). Female olfactory stimuli increased the number of action potentials recorded in the medulla of males in response to tactile stimulation of the cloaca, which triggers the clasp motor reflex, as well as to tactile stimulation of the snout and hindlimb. That enhancement was blocked by exposing the medulla to a V1a receptor antagonist before pheromone exposure. However, the antagonist did not affect medullary responses to tactile stimuli in the absence of pheromone exposure, suggesting that pheromones amplify somatosensory signals by inducing endogenous VT release. The ability of VT to couple sensory systems together in response to social stimulation could allow this peptide to induce variable behavioural outcomes, depending on the immediate context of the social interaction and thus on the nature of the associated stimuli that are amplified. If widespread in vertebrates, this mechanism could account for some of the behavioural variability associated with this and related peptides both within and across species.

A High-Performance Neural Prosthesis Incorporating Discrete State Selection With Hidden Markov Models.

PubMed

Kao, Jonathan C; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V

2017-04-01

Communication neural prostheses aim to restore efficient communication to people with motor neurological injury or disease by decoding neural activity into control signals. These control signals are both analog (e.g., the velocity of a computer mouse) and discrete (e.g., clicking an icon with a computer mouse) in nature. Effective, high-performing, and intuitive-to-use communication prostheses should be capable of decoding both analog and discrete state variables seamlessly. However, to date, the highest-performing autonomous communication prostheses rely on precise analog decoding and typically do not incorporate high-performance discrete decoding. In this report, we incorporated a hidden Markov model (HMM) into an intracortical communication prosthesis to enable accurate and fast discrete state decoding in parallel with analog decoding. In closed-loop experiments with nonhuman primates implanted with multielectrode arrays, we demonstrate that incorporating an HMM into a neural prosthesis can increase state-of-the-art achieved bitrate by 13.9% and 4.2% in two monkeys ( ). We found that the transition model of the HMM is critical to achieving this performance increase. Further, we found that using an HMM resulted in the highest achieved peak performance we have ever observed for these monkeys, achieving peak bitrates of 6.5, 5.7, and 4.7 bps in Monkeys J, R, and L, respectively. Finally, we found that this neural prosthesis was robustly controllable for the duration of entire experimental sessions. These results demonstrate that high-performance discrete decoding can be beneficially combined with analog decoding to achieve new state-of-the-art levels of performance.

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Yang-Baxter maps, discrete integrable equations and quantum groups

NASA Astrophysics Data System (ADS)

Bazhanov, Vladimir V.; Sergeev, Sergey M.

2018-01-01

For every quantized Lie algebra there exists a map from the tensor square of the algebra to itself, which by construction satisfies the set-theoretic Yang-Baxter equation. This map allows one to define an integrable discrete quantum evolution system on quadrilateral lattices, where local degrees of freedom (dynamical variables) take values in a tensor power of the quantized Lie algebra. The corresponding equations of motion admit the zero curvature representation. The commuting Integrals of Motion are defined in the standard way via the Quantum Inverse Problem Method, utilizing Baxter's famous commuting transfer matrix approach. All elements of the above construction have a meaningful quasi-classical limit. As a result one obtains an integrable discrete Hamiltonian evolution system, where the local equation of motion are determined by a classical Yang-Baxter map and the action functional is determined by the quasi-classical asymptotics of the universal R-matrix of the underlying quantum algebra. In this paper we present detailed considerations of the above scheme on the example of the algebra Uq (sl (2)) leading to discrete Liouville equations, however the approach is rather general and can be applied to any quantized Lie algebra.

The Effect of Childhood Health Status on Adult Health in China.

PubMed

Wang, Qing; Zhang, Huyang; Rizzo, John A; Fang, Hai

2018-01-26

Childhood health in China was poor in the 1950s and 1960s because of limited nutrition. In the last three decades, China has distinguished itself through its tremendous economic growth and improvements in health and nutrition. However, prior to such growth, access to good nutrition was more variable, with potentially important implications, not only for childhood health, but also for adult health, because of its long-term effects lasting into adulthood. To shed light on these issues, this study examined the long-run association between childhood health and adult health outcomes among a middle-aged Chinese population and addresses the endogeneity of childhood health. A nationwide database from the 2011 China Health and Retirement Longitudinal Study (CHARLS) was employed. Three adult health outcomes variables were used: self-reported health status, cognition, and physical function. The local variation in grain production in the subjects' fetal period and the first 24 months following birth was employed as an instrument for childhood health in order to correct for its endogeneity. Childhood health recalled by the respondents was positively and significantly associated with their adult health outcomes in terms of self-reported health status, cognition, and physical function in single-equation estimates that did not correct for the endogeneity of childhood health. A good childhood health status increased the probabilities of good adult health, good adult cognitive function, and good adult physical function by 16% (95% CI: 13-18%), 13% (95% CI: 10-15%), and 14% (95% CI: 12-17%), respectively. After correcting for endogeneity, the estimated effects of good childhood health were consistent but stronger. We also studied the male and female populations separately, finding that the positive effects of childhood health on adult health were larger for males. In China, childhood health significantly affects adult health. This suggests that early interventions to promote childhood health will have long-term benefits in China and that health-care policies should consider their long-term impacts over the life cycle in addition to their effects on specific age groups.

The Effect of Childhood Health Status on Adult Health in China

PubMed Central

Wang, Qing; Zhang, Huyang; Rizzo, John A.; Fang, Hai

2018-01-01

Childhood health in China was poor in the 1950s and 1960s because of limited nutrition. In the last three decades, China has distinguished itself through its tremendous economic growth and improvements in health and nutrition. However, prior to such growth, access to good nutrition was more variable, with potentially important implications, not only for childhood health, but also for adult health, because of its long-term effects lasting into adulthood. To shed light on these issues, this study examined the long-run association between childhood health and adult health outcomes among a middle-aged Chinese population and addresses the endogeneity of childhood health. A nationwide database from the 2011 China Health and Retirement Longitudinal Study (CHARLS) was employed. Three adult health outcomes variables were used: self-reported health status, cognition, and physical function. The local variation in grain production in the subjects’ fetal period and the first 24 months following birth was employed as an instrument for childhood health in order to correct for its endogeneity. Childhood health recalled by the respondents was positively and significantly associated with their adult health outcomes in terms of self-reported health status, cognition, and physical function in single-equation estimates that did not correct for the endogeneity of childhood health. A good childhood health status increased the probabilities of good adult health, good adult cognitive function, and good adult physical function by 16% (95% CI: 13–18%), 13% (95% CI: 10–15%), and 14% (95% CI: 12–17%), respectively. After correcting for endogeneity, the estimated effects of good childhood health were consistent but stronger. We also studied the male and female populations separately, finding that the positive effects of childhood health on adult health were larger for males. In China, childhood health significantly affects adult health. This suggests that early interventions to promote childhood health will have long-term benefits in China and that health-care policies should consider their long-term impacts over the life cycle in addition to their effects on specific age groups. PMID:29373554

An Efficient Variable Length Coding Scheme for an IID Source

NASA Technical Reports Server (NTRS)

Cheung, K. -M.

1995-01-01

A scheme is examined for using two alternating Huffman codes to encode a discrete independent and identically distributed source with a dominant symbol. This combined strategy, or alternating runlength Huffman (ARH) coding, was found to be more efficient than ordinary coding in certain circumstances.

Psychopathy as a Taxon: Evidence That Psychopaths Are a Discrete Class.

ERIC Educational Resources Information Center

Harris, Grant T.; And Others

1994-01-01

Applied taxometric analyses to construct of psychopathy (as measured by Psychopathy Checklist) and to several variables reflecting antisocial childhood, adult criminality, and criminal recidivism. Findings from 653 serious offenders assessed or treated in maximum-security institution supported existence of taxon underlying psychopathy. Childhood…

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Stochastic dynamics of time correlation in complex systems with discrete time

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail

2000-11-01

In this paper we present the concept of description of random processes in complex systems with discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCFs). We have introduced the dynamic (time dependent) information Shannon entropy Si(t) where i=0,1,2,3,..., as an information measure of stochastic dynamics of time correlation (i=0) and time memory (i=1,2,3,...). The set of functions Si(t) constitute the quantitative measure of time correlation disorder (i=0) and time memory disorder (i=1,2,3,...) in complex system. The theory developed started from the careful analysis of time correlation involving dynamics of vectors set of various chaotic states. We examine two stochastic processes involving the creation and annihilation of time correlation (or time memory) in details. We carry out the analysis of vectors' dynamics employing finite-difference equations for random variables and the evolution operator describing their natural motion. The existence of TCF results in the construction of the set of projection operators by the usage of scalar product operation. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCFs and memory functions (MFs). The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. This offers new opportunities for detecting the frequency spectra of power of entropy function Si(t) for time correlation (i=0) and time memory (i=1,2,3,...). The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short- and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties.

Endogenous DNA damage and testicular germ cell tumors

PubMed Central

Cook, Michael B.; Sigurdson, Alice J.; Jones, Irene M.; Thomas, Cynthia B.; Graubard, Barry I.; Korde, Larissa; Greene, Mark H.; McGlynn, Katherine A.

2008-01-01

Testicular germ cell tumors (TGCT) are comprised of two histologic groups, seminomas and nonseminomas. We postulated that the possible divergent pathogeneses of these histologies may be partially explained by variable levels of net endogenous DNA damage. To test our hypothesis, we conducted a case-case analysis of 51 seminoma and 61 nonseminoma patients using data and specimens from the Familial Testicular Cancer study and the U.S. Radiologic Technologists cohort. A lymphoblastoid cell line was cultured for each patient and the alkaline comet assay was used to determine four parameters: tail DNA, tail length, comet distributed moment (CDM) and Olive tail moment (OTM). Odds ratios (OR) and 95% confidence intervals (95%CI) were estimated using logistic regression. Values for tail length, tail DNA, CDM and OTM were modeled as categorical variables using the 50th and 75th percentiles of the seminoma group. Tail DNA was significantly associated with nonseminoma compared to seminoma (OR50th percentile=3.31, 95%CI: 1.00, 10.98; OR75th percentile=3.71, 95%CI: 1.04, 13.20; p for trend=0.039). OTM exhibited similar, albeit statistically non-significant, risk estimates (OR50th percentile=2.27, 95%CI: 0.75, 6.87; OR75th percentile=2.40, 95%CI: 0.75, 7.71; p for trend=0.12) whereas tail length and CDM showed no association. In conclusion, the results for tail DNA and OTM indicate that net endogenous levels are higher in patients who develop nonseminoma compared with seminoma. This may partly explain the more aggressive biology and younger age-of-onset of this histologic subgroup compared with the relatively less aggressive, later-onset seminoma. PMID:18657195

Endogenous contributions to egg protein formation in lesser scaup Aythya affinis

USGS Publications Warehouse

Cutting, Kyle A.; Hobson, Keith A.; Rotella, Jay J.; Warren, Jeffrey M.; Wainwright-de la Cruz, Susan E.; Takekawa, John Y.

2011-01-01

Lesser scaup Aythya affinis populations have declined throughout the North American continent for the last three decades. It has been hypothesized that the loss and degradation of staging habitats has resulted in reduced female body condition on the breeding grounds and a concomitant decline in productivity. We explored the importance of body (endogenous) reserves obtained prior to arrival on the breeding ground in egg protein formation in southwestern Montana during 2006–2008 using stable-carbon (δ13C) and nitrogen (δ15N) isotope analyses of scaup egg components, female tissue, and local prey items. From arrival on the breeding grounds through the egg-laying period, δ15N values of scaup red blood cells decreased while δ13C values became less variable; a pattern consistent with endogenous tissues equilibrating with local (freshwater) dietary sources. In 2006 and 2008, isotopic values for egg albumen and yolk protein indicated that most (>90%) protein used to produce these components was obtained on the breeding grounds. However, in 2007, a year with an exceptionally warm and dry spring, endogenous reserves contributed on average 41% of yolk and 29% of albumen. Results from this study suggest that female scaup can meet the protein needs of egg production largely from local dietary food sources. This highlights the importance of providing high-quality breeding habitats for scaup. Whether this pattern holds in areas with similar breeding season lengths but longer migration routes, such as those found in the western boreal forest, should be investigated.

Restriction by APOBEC3 proteins of endogenous retroviruses with an extracellular life cycle: ex vivo effects and in vivo "traces" on the murine IAPE and human HERV-K elements

PubMed Central

Esnault, Cécile; Priet, Stéphane; Ribet, David; Heidmann, Odile; Heidmann, Thierry

2008-01-01

Background APOBEC3 cytosine deaminases have been demonstrated to restrict infectivity of a series of retroviruses, with different efficiencies depending on the retrovirus. In addition, APOBEC3 proteins can severely restrict the intracellular transposition of a series of retroelements with a strictly intracellular life cycle, including the murine IAP and MusD LTR-retrotransposons. Results Here we show that the IAPE element, which is the infectious progenitor of the strictly intracellular IAP elements, and the infectious human endogenous retrovirus HERV-K are restricted by both murine and human APOBEC3 proteins in an ex vivo assay for infectivity, with evidence in most cases of strand-specific G-to-A editing of the proviruses, with the expected signatures. In silico analysis of the naturally occurring genomic copies of the corresponding endogenous elements performed on the mouse and human genomes discloses "traces" of APOBEC3-editing, with the specific signature of the murine APOBEC3 and human APOBEC3G enzymes, respectively, and to a variable extent depending on the family member. Conclusion These results indicate that the IAPE and HERV-K elements, which can only replicate via an extracellular infection cycle, have been restricted at the time of their entry, amplification and integration into their target host genomes by definite APOBEC3 proteins, most probably acting in evolution to limit the mutagenic effect of these endogenized extracellular parasites. PMID:18702815

Determinants of Household Water Conservation Retrofit Activity: A Discrete Choice Model Using Survey Data

NASA Astrophysics Data System (ADS)

Cameron, T. A.; Wright, M. B.

1990-02-01

Economic analyses of residential water demand have typically concentrated on price and income elasticities. In the short run a substantial change in water prices might induce only small changes in consumption levels. As time passes, however, households will have the opportunity to "retrofit" existing water-using equipment to make it less water-intensive. This produces medium- to long-run demand elasticities that are higher than short-run studies suggest. We examine responses to water conservation questions appearing on the Los Angeles Department of Water and Power's 1983 residential energy survey. We find that households' decisions to install shower retrofit devices are influenced by the potential to save money on water heating bills. We attribute toilet retrofit decisions more to noneconomic factors which might be characterized as "general conservation mindedness." The endogeneity of these retrofit decisions casts some doubt on the results of studies of individual households that treat voluntary retrofits as exogenous.

On the use of microwave radar devices in chronobiology studies: an application with Periplaneta americana.

PubMed

Pasquali, Vittorio; Renzi, Paolo

2005-08-01

Modified motion detectors can be used to monitor locomotor activity and measure endogenous rhythms. Although these devices can help monitor insects in their home cages, the small size of the animals requires a very short wavelength detector. We modified a commercial microwave-based detection device, connected the detector's output to the digital input of a computer, and validated the device by recording circadian and ultradian rhythms. Periplaneta americana were housed in individual cages, and their activity was monitored at 18 degrees C and subsequently at 28 degrees C in constant darkness. Time series were analyzed by a discrete Fourier transform and a chi-square periodogram. Q10 values and the circadian free-running period confirmed the data reported in the literature, validating the apparatus. Moreover, the spectral analysis and periodogram revealed the presence of ultradian rhythmicity in the range of 1-8 h.

Locus-specific epigenetic remodeling controls addiction- and depression-related behaviors.

PubMed

Heller, Elizabeth A; Cates, Hannah M; Peña, Catherine J; Sun, Haosheng; Shao, Ningyi; Feng, Jian; Golden, Sam A; Herman, James P; Walsh, Jessica J; Mazei-Robison, Michelle; Ferguson, Deveroux; Knight, Scott; Gerber, Mark A; Nievera, Christian; Han, Ming-Hu; Russo, Scott J; Tamminga, Carol S; Neve, Rachael L; Shen, Li; Zhang, H Steve; Zhang, Feng; Nestler, Eric J

2014-12-01

Chronic exposure to drugs of abuse or stress regulates transcription factors, chromatin-modifying enzymes and histone post-translational modifications in discrete brain regions. Given the promiscuity of the enzymes involved, it has not yet been possible to obtain direct causal evidence to implicate the regulation of transcription and consequent behavioral plasticity by chromatin remodeling that occurs at a single gene. We investigated the mechanism linking chromatin dynamics to neurobiological phenomena by applying engineered transcription factors to selectively modify chromatin at a specific mouse gene in vivo. We found that histone methylation or acetylation at the Fosb locus in nucleus accumbens, a brain reward region, was sufficient to control drug- and stress-evoked transcriptional and behavioral responses via interactions with the endogenous transcriptional machinery. This approach allowed us to relate the epigenetic landscape at a given gene directly to regulation of its expression and to its subsequent effects on reward behavior.

Reliability study of tibialis posterior and selected leg muscle EMG and multi-segment foot kinematics in rheumatoid arthritis associated pes planovalgus

PubMed Central

Barn, Ruth; Rafferty, Daniel; Turner, Deborah E.; Woodburn, James

2012-01-01

Objective To determine within- and between-day reliability characteristics of electromyographic (EMG) activity patterns of selected lower leg muscles and kinematic variables in patients with rheumatoid arthritis (RA) and pes planovalgus. Methods Five patients with RA underwent gait analysis barefoot and shod on two occasions 1 week apart. Fine-wire (tibialis posterior [TP]) and surface EMG for selected muscles and 3D kinematics using a multi-segmented foot model was undertaken barefoot and shod. Reliability of pre-determined variables including EMG activity patterns and inter-segment kinematics were analysed using coefficients of multiple correlation, intraclass correlation coefficients (ICC) and the standard error of the measurement (SEM). Results Muscle activation patterns within- and between-day ranged from fair-to-good to excellent in both conditions. Discrete temporal and amplitude variables were highly variable across all muscle groups in both conditions but particularly poor for TP and peroneus longus. SEMs ranged from 1% to 9% of stance and 4% to 27% of maximum voluntary contraction; in most cases the 95% confidence interval crossed zero. Excellent within-day reliability was found for the inter-segment kinematics in both conditions. Between-day reliability ranged from fair-to-good to excellent for kinematic variables and all ICCs were excellent; the SEM ranged from 0.60° to 1.99°. Conclusion Multi-segmented foot kinematics can be reliably measured in RA patients with pes planovalgus. Serial measurement of discrete variables for TP and other selected leg muscles via EMG is not supported from the findings in this cohort of RA patients. Caution should be exercised when EMG measurements are considered to study disease progression or intervention effects. PMID:22721819

High Resolution Studies of the Structure of the Solar Atmosphere

DTIC Science & Technology

1993-08-04

two-fluid solar wind model", submitted to J. Geophys. Res., August 1993. M. B. Arndt, S. R. Habbal, and M. Karovska , "Discrete and localized nature of...the variable emission from active regions", submitted to Solar Phys., August 1993. M. Karovska and F. Blundell, "The fine structure at the limb in a...coronal hole", submitted to Ap. J, August 1993. M. Karovska , M. Arndt and S. R. Habbal, "Spatial and temporal variability of the emission at the limb

A continuous 250,000 yr record of oxygen and carbon isotopes in ostracode and bulk-sediment carbonate from Bear Lake, Utah-Idaho

USGS Publications Warehouse

Bright, Jordon; Kaufman, D.S.; Forester, R.M.; Dean, W.E.

2006-01-01

Oxygen and carbon isotopes from a continuous, 120-m-long, carbonate-rich core from Bear Lake, Utah-Idaho, document dramatic fluctuations in the hydrologic budget of the lake over the last 250,000 yr. Isotopic analyses of bulk sediment samples capture millennial-scale variability. Ostracode calcite was analyzed from 78 levels, mainly from the upper half of the core where valves are better preserved, to compare the isotopic value of purely endogenic carbonate with the bulk sediment, which comprises both endogenic and detrital components. The long core exhibits three relatively brief intervals with abundant endogenic aragonite (50??10%) and enriched ??18O and ??13C. These intervals are interpreted as warm/dry periods when the lake retracted into a topographically closed basin. We correlate these intervals with the interglacial periods of marine oxygen-isotope stages 1, 5e, and 7a, consistent with the presently available geochronological control. During most of the time represented by the core, the lake was fresher than the modern lake, as evidenced by depleted ??18O and ??13C in bulk-sediment carbonate. ?? 2006 Elsevier Ltd. All rights reserved.

Using the Nobel Laureates in Economics to Teach Quantitative Methods

ERIC Educational Resources Information Center

Becker, William E.; Greene, William H.

2005-01-01

The authors show how the work of Nobel Laureates in economics can enhance student understanding and bring them up to date on topics such as probability, uncertainty and decision theory, hypothesis testing, regression to the mean, instrumental variable techniques, discrete choice modeling, and time-series analysis. (Contains 2 notes.)

Probability Distributions of Minkowski Distances between Discrete Random Variables.

ERIC Educational Resources Information Center

Schroger, Erich; And Others

1993-01-01

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

A Cognitive Diagnosis Model for Cognitively Based Multiple-Choice Options

ERIC Educational Resources Information Center

de la Torre, Jimmy

2009-01-01

Cognitive or skills diagnosis models are discrete latent variable models developed specifically for the purpose of identifying the presence or absence of multiple fine-grained skills. However, applications of these models typically involve dichotomous or dichotomized data, including data from multiple-choice (MC) assessments that are scored as…

Instructive Feedback Embedded within Group Instruction for Children Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Leaf, Justin B.; Cihon, Joseph H.; Alcalay, Aditt; Mitchell, Erin; Townley-Cochran, Donna; Miller, Kevin; Leaf, Ronald; Taubman, Mitchell; McEachin, John

2017-01-01

The present study evaluated the effects of instructive feedback embedded within a group discrete trial teaching to teach tact relations to nine children diagnosed with autism spectrum disorder using a nonconcurrent multiple-baseline design. Dependent variables included correct responses for: primary targets (directly taught), secondary targets…

Educational Attainment as Process: Using Hierarchical Discrete-Time Event History Analysis to Model Rate of Progress

ERIC Educational Resources Information Center

Bahr, Peter Riley

2009-01-01

Variables that address student enrollment patterns (e.g., persistence, enrollment inconsistency, completed credit hours, course credit load, course completion rate, procrastination) constitute a longstanding fixture of analytical strategies in educational research, particularly research that focuses on explaining variation in academic outcomes.…

Meteorology, Emissions, and Grid Resolution: Effects on Discrete and Probabilistic Model Performance

EPA Science Inventory

In this study, we analyze the impacts of perturbations in meteorology and emissions and variations in grid resolution on air quality forecast simulations. The meteorological perturbations con-sidered in this study introduce a typical variability of ~1°C, 250 - 500 m, 1 m/s, and 1...

AN ACCURATE AND EFFICIENT ALGORITHM FOR NUMERICAL SIMULATION OF CONDUCTION-TYPE PROBLEMS. (R824801)

EPA Science Inventory

Abstract

A modification of the finite analytic numerical method for conduction-type (diffusion) problems is presented. The finite analytic discretization scheme is derived by means of the Fourier series expansion for the most general case of nonuniform grid and variabl...

40 CFR 1042.505 - Testing engines using discrete-mode or ramped-modal duty cycles.

Code of Federal Regulations, 2013 CFR

2013-07-01

... used with) controllable-pitch propellers or with electrically coupled propellers, unless these engines... engines that are used with (or intended to be used with) controllable-pitch propellers or with electrically coupled propellers. Use this duty cycle also for variable-speed propulsion marine engines that are...

40 CFR 1042.505 - Testing engines using discrete-mode or ramped-modal duty cycles.

Code of Federal Regulations, 2011 CFR

2011-07-01

... used with) controllable-pitch propellers or with electrically coupled propellers, unless these engines... engines that are used with (or intended to be used with) controllable-pitch propellers or with electrically coupled propellers. Use this duty cycle also for variable-speed propulsion marine engines that are...

40 CFR 1042.505 - Testing engines using discrete-mode or ramped-modal duty cycles.

Code of Federal Regulations, 2012 CFR

2012-07-01

... used with) controllable-pitch propellers or with electrically coupled propellers, unless these engines... engines that are used with (or intended to be used with) controllable-pitch propellers or with electrically coupled propellers. Use this duty cycle also for variable-speed propulsion marine engines that are...

The Work for Pay Exchange in Public School Administration.

ERIC Educational Resources Information Center

McGee, William L.; Gibson, R. Oliver

This study explains assessments of fair pay for public school administrators in terms of some individual, job-related, and contextual variables, and it tests Jaques' hypothesis that time-span of discretion is the unconscious measure of level of work in bureaucracies. Data were gathered primarily through telephone interviews with…

ESTIMATION OF TOTAL DISSOLVED NITRATE LOAD IN NATURAL STREAM FLOWS USING AN IN-STREAM MONITOR

EPA Science Inventory

Estuaries respond rapidly to rain events and the nutrients carried by inflowing rivers such that discrete samples at weekly or monthly intervals are inadequate to catch the maxima and minima in nutrient variability. To acquire data with sufficient sampling frequency to realistica...

Upregulating endogenous genes by an RNA-programmable artificial transactivator

PubMed Central

Fimiani, Cristina; Goina, Elisa; Mallamaci, Antonello

2015-01-01

To promote expression of endogenous genes ad libitum, we developed a novel, programmable transcription factor prototype. Kept together via an MS2 coat protein/RNA interface, it includes a fixed, polypeptidic transactivating domain and a variable RNA domain that recognizes the desired gene. Thanks to this device, we specifically upregulated five genes, in cell lines and primary cultures of murine pallial precursors. Gene upregulation was small, however sufficient to robustly inhibit neuronal differentiation. The transactivator interacted with target gene chromatin via its RNA cofactor. Its activity was restricted to cells in which the target gene is normally transcribed. Our device might be useful for specific applications. However for this purpose, it will require an improvement of its transactivation power as well as a better characterization of its target specificity and mechanism of action. PMID:26152305

On multilevel RBF collocation to solve nonlinear PDEs arising from endogenous stochastic volatility models

NASA Astrophysics Data System (ADS)

Bastani, Ali Foroush; Dastgerdi, Maryam Vahid; Mighani, Abolfazl

2018-06-01

The main aim of this paper is the analytical and numerical study of a time-dependent second-order nonlinear partial differential equation (PDE) arising from the endogenous stochastic volatility model, introduced in [Bensoussan, A., Crouhy, M. and Galai, D., Stochastic equity volatility related to the leverage effect (I): equity volatility behavior. Applied Mathematical Finance, 1, 63-85, 1994]. As the first step, we derive a consistent set of initial and boundary conditions to complement the PDE, when the firm is financed by equity and debt. In the sequel, we propose a Newton-based iteration scheme for nonlinear parabolic PDEs which is an extension of a method for solving elliptic partial differential equations introduced in [Fasshauer, G. E., Newton iteration with multiquadrics for the solution of nonlinear PDEs. Computers and Mathematics with Applications, 43, 423-438, 2002]. The scheme is based on multilevel collocation using radial basis functions (RBFs) to solve the resulting locally linearized elliptic PDEs obtained at each level of the Newton iteration. We show the effectiveness of the resulting framework by solving a prototypical example from the field and compare the results with those obtained from three different techniques: (1) a finite difference discretization; (2) a naive RBF collocation and (3) a benchmark approximation, introduced for the first time in this paper. The numerical results confirm the robustness, higher convergence rate and good stability properties of the proposed scheme compared to other alternatives. We also comment on some possible research directions in this field.

Path analysis and multi-criteria decision making: an approach for multivariate model selection and analysis in health.

PubMed

Vasconcelos, A G; Almeida, R M; Nobre, F F

2001-08-01

This paper introduces an approach that includes non-quantitative factors for the selection and assessment of multivariate complex models in health. A goodness-of-fit based methodology combined with fuzzy multi-criteria decision-making approach is proposed for model selection. Models were obtained using the Path Analysis (PA) methodology in order to explain the interrelationship between health determinants and the post-neonatal component of infant mortality in 59 municipalities of Brazil in the year 1991. Socioeconomic and demographic factors were used as exogenous variables, and environmental, health service and agglomeration as endogenous variables. Five PA models were developed and accepted by statistical criteria of goodness-of fit. These models were then submitted to a group of experts, seeking to characterize their preferences, according to predefined criteria that tried to evaluate model relevance and plausibility. Fuzzy set techniques were used to rank the alternative models according to the number of times a model was superior to ("dominated") the others. The best-ranked model explained above 90% of the endogenous variables variation, and showed the favorable influences of income and education levels on post-neonatal mortality. It also showed the unfavorable effect on mortality of fast population growth, through precarious dwelling conditions and decreased access to sanitation. It was possible to aggregate expert opinions in model evaluation. The proposed procedure for model selection allowed the inclusion of subjective information in a clear and systematic manner.

A high-order positivity-preserving single-stage single-step method for the ideal magnetohydrodynamic equations

NASA Astrophysics Data System (ADS)

Christlieb, Andrew J.; Feng, Xiao; Seal, David C.; Tang, Qi

2016-07-01

We propose a high-order finite difference weighted ENO (WENO) method for the ideal magnetohydrodynamics (MHD) equations. The proposed method is single-stage (i.e., it has no internal stages to store), single-step (i.e., it has no time history that needs to be stored), maintains a discrete divergence-free condition on the magnetic field, and has the capacity to preserve the positivity of the density and pressure. To accomplish this, we use a Taylor discretization of the Picard integral formulation (PIF) of the finite difference WENO method proposed in Christlieb et al. (2015) [23], where the focus is on a high-order discretization of the fluxes (as opposed to the conserved variables). We use the version where fluxes are expanded to third-order accuracy in time, and for the fluid variables space is discretized using the classical fifth-order finite difference WENO discretization. We use constrained transport in order to obtain divergence-free magnetic fields, which means that we simultaneously evolve the magnetohydrodynamic (that has an evolution equation for the magnetic field) and magnetic potential equations alongside each other, and set the magnetic field to be the (discrete) curl of the magnetic potential after each time step. In this work, we compute these derivatives to fourth-order accuracy. In order to retain a single-stage, single-step method, we develop a novel Lax-Wendroff discretization for the evolution of the magnetic potential, where we start with technology used for Hamilton-Jacobi equations in order to construct a non-oscillatory magnetic field. The end result is an algorithm that is similar to our previous work Christlieb et al. (2014) [8], but this time the time stepping is replaced through a Taylor method with the addition of a positivity-preserving limiter. Finally, positivity preservation is realized by introducing a parameterized flux limiter that considers a linear combination of high and low-order numerical fluxes. The choice of the free parameter is then given in such a way that the fluxes are limited towards the low-order solver until positivity is attained. Given the lack of additional degrees of freedom in the system, this positivity limiter lacks energy conservation where the limiter turns on. However, this ingredient can be dropped for problems where the pressure does not become negative. We present two and three dimensional numerical results for several standard test problems including a smooth Alfvén wave (to verify formal order of accuracy), shock tube problems (to test the shock-capturing ability of the scheme), Orszag-Tang, and cloud shock interactions. These results assert the robustness and verify the high-order of accuracy of the proposed scheme.

Time-Structured and Net Intraindividual Variability: Tools for Examining the Development of Dynamic Characteristics and Processes

PubMed Central

Ram, Nilam; Gerstorf, Denis

2009-01-01

The study of intraindividual variability is the study of fluctuations, oscillations, adaptations, and “noise” in behavioral outcomes that manifest on micro-time scales. This paper provides a descriptive frame for the combined study of intraindividual variability and aging/development. At the conceptual level, we highlight that the study of intraindividual variability provides access to dynamic characteristics – construct-level descriptions of individuals' capacities for change (e.g., lability), and dynamic processes – the systematic changes individuals' exhibit in response to endogenous and exogenous influences (e.g., regulation). At the methodological level, we review how quantifications of net intraindividual variability (e.g., iSD) and models of time-structured intraindividual variability (e.g., time-series) are being used to measure and describe dynamic characteristics and processes. At the research design level, we point to the benefits of measurement burst study designs, wherein data are obtained across multiple time scales, for the study of development. PMID:20025395

A Probabilistic Framework for Peptide and Protein Quantification from Data-Dependent and Data-Independent LC-MS Proteomics Experiments

PubMed Central

Richardson, Keith; Denny, Richard; Hughes, Chris; Skilling, John; Sikora, Jacek; Dadlez, Michał; Manteca, Angel; Jung, Hye Ryung; Jensen, Ole Nørregaard; Redeker, Virginie; Melki, Ronald; Langridge, James I.; Vissers, Johannes P.C.

2013-01-01

A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods. PMID:22871168

Delay-induced wave instabilities in single-species reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Otto, Andereas; Wang, Jian; Radons, Günter

2017-11-01

The Turing (wave) instability is only possible in reaction-diffusion systems with more than one (two) components. Motivated by the fact that a time delay increases the dimension of a system, we investigate the presence of diffusion-driven instabilities in single-species reaction-diffusion systems with delay. The stability of arbitrary one-component systems with a single discrete delay, with distributed delay, or with a variable delay is systematically analyzed. We show that a wave instability can appear from an equilibrium of single-species reaction-diffusion systems with fluctuating or distributed delay, which is not possible in similar systems with constant discrete delay or without delay. More precisely, we show by basic analytic arguments and by numerical simulations that fast asymmetric delay fluctuations or asymmetrically distributed delays can lead to wave instabilities in these systems. Examples, for the resulting traveling waves are shown for a Fisher-KPP equation with distributed delay in the reaction term. In addition, we have studied diffusion-induced instabilities from homogeneous periodic orbits in the same systems with variable delay, where the homogeneous periodic orbits are attracting resonant periodic solutions of the system without diffusion, i.e., periodic orbits of the Hutchinson equation with time-varying delay. If diffusion is introduced, standing waves can emerge whose temporal period is equal to the period of the variable delay.

GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns

DOE PAGES

Senin, Pavel; Lin, Jessica; Wang, Xing; ...

2018-02-23

The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discoverymore » that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.« less

Chrestenson transform FPGA embedded factorizations.

PubMed

Corinthios, Michael J

2016-01-01

Chrestenson generalized Walsh transform factorizations for parallel processing imbedded implementations on field programmable gate arrays are presented. This general base transform, sometimes referred to as the Discrete Chrestenson transform, has received special attention in recent years. In fact, the Discrete Fourier transform and Walsh-Hadamard transform are but special cases of the Chrestenson generalized Walsh transform. Rotations of a base-p hypercube, where p is an arbitrary integer, are shown to produce dynamic contention-free memory allocation, in processor architecture. The approach is illustrated by factorizations involving the processing of matrices of the transform which are function of four variables. Parallel operations are implemented matrix multiplications. Each matrix, of dimension N × N, where N = p (n) , n integer, has a structure that depends on a variable parameter k that denotes the iteration number in the factorization process. The level of parallelism, in the form of M = p (m) processors can be chosen arbitrarily by varying m between zero to its maximum value of n - 1. The result is an equation describing the generalised parallelism factorization as a function of the four variables n, p, k and m. Applications of the approach are shown in relation to configuring field programmable gate arrays for digital signal processing applications.

GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns

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

Senin, Pavel; Lin, Jessica; Wang, Xing

The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, most existing detection algorithms require that the patterns have discriminative characteristics and have its length known in advance and provided as input, which is an unreasonable requirement for many real-world problems. In addition, patterns of similar structure, but of different lengths may co-exist in a time series. In order to address these issues, we have developed algorithms for variable-length time series pattern discoverymore » that are based on symbolic discretization and grammar inference—two techniques whose combination enables the structured reduction of the search space and discovery of the candidate patterns in linear time. In this work, we present GrammarViz 3.0—a software package that provides implementations of proposed algorithms and graphical user interface for interactive variable-length time series pattern discovery. The current version of the software provides an alternative grammar inference algorithm that improves the time series motif discovery workflow, and introduces an experimental procedure for automated discretization parameter selection that builds upon the minimum cardinality maximum cover principle and aids the time series recurrent and anomalous pattern discovery.« less

Improved detection of congestive heart failure via probabilistic symbolic pattern recognition and heart rate variability metrics.

PubMed

Mahajan, Ruhi; Viangteeravat, Teeradache; Akbilgic, Oguz

2017-12-01

A timely diagnosis of congestive heart failure (CHF) is crucial to evade a life-threatening event. This paper presents a novel probabilistic symbol pattern recognition (PSPR) approach to detect CHF in subjects from their cardiac interbeat (R-R) intervals. PSPR discretizes each continuous R-R interval time series by mapping them onto an eight-symbol alphabet and then models the pattern transition behavior in the symbolic representation of the series. The PSPR-based analysis of the discretized series from 107 subjects (69 normal and 38 CHF subjects) yielded discernible features to distinguish normal subjects and subjects with CHF. In addition to PSPR features, we also extracted features using the time-domain heart rate variability measures such as average and standard deviation of R-R intervals. An ensemble of bagged decision trees was used to classify two groups resulting in a five-fold cross-validation accuracy, specificity, and sensitivity of 98.1%, 100%, and 94.7%, respectively. However, a 20% holdout validation yielded an accuracy, specificity, and sensitivity of 99.5%, 100%, and 98.57%, respectively. Results from this study suggest that features obtained with the combination of PSPR and long-term heart rate variability measures can be used in developing automated CHF diagnosis tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates.

PubMed

Pardo-Igúzquiza, Eulogio; Chica-Olmo, Mario; Luque-Espinar, Juan A; Rodríguez-Galiano, Víctor

2015-11-01

Contamination by nitrates is an important cause of groundwater pollution and represents a potential risk to human health. Management decisions must be made using probability maps that assess the nitrate concentration potential of exceeding regulatory thresholds. However these maps are obtained with only a small number of sparse monitoring locations where the nitrate concentrations have been measured. It is therefore of great interest to have an efficient methodology for obtaining those probability maps. In this paper, we make use of the fact that the discrete probability density function is a compositional variable. The spatial discrete probability density function is estimated by compositional cokriging. There are several advantages in using this approach: (i) problems of classical indicator cokriging, like estimates outside the interval (0,1) and order relations, are avoided; (ii) secondary variables (e.g. aquifer parameters) can be included in the estimation of the probability maps; (iii) uncertainty maps of the probability maps can be obtained; (iv) finally there are modelling advantages because the variograms and cross-variograms of real variables that do not have the restrictions of indicator variograms and indicator cross-variograms. The methodology was applied to the Vega de Granada aquifer in Southern Spain and the advantages of the compositional cokriging approach were demonstrated. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimal resolution in maximum entropy image reconstruction from projections with multigrid acceleration

NASA Technical Reports Server (NTRS)

Limber, Mark A.; Manteuffel, Thomas A.; Mccormick, Stephen F.; Sholl, David S.

1993-01-01

We consider the problem of image reconstruction from a finite number of projections over the space L(sup 1)(Omega), where Omega is a compact subset of the set of Real numbers (exp 2). We prove that, given a discretization of the projection space, the function that generates the correct projection data and maximizes the Boltzmann-Shannon entropy is piecewise constant on a certain discretization of Omega, which we call the 'optimal grid'. It is on this grid that one obtains the maximum resolution given the problem setup. The size of this grid grows very quickly as the number of projections and number of cells per projection grow, indicating fast computational methods are essential to make its use feasible. We use a Fenchel duality formulation of the problem to keep the number of variables small while still using the optimal discretization, and propose a multilevel scheme to improve convergence of a simple cyclic maximization scheme applied to the dual problem.

Incompressible Navier-Stokes and parabolized Navier-Stokes solution procedures and computational techniques

NASA Technical Reports Server (NTRS)

Rubin, S. G.

1982-01-01

Recent developments with finite-difference techniques are emphasized. The quotation marks reflect the fact that any finite discretization procedure can be included in this category. Many so-called finite element collocation and galerkin methods can be reproduced by appropriate forms of the differential equations and discretization formulas. Many of the difficulties encountered in early Navier-Stokes calculations were inherent not only in the choice of the different equations (accuracy), but also in the method of solution or choice of algorithm (convergence and stability, in the manner in which the dependent variables or discretized equations are related (coupling), in the manner that boundary conditions are applied, in the manner that the coordinate mesh is specified (grid generation), and finally, in recognizing that for many high Reynolds number flows not all contributions to the Navier-Stokes equations are necessarily of equal importance (parabolization, preferred direction, pressure interaction, asymptotic and mathematical character). It is these elements that are reviewed. Several Navier-Stokes and parabolized Navier-Stokes formulations are also presented.

Auto-Bäcklund transformations for a matrix partial differential equation

NASA Astrophysics Data System (ADS)

Gordoa, P. R.; Pickering, A.

2018-07-01

We derive auto-Bäcklund transformations, analogous to those of the matrix second Painlevé equation, for a matrix partial differential equation. We also then use these auto-Bäcklund transformations to derive matrix equations involving shifts in a discrete variable, a process analogous to the use of the auto-Bäcklund transformations of the matrix second Painlevé equation to derive a discrete matrix first Painlevé equation. The equations thus derived then include amongst other examples a semidiscrete matrix equation which can be considered to be an extension of this discrete matrix first Painlevé equation. The application of this technique to the auto-Bäcklund transformations of the scalar case of our partial differential equation has not been considered before, and so the results obtained here in this scalar case are also new. Other equations obtained here using this technique include a scalar semidiscrete equation which arises in the case of the second Painlevé equation, and which does not seem to have been thus derived previously.