#### Sample records for quadratic inference functions

1. Confidence set inference with a prior quadratic bound

NASA Technical Reports Server (NTRS)

Backus, George E.

1989-01-01

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z=(z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y (sup 0) = (y (sub 1) (sup 0), ..., y (sub D (sup 0)), using full or partial knowledge of the statistical distribution of the random errors in y (sup 0). The data space Y containing y(sup 0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x, Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. Confidence set inference is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface.

2. Confidence set inference with a prior quadratic bound

NASA Technical Reports Server (NTRS)

Backus, George E.

1988-01-01

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

3. Integration of the Quadratic Function and Generalization

ERIC Educational Resources Information Center

Mitsuma, Kunio

2011-01-01

We will first recall useful formulas in integration that simplify the calculation of certain definite integrals with the quadratic function. A main formula relies only on the coefficients of the function. We will then explore a geometric proof of one of these formulas. Finally, we will extend the formulas to more general cases. (Contains 3…

4. Characterization of a Quadratic Function in Rn

ERIC Educational Resources Information Center

Xu, Conway

2010-01-01

It is proved that a scalar-valued function "f"(x) defined in "n"-dimensional space must be quadratic, if the intersection of tangent planes at x[subscript 1] and x[subscript 2] always contains the midpoint of the line joining x[subscript 1] and x[subscript 2]. This is the converse of a result of Stenlund proved in this JOURNAL in 2001.

5. Optimal Approximation of Quadratic Interval Functions

NASA Technical Reports Server (NTRS)

Koshelev, Misha; Taillibert, Patrick

1997-01-01

Measurements are never absolutely accurate, as a result, after each measurement, we do not get the exact value of the measured quantity; at best, we get an interval of its possible values, For dynamically changing quantities x, the additional problem is that we cannot measure them continuously; we can only measure them at certain discrete moments of time t(sub 1), t(sub 2), ... If we know that the value x(t(sub j)) at a moment t(sub j) of the last measurement was in the interval [x-(t(sub j)), x + (t(sub j))], and if we know the upper bound D on the rate with which x changes, then, for any given moment of time t, we can conclude that x(t) belongs to the interval [x-(t(sub j)) - D (t - t(sub j)), x + (t(sub j)) + D (t - t(sub j))]. This interval changes linearly with time, an is, therefore, called a linear interval function. When we process these intervals, we get an expression that is quadratic and higher order w.r.t. time t, Such "quadratic" intervals are difficult to process and therefore, it is necessary to approximate them by linear ones. In this paper, we describe an algorithm that gives the optimal approximation of quadratic interval functions by linear ones.

6. L -functions and class numbers of imaginary quadratic fields and of quadratic extensions of an imaginary quadratic field

Louboutin, Stephane

1992-07-01

Starting from the analytic class number formula involving its L-function, we first give an expression for the class number of an imaginary quadratic field which, in the case of large discriminants, provides us with a much more powerful numerical technique than that of counting the number of reduced definite positive binary quadratic forms, as has been used by Buell in order to compute his class number tables. Then, using class field theory, we will construct a periodic character &chi , defined on the ring of integers of a field K that is a quadratic extension of a principal imaginary quadratic field k, such that the zeta function of K is the product of the zeta function of k and of the L-function L(s,χ) . We will then determine an integral representation of this L-function that enables us to calculate the class number of K numerically, as soon as its regulator is known. It will also provide us with an upper bound for these class numbers, showing that Hua's bound for the class numbers of imaginary and real quadratic fields is not the best that one could expect. We give statistical results concerning the class numbers of the first 50000 quadratic extensions of {Q}(i) with prime relative discriminant (and with K/Q a non-Galois quartic extension). Our analytic calculation improves the algebraic calculation used by Lakein in the same way as the analytic calculation of the class numbers of real quadratic fields made by Williams and Broere improved the algebraic calculation consisting in counting the number of cycles of reduced ideals. Finally, we give upper bounds for class numbers of K that is a quadratic extension of an imaginary quadratic field k which is no longer assumed to be of class number one.

7. Quadratic function approaching method for magnetotelluric soundingdata inversion

SciTech Connect

Liangjun, Yan; Wenbao, Hu; Zhang, Keni

2004-04-05

The quadratic function approaching method (QFAM) is introduced for magnetotelluric sounding (MT) data inversion. The method takes the advantage of that quadratic function has single extreme value, which avoids leading to an inversion solution for local minimum and ensures the solution for global minimization of an objective function. The method does not need calculation of sensitivity matrix and not require a strict initial earth model. Examples for synthetic data and field measurement data indicate that the proposed inversion method is effective.

8. Four Labs to Introduce Quadratic Functions.

ERIC Educational Resources Information Center

Malone, Jim

1989-01-01

Describes four laboratory activities in algebra and precalculus classes that provide hands-on experiences related to functions: slowing down the acceleration of gravity; calculating the acceleration of gravity; generating a parabola using a steel ball and a tilted board; and photographing projectile motion. (YP)

9. The non-avian theropod quadrate I: standardized terminology with an overview of the anatomy and function.

PubMed

Hendrickx, Christophe; Araújo, Ricardo; Mateus, Octávio

2015-01-01

10. The non-avian theropod quadrate I: standardized terminology with an overview of the anatomy and function

PubMed Central

Araújo, Ricardo; Mateus, Octávio

2015-01-01

PubMed

Elmas, Begum; Tuncel, Murvet; Senel, Serap; Patir, S; Tuncel, Ali

2007-09-01

12. On the connection of the quadratic Lienard equation with an equation for the elliptic functions

Kudryashov, Nikolay A.; Sinelshchikov, Dmitry I.

2015-07-01

The quadratic Lienard equation is widely used in many applications. A connection between this equation and a linear second-order differential equation has been discussed. Here we show that the whole family of quadratic Lienard equations can be transformed into an equation for the elliptic functions. We demonstrate that this connection can be useful for finding explicit forms of general solutions of the quadratic Lienard equation. We provide several examples of application of our approach.

13. The wave function and minimum uncertainty function of the bound quadratic Hamiltonian system

NASA Technical Reports Server (NTRS)

Yeon, Kyu Hwang; Um, Chung IN; George, T. F.

1994-01-01

The bound quadratic Hamiltonian system is analyzed explicitly on the basis of quantum mechanics. We have derived the invariant quantity with an auxiliary equation as the classical equation of motion. With the use of this invariant it can be determined whether or not the system is bound. In bound system we have evaluated the exact eigenfunction and minimum uncertainty function through unitary transformation.

14. Computing the Partial Fraction Decomposition of Rational Functions with Irreducible Quadratic Factors in the Denominators

ERIC Educational Resources Information Center

Man, Yiu-Kwong

2012-01-01

In this note, a new method for computing the partial fraction decomposition of rational functions with irreducible quadratic factors in the denominators is presented. This method involves polynomial divisions and substitutions only, without having to solve for the complex roots of the irreducible quadratic polynomial or to solve a system of linear…

15. Automated calculation of anharmonic vibrational contributions to first hyperpolarizabilities: Quadratic response functions from vibrational configuration interaction wave functions

Hansen, Mikkel Bo; Christiansen, Ove; Hättig, Christof

2009-10-01

Quadratic response functions are derived and implemented for a vibrational configuration interaction state. Combined electronic and vibrational quadratic response functions are derived using Born-Oppenheimer vibronic product wave functions. Computational tractable expressions are derived for determining the total quadratic response contribution as a sum of contributions involving both electronic and vibrational linear and quadratic response functions. In the general frequency-dependent case this includes a new and more troublesome type of electronic linear response function. Pilot calculations for the FH, H2O, CH2O, and pyrrole molecules demonstrate the importance of vibrational contributions for accurate comparison to experiment and that the vibrational contributions in some cases can be very large. The calculation of transition properties between vibrational states is combined with sum-over-states expressions for analysis purposes. On the basis of this some simple analysis methods are suggested. Also, a preliminary study of the effect of finite lifetimes on quadratic response functions is presented.

16. Quadratic Interaction Functional for General Systems of Conservation Laws

Bianchini, Stefano; Modena, Stefano

2015-09-01

For the Glimm scheme approximation to the solution of the system of conservation laws in one space dimension with initial data u 0 with small total variation, we prove a quadratic (w.r.t. Tot. Var. ( u 0)) interaction estimate, which has been used in the literature for stability and convergence results. No assumptions on the structure of the flux f are made (apart from smoothness), and this estimate is the natural extension of the Glimm type interaction estimate for genuinely nonlinear systems. More precisely, we obtain the following results: a new analysis of the interaction estimates of simple waves;

17. Failures and Inabilities of High School Students about Quadratic Equations and Functions

ERIC Educational Resources Information Center

Memnun, Dilek Sezgin; Aydin, Bünyamin; Dinç, Emre; Çoban, Merve; Sevindik, Fatma

2015-01-01

In this research study, it was aimed to examine failures and inabilities of eleventh grade students about quadratic equations and functions. For this purpose, these students were asked ten open-ended questions. The analysis of the answers given by the students to these questions indicated that a significant part of these students had failures and…

18. Emotion suppression moderates the quadratic association between RSA and executive function

PubMed Central

Spangler, Derek P.; Bell, Martha Ann; Deater-Deckard, Kirby

2016-01-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated: (1) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (2) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a two-minute resting period during which ECG was continually assessed. In the next phase, the women completed an array of executive function and non-executive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. PMID:26018941

19. The Effects of an Undergraduate Algebra Course on Prospective Middle School Teachers' Understanding of Functions, Especially Quadratic Functions

ERIC Educational Resources Information Center

Duarte, Jonathan T.

2010-01-01

Although current reform movements have stressed the importance of developing prospective middle school mathematics teachers' subject matter knowledge and understandings, there is a dearth of research studies with regard to prospective middle school teachers' confidence and knowledge with respect to quadratic functions. This study was intended to…

20. Functional network inference of the suprachiasmatic nucleus.

PubMed

Abel, John H; Meeker, Kirsten; Granados-Fuentes, Daniel; St John, Peter C; Wang, Thomas J; Bales, Benjamin B; Doyle, Francis J; Herzog, Erik D; Petzold, Linda R

2016-04-19

In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure. PMID:27044085

1. On the use of the OCM's quadratic objective function as a pilot rating metric

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1981-01-01

A correlation between the magnitude of the quadratic objective function from an optimal control pilot model and the subjective rating of the vehicle and task provides a valuable tool for handling qualities research and flight control synthesis. An analysis of simulation results for fourteen aircraft configurations flight tested earlier was conducted. A fixed set of pilot model parameters, are found for all cases in modeling the simulated regulation task. The agreement obtained between performance statistics is shown and a strong correlation was obtained between the cost function and rating.

2. Quadratic and rate-independent limits for a large-deviations functional

Bonaschi, Giovanni A.; Peletier, Mark A.

2016-07-01

We construct a stochastic model showing the relationship between noise, gradient flows and rate-independent systems. The model consists of a one-dimensional birth-death process on a lattice, with rates derived from Kramers' law as an approximation of a Brownian motion on a wiggly energy landscape. Taking various limits, we show how to obtain a whole family of generalized gradient flows, ranging from quadratic to rate-independent ones, connected via  L log L' gradient flows. This is achieved via Mosco-convergence of the renormalized large-deviations rate functional of the stochastic process.

PubMed

Villa, Jesús; Rodríguez, Gustavo; Ivanov, Rumen; González, Efrén

2016-05-15

From the Bayesian regularization theory we derive a quadratic cost-function for integrating wave-front gradient fields. In the proposed cost-function, the term of conditional distribution uses a central-differences model to make the estimated function well consistent with the observed gradient field. As will be shown, the results obtained with the central-differences model are superior to the results obtained with the backward-differences model, commonly used in other integration techniques. As a regularization term we use an isotropic first-order differences Markov Random-Field model, which acts as a low-pass filter reducing the errors caused by the noise. We present simulated and real experiments of the proposal applied in the Foucault test, obtaining good results. PMID:27176991

4. An efficient ensemble of radial basis functions method based on quadratic programming

Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian

2016-07-01

Radial basis function (RBF) surrogate models have been widely applied in engineering design optimization problems to approximate computationally expensive simulations. Ensemble of radial basis functions (ERBF) using the weighted sum of stand-alone RBFs improves the approximation performance. To achieve a good trade-off between the accuracy and efficiency of the modelling process, this article presents a novel efficient ERBF method to determine the weights through solving a quadratic programming subproblem, denoted ERBF-QP. Several numerical benchmark functions are utilized to test the performance of the proposed ERBF-QP method. The results show that ERBF-QP can significantly improve the modelling efficiency compared with several existing ERBF methods. Moreover, ERBF-QP also provides satisfactory performance in terms of approximation accuracy. Finally, the ERBF-QP method is applied to a satellite multidisciplinary design optimization problem to illustrate its practicality and effectiveness for real-world engineering applications.

5. Intelligent, Robust Control of Deteriorated Turbofan Engines via Linear Parameter Varying Quadratic Lyapunov Function Design

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A method for accommodating engine deterioration via a scheduled Linear Parameter Varying Quadratic Lyapunov Function (LPVQLF)-Based controller is presented. The LPVQLF design methodology provides a means for developing unconditionally stable, robust control of Linear Parameter Varying (LPV) systems. The controller is scheduled on the Engine Deterioration Index, a function of estimated parameters that relate to engine health, and is computed using a multilayer feedforward neural network. Acceptable thrust response and tight control of exhaust gas temperature (EGT) is accomplished by adjusting the performance weights on these parameters for different levels of engine degradation. Nonlinear simulations demonstrate that the controller achieves specified performance objectives while being robust to engine deterioration as well as engine-to-engine variations.

6. Functional neuroanatomy of intuitive physical inference.

PubMed

Fischer, Jason; Mikhael, John G; Tenenbaum, Joshua B; Kanwisher, Nancy

2016-08-23

To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action. PMID:27503892

7. Robustness of the Quadratic Discriminant Function to correlated and uncorrelated normal training samples.

PubMed

Adebanji, Atinuke; Asamoah-Boaheng, Michael; Osei-Tutu, Olivia

2016-01-01

This study investigates the asymptotic performance of the Quadratic Discriminant Function (QDF) under correlated and uncorrelated normal training samples. This paper specifically examines the effect of correlation, uncorrelation considering different sample size ratios, number of variables and varying group centroid separators ([Formula: see text], [Formula: see text]) on classification accuracy of the QDF using simulated data from three populations ([Formula: see text]). The three populations differs with respect to their mean vector and covariance matrices. The results show the correlated normal distribution exhibits high coefficient of variation as [Formula: see text] increased. The QDF performed better when the training samples were correlated than when they were under uncorrelated normal distribution. The QDF performed better resulting in the reduction in misclassification error rates as group centroid separator increases with non increasing sample size under correlated training samples. PMID:26877900

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

PubMed Central

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

2015-01-01

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

9. Quadratic response functions in the time-dependent four-component Hartree-Fock approximation.

PubMed

Norman, Patrick; Jensen, Hans Jørgen Aa

2004-10-01

The second-order response function has been implemented in the time-dependent four-component Hartree-Fock approximation. The implementation is atomic orbital direct and formulated in terms of Fock-type matrices. It employs a quaternion symmetry scheme that provides maximum computational efficiency with consideration made to time-reversal and spatial symmetries. Calculations are presented for the electric dipole first-order hyperpolarizabilities of CsAg and CsAu in the second-harmonic generation optical process beta(-2omega;omega,omega). It is shown that relativistic corrections to property values are substantial in these cases--the orientationally averaged hyperpolarizabilities in the static limit beta(0;0,0) are overestimated in nonrelativistic calculations by 18% and 66% for CsAg and CsAu, respectively. The dispersion displays anomalies in the band gap region due to one- and two-photon resonances with nonrelativistically spin-forbidden states. Although weakly absorbing these states inflict divergences in the quadratic response function, since the response theoretical approach which is used adopts the infinite excited-state lifetime approximation. This fact calls for caution in applications where knowledge of the exact positioning of all excited states in the spectrum is unknown. PMID:15446908

10. Quadratic response functions in the time-dependent four-component Hartree-Fock approximation

Norman, Patrick; Jensen, Hans Jørgen Aa.

2004-10-01

The second-order response function has been implemented in the time-dependent four-component Hartree-Fock approximation. The implementation is atomic orbital direct and formulated in terms of Fock-type matrices. It employs a quaternion symmetry scheme that provides maximum computational efficiency with consideration made to time-reversal and spatial symmetries. Calculations are presented for the electric dipole first-order hyperpolarizabilities of CsAg and CsAu in the second-harmonic generation optical process β(-2ω;ω,ω). It is shown that relativistic corrections to property values are substantial in these cases—the orientationally averaged hyperpolarizabilities in the static limit β¯(0;0,0) are overestimated in nonrelativistic calculations by 18% and 66% for CsAg and CsAu, respectively. The dispersion displays anomalies in the band gap region due to one- and two-photon resonances with nonrelativistically spin-forbidden states. Although weakly absorbing these states inflict divergences in the quadratic response function, since the response theoretical approach which is used adopts the infinite excited-state lifetime approximation. This fact calls for caution in applications where knowledge of the exact positioning of all excited states in the spectrum is unknown.

11. High School Teachers' Use of Graphing Calculators When Teaching Linear and Quadratic Functions: Professed Beliefs and Observed Practice

ERIC Educational Resources Information Center

Molenje, Levi

2012-01-01

This study was designed to explore secondary mathematics teachers' beliefs about graphing calculators, their practices with the graphing calculators when teaching linear and quadratic functions, and the relationship between the teachers' beliefs and their practices. The study was conducted in two phases. In the first phase, 81 teachers…

12. Nonparametric inference on median residual life function.

PubMed

Jeong, Jong-Hyeon; Jung, Sin-Ho; Costantino, Joseph P

2008-03-01

A simple approach to the estimation of the median residual lifetime is proposed for a single group by inverting a function of the Kaplan-Meier estimators. A test statistic is proposed to compare two median residual lifetimes at any fixed time point. The test statistic does not involve estimation of the underlying probability density function of failure times under censoring. Extensive simulation studies are performed to validate the proposed test statistic in terms of type I error probabilities and powers at various time points. One of the oldest data sets from the National Surgical Adjuvant Breast and Bowel Project (NSABP), which has more than a quarter century of follow-up, is used to illustrate the method. The analysis results indicate that, without systematic post-operative therapy, a significant difference in median residual lifetimes between node-negative and node-positive breast cancer patients persists for about 10 years after surgery. The new estimates of the median residual lifetime could serve as a baseline for physicians to explain any incremental effects of post-operative treatments in terms of delaying breast cancer recurrence or prolonging remaining lifetimes of breast cancer patients. PMID:17501936

13. Functional inferences of environmental coccolithovirus biodiversity.

PubMed

Nissimov, Jozef I; Jones, Mark; Napier, Johnathan A; Munn, Colin B; Kimmance, Susan A; Allen, Michael J

2013-10-01

The cosmopolitan calcifying alga Emiliania huxleyi is one of the most abundant bloom forming coccolithophore species in the oceans and plays an important role in global biogeochemical cycling. Coccolithoviruses are a major cause of coccolithophore bloom termination and have been studied in laboratory, mesocosm and open ocean studies. However, little is known about the dynamic interactions between the host and its viruses, and less is known about the natural diversity and role of functionally important genes within natural coccolithovirus communities. Here, we investigate the temporal and spatial distribution of coccolithoviruses by the use of molecular fingerprinting techniques PCR, DGGE and genomic sequencing. The natural biodiversity of the virus genes encoding the major capsid protein (MCP) and serine palmitoyltransferase (SPT) were analysed in samples obtained from the Atlantic Meridional Transect (AMT), the North Sea and the L4 site in the Western Channel Observatory. We discovered nine new coccolithovirus genotypes across the AMT and L4 site, with the majority of MCP sequences observed at the deep chlorophyll maximum layer of the sampled sites on the transect. We also found four new SPT gene variations in the North Sea and at L4. Their translated fragments and the full protein sequence of SPT from laboratory strains EhV-86 and EhV-99B1 were modelled and revealed that the theoretical fold differs among strains. Variation identified in the structural distance between the two domains of the SPT protein may have an impact on the catalytic capabilities of its active site. In summary, the combined use of 'standard' markers (i.e. MCP), in combination with metabolically relevant markers (i.e. SPT) are useful in the study of the phylogeny and functional biodiversity of coccolithoviruses, and can provide an interesting intracellular insight into the evolution of these viruses and their ability to infect and replicate within their algal hosts. PMID:24006045

14. Students' Understanding of the Concept of Vertex of Quadratic Functions in Relation to Their Personal Meaning of the Concept of Vertex

ERIC Educational Resources Information Center

Childers, Annie Burns; Vidakovic, Draga

2014-01-01

This paper explores sixty-six students' personal meaning and interpretation of the vertex of a quadratic function in relation to their understanding of quadratic functions in two different representations, algebraic and word problem. Several categories emerged from students' personal meaning of the vertex including vertex as maximum or…

ERIC Educational Resources Information Center

Fay, Temple H.

2012-01-01

Quadratic friction involves a discontinuous damping term in equations of motion in order that the frictional force always opposes the direction of the motion. Perhaps for this reason this topic is usually omitted from beginning texts in differential equations and physics. However, quadratic damping is more realistic than viscous damping in many…

16. A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

Xu, Jiuping; Li, Jun

2002-09-01

In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

17. Minimization of the root of a quadratic functional under a system of affine equality constraints with application to portfolio management

Landsman, Zinoviy

2008-10-01

We present an explicit closed form solution of the problem of minimizing the root of a quadratic functional subject to a system of affine constraints. The result generalizes Z. Landsman, Minimization of the root of a quadratic functional under an affine equality constraint, J. Comput. Appl. Math. 2007, to appear, see , articles in press, where the optimization problem was solved under only one linear constraint. This is of interest for solving significant problems pertaining to financial economics as well as some classes of feasibility and optimization problems which frequently occur in tomography and other fields. The results are illustrated in the problem of optimal portfolio selection and the particular case when the expected return of finance portfolio is certain is discussed.

18. Classical methods for interpreting objective function minimization as intelligent inference

SciTech Connect

Golden, R.M.

1996-12-31

Most recognition algorithms and neural networks can be formally viewed as seeking a minimum value of an appropriate objective function during either classification or learning phases. The goal of this paper is to argue that in order to show a recognition algorithm is making intelligent inferences, it is not sufficient to show that the recognition algorithm is computing (or trying to compute) the global minimum of some objective function. One must explicitly define a {open_quotes}relational system{close_quotes} for the recognition algorithm or neural network which identifies the: (i) sample space, (ii) the relevant sigmafield of events generated by the sample space, and (iii) the {open_quotes}relation{close_quotes} for that relational system. Only when such a {open_quotes}relational system{close_quotes} is properly defined, is it possible to formally establish the sense in which computing the global minimum of an objective function is an intelligent, inference.

19. Legendre-tau approximation for functional differential equations. Part 2: The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, K.; Teglas, R.

1984-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

20. Legendre-tau approximation for functional differential equations. II - The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, Kazufumi; Teglas, Russell

1987-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

1. Receiver function deconvolution using transdimensional hierarchical Bayesian inference

Kolb, J. M.; Lekić, V.

2014-06-01

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

2. Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

SciTech Connect

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

3. Beyond the bounds of orthology: functional inference from metagenomic context.

PubMed

Vey, Gregory; Moreno-Hagelsieb, Gabriel

2010-07-01

The effectiveness of the computational inference of function by genomic context is bounded by the diversity of known microbial genomes. Although metagenomes offer access to previously inaccessible organisms, their fragmentary nature prevents the conventional establishment of orthologous relationships required for reliably predicting functional interactions. We introduce a protocol for the prediction of functional interactions using data sources without information about orthologous relationships. To illustrate this process, we use the Sargasso Sea metagenome to construct a functional interaction network for the Escherichia coli K12 genome. We identify two reliability metrics, target intergenic distance and source interaction count, and apply them to selectively filter the predictions retained to construct the network of functional interactions. The resulting network contains 2297 nodes with 10 072 edges with a positive predictive value of 0.80. The metagenome yielded 8423 functional interactions beyond those found using only the genomic orthologs as a data source. This amounted to a 134% increase in the total number of functional interactions that are predicted by combining the metagenome and the genomic orthologs versus the genomic orthologs alone. In the absence of detectable orthologous relationships it remains feasible to derive a reliable set of predicted functional interactions. This offers a strategy for harnessing other metagenomes and homologs in general. Because metagenomes allow access to previously unreachable microorganisms, this will result in expanding the universe of known functional interactions thus furthering our understanding of functional organization. PMID:20419183

4. Network inference from functional experimental data (Conference Presentation)

Desrosiers, Patrick; Labrecque, Simon; Tremblay, Maxime; Bélanger, Mathieu; De Dorlodot, Bertrand; Côté, Daniel C.

2016-03-01

Functional connectivity maps of neuronal networks are critical tools to understand how neurons form circuits, how information is encoded and processed by neurons, how memory is shaped, and how these basic processes are altered under pathological conditions. Current light microscopy allows to observe calcium or electrical activity of thousands of neurons simultaneously, yet assessing comprehensive connectivity maps directly from such data remains a non-trivial analytical task. There exist simple statistical methods, such as cross-correlation and Granger causality, but they only detect linear interactions between neurons. Other more involved inference methods inspired by information theory, such as mutual information and transfer entropy, identify more accurately connections between neurons but also require more computational resources. We carried out a comparative study of common connectivity inference methods. The relative accuracy and computational cost of each method was determined via simulated fluorescence traces generated with realistic computational models of interacting neurons in networks of different topologies (clustered or non-clustered) and sizes (10-1000 neurons). To bridge the computational and experimental works, we observed the intracellular calcium activity of live hippocampal neuronal cultures infected with the fluorescent calcium marker GCaMP6f. The spontaneous activity of the networks, consisting of 50-100 neurons per field of view, was recorded from 20 to 50 Hz on a microscope controlled by a homemade software. We implemented all connectivity inference methods in the software, which rapidly loads calcium fluorescence movies, segments the images, extracts the fluorescence traces, and assesses the functional connections (with strengths and directions) between each pair of neurons. We used this software to assess, in real time, the functional connectivity from real calcium imaging data in basal conditions, under plasticity protocols, and epileptic

5. Visualization of group inference data in functional neuroimaging.

PubMed

Gläscher, Jan

2009-01-01

While thresholded statistical parametric maps can convey an accurate account for the location and spatial extent of an effect in functional neuroimaging studies, their use is somewhat limited for characterizing more complex experimental effects, such as interactions in a factorial design. The resulting necessity for plotting the underlying data has long been recognized. Statistical Parametric Mapping (SPM) is a widely used software package for analyzing functional neuroimaging data that offers a variety of options for visualizing data from first level analyses. However, nowadays, the thrust of the statistical inference lies at the second level thus allowing for population inference. Unfortunately, the options for visualizing data from second level analyses are quite sparse. rfxplot is a new toolbox designed to alleviate this problem by providing a comprehensive array of options for plotting data from within second level analyses in SPM. These include graphs of average effect sizes (across subjects), averaged fitted responses and event-related blood oxygen level-dependent (BOLD) time courses. All data are retrieved from the underlying first level analyses and voxel selection can be tailored to the maximum effect in each subject within a defined search volume. All plot configurations can be easily configured via a graphical user-interface as well as non-interactively via a script. The large variety of plot options renders rfxplot suitable both for data exploration as well as producing high-quality figures for publications. PMID:19140033

6. Explanation and inference: mechanistic and functional explanations guide property generalization

PubMed Central

Lombrozo, Tania; Gwynne, Nicholas Z.

2014-01-01

The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations. PMID:25309384

7. Medical-Legal Inferences From Functional Neuroimaging Evidence.

PubMed

Mayberg

1996-07-01

Positron emission (PET) and single-photon emission tomography (SPECT) are validated functional imaging techniques for the in vivo measurement of many neuro-phsyiological and neurochemical parameters. Research studies of patients with a broad range of neurological and psychiatric illness have been published. Reproducible and specific patterns of altered cerebral blood flow and glucose metabolism, however, have been demonstrated and confirmed for only a limited number of specific illnesses. The association of functional scan patterns with specific deficits is less conclusive. Correlations of regional abnormalities with clinical symptoms such as motor weakness, aphasia, and visual spatial dysfunction are the most reproducible but are more poorly localized than lesion-deficit studies would suggest. Findings are even less consistent for nonlocalizing behavioral symptoms such as memory difficulties, poor concentration, irritability, or chronic pain, and no reliable patterns have been demonstrated. In a forensic context, homicidal and sadistic tendencies, aberrant sexual drive, violent impulsivity, psychopathic and sociopathic personality traits, as well as impaired judgement and poor insight, have no known PET or SPECT patterns, and their presence in an individual with any PET or SPECT scan finding cannot be inferred or concluded. Furthermore, the reliable prediction of any specific neurological, psychiatric, or behavioral deficits from specific scan findings has not been demonstrated. Unambiguous results from experiments designed to specifically examine the causative relationships between regional brain dysfunction and these types of complex behaviors are needed before any introduction of functional scans into the courts can be considered scientifically justified or legally admissible. PMID:10320420

8. Constructing a Flexible Likelihood Function for Spectroscopic Inference

Czekala, Ian; Andrews, Sean M.; Mandel, Kaisey S.; Hogg, David W.; Green, Gregory M.

2015-10-01

We present a modular, extensible likelihood framework for spectroscopic inference based on synthetic model spectra. The subtraction of an imperfect model from a continuously sampled spectrum introduces covariance between adjacent datapoints (pixels) into the residual spectrum. For the high signal-to-noise data with large spectral range that is commonly employed in stellar astrophysics, that covariant structure can lead to dramatically underestimated parameter uncertainties (and, in some cases, biases). We construct a likelihood function that accounts for the structure of the covariance matrix, utilizing the machinery of Gaussian process kernels. This framework specifically addresses the common problem of mismatches in model spectral line strengths (with respect to data) due to intrinsic model imperfections (e.g., in the atomic/molecular databases or opacity prescriptions) by developing a novel local covariance kernel formalism that identifies and self-consistently downweights pathological spectral line “outliers.” By fitting many spectra in a hierarchical manner, these local kernels provide a mechanism to learn about and build data-driven corrections to synthetic spectral libraries. An open-source software implementation of this approach is available at http://iancze.github.io/Starfish, including a sophisticated probabilistic scheme for spectral interpolation when using model libraries that are sparsely sampled in the stellar parameters. We demonstrate some salient features of the framework by fitting the high-resolution V-band spectrum of WASP-14, an F5 dwarf with a transiting exoplanet, and the moderate-resolution K-band spectrum of Gliese 51, an M5 field dwarf.

9. Time domain simulation of tandem silicon solar cells with optimal textured light trapping enabled by the quadratic complex rational function.

PubMed

Chung, H; Jung, K-Y; Tee, X T; Bermel, P

2014-05-01

Amorphous silicon/crystalline silicon (a-Si/c-Si) micromorph tandem cells, with best confirmed efficiency of 12.3%, have yet to fully approach their theoretical performance limits. In this work, we consider a strategy for improving the light trapping and charge collection of a-Si/c-Si micromorph tandem cells using random texturing with adjustable short-range correlations and long-range periodicity. In order to consider the full-spectrum absorption of a-Si and c-Si, a novel dispersion model known as a quadratic complex rational function (QCRF) is applied to photovoltaic materials (e.g., a-Si, c-Si and silver). It has the advantage of accurately modeling experimental semiconductor dielectric values over the entire relevant solar bandwidth from 300-1000 nm in a single simulation. This wide-band dispersion model is then used to model a silicon tandem cell stack (ITO/a-Si:H/c-Si:H/silver), as two parameters are varied: maximum texturing height h and correlation parameter f. Even without any other light trapping methods, our front texturing method demonstrates 12.37% stabilized cell efficiency and 12.79 mA/cm² in a 2 μm-thick active layer. PMID:24922389

10. Analytic derivative couplings in time-dependent density functional theory: Quadratic response theory versus pseudo-wavefunction approach

SciTech Connect

Zhang, Xing; Herbert, John M.

2015-02-14

We revisit the formalism for analytic derivative couplings between excited states in time-dependent density functional theory (TDDFT). We derive and implement these couplings using quadratic response theory, then numerically compare this response-theory formulation to couplings implemented previously based on a pseudo-wavefunction formalism and direct differentiation of the Kohn-Sham determinant. Numerical results, including comparison to full configuration interaction calculations, suggest that the two approaches perform equally well for many molecular systems, provided that the underlying DFT method affords accurate potential energy surfaces. The response contributions are found to be important for certain systems with high symmetry, but can be calculated with only a moderate increase in computational cost beyond what is required for the pseudo-wavefunction approach. In the case of spin-flip TDDFT, we provide a formal proof that the derivative couplings obtained using response theory are identical to those obtained from the pseudo-wavefunction formulation, which validates our previous implementation based on the latter formalism.

11. Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

SciTech Connect

Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

2007-09-02

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

12. OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE

PubMed Central

Xie, Xianchao; Kou, S. C.; Brown, Lawrence

2015-01-01

This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results. PMID:27041778

ERIC Educational Resources Information Center

2012-01-01

We show that there are exactly four quadratic polynomials, Q(x) = x [superscript 2] + ax + b, such that (x[superscript 2] + ax + b) (x[superscript 2] - ax + b) = (x[superscript 4] + ax[superscript 2] + b). For n = 1, 2, ..., these quadratic polynomials can be written as the product of N = 2[superscript n] quadratic polynomials in x[superscript…

14. Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come. PMID:27034708

15. Bayesian Inference for Functional Dynamics Exploring in fMRI Data

PubMed Central

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come. PMID:27034708

16. Role of Utility and Inference in the Evolution of Functional Information

PubMed Central

Sharov, Alexei A.

2009-01-01

Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are

17. Craniofacial biomechanics and functional and dietary inferences in hominin paleontology.

PubMed

Grine, Frederick E; Judex, Stefan; Daegling, David J; Ozcivici, Engin; Ungar, Peter S; Teaford, Mark F; Sponheimer, Matt; Scott, Jessica; Scott, Robert S; Walker, Alan

2010-04-01

Finite element analysis (FEA) is a potentially powerful tool by which the mechanical behaviors of different skeletal and dental designs can be investigated, and, as such, has become increasingly popular for biomechanical modeling and inferring the behavior of extinct organisms. However, the use of FEA to extrapolate from characterization of the mechanical environment to questions of trophic or ecological adaptation in a fossil taxon is both challenging and perilous. Here, we consider the problems and prospects of FEA applications in paleoanthropology, and provide a critical examination of one such study of the trophic adaptations of Australopithecus africanus. This particular FEA is evaluated with regard to 1) the nature of the A. africanus cranial composite, 2) model validation, 3) decisions made with respect to model parameters, 4) adequacy of data presentation, and 5) interpretation of the results. Each suggests that the results reflect methodological decisions as much as any underlying biological significance. Notwithstanding these issues, this model yields predictions that follow from the posited emphasis on premolar use by A. africanus. These predictions are tested with data from the paleontological record, including a phylogenetically-informed consideration of relative premolar size, and postcanine microwear fabrics and antemortem enamel chipping. In each instance, the data fail to conform to predictions from the model. This model thus serves to emphasize the need for caution in the application of FEA in paleoanthropological enquiry. Theoretical models can be instrumental in the construction of testable hypotheses; but ultimately, the studies that serve to test these hypotheses - rather than data from the models - should remain the source of information pertaining to hominin paleobiology and evolution. PMID:20227747

18. Generalised partition functions: inferences on phase space distributions

Treumann, Rudolf A.; Baumjohann, Wolfgang

2016-06-01

It is demonstrated that the statistical mechanical partition function can be used to construct various different forms of phase space distributions. This indicates that its structure is not restricted to the Gibbs-Boltzmann factor prescription which is based on counting statistics. With the widely used replacement of the Boltzmann factor by a generalised Lorentzian (also known as the q-deformed exponential function, where κ = 1/|q - 1|, with κ, q ∈ R) both the kappa-Bose and kappa-Fermi partition functions are obtained in quite a straightforward way, from which the conventional Bose and Fermi distributions follow for κ → ∞. For κ ≠ ∞ these are subject to the restrictions that they can be used only at temperatures far from zero. They thus, as shown earlier, have little value for quantum physics. This is reasonable, because physical κ systems imply strong correlations which are absent at zero temperature where apart from stochastics all dynamical interactions are frozen. In the classical large temperature limit one obtains physically reasonable κ distributions which depend on energy respectively momentum as well as on chemical potential. Looking for other functional dependencies, we examine Bessel functions whether they can be used for obtaining valid distributions. Again and for the same reason, no Fermi and Bose distributions exist in the low temperature limit. However, a classical Bessel-Boltzmann distribution can be constructed which is a Bessel-modified Lorentzian distribution. Whether it makes any physical sense remains an open question. This is not investigated here. The choice of Bessel functions is motivated solely by their convergence properties and not by reference to any physical demands. This result suggests that the Gibbs-Boltzmann partition function is fundamental not only to Gibbs-Boltzmann but also to a large class of generalised Lorentzian distributions as well as to the corresponding nonextensive statistical mechanics.

19. On the functional equivalence of fuzzy inference systems and spline-based networks.

PubMed

Hunt, K J; Haas, R; Brown, M

1995-06-01

The conditions under which spline-based networks are functionally equivalent to the Takagi-Sugeno-model of fuzzy inference are formally established. We consider a generalized form of basis function network whose basis functions are splines. The result admits a wide range of fuzzy membership functions which are commonly encountered in fuzzy systems design. We use the theoretical background of functional equivalence to develop a hybrid fuzzy-spline net for inverse dynamic modeling of a hydraulically driven robot manipulator. PMID:7496588

20. Denoising inferred functional association networks obtained by gene fusion analysis

PubMed Central

Kamburov, Atanas; Goldovsky, Leon; Freilich, Shiri; Kapazoglou, Aliki; Kunin, Victor; Enright, Anton J; Tsaftaris, Athanasios; Ouzounis, Christos A

2007-01-01

Background Gene fusion detection – also known as the 'Rosetta Stone' method – involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. The precision of this method typically improves with an ever-increasing number of reference genomes. Results In order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for 184 genomes using an efficient variant of a previously developed protocol. By analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. With this generally applicable approach, we generate a robust set of over 2 million distinct and testable interactions encompassing 696,894 proteins in 184 species or strains, most of which have never been the subject of high-throughput experimental proteomics. We investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. We also examine the percentage of component (and composite) proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions. Conclusion We illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function. PMID:18081932

1. Structure and function of the mammalian middle ear. II: Inferring function from structure.

PubMed

Mason, Matthew J

2016-02-01

Anatomists and zoologists who study middle ear morphology are often interested to know what the structure of an ear can reveal about the auditory acuity and hearing range of the animal in question. This paper represents an introduction to middle ear function targetted towards biological scientists with little experience in the field of auditory acoustics. Simple models of impedance matching are first described, based on the familiar concepts of the area and lever ratios of the middle ear. However, using the Mongolian gerbil Meriones unguiculatus as a test case, it is shown that the predictions made by such 'ideal transformer' models are generally not consistent with measurements derived from recent experimental studies. Electrical analogue models represent a better way to understand some of the complex, frequency-dependent responses of the middle ear: these have been used to model the effects of middle ear subcavities, and the possible function of the auditory ossicles as a transmission line. The concepts behind such models are explained here, again aimed at those with little background knowledge. Functional inferences based on middle ear anatomy are more likely to be valid at low frequencies. Acoustic impedance at low frequencies is dominated by compliance; expanded middle ear cavities, found in small desert mammals including gerbils, jerboas and the sengi Macroscelides, are expected to improve low-frequency sound transmission, as long as the ossicular system is not too stiff. PMID:26100915

2. An Unexpected Influence on a Quadratic

ERIC Educational Resources Information Center

Davis, Jon D.

2013-01-01

Using technology to explore the coefficients of a quadratic equation can lead to an unexpected result. This article describes an investigation that involves sliders and dynamically linked representations. It guides students to notice the effect that the parameter "a" has on the graphical representation of a quadratic function in the form…

3. Crustal structure beneath northeast India inferred from receiver function modeling

Borah, Kajaljyoti; Bora, Dipok K.; Goyal, Ayush; Kumar, Raju

2016-09-01

We estimated crustal shear velocity structure beneath ten broadband seismic stations of northeast India, by using H-Vp/Vs stacking method and a non-linear direct search approach, Neighbourhood Algorithm (NA) technique followed by joint inversion of Rayleigh wave group velocity and receiver function, calculated from teleseismic earthquakes data. Results show significant variations of thickness, shear velocities (Vs) and Vp/Vs ratio in the crust of the study region. The inverted shear wave velocity models show crustal thickness variations of 32-36 km in Shillong Plateau (North), 36-40 in Assam Valley and ∼44 km in Lesser Himalaya (South). Average Vp/Vs ratio in Shillong Plateau is less (1.73-1.77) compared to Assam Valley and Lesser Himalaya (∼1.80). Average crustal shear velocity beneath the study region varies from 3.4 to 3.5 km/s. Sediment structure beneath Shillong Plateau and Assam Valley shows 1-2 km thick sediment layer with low Vs (2.5-2.9 km/s) and high Vp/Vs ratio (1.8-2.1), while it is observed to be of greater thickness (4 km) with similar Vs and high Vp/Vs (∼2.5) in RUP (Lesser Himalaya). Both Shillong Plateau and Assam Valley show thick upper and middle crust (10-20 km), and thin (4-9 km) lower crust. Average Vp/Vs ratio in Assam Valley and Shillong Plateau suggest that the crust is felsic-to-intermediate and intermediate-to-mafic beneath Shillong Plateau and Assam Valley, respectively. Results show that lower crust rocks beneath the Shillong Plateau and Assam Valley lies between mafic granulite and mafic garnet granulite.

SciTech Connect

Walsh, Timothy Francis; Day, David Minot

2007-04-01

In this report we will describe some nonlinear eigenvalue problems that arise in the areas of solid mechanics, acoustics, and coupled structural acoustics. We will focus mostly on quadratic eigenvalue problems, which are a special case of nonlinear eigenvalue problems. Algorithms for solving the quadratic eigenvalue problem will be presented, along with some example calculations.

5. Pragmatic Inference Abilities in Individuals with Asperger Syndrome or High-Functioning Autism. A Review

ERIC Educational Resources Information Center

Loukusa, Soile; Moilanen, Irma

2009-01-01

This review summarizes studies involving pragmatic language comprehension and inference abilities in individuals with Asperger syndrome or high-functioning autism. Systematic searches of three electronic databases, selected journals, and reference lists identified 20 studies meeting the inclusion criteria. These studies were evaluated in terms of:…

6. Sufficient Conditions for Global Minimality of Metastable States in a Class of Non-convex Functionals: A Simple Approach Via Quadratic Lower Bounds

Shirokoff, David; Choksi, Rustum; Nave, Jean-Christophe

2015-06-01

We consider mass-constrained minimizers for a class of non-convex energy functionals involving a double-well potential. Based upon global quadratic lower bounds to the energy, we introduce a simple strategy to find sufficient conditions on a given critical point (metastable state) to be a global minimizer. We show that this strategy works well for the one exact and known metastable state: the constant state. In doing so, we numerically derive an almost optimal lower bound for both the order-disorder transition curve of the Ohta-Kawasaki energy and the liquid-solid interface of the phase-field crystal energy. We discuss how this strategy extends to non-constant computed metastable states, and the resulting symmetry issues that one must overcome. We give a preliminary analysis of these symmetry issues by addressing the global optimality of a computed lamellar structure for the Ohta-Kawasaki energy in one (1D) and two (2D) space dimensions. We also consider global optimality of a non-constant state for a spatially in-homogenous perturbation of the 2D Ohta-Kawasaki energy. Finally we use one of our simple quadratic lower bounds to rigorously prove that for certain values of the Ohta-Kawasaki parameter and aspect ratio of an asymmetric torus, any global minimizer for the 1D problem is automatically a global minimizer for the 2D problem on the asymmetric torus.

7. Function formula oriented construction of Bayesian inference nets for diagnosis of cardiovascular disease.

PubMed

Sekar, Booma Devi; Dong, Mingchui

2014-01-01

An intelligent cardiovascular disease (CVD) diagnosis system using hemodynamic parameters (HDPs) derived from sphygmogram (SPG) signal is presented to support the emerging patient-centric healthcare models. To replicate clinical approach of diagnosis through a staged decision process, the Bayesian inference nets (BIN) are adapted. New approaches to construct a hierarchical multistage BIN using defined function formulas and a method employing fuzzy logic (FL) technology to quantify inference nodes with dynamic values of statistical parameters are proposed. The suggested methodology is validated by constructing hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose various heart pathologies from the deduced HDPs. The preliminary diagnostic results show that the proposed methodology has salient validity and effectiveness in the diagnosis of cardiovascular disease. PMID:25247174

8. Function Formula Oriented Construction of Bayesian Inference Nets for Diagnosis of Cardiovascular Disease

PubMed Central

Sekar, Booma Devi; Dong, Mingchui

2014-01-01

An intelligent cardiovascular disease (CVD) diagnosis system using hemodynamic parameters (HDPs) derived from sphygmogram (SPG) signal is presented to support the emerging patient-centric healthcare models. To replicate clinical approach of diagnosis through a staged decision process, the Bayesian inference nets (BIN) are adapted. New approaches to construct a hierarchical multistage BIN using defined function formulas and a method employing fuzzy logic (FL) technology to quantify inference nodes with dynamic values of statistical parameters are proposed. The suggested methodology is validated by constructing hierarchical Bayesian fuzzy inference nets (HBFIN) to diagnose various heart pathologies from the deduced HDPs. The preliminary diagnostic results show that the proposed methodology has salient validity and effectiveness in the diagnosis of cardiovascular disease. PMID:25247174

2012-06-01

We show that there are exactly four quadratic polynomials, Q(x) = x 2 + ax + b, such that For n = 1, 2, … , these quadratic polynomials can be written as the product of N = 2 n quadratic polynomials in x 1/N , namely, ? , where w N is the Nth root of 1.

10. A Model-Based Analysis to Infer the Functional Content of a Gene List

PubMed Central

Newton, Michael A.; He, Qiuling; Kendziorski, Christina

2012-01-01

An important challenge in statistical genomics concerns integrating experimental data with exogenous information about gene function. A number of statistical methods are available to address this challenge, but most do not accommodate complexities in the functional record. To infer activity of a functional category (e.g., a gene ontology term), most methods use gene-level data on that category, but do not use other functional properties of the same genes. Not doing so creates undue errors in inference. Recent developments in model-based category analysis aim to overcome this difficulty, but in attempting to do so they are faced with serious computational problems. This paper investigates statistical properties and the structure of posterior computation in one such model for the analysis of functional category data. We examine the graphical structures underlying posterior computation in the original parameterization and in a new parameterization aimed at leveraging elements of the model. We characterize identifiability of the underlying activation states, describe a new prior distribution, and introduce approximations that aim to support numerical methods for posterior inference. PMID:22499692

11. Vikodak - A Modular Framework for Inferring Functional Potential of Microbial Communities from 16S Metagenomic Datasets

PubMed Central

Nagpal, Sunil; Haque, Mohammed Monzoorul; Mande, Sharmila S.

2016-01-01

Background The overall metabolic/functional potential of any given environmental niche is a function of the sum total of genes/proteins/enzymes that are encoded and expressed by various interacting microbes residing in that niche. Consequently, prior (collated) information pertaining to genes, enzymes encoded by the resident microbes can aid in indirectly (re)constructing/ inferring the metabolic/ functional potential of a given microbial community (given its taxonomic abundance profile). In this study, we present Vikodak—a multi-modular package that is based on the above assumption and automates inferring and/ or comparing the functional characteristics of an environment using taxonomic abundance generated from one or more environmental sample datasets. With the underlying assumptions of co-metabolism and independent contributions of different microbes in a community, a concerted effort has been made to accommodate microbial co-existence patterns in various modules incorporated in Vikodak. Results Validation experiments on over 1400 metagenomic samples have confirmed the utility of Vikodak in (a) deciphering enzyme abundance profiles of any KEGG metabolic pathway, (b) functional resolution of distinct metagenomic environments, (c) inferring patterns of functional interaction between resident microbes, and (d) automating statistical comparison of functional features of studied microbiomes. Novel features incorporated in Vikodak also facilitate automatic removal of false positives and spurious functional predictions. Conclusions With novel provisions for comprehensive functional analysis, inclusion of microbial co-existence pattern based algorithms, automated inter-environment comparisons; in-depth analysis of individual metabolic pathways and greater flexibilities at the user end, Vikodak is expected to be an important value addition to the family of existing tools for 16S based function prediction. Availability and Implementation A web implementation of Vikodak

12. Approximation Of Multi-Valued Inverse Functions Using Clustering And Sugeno Fuzzy Inference

NASA Technical Reports Server (NTRS)

Walden, Maria A.; Bikdash, Marwan; Homaifar, Abdollah

1998-01-01

Finding the inverse of a continuous function can be challenging and computationally expensive when the inverse function is multi-valued. Difficulties may be compounded when the function itself is difficult to evaluate. We show that we can use fuzzy-logic approximators such as Sugeno inference systems to compute the inverse on-line. To do so, a fuzzy clustering algorithm can be used in conjunction with a discriminating function to split the function data into branches for the different values of the forward function. These data sets are then fed into a recursive least-squares learning algorithm that finds the proper coefficients of the Sugeno approximators; each Sugeno approximator finds one value of the inverse function. Discussions about the accuracy of the approximation will be included.

13. Study of static and dynamic first hyperpolarizabilities using time-dependent density functional quadratic response theory with local contribution and natural bond orbital analysis.

PubMed

Ye, Aijun; Autschbach, Jochen

2006-12-21

We apply time-dependent density-functional quadratic response theory to investigate the static and dynamic second-order polarizabilities (first hyperpolarizability) beta. A new implementation using Slater-type basis functions, numerical integration, and density fitting techniques is reported. The second order coupled perturbed Kohn-Sham equations are solved and the second-order perturbed charge density is obtained. It is useful to highlight atomic and bond contributions to understand the relation between molecular structure and properties. Four moderately sized molecules (para-nitroaniline and derivatives thereof) are investigated to assess the accuracy of the time-dependent density-functional theory computations and to investigate the distribution of the second-order charge density as well as the "beta density." Our results highlight the contributions from atoms and bonds on different functional groups to the total value of beta with Mulliken-type and natural bond orbital (NBO) analyses, and demonstrate in some cases how contributions from a particular bond may be identified easily by visual inspection of the beta density. In addition, the position of side group substitution on carbon-carbon bonds significantly affects the hyperpolarizability. A contribution analysis as performed here might be helpful for the design of new materials with desired properties. PMID:17190541

14. INTEGRATING EVOLUTIONARY AND FUNCTIONAL APPROACHES TO INFER ADAPTATION AT SPECIFIC LOCI

PubMed Central

Storz, Jay F.; Wheat, Christopher W.

2010-01-01

Inferences about adaptation at specific loci are often exclusively based on the static analysis of DNA sequence variation. Ideally, population-genetic evidence for positive selection serves as a stepping-off point for experimental studies to elucidate the functional significance of the putatively adaptive variation. We argue that inferences about adaptation at specific loci are best achieved by integrating the indirect, retrospective insights provided by population-genetic analyses with the more direct, mechanistic insights provided by functional experiments. Integrative studies of adaptive genetic variation may sometimes be motivated by experimental insights into molecular function, which then provide the impetus to perform population genetic tests to evaluate whether the functional variation is of adaptive significance. In other cases, studies may be initiated by genome scans of DNA variation to identify candidate loci for recent adaptation. Results of such analyses can then motivate experimental efforts to test whether the identified candidate loci do in fact contribute to functional variation in some fitness-related phenotype. Functional studies can provide corroborative evidence for positive selection at particular loci, and can potentially reveal specific molecular mechanisms of adaptation. PMID:20500215

15. Weight of quadratic forms and graph states

Cosentino, Alessandro; Severini, Simone

2009-11-01

We prove a connection between Schmidt rank and weight of quadratic forms. This provides a new tool for the classification of graph states based on entanglement. Our main tool arises from a reformulation of previously known results concerning the weight of quadratic forms in terms of graph states properties. As a byproduct, we obtain a straightforward characterization of the weight of functions associated with pivot-minor of bipartite graphs.

16. Using evolutionary sequence variation to make inferences about protein structure and function

Colwell, Lucy

2015-03-01

The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. The explosive growth in the number of available protein sequences raises the possibility of using the natural variation present in homologous protein sequences to infer these constraints and thus identify residues that control different protein phenotypes. Because in many cases phenotypic changes are controlled by more than one amino acid, the mutations that separate one phenotype from another may not be independent, requiring us to understand the correlation structure of the data. To address this we build a maximum entropy probability model for the protein sequence. The parameters of the inferred model are constrained by the statistics of a large sequence alignment. Pairs of sequence positions with the strongest interactions accurately predict contacts in protein tertiary structure, enabling all atom structural models to be constructed. We describe development of a theoretical inference framework that enables the relationship between the amount of available input data and the reliability of structural predictions to be better understood.

ERIC Educational Resources Information Center

March, Robert H.

1993-01-01

Uses projectile motion to explain the two roots found when using the quadratic formula. An example is provided for finding the time of flight for a projectile which has a negative root implying a negative time of flight. This negative time of flight also has a useful physical meaning. (MVL)

ERIC Educational Resources Information Center

Fay, Temple H.

2010-01-01

Through numerical investigations, we study examples of the forced quadratic spring equation [image omitted]. By performing trial-and-error numerical experiments, we demonstrate the existence of stability boundaries in the phase plane indicating initial conditions yielding bounded solutions, investigate the resonance boundary in the [omega]…

19. Impact of Prematurity and Perinatal Antibiotics on the Developing Intestinal Microbiota: A Functional Inference Study

PubMed Central

Arboleya, Silvia; Sánchez, Borja; Solís, Gonzalo; Fernández, Nuria; Suárez, Marta; Hernández-Barranco, Ana M.; Milani, Christian; Margolles, Abelardo; de los Reyes-Gavilán, Clara G.; Ventura, Marco; Gueimonde, Miguel

2016-01-01

Background: The microbial colonization of the neonatal gut provides a critical stimulus for normal maturation and development. This process of early microbiota establishment, known to be affected by several factors, constitutes an important determinant for later health. Methods: We studied the establishment of the microbiota in preterm and full-term infants and the impact of perinatal antibiotics upon this process in premature babies. To this end, 16S rRNA gene sequence-based microbiota assessment was performed at phylum level and functional inference analyses were conducted. Moreover, the levels of the main intestinal microbial metabolites, the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were measured by Gas-Chromatography Flame ionization/Mass spectrometry detection. Results: Prematurity affects microbiota composition at phylum level, leading to increases of Proteobacteria and reduction of other intestinal microorganisms. Perinatal antibiotic use further affected the microbiota of the preterm infant. These changes involved a concomitant alteration in the levels of intestinal SCFA. Moreover, functional inference analyses allowed for identifying metabolic pathways potentially affected by prematurity and perinatal antibiotics use. Conclusion: A deficiency or delay in the establishment of normal microbiota function seems to be present in preterm infants. Perinatal antibiotic use, such as intrapartum prophylaxis, affected the early life microbiota establishment in preterm newborns, which may have consequences for later health. PMID:27136545

20. Inferring the functional effect of gene expression changes in signaling pathways.

PubMed

Sebastián-León, Patricia; Carbonell, José; Salavert, Francisco; Sanchez, Rubén; Medina, Ignacio; Dopazo, Joaquín

2013-07-01

Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case-control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/. PMID:23748960

1. Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

2. Inferring deep biosphere function and diversity through (near) surface biosphere portals (Invited)

Meyer-Dombard, D. R.; Cardace, D.; Woycheese, K. M.; Swingley, W.; Schubotz, F.; Shock, E.

2013-12-01

The consideration of surface expressions of the deep subsurface- such as springs- remains one of the most economically viable means to query the deep biosphere's diversity and function. Hot spring source pools are ideal portals for accessing and inferring the taxonomic and functional diversity of related deep subsurface microbial communities. Consideration of the geochemical composition of deep vs. surface fluids provides context for interpretation of community function. Further, parallel assessment of 16S rRNA data, metagenomic sequencing, and isotopic compositions of biomass in surface springs allows inference of the functional capacities of subsurface ecosystems. Springs in Yellowstone National Park (YNP), the Philippines, and Turkey are considered here, incorporating near-surface, transition, and surface ecosystems to identify 'legacy' taxa and functions of the deep biosphere. We find that source pools often support functional capacity suited to subsurface ecosystems. For example, in hot ecosystems, source pools are strictly chemosynthetic, and surface environments with measureable dissolved oxygen may contain evidence of community functions more favorable under anaerobic conditions. Metagenomic reads from a YNP ecosystem indicate the genetic capacity for sulfate reduction at high temperature. However, inorganic sulfate reduction is only minimally energy-yielding in these surface environments suggesting the potential that sulfate reduction is a 'legacy' function of deeper biosphere ecosystems. Carbon fixation tactics shift with increased surface exposure of the thermal fluids. Genes related to the rTCA cycle and the acetyl co-A pathway are most prevalent in highest temperature, anaerobic sites. At lower temperature sites, fewer total carbon fixation genes were observed, perhaps indicating an increase in heterotrophic metabolism with increased surface exposure. In hydrogen and methane rich springs in the Philippines and Turkey, methanogenic taxa dominate source

3. LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns

PubMed Central

Li, Yongsheng; Chen, Hong; Pan, Tao; Jiang, Chunjie; Zhao, Zheng; Wang, Zishan; Zhang, Jinwen; Xu, Juan; Li, Xia

2015-01-01

Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome profiling. We propose an integrative method for genome-wide functional predictions of lncRNAs by combining chromatin states data with gene expression patterns. We first validated the method using protein-coding genes with known function annotations. Our validation results indicated that our integrative method performs better than co-expression analysis, and is accurate across different conditions. Next, by applying the integrative model genome-wide, we predicted the probable functions for more than 97% of human lncRNAs. The putative functions inferred by our method match with previously annotated by the targets of lncRNAs. Moreover, the linkage from the cellular processes influenced by cancer-associated lncRNAs to the cancer hallmarks provided a “lncRNA point-of-view” on tumor biology. Our approach provides a functional annotation of the lncRNAs, which we developed into a web-based application, LncRNA Ontology, to provide visualization, analysis, and downloading of lncRNA putative functions. PMID:26485761

4. Inferring modules of functionally interacting proteins using the Bond Energy Algorithm

PubMed Central

Watanabe, Ryosuke LA; Morett, Enrique; Vallejo, Edgar E

2008-01-01

Background Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or structure similarity. Those methods rely heavily on traditional similarity metrics defined on pairs of phylogenetic patterns. Proteins do not exclusively interact in pairs as the final biological function of a protein in the cellular context is often hold by a group of proteins. In order to accurately infer modules of functionally interacting proteins, the consideration of not only direct but also indirect relationships is required. In this paper, we used the Bond Energy Algorithm (BEA) to predict functionally related groups of proteins. With BEA we create clusters of phylogenetic profiles based on the associations of the surrounding elements of the analyzed data using a metric that considers linked relationships among elements in the data set. Results Using phylogenetic profiles obtained from the Cluster of Orthologous Groups of Proteins (COG) database, we conducted a series of clustering experiments using BEA to predict (upper level) relationships between profiles. We evaluated our results by comparing with COG's functional categories, And even more, with the experimentally determined functional relationships between proteins provided by the DIP and ECOCYC databases. Our results demonstrate that BEA is capable of predicting meaningful modules of functionally related proteins. BEA outperforms traditionally used clustering methods, such as k-means and hierarchical clustering by predicting functional relationships between proteins with higher accuracy. Conclusion This study shows that the linked relationships of phylogenetic profiles obtained by BEA is useful for detecting functional associations between profiles and extending functional modules not found by traditional methods. BEA is capable of detecting relationship among phylogenetic patterns by linking them through a common element shared in

5. Brain imaging and cognitive neuroscience. Toward strong inference in attributing function to structure.

PubMed

Sarter, M; Berntson, G G; Cacioppo, J T

1996-01-01

Cognitive neuroscience has emerged from the neurosciences and cognitive psychology as a scientific discipline that aims at the determination of "how brain function gives rise to mental activity" (S. M. Kosslyn & L. M. Shin, 1992, p. 146). While research in cognitive neuroscience combines many levels of neuroscientific and psychological analyses, modern imaging techniques that monitor brain activity during behavioral or cognitive operations have significantly contributed to the emergence of this discipline. The conclusions deduced from these studies are inherently localizationistic in nature; in other words, they describe cognitive functions as being localized in focal brain regions (brain activity in a defined brain region, phi, is involved in specific cognitive function, psi). A broad discussion about the virtues and limitations of such conclusions may help avoid the emergence of a mentalistic localizationism (i.e., the attribution of mentalistic concepts such as happiness, morality, or consciousness to brain structure) and illustrates the importance of a convergence with information generated by different research strategies (such as, for example, evidence generated by studies in which the effects of experimental manipulations of local neuronal processes on cognitive functions are assessed). Progress in capitalizing on brain-imaging studies to investigate questions of the form "brain structure or event phi is associated with cognitive function psi" may be impeded because of the way in which inferences are typically formulated in the brain imaging literature. A conceptual framework to advance the interpretation of data describing the relationships between cognitive phenomena and brain structure activity is provided. PMID:8585670

6. Pragmatic inferences in high-functioning adults with autism and Asperger syndrome.

PubMed

Pijnacker, Judith; Hagoort, Peter; Buitelaar, Jan; Teunisse, Jan-Pieter; Geurts, Bart

2009-04-01

Although people with autism spectrum disorders (ASD) often have severe problems with pragmatic aspects of language, little is known about their pragmatic reasoning. We carried out a behavioral study on high-functioning adults with autistic disorder (n = 11) and Asperger syndrome (n = 17) and matched controls (n = 28) to investigate whether they are capable of deriving scalar implicatures, which are generally considered to be pragmatic inferences. Participants were presented with underinformative sentences like "Some sparrows are birds". This sentence is logically true, but pragmatically inappropriate if the scalar implicature "Not all sparrows are birds" is derived. The present findings indicate that the combined ASD group was just as likely as controls to derive scalar implicatures, yet there was a difference between participants with autistic disorder and Asperger syndrome, suggesting a potential differentiation between these disorders in pragmatic reasoning. Moreover, our results suggest that verbal intelligence is a constraint for task performance in autistic disorder but not in Asperger syndrome. PMID:19052858

7. On the inference of function from structure using biomechanical modelling and simulation of extinct organisms.

PubMed

Hutchinson, John R

2012-02-23

Biomechanical modelling and simulation techniques offer some hope for unravelling the complex inter-relationships of structure and function perhaps even for extinct organisms, but have their limitations owing to this complexity and the many unknown parameters for fossil taxa. Validation and sensitivity analysis are two indispensable approaches for quantifying the accuracy and reliability of such models or simulations. But there are other subtleties in biomechanical modelling that include investigator judgements about the level of simplicity versus complexity in model design or how uncertainty and subjectivity are dealt with. Furthermore, investigator attitudes toward models encompass a broad spectrum between extreme credulity and nihilism, influencing how modelling is conducted and perceived. Fundamentally, more data and more testing of methodology are required for the field to mature and build confidence in its inferences. PMID:21666064

Colin, M.; Di Menza, L.; Saut, J. C.

2016-03-01

In this paper, we investigate the properties of solitonic structures arising in quadratic media. First, we recall the derivation of systems governing the interaction process for waves propagating in such media and we check the local and global well-posedness of the corresponding Cauchy problem. Then, we look for stationary states in the context of normal or anomalous dispersion regimes, that lead us to either elliptic or non-elliptic systems and we address the problem of orbital stability. Finally, some numerical experiments are carried out in order to compute localized states for several regimes and to study dynamic stability as well as long-time asymptotics.

9. LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

SciTech Connect

Zhang, Weiwen; Culley, David E.; Gritsenko, Marina A.; Moore, Ronald J.; Nie, Lei; Scholten, Johannes C.; Petritis, Konstantinos; Strittmatter, Eric F.; Camp, David G.; Smith, Richard D.; Brockman, Fred J.

2006-11-03

ABSTRACT In the previous study, the whole-genome gene expression profiles of D. vulgaris in response to oxidative stress and heat shock were determined. The results showed 24-28% of the responsive genes were hypothetical proteins that have not been experimentally characterized or whose function can not be deduced by simple sequence comparison. To further explore the protecting mechanisms employed in D. vulgaris against the oxidative stress and heat shock, attempt was made in this study to infer functions of these hypothetical proteins by phylogenomic profiling along with detailed sequence comparison against various publicly available databases. By this approach we were ableto assign possible functions to 25 responsive hypothetical proteins. The findings included that DVU0725, induced by oxidative stress, may be involved in lipopolysaccharide biosynthesis, implying that the alternation of lipopolysaccharide on cell surface might service as a mechanism against oxidative stress in D. vulgaris. In addition, two responsive proteins, DVU0024 encoding a putative transcriptional regulator and DVU1670 encoding predicted redox protein, were sharing co-evolution atterns with rubrerythrin in Archaeoglobus fulgidus and Clostridium perfringens, respectively, implying that they might be part of the stress response and protective systems in D. vulgaris. The study demonstrated that phylogenomic profiling is a useful tool in interpretation of experimental genomics data, and also provided further insight on cellular response to oxidative stress and heat shock in D. vulgaris.

10. Guises and disguises of quadratic divergences

SciTech Connect

Cherchiglia, A.L.; Vieira, A.R.; Hiller, Brigitte; Baêta Scarpelli, A.P.; Sampaio, Marcos

2014-12-15

In this contribution, we present a new perspective on the control of quadratic divergences in quantum field theory, in general, and in the Higgs naturalness problem, in particular. Our discussion is essentially based on an approach where UV divergences are parameterized, after being reduced to basic divergent integrals (BDI) in one internal momentum, as functions of a cutoff and a renormalization group scale λ. We illustrate our proposal with well-known examples, such as the gluon vacuum self energy of QCD and the Higgs decay in two photons within this approach. We also discuss frameworks in effective low-energy QCD models, where quadratic divergences are indeed fundamental.

Quadratic spatial soliton interactions were investigated in this Dissertation. The first part deals with characterizing the principal features of multi-soliton generation and soliton self-reflection. The second deals with two beam processes leading to soliton interactions and collisions. These subjects were investigated both theoretically and experimentally. The experiments were performed by using potassium niobate (KNBO 3) and periodically poled potassium titanyl phosphate (KTP) crystals. These particular crystals were desirable for these experiments because of their large nonlinear coefficients and, more importantly, because the experiments could be performed under non-critical-phase-matching (NCPM) conditions. The single soliton generation measurements, performed on KNBO3 by launching the fundamental component only, showed a broad angular acceptance bandwidth which was important for the soliton collisions performed later. Furthermore, at high input intensities multi-soliton generation was observed for the first time. The influence on the multi-soliton patterns generated of the input intensity and beam symmetry was investigated. The combined experimental and theoretical efforts indicated that spatial and temporal noise on the input laser beam induced multi-soliton patterns. Another research direction pursued was intensity dependent soliton routing by using of a specially engineered quadratically nonlinear interface within a periodically poled KTP sample. This was the first time demonstration of the self-reflection phenomenon in a system with a quadratic nonlinearity. The feature investigated is believed to have a great potential for soliton routing and manipulation by engineered structures. A detailed investigation was conducted on two soliton interaction and collision processes. Birth of an additional soliton resulting from a two soliton collision was observed and characterized for the special case of a non-planar geometry. A small amount of spiraling, up to 30

Jankovic, Ladislav; Kim, Hongki; Stegeman, George; Carrasco, Silvia; Torner, Lluis; Katz, Mordechai

2003-11-01

The reflection of bulk quadratic solutions incident onto a quadratically nonlinear interface in periodically poled potassium titanyl phosphate was observed. The interface consisted of the boundary between two quasi-phase-matched regions displaced from each other by a half-period. At high intensities and small angles of incidence the soliton is reflected.

13. Inferring muscle functional roles of the ostrich pelvic limb during walking and running using computer optimization.

PubMed

Rankin, Jeffery W; Rubenson, Jonas; Hutchinson, John R

2016-05-01

Owing to their cursorial background, ostriches (Struthio camelus) walk and run with high metabolic economy, can reach very fast running speeds and quickly execute cutting manoeuvres. These capabilities are believed to be a result of their ability to coordinate muscles to take advantage of specialized passive limb structures. This study aimed to infer the functional roles of ostrich pelvic limb muscles during gait. Existing gait data were combined with a newly developed musculoskeletal model to generate simulations of ostrich walking and running that predict muscle excitations, force and mechanical work. Consistent with previous avian electromyography studies, predicted excitation patterns showed that individual muscles tended to be excited primarily during only stance or swing. Work and force estimates show that ostrich gaits are partially hip-driven with the bi-articular hip-knee muscles driving stance mechanics. Conversely, the knee extensors acted as brakes, absorbing energy. The digital extensors generated large amounts of both negative and positive mechanical work, with increased magnitudes during running, providing further evidence that ostriches make extensive use of tendinous elastic energy storage to improve economy. The simulations also highlight the need to carefully consider non-muscular soft tissues that may play a role in ostrich gait. PMID:27146688

14. Inferring muscle functional roles of the ostrich pelvic limb during walking and running using computer optimization

PubMed Central

Rubenson, Jonas

2016-01-01

Owing to their cursorial background, ostriches (Struthio camelus) walk and run with high metabolic economy, can reach very fast running speeds and quickly execute cutting manoeuvres. These capabilities are believed to be a result of their ability to coordinate muscles to take advantage of specialized passive limb structures. This study aimed to infer the functional roles of ostrich pelvic limb muscles during gait. Existing gait data were combined with a newly developed musculoskeletal model to generate simulations of ostrich walking and running that predict muscle excitations, force and mechanical work. Consistent with previous avian electromyography studies, predicted excitation patterns showed that individual muscles tended to be excited primarily during only stance or swing. Work and force estimates show that ostrich gaits are partially hip-driven with the bi-articular hip–knee muscles driving stance mechanics. Conversely, the knee extensors acted as brakes, absorbing energy. The digital extensors generated large amounts of both negative and positive mechanical work, with increased magnitudes during running, providing further evidence that ostriches make extensive use of tendinous elastic energy storage to improve economy. The simulations also highlight the need to carefully consider non-muscular soft tissues that may play a role in ostrich gait. PMID:27146688

15. Students' Understanding of Quadratic Equations

ERIC Educational Resources Information Center

López, Jonathan; Robles, Izraim; Martínez-Planell, Rafael

2016-01-01

Action-Process-Object-Schema theory (APOS) was applied to study student understanding of quadratic equations in one variable. This required proposing a detailed conjecture (called a genetic decomposition) of mental constructions students may do to understand quadratic equations. The genetic decomposition which was proposed can contribute to help…

16. Inference of the cold dark matter substructure mass function at z = 0.2 using strong gravitational lenses

Vegetti, S.; Koopmans, L. V. E.; Auger, M. W.; Treu, T.; Bolton, A. S.

2014-08-01

We present the results of a search for galaxy substructures in a sample of 11 gravitational lens galaxies from the Sloan Lens ACS Survey by Bolton et al. We find no significant detection of mass clumps, except for a luminous satellite in the system SDSS J0956+5110. We use these non-detections, in combination with a previous detection in the system SDSS J0946+1006, to derive constraints on the substructure mass function in massive early-type host galaxies with an average redshift ˜ 0.2 and an average velocity dispersion <σeff> ˜ 270 km s-1. We perform a Bayesian inference on the substructure mass function, within a median region of about 32 kpc2 around the Einstein radius ( ˜ 4.2 kpc). We infer a mean projected substructure mass fraction f = 0.0076_{-0.0052}^{+0.0208} at the 68 per cent confidence level and a substructure mass function slope α < 2.93 at the 95 per cent confidence level for a uniform prior probability density on α. For a Gaussian prior based on cold dark matter (CDM) simulations, we infer f = 0.0064^{+0.0080}_{-0.0042} and a slope of α = 1.90^{+0.098}_{-0.098} at the 68 per cent confidence level. Since only one substructure was detected in the full sample, we have little information on the mass function slope, which is therefore poorly constrained (i.e. the Bayes factor shows no positive preference for any of the two models). The inferred fraction is consistent with the expectations from CDM simulations and with inference from flux ratio anomalies at the 68 per cent confidence level.

17. Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum.

PubMed

Tanaka, Shingo; Pan, Xiaochuan; Oguchi, Mineki; Taylor, Jessica E; Sakagami, Masamichi

2015-01-01

In a complex and uncertain world, how do we select appropriate behavior? One possibility is that we choose actions that are highly reinforced by their probabilistic consequences (model-free processing). However, we may instead plan actions prior to their actual execution by predicting their consequences (model-based processing). It has been suggested that the brain contains multiple yet distinct systems involved in reward prediction. Several studies have tried to allocate model-free and model-based systems to the striatum and the lateral prefrontal cortex (LPFC), respectively. Although there is much support for this hypothesis, recent research has revealed discrepancies. To understand the nature of the reward prediction systems in the LPFC and the striatum, a series of single-unit recording experiments were conducted. LPFC neurons were found to infer the reward associated with the stimuli even when the monkeys had not yet learned the stimulus-reward (SR) associations directly. Striatal neurons seemed to predict the reward for each stimulus only after directly experiencing the SR contingency. However, the one exception was "Exclusive Or" situations in which striatal neurons could predict the reward without direct experience. Previous single-unit studies in monkeys have reported that neurons in the LPFC encode category information, and represent reward information specific to a group of stimuli. Here, as an extension of these, we review recent evidence that a group of LPFC neurons can predict reward specific to a category of visual stimuli defined by relevant behavioral responses. We suggest that the functional difference in reward prediction between the LPFC and the striatum is that while LPFC neurons can utilize abstract code, striatal neurons can code individual associations between stimuli and reward but cannot utilize abstract code. PMID:26236266

18. Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum

PubMed Central

Tanaka, Shingo; Pan, Xiaochuan; Oguchi, Mineki; Taylor, Jessica E.; Sakagami, Masamichi

2015-01-01

In a complex and uncertain world, how do we select appropriate behavior? One possibility is that we choose actions that are highly reinforced by their probabilistic consequences (model-free processing). However, we may instead plan actions prior to their actual execution by predicting their consequences (model-based processing). It has been suggested that the brain contains multiple yet distinct systems involved in reward prediction. Several studies have tried to allocate model-free and model-based systems to the striatum and the lateral prefrontal cortex (LPFC), respectively. Although there is much support for this hypothesis, recent research has revealed discrepancies. To understand the nature of the reward prediction systems in the LPFC and the striatum, a series of single-unit recording experiments were conducted. LPFC neurons were found to infer the reward associated with the stimuli even when the monkeys had not yet learned the stimulus-reward (SR) associations directly. Striatal neurons seemed to predict the reward for each stimulus only after directly experiencing the SR contingency. However, the one exception was “Exclusive Or” situations in which striatal neurons could predict the reward without direct experience. Previous single-unit studies in monkeys have reported that neurons in the LPFC encode category information, and represent reward information specific to a group of stimuli. Here, as an extension of these, we review recent evidence that a group of LPFC neurons can predict reward specific to a category of visual stimuli defined by relevant behavioral responses. We suggest that the functional difference in reward prediction between the LPFC and the striatum is that while LPFC neurons can utilize abstract code, striatal neurons can code individual associations between stimuli and reward but cannot utilize abstract code. PMID:26236266

19. Quadratic algebras for three-dimensional superintegrable systems

SciTech Connect

2010-02-15

The three-dimensional superintegrable systems with quadratic integrals of motion have five functionally independent integrals, one among them is the Hamiltonian. Kalnins, Kress, and Miller have proved that in the case of nondegenerate potentials with quadratic integrals of motion there is a sixth quadratic integral, which is linearly independent of the other integrals. The existence of this sixth integral implies that the integrals of motion form a ternary parafermionic-like quadratic Poisson algebra with five generators. In this contribution we investigate the structure of this algebra. We show that in all the nondegenerate cases there is at least one subalgebra of three integrals having a Poisson quadratic algebra structure, which is similar to the two-dimensional case.

20. Quadratic Programming for Allocating Control Effort

NASA Technical Reports Server (NTRS)

Singh, Gurkirpal

2005-01-01

A computer program calculates an optimal allocation of control effort in a system that includes redundant control actuators. The program implements an iterative (but otherwise single-stage) algorithm of the quadratic-programming type. In general, in the quadratic-programming problem, one seeks the values of a set of variables that minimize a quadratic cost function, subject to a set of linear equality and inequality constraints. In this program, the cost function combines control effort (typically quantified in terms of energy or fuel consumed) and control residuals (differences between commanded and sensed values of variables to be controlled). In comparison with prior control-allocation software, this program offers approximately equal accuracy but much greater computational efficiency. In addition, this program offers flexibility, robustness to actuation failures, and a capability for selective enforcement of control requirements. The computational efficiency of this program makes it suitable for such complex, real-time applications as controlling redundant aircraft actuators or redundant spacecraft thrusters. The program is written in the C language for execution in a UNIX operating system.

1. A phylogeny-based benchmarking test for orthology inference reveals the limitations of function-based validation.

PubMed

Trachana, Kalliopi; Forslund, Kristoffer; Larsson, Tomas; Powell, Sean; Doerks, Tobias; von Mering, Christian; Bork, Peer

2014-01-01

Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality "gold standard" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a "core" species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2. PMID:25369365

2. A Phylogeny-Based Benchmarking Test for Orthology Inference Reveals the Limitations of Function-Based Validation

PubMed Central

Larsson, Tomas; Powell, Sean; Doerks, Tobias; von Mering, Christian

2014-01-01

Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality "gold standard" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a “core” species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2. PMID:25369365

3. Inference of S-system models of genetic networks by solving one-dimensional function optimization problems.

PubMed

Kimura, S; Araki, D; Matsumura, K; Okada-Hatakeyama, M

2012-02-01

Voit and Almeida have proposed the decoupling approach as a method for inferring the S-system models of genetic networks. The decoupling approach defines the inference of a genetic network as a problem requiring the solutions of sets of algebraic equations. The computation can be accomplished in a very short time, as the approach estimates S-system parameters without solving any of the differential equations. Yet the defined algebraic equations are non-linear, which sometimes prevents us from finding reasonable S-system parameters. In this study, we propose a new technique to overcome this drawback of the decoupling approach. This technique transforms the problem of solving each set of algebraic equations into a one-dimensional function optimization problem. The computation can still be accomplished in a relatively short time, as the problem is transformed by solving a linear programming problem. We confirm the effectiveness of the proposed approach through numerical experiments. PMID:22155075

4. Students' understanding of quadratic equations

López, Jonathan; Robles, Izraim; Martínez-Planell, Rafael

2016-05-01

Action-Process-Object-Schema theory (APOS) was applied to study student understanding of quadratic equations in one variable. This required proposing a detailed conjecture (called a genetic decomposition) of mental constructions students may do to understand quadratic equations. The genetic decomposition which was proposed can contribute to help students achieve an understanding of quadratic equations with improved interrelation of ideas and more flexible application of solution methods. Semi-structured interviews with eight beginning undergraduate students explored which of the mental constructions conjectured in the genetic decomposition students could do, and which they had difficulty doing. Two of the mental constructions that form part of the genetic decomposition are highlighted and corresponding further data were obtained from the written work of 121 undergraduate science and engineering students taking a multivariable calculus course. The results suggest the importance of explicitly considering these two highlighted mental constructions.

NASA Technical Reports Server (NTRS)

Harrison, D. C.; Staples, M. H.

1980-01-01

An analog-to-digital converter with a square root transfer function has been developed for use with a pair of CCD imaging detectors in the White Light Coronagraph/X-ray XUV Telescope experiment to be flown as part of the Internal Solar Polar Mission. It is shown that in background-noise-limited instrumentation systems a quadratic analog-to-digital converter will allow a maximum dynamic range with a fixed number of data bits. Low power dissipation, moderately fast conversion time, and reliability are achieved in the proposed design using standard components and avoiding nonlinear elements.

6. Inferring gene function from evolutionary change in signatures of translation efficiency

PubMed Central

2014-01-01

Background The genetic code is redundant, meaning that most amino acids can be encoded by more than one codon. Highly expressed genes tend to use optimal codons to increase the accuracy and speed of translation. Thus, codon usage biases provide a signature of the relative expression levels of genes, which can, uniquely, be quantified across the domains of life. Results Here we describe a general statistical framework to exploit this phenomenon and to systematically associate genes with environments and phenotypic traits through changes in codon adaptation. By inferring evolutionary signatures of translation efficiency in 911 bacterial and archaeal genomes while controlling for confounding effects of phylogeny and inter-correlated phenotypes, we linked 187 gene families to 24 diverse phenotypic traits. A series of experiments in Escherichia coli revealed that 13 of 15, 19 of 23, and 3 of 6 gene families with changes in codon adaptation in aerotolerant, thermophilic, or halophilic microbes. Respectively, confer specific resistance to, respectively, hydrogen peroxide, heat, and high salinity. Further, we demonstrate experimentally that changes in codon optimality alone are sufficient to enhance stress resistance. Finally, we present evidence that multiple genes with altered codon optimality in aerobes confer oxidative stress resistance by controlling the levels of iron and NAD(P)H. Conclusions Taken together, these results provide experimental evidence for a widespread connection between changes in translation efficiency and phenotypic adaptation. As the number of sequenced genomes increases, this novel genomic context method for linking genes to phenotypes based on sequence alone will become increasingly useful. PMID:24580753

7. Effect of taxonomic resolution on ecological and palaeoecological inference - a test using testate amoeba water table depth transfer functions

Mitchell, Edward A. D.; Lamentowicz, Mariusz; Payne, Richard J.; Mazei, Yuri

2014-05-01

Sound taxonomy is a major requirement for quantitative environmental reconstruction using biological data. Transfer function performance should theoretically be expected to decrease with reduced taxonomic resolution. However for many groups of organisms taxonomy is imperfect and species level identification not always possible. We conducted numerical experiments on five testate amoeba water table (DWT) transfer function data sets. We sequentially reduced the number of taxonomic groups by successively merging morphologically similar species and removing inconspicuous species. We then assessed how these changes affected model performance and palaeoenvironmental reconstruction using two fossil data sets. Model performance decreased with decreasing taxonomic resolution, but this had only limited effects on patterns of inferred DWT, at least to detect major dry/wet shifts. Higher-resolution taxonomy may however still be useful to detect more subtle changes, or for reconstructed shifts to be significant.

8. A Genome-Scale Investigation of How Sequence, Function, and Tree-Based Gene Properties Influence Phylogenetic Inference.

PubMed

Shen, Xing-Xing; Salichos, Leonidas; Rokas, Antonis

2016-01-01

Molecular phylogenetic inference is inherently dependent on choices in both methodology and data. Many insightful studies have shown how choices in methodology, such as the model of sequence evolution or optimality criterion used, can strongly influence inference. In contrast, much less is known about the impact of choices in the properties of the data, typically genes, on phylogenetic inference. We investigated the relationships between 52 gene properties (24 sequence-based, 19 function-based, and 9 tree-based) with each other and with three measures of phylogenetic signal in two assembled data sets of 2,832 yeast and 2,002 mammalian genes. We found that most gene properties, such as evolutionary rate (measured through the percent average of pairwise identity across taxa) and total tree length, were highly correlated with each other. Similarly, several gene properties, such as gene alignment length, Guanine-Cytosine content, and the proportion of tree distance on internal branches divided by relative composition variability (treeness/RCV), were strongly correlated with phylogenetic signal. Analysis of partial correlations between gene properties and phylogenetic signal in which gene evolutionary rate and alignment length were simultaneously controlled, showed similar patterns of correlations, albeit weaker in strength. Examination of the relative importance of each gene property on phylogenetic signal identified gene alignment length, alongside with number of parsimony-informative sites and variable sites, as the most important predictors. Interestingly, the subsets of gene properties that optimally predicted phylogenetic signal differed considerably across our three phylogenetic measures and two data sets; however, gene alignment length and RCV were consistently included as predictors of all three phylogenetic measures in both yeasts and mammals. These results suggest that a handful of sequence-based gene properties are reliable predictors of phylogenetic signal

9. Tectonomagmatic origin of Precambrian rocks of Mexico and Argentina inferred from multi-dimensional discriminant-function based discrimination diagrams

Pandarinath, Kailasa

2014-12-01

Several new multi-dimensional tectonomagmatic discrimination diagrams employing log-ratio variables of chemical elements and probability based procedure have been developed during the last 10 years for basic-ultrabasic, intermediate and acid igneous rocks. There are numerous studies on extensive evaluations of these newly developed diagrams which have indicated their successful application to know the original tectonic setting of younger and older as well as sea-water and hydrothermally altered volcanic rocks. In the present study, these diagrams were applied to Precambrian rocks of Mexico (southern and north-eastern) and Argentina. The study indicated the original tectonic setting of Precambrian rocks from the Oaxaca Complex of southern Mexico as follows: (1) dominant rift (within-plate) setting for rocks of 1117-988 Ma age; (2) dominant rift and less-dominant arc setting for rocks of 1157-1130 Ma age; and (3) a combined tectonic setting of collision and rift for Etla Granitoid Pluton (917 Ma age). The diagrams have indicated the original tectonic setting of the Precambrian rocks from the north-eastern Mexico as: (1) a dominant arc tectonic setting for the rocks of 988 Ma age; and (2) an arc and collision setting for the rocks of 1200-1157 Ma age. Similarly, the diagrams have indicated the dominant original tectonic setting for the Precambrian rocks from Argentina as: (1) with-in plate (continental rift-ocean island) and continental rift (CR) setting for the rocks of 800 Ma and 845 Ma age, respectively; and (2) an arc setting for the rocks of 1174-1169 Ma and of 1212-1188 Ma age. The inferred tectonic setting for these Precambrian rocks are, in general, in accordance to the tectonic setting reported in the literature, though there are some inconsistence inference of tectonic settings by some of the diagrams. The present study confirms the importance of these newly developed discriminant-function based diagrams in inferring the original tectonic setting of

10. A Genome-Scale Investigation of How Sequence, Function, and Tree-Based Gene Properties Influence Phylogenetic Inference

PubMed Central

Shen, Xing-Xing; Salichos, Leonidas; Rokas, Antonis

2016-01-01

Molecular phylogenetic inference is inherently dependent on choices in both methodology and data. Many insightful studies have shown how choices in methodology, such as the model of sequence evolution or optimality criterion used, can strongly influence inference. In contrast, much less is known about the impact of choices in the properties of the data, typically genes, on phylogenetic inference. We investigated the relationships between 52 gene properties (24 sequence-based, 19 function-based, and 9 tree-based) with each other and with three measures of phylogenetic signal in two assembled data sets of 2,832 yeast and 2,002 mammalian genes. We found that most gene properties, such as evolutionary rate (measured through the percent average of pairwise identity across taxa) and total tree length, were highly correlated with each other. Similarly, several gene properties, such as gene alignment length, Guanine-Cytosine content, and the proportion of tree distance on internal branches divided by relative composition variability (treeness/RCV), were strongly correlated with phylogenetic signal. Analysis of partial correlations between gene properties and phylogenetic signal in which gene evolutionary rate and alignment length were simultaneously controlled, showed similar patterns of correlations, albeit weaker in strength. Examination of the relative importance of each gene property on phylogenetic signal identified gene alignment length, alongside with number of parsimony-informative sites and variable sites, as the most important predictors. Interestingly, the subsets of gene properties that optimally predicted phylogenetic signal differed considerably across our three phylogenetic measures and two data sets; however, gene alignment length and RCV were consistently included as predictors of all three phylogenetic measures in both yeasts and mammals. These results suggest that a handful of sequence-based gene properties are reliable predictors of phylogenetic signal

11. Bayesian inverse modeling of vadose zone hydraulic properties in a layered soil profile with data-driven likelihood function inference

Over, M. W.; Wollschlaeger, U.; Osorio-Murillo, C. A.; Ames, D. P.; Rubin, Y.

2013-12-01

Good estimates for water retention and hydraulic conductivity functions are essential for accurate modeling of the nonlinear water dynamics of unsaturated soils. Parametric mathematical models for these functions are utilized in numerical applications of vadose zone dynamics; therefore, characterization of the model parameters to represent in situ soil properties is the goal of many inversion or calibration techniques. A critical, statistical challenge of existing approaches is the subjective, user-definition of a likelihood function or objective function - a step known to introduce bias in the results. We present a methodology for Bayesian inversion where the likelihood function is inferred directly from the simulation data, which eliminates subjectivity. Additionally, our approach assumes that there is no one parameterization that is appropriate for soils, but rather that the parameters are randomly distributed. This introduces the familiar concept from groundwater hydrogeology of structural models into vadose zone applications, but without attempting to apply geostatistics, which is extremely difficult in unsaturated problems. We validate our robust statistical approach on field data obtained during a multi-layer, natural boundary condition experiment and compare with previous optimizations using the same data. Our confidence intervals for the water retention and hydraulic conductivity functions as well as joint posterior probability distributions of the Mualem-van Genuchten parameters compare well with the previous work. The entire analysis was carried out using the free, open-source MAD# software available at http://mad.codeplex.com/.

12. Inferring Functional Interaction and Transition Patterns via Dynamic Bayesian Variable Partition Models

PubMed Central

Zhang, Jing; Li, Xiang; Li, Cong; Lian, Zhichao; Huang, Xiu; Zhong, Guocheng; Zhu, Dajiang; Li, Kaiming; Jin, Changfeng; Hu, Xintao; Han, Junwei; Guo, Lei; Hu, Xiaoping; Li, Lingjiang; Liu, Tianming

2014-01-01

Multivariate connectivity and functional dynamics have been of wide interest in the neuroimaging field, and a variety of methods have been developed to study functional interactions and dynamics. In contrast, the temporal dynamic transitions of multivariate functional interactions among brain networks, in particular, in resting state, have been much less explored. This paper presents a novel dynamic Bayesian variable partition model (DBVPM) that simultaneously considers and models multivariate functional interactions and their dynamics via a unified Bayesian framework. The basic idea is to detect the temporal boundaries of piecewise quasi-stable functional interaction patterns, which are then modeled by representative signature patterns and whose temporal transitions are characterized by finite-state transition machines. Results on both simulated and experimental datasets demonstrated the effectiveness and accuracy of the DBVPM in dividing temporally transiting functional interaction patterns. The application of DBVPM on a post-traumatic stress disorder (PTSD) dataset revealed substantially different multivariate functional interaction signatures and temporal transitions in the default mode and emotion networks of PTSD patients, in comparison with those in healthy controls. This result demonstrated the utility of DBVPM in elucidating salient features that cannot be revealed by static pair-wise functional connectivity analysis. PMID:24222313

13. Orthogonality preserving infinite dimensional quadratic stochastic operators

SciTech Connect

Akın, Hasan; Mukhamedov, Farrukh

2015-09-18

In the present paper, we consider a notion of orthogonal preserving nonlinear operators. We introduce π-Volterra quadratic operators finite and infinite dimensional settings. It is proved that any orthogonal preserving quadratic operator on finite dimensional simplex is π-Volterra quadratic operator. In infinite dimensional setting, we describe all π-Volterra operators in terms orthogonal preserving operators.

14. INFERRING FUNCTIONAL NETWORK-BASED SIGNATURES VIA STRUCTURALLY-WEIGHTED LASSO MODEL

PubMed Central

Zhu, Dajiang; Shen, Dinggang; Liu, Tianming

2014-01-01

Most current research approaches for functional/effective connectivity analysis focus on pair-wise connectivity and cannot deal with network-scale functional interactions. In this paper, we propose a structurally-weighted LASSO (SW-LASSO) regression model to represent the functional interaction among multiple regions of interests (ROIs) based on resting state fMRI (R-fMRI) data. The structural connectivity constraints derived from diffusion tenor imaging (DTI) data will guide the selection of the weights which adjust the penalty levels of different coefficients corresponding to different ROIs. Using the Default Mode Network (DMN) as a test-bed, our results indicate that the learned SW-LASSO has good capability of differentiating Mild Cognitive Impairment (MCI) subjects from their normal controls and has promising potential to characterize the brain functions among different condition, thus serving as the functional network-based signature. PMID:25002915

15. Ecological Inference

King, Gary; Rosen, Ori; Tanner, Martin A.

2004-09-01

This collection of essays brings together a diverse group of scholars to survey the latest strategies for solving ecological inference problems in various fields. The last half-decade has witnessed an explosion of research in ecological inference--the process of trying to infer individual behavior from aggregate data. Although uncertainties and information lost in aggregation make ecological inference one of the most problematic types of research to rely on, these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, by business in marketing research, and by governments in policy analysis.

16. Preliminary Results of the Lithospheric Structure Beneath the Aeolian Archipelago (Italy) Inferred from Teleseismic Receiver Functions

Musumeci, C.; Martinez-Arevalo, C.; de Lis Mancilla3, F.; Patanè, D.

2009-12-01

The Aeolian archipelago (Italy) represents an approximately one-million-year-old volcanic arc related to the subduction of the Ionian oceanic plate beneath the Calabrian continental crust. The objective of this work is to develop a better understanding of the regional structure of the whole archipelago. The crustal structure under each station was obtained applying P-receiver function technique to the teleseismic P-coda data recorded by the broadband seismic network (10 stations) installed by the Istituto Nazionale di Geofisica e Volcanologia (INGV-CT). Receiver functions were computed by using the Extended-Time Multitaper Frequency Domain Cross-Correlation Receiver Function (ET-MTRF) method. The preliminary results suggest a very similar listhospheric structure below all the islands of the Aeolian archipelago, with the exception of Stromboli. The boundary between the subducting ocean crust of the Ionian plate and the Thyrrenian mantle is clearly observed below all the stations.

17. Phylogenetic Gaussian Process Model for the Inference of Functionally Important Regions in Protein Tertiary Structures

PubMed Central

Huang, Yi-Fei; Golding, G. Brian

2014-01-01

A critical question in biology is the identification of functionally important amino acid sites in proteins. Because functionally important sites are under stronger purifying selection, site-specific substitution rates tend to be lower than usual at these sites. A large number of phylogenetic models have been developed to estimate site-specific substitution rates in proteins and the extraordinarily low substitution rates have been used as evidence of function. Most of the existing tools, e.g. Rate4Site, assume that site-specific substitution rates are independent across sites. However, site-specific substitution rates may be strongly correlated in the protein tertiary structure, since functionally important sites tend to be clustered together to form functional patches. We have developed a new model, GP4Rate, which incorporates the Gaussian process model with the standard phylogenetic model to identify slowly evolved regions in protein tertiary structures. GP4Rate uses the Gaussian process to define a nonparametric prior distribution of site-specific substitution rates, which naturally captures the spatial correlation of substitution rates. Simulations suggest that GP4Rate can potentially estimate site-specific substitution rates with a much higher accuracy than Rate4Site and tends to report slowly evolved regions rather than individual sites. In addition, GP4Rate can estimate the strength of the spatial correlation of substitution rates from the data. By applying GP4Rate to a set of mammalian B7-1 genes, we found a highly conserved region which coincides with experimental evidence. GP4Rate may be a useful tool for the in silico prediction of functionally important regions in the proteins with known structures. PMID:24453956

18. Pragmatic Inferences in High-Functioning Adults with Autism and Asperger Syndrome

ERIC Educational Resources Information Center

Pijnacker, Judith; Hagoort, Peter; Buitelaar, Jan; Teunisse, Jan-Pieter; Geurts, Bart

2009-01-01

Although people with autism spectrum disorders (ASD) often have severe problems with pragmatic aspects of language, little is known about their pragmatic reasoning. We carried out a behavioral study on high-functioning adults with autistic disorder (n = 11) and Asperger syndrome (n = 17) and matched controls (n = 28) to investigate whether they…

19. STATISTICAL INFERENCE PROCEDURES FOR PROBABILITY SELECTION FUNCTIONS IN LONG-TERM MONITORING PROGRAMS

EPA Science Inventory

This report develops the theory and illustrates the use of selection functions to describe changes over time in the distributions of environmentally important variables at sites sampled as part of environmental monitoring programs. he first part of the report provides a review of...

20. Microbial manipulation of immune function for asthma prevention: inferences from clinical trials.

PubMed

Yoo, Jennifer; Tcheurekdjian, Haig; Lynch, Susan V; Cabana, Michael; Boushey, Homer A

2007-07-01

The "hygiene hypothesis" proposes that the increase in allergic diseases in developing countries reflects a decrease in infections during childhood. Cohort studies suggest, however, that the risks of asthma are increased in children who suffer severe illness from a viral respiratory infection in infancy. This apparent inconsistency can be reconciled through consideration of epidemiologic, clinical, and animal studies. The elements of this line of reasoning are that viral infections can predispose to organ-specific expression of allergic sensitization, and that the severity of illness is shaped by the maturity of immune function, which in turn is influenced by previous contact with bacteria and viruses, whether pathogenic or not. Clinical studies of children and interventional studies of animals indeed suggest that the exposure to microbes through the gastrointestinal tract powerfully shapes immune function. Intestinal microbiota differ in infants who later develop allergic diseases, and feeding Lactobacillus casei to infants at risk has been shown to reduce their rate of developing eczema. This has prompted studies of feeding probiotics as a primary prevention strategy for asthma. We propose that the efficacy of this approach depends on its success in inducing maturation of immune function important in defense against viral infection, rather than on its effectiveness in preventing allergic sensitization. It follows that the endpoints of studies of feeding probiotics to infants at risk for asthma should include not simply tests of responsiveness to allergens, but also assessment of intestinal flora, immune function, and the clinical response to respiratory viral infection. PMID:17607013

1. Using Functional Behavioral Assessment Data to Infer Learning Histories and Guide Interventions: A Consultation Case Study

ERIC Educational Resources Information Center

Parker, Megan; Skinner, Christopher; Booher, Joshua

2010-01-01

A teacher requested behavioral consultation services to address a first-grade student's disruptive behavior. Functional behavior assessment (FBA) suggested the behavior was being reinforced by "negative" teacher attention (e.g., reprimands, redirections, response cost). Based on this analysis, the teacher and consultant posited that this student…

2. Inference for the median residual life function in sequential multiple assignment randomized trials

PubMed Central

Kidwell, Kelley M.; Ko, Jin H.; Wahed, Abdus S.

2014-01-01

In survival analysis, median residual lifetime is often used as a summary measure to assess treatment effectiveness; it is not clear, however, how such a quantity could be estimated for a given dynamic treatment regimen using data from sequential randomized clinical trials. We propose a method to estimate a dynamic treatment regimen-specific median residual life (MERL) function from sequential multiple assignment randomized trials. We present the MERL estimator, which is based on inverse probability weighting, as well as, two variance estimates for the MERL estimator. One variance estimate follows from Lunceford, Davidian and Tsiatis’ 2002 survival function-based variance estimate and the other uses the sandwich estimator. The MERL estimator is evaluated, and its two variance estimates are compared through simulation studies, showing that the estimator and both variance estimates produce approximately unbiased results in large samples. To demonstrate our methods, the estimator has been applied to data from a sequentially randomized leukemia clinical trial. PMID:24254496

3. PrOnto database : GO term functional dissimilarity inferred from biological data

PubMed Central

Chapple, Charles E.; Herrmann, Carl; Brun, Christine

2015-01-01

Moonlighting proteins are defined by their involvement in multiple, unrelated functions. The computational prediction of such proteins requires a formal method of assessing the similarity of cellular processes, for example, by identifying dissimilar Gene Ontology terms. While many measures of Gene Ontology term similarity exist, most depend on abstract mathematical analyses of the structure of the GO tree and do not necessarily represent the underlying biology. Here, we propose two metrics of GO term functional dissimilarity derived from biological information, one based on the protein annotations and the other on the interactions between proteins. They have been collected in the PrOnto database, a novel tool which can be of particular use for the identification of moonlighting proteins. The database can be queried via an web-based interface which is freely available at http://tagc.univ-mrs.fr/pronto. PMID:26089836

4. Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2003-01-01

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

5. Epigenetic regulation of human placental function and pregnancy outcome: considerations for causal inference.

PubMed

Januar, Vania; Desoye, Gernot; Novakovic, Boris; Cvitic, Silvija; Saffery, Richard

2015-10-01

Epigenetic mechanisms, often defined as regulating gene activity independently of underlying DNA sequence, are crucial for healthy development. The sum total of epigenetic marks within a cell or tissue (the epigenome) is sensitive to environmental influence, and disruption of the epigenome in utero has been associated with adverse pregnancy outcomes. Not surprisingly, given its multifaceted functions and important role in regulating pregnancy outcome, the placenta shows unique epigenetic features. Interestingly however, many of these are only otherwise seen in human malignancy (the pseudomalignant placental epigenome). Epigenetic variation in the placenta is now emerging as a candidate mediator of environmental influence on placental functioning and a key regulator of pregnancy outcome. However, replication of findings is generally lacking, most likely due to small sample sizes and a lack of standardization of analytical approaches. Defining DNA methylation "signatures" in the placenta associated with maternal and fetal outcomes offers tremendous potential to improve pregnancy outcomes, but care must be taken in interpretation of findings. Future placental epigenetic research would do well to address the issues present in epigenetic epidemiology more generally, including careful consideration of sample size, potentially confounding factors, issues of tissue heterogeneity, reverse causation, and the role of genetics in modulating epigenetic profile. The importance of animal or in vitro models in establishing a functional role of epigenetic variation identified in human beings, which is key to establishing causation, should not be underestimated. PMID:26428498

6. Inferring functional connectivity in MRI using Bayesian network structure learning with a modified PC algorithm.

PubMed

Iyer, Swathi P; Shafran, Izhak; Grayson, David; Gates, Kathleen; Nigg, Joel T; Fair, Damien A

2013-07-15

Resting state functional connectivity MRI (rs-fcMRI) is a popular technique used to gauge the functional relatedness between regions in the brain for typical and special populations. Most of the work to date determines this relationship by using Pearson's correlation on BOLD fMRI timeseries. However, it has been recognized that there are at least two key limitations to this method. First, it is not possible to resolve the direct and indirect connections/influences. Second, the direction of information flow between the regions cannot be differentiated. In the current paper, we follow-up on recent work by Smith et al. (2011), and apply PC algorithm to both simulated data and empirical data to determine whether these two factors can be discerned with group average, as opposed to single subject, functional connectivity data. When applied on simulated individual subjects, the algorithm performs well determining indirect and direct connection but fails in determining directionality. However, when applied at group level, PC algorithm gives strong results for both indirect and direct connections and the direction of information flow. Applying the algorithm on empirical data, using a diffusion-weighted imaging (DWI) structural connectivity matrix as the baseline, the PC algorithm outperformed the direct correlations. We conclude that, under certain conditions, the PC algorithm leads to an improved estimate of brain network structure compared to the traditional connectivity analysis based on correlations. PMID:23501054

7. A transient, quadratic nodal method for triangular-Z geometry

SciTech Connect

DeLorey, T.F.

1993-06-01

Many systematically-derived nodal methods have been developed for Cartesian geometry due to the extensive interest in Light Water Reactors. These methods typically model the transverse-integrated flux as either an analytic or low order polynomial function of position within the node. Recently, quadratic nodal methods have been developed for R-Z and hexagonal geometry. A static and transient quadratic nodal method is developed for triangular-Z geometry. This development is particularly challenging because the quadratic expansion in each node must be performed between the node faces and the triangular points. As a consequence, in the 2-D plane, the flux and current at the points of the triangles must be treated. Quadratic nodal equations are solved using a non-linear iteration scheme, which utilizes the corrected, mesh-centered finite difference equations, and forces these equations to match the quadratic equations by computing discontinuity factors during the solution. Transient nodal equations are solved using the improved quasi-static method, which has been shown to be a very efficient solution method for transient problems. Several static problems are used to compare the quadratic nodal method to the Coarse Mesh Finite Difference (CMFD) method. The quadratic method is shown to give more accurate node-averaged fluxes. However, it appears that the method has difficulty predicting node leakages near reactor boundaries and severe material interfaces. The consequence is that the eigenvalue may be poorly predicted for certain reactor configurations. The transient methods are tested using a simple analytic test problem, a heterogeneous heavy water reactor benchmark problem, and three thermal hydraulic test problems. Results indicate that the transient methods have been implemented correctly.

8. Coherent states for quadratic Hamiltonians

Contreras-Astorga, Alonso; Fernández C, David J.; Velázquez, Mercedes

2011-01-01

The coherent states for a set of quadratic Hamiltonians in the trap regime are constructed. A matrix technique which allows us to directly identify the creation and annihilation operators will be presented. Then, the coherent states as simultaneous eigenstates of the annihilation operators will be derived, and will be compared with those attained through the displacement operator method. The corresponding wavefunction will be found, and a general procedure for obtaining several mean values involving the canonical operators in these states will be described. The results will be illustrated through the asymmetric Penning trap.

9. The luminosity function at z ∼ 8 from 97 Y-band dropouts: Inferences about reionization

SciTech Connect

Schmidt, Kasper B.; Treu, Tommaso; Kelly, Brandon C.; Trenti, Michele; Bradley, Larry D.; Stiavelli, Massimo; Oesch, Pascal A.; Shull, J. Michael

2014-05-01

We present the largest search to date for Y-band dropout galaxies (z ∼ 8 Lyman break galaxies, LBGs) based on 350 arcmin{sup 2} of Hubble Space Telescope observations in the V, Y, J, and H bands from the Brightest of Reionizing Galaxies (BoRG) survey. In addition to previously published data, the BoRG13 data set presented here includes approximately 50 arcmin{sup 2} of new data and deeper observations of two previous BoRG pointings, from which we present 9 new z ∼ 8 LBG candidates, bringing the total number of BoRG Y-band dropouts to 38 with 25.5 ≤ m{sub J} ≤ 27.6 (AB system). We introduce a new Bayesian formalism for estimating the galaxy luminosity function, which does not require binning (and thus smearing) of the data and includes a likelihood based on the formally correct binomial distribution as opposed to the often-used approximate Poisson distribution. We demonstrate the utility of the new method on a sample of 97 Y-band dropouts that combines the bright BoRG galaxies with the fainter sources published in Bouwens et al. from the Hubble Ultra Deep Field and Early Release Science programs. We show that the z ∼ 8 luminosity function is well described by a Schechter function over its full dynamic range with a characteristic magnitude M{sup ⋆}=−20.15{sub −0.38}{sup +0.29}, a faint-end slope of α=−1.87{sub −0.26}{sup +0.26}, and a number density of log{sub 10} ϕ{sup ⋆}[Mpc{sup −3}]=−3.24{sub −0.24}{sup +0.25}. Integrated down to M = –17.7, this luminosity function yields a luminosity density log{sub 10} ϵ[erg s{sup −1} Hz{sup −1} Mpc{sup −3}]=25.52{sub −0.05}{sup +0.05}. Our luminosity function analysis is consistent with previously published determinations within 1σ. The error analysis suggests that uncertainties on the faint-end slope are still too large to draw a firm conclusion about its evolution with redshift. We use our statistical framework to discuss the implication of our study for the physics of

10. Function of pretribosphenic and tribosphenic mammalian molars inferred from 3D animation.

PubMed

Schultz, Julia A; Martin, Thomas

2014-10-01

Appearance of the tribosphenic molar in the Late Jurassic (160 Ma) is a crucial innovation for food processing in mammalian evolution. This molar type is characterized by a protocone, a talonid basin and a two-phased chewing cycle, all of which are apomorphic. In this functional study on the teeth of Late Jurassic Dryolestes leiriensis and the living marsupial Monodelphis domestica, we demonstrate that pretribosphenic and tribosphenic molars show fundamental differences of food reduction strategies, representing a shift in dental function during the transition of tribosphenic mammals. By using the Occlusal Fingerprint Analyser (OFA), we simulated the chewing motions of the pretribosphenic Dryolestes that represents an evolutionary precursor condition to such tribosphenic mammals as Monodelphis. Animation of chewing path and detection of collisional contacts between virtual models of teeth suggests that Dryolestes differs from the classical two-phased chewing movement of tribosphenidans, due to the narrowing of the interdental space in cervical (crown-root transition) direction, the inclination angle of the hypoflexid groove, and the unicuspid talonid. The pretribosphenic chewing cycle is equivalent to phase I of the tribosphenic chewing cycle, but the former lacks phase II of the tribosphenic chewing. The new approach can analyze the chewing cycle of the jaw by using polygonal 3D models of tooth surfaces, in a way that is complementary to the electromyography and strain gauge studies of muscle function of living animals. The technique allows alignment and scaling of isolated fossil teeth and utilizes the wear facet orientation and striation of the teeth to reconstruct the chewing path of extinct mammals. PMID:25091547

11. Function of pretribosphenic and tribosphenic mammalian molars inferred from 3D animation

Schultz, Julia A.; Martin, Thomas

2014-10-01

Appearance of the tribosphenic molar in the Late Jurassic (160 Ma) is a crucial innovation for food processing in mammalian evolution. This molar type is characterized by a protocone, a talonid basin and a two-phased chewing cycle, all of which are apomorphic. In this functional study on the teeth of Late Jurassic Dryolestes leiriensis and the living marsupial Monodelphis domestica, we demonstrate that pretribosphenic and tribosphenic molars show fundamental differences of food reduction strategies, representing a shift in dental function during the transition of tribosphenic mammals. By using the Occlusal Fingerprint Analyser (OFA), we simulated the chewing motions of the pretribosphenic Dryolestes that represents an evolutionary precursor condition to such tribosphenic mammals as Monodelphis. Animation of chewing path and detection of collisional contacts between virtual models of teeth suggests that Dryolestes differs from the classical two-phased chewing movement of tribosphenidans, due to the narrowing of the interdental space in cervical (crown-root transition) direction, the inclination angle of the hypoflexid groove, and the unicuspid talonid. The pretribosphenic chewing cycle is equivalent to phase I of the tribosphenic chewing cycle, but the former lacks phase II of the tribosphenic chewing. The new approach can analyze the chewing cycle of the jaw by using polygonal 3D models of tooth surfaces, in a way that is complementary to the electromyography and strain gauge studies of muscle function of living animals. The technique allows alignment and scaling of isolated fossil teeth and utilizes the wear facet orientation and striation of the teeth to reconstruct the chewing path of extinct mammals.

12. Bayesian nonparametric inference on quantile residual life function: Application to breast cancer data.

PubMed

Park, Taeyoung; Jeong, Jong-Hyeon; Lee, Jae Won

2012-08-15

There is often an interest in estimating a residual life function as a summary measure of survival data. For ease in presentation of the potential therapeutic effect of a new drug, investigators may summarize survival data in terms of the remaining life years of patients. Under heavy right censoring, however, some reasonably high quantiles (e.g., median) of a residual lifetime distribution cannot be always estimated via a popular nonparametric approach on the basis of the Kaplan-Meier estimator. To overcome the difficulties in dealing with heavily censored survival data, this paper develops a Bayesian nonparametric approach that takes advantage of a fully model-based but highly flexible probabilistic framework. We use a Dirichlet process mixture of Weibull distributions to avoid strong parametric assumptions on the unknown failure time distribution, making it possible to estimate any quantile residual life function under heavy censoring. Posterior computation through Markov chain Monte Carlo is straightforward and efficient because of conjugacy properties and partial collapse. We illustrate the proposed methods by using both simulated data and heavily censored survival data from a recent breast cancer clinical trial conducted by the National Surgical Adjuvant Breast and Bowel Project. PMID:22437758

13. Functional morphology of the hallucal metatarsal with implications for inferring grasping ability in extinct primates.

PubMed

Goodenberger, Katherine E; Boyer, Doug M; Orr, Caley M; Jacobs, Rachel L; Femiani, John C; Patel, Biren A

2015-03-01

Primate evolutionary morphologists have argued that selection for life in a fine branch niche resulted in grasping specializations that are reflected in the hallucal metatarsal (Mt1) morphology of extant "prosimians", while a transition to use of relatively larger, horizontal substrates explains the apparent loss of such characters in anthropoids. Accordingly, these morphological characters-Mt1 torsion, peroneal process length and thickness, and physiological abduction angle-have been used to reconstruct grasping ability and locomotor mode in the earliest fossil primates. Although these characters are prominently featured in debates on the origin and subsequent radiation of Primates, questions remain about their functional significance. This study examines the relationship between these morphological characters of the Mt1 and a novel metric of pedal grasping ability for a large number of extant taxa in a phylogenetic framework. Results indicate greater Mt1 torsion in taxa that engage in hallucal grasping and in those that utilize relatively small substrates more frequently. This study provides evidence that Carpolestes simpsoni has a torsion value more similar to grasping primates than to any scandentian. The results also show that taxa that habitually grasp vertical substrates are distinguished from other taxa in having relatively longer peroneal processes. Furthermore, a longer peroneal process is also correlated with calcaneal elongation, a metric previously found to reflect leaping proclivity. A more refined understanding of the functional associations between Mt1 morphology and behavior in extant primates enhances the potential for using these morphological characters to comprehend primate (locomotor) evolution. PMID:25378276

14. Inferring cortical function in the mouse visual system through large-scale systems neuroscience.

PubMed

Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

2016-07-01

The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort. PMID:27382147

15. Inferring cortical function in the mouse visual system through large-scale systems neuroscience

PubMed Central

Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W.; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R. Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

2016-01-01

The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort. PMID:27382147

16. Bayesian inference in an item response theory model with a generalized student t link function

Azevedo, Caio L. N.; Migon, Helio S.

2012-10-01

In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

17. Crustal structure beneath the Japanese Islands inferred from receiver function analysis using similar earthquakes

Igarashi, Toshihiro

2016-04-01

The stress concentration and strain accumulation process due to inter-plate coupling of the subducting plate should have a large effect on inland shallow earthquakes that occur in the overriding plate. Information on the crustal structure and the crustal thickness is important to understanding their process. In this study, I applied receiver function analysis using similar earthquakes to estimate the crustal velocity structures beneath the Japanese Islands. Because similar earthquakes are caused repeatedly at almost the same place, they are useful for extracting information on spatial distribution and temporal changes of seismic velocity structures beneath the seismic stations. I used telemetric seismographic network data covered the Japanese Islands and moderate-sized similar earthquakes which occurred in the southern Hemisphere with epicentral distances between 30 and 90 degrees for about 26 years from October 1989. Data analysis was performed separately before and after the 2011 Tohoku-Oki earthquake. To identify the spatial distribution of crustal structure, I searched for the best-correlated model between an observed receiver function at each station and synthetic ones by using a grid search method. As results, I clarified the spatial distribution of the crustal velocity structures. The spatial patterns of velocities from the ground surface to 5 km deep are corresponding with basement depth models although the velocities are slower than those of tomography models. They indicate thick sediment layers in several plain and basin areas. The crustal velocity perturbations are consistent with existing tomography models. The active volcanoes correspond low-velocity zones from the upper crust to the crust-mantle transition. A comparison of the crustal structure before and after the 2011 Tohoku-Oki earthquake suggests that the northeastern Japan arc changed to lower velocities in some areas. This kind of velocity changes might be due to other effects such as changes of

18. Symmetric quadratic Hamiltonians with pseudo-Hermitian matrix representation

Fernández, Francisco M.

2016-06-01

We prove that any symmetric Hamiltonian that is a quadratic function of the coordinates and momenta has a pseudo-Hermitian adjoint or regular matrix representation. The eigenvalues of the latter matrix are the natural frequencies of the Hamiltonian operator. When all the eigenvalues of the matrix are real, then the spectrum of the symmetric Hamiltonian is real and the operator is Hermitian. As illustrative examples we choose the quadratic Hamiltonians that model a pair of coupled resonators with balanced gain and loss, the electromagnetic self-force on an oscillating charged particle and an active LRC circuit.

19. Sediment thickness beneath the Indo-Gangetic Plain and Siwalik Himalaya inferred from receiver function modelling

Borah, Kajaljyoti; Kanna, Nagaraju; Rai, S. S.; Prakasam, K. S.

2015-03-01

The Indo-Gangetic Plain and the adjoining Siwalik Himalaya are the seismically most vulnerable regions due to high density of human population and presence of thick sediments that amplify the seismic waves due to an earthquake in the region. We investigate the sedimentary structure and crustal thickness of the region through joint inversion of the receiver function time series at 14 broadband seismograph locations and the available Rayleigh velocity data for the region. Results show significant variability of sedimentary layer thicknesses from 1.0 to 2.0 km beneath the Delhi region to 2.0-5.0 km beneath the Indo-Gangetic Plain and the Siwalik Himalaya. As we progress from the Delhi to the Indo-Gangetic Plain, we observe a decrease in the shear velocity in sedimentary layer from ∼2.0 km/s to ∼1.3 km/s while the layer thickness increases progressively from ∼1.0 km in south to 2.0-5.0 km in the north. Average S-velocity in the sedimentary layer beneath the Siwalik Himalaya is ∼2.1 km/s. Crustal thicknesses varies from ∼42 in the Delhi region, ∼48 km in the Indo-Gangetic Plain, ∼50 km in the western part of Siwalik Himalaya to ∼60 km in the Kumaon region of Siwalik Himalaya.

20. On Volterra quadratic stochastic operators with continual state space

SciTech Connect

Ganikhodjaev, Nasir; Hamzah, Nur Zatul Akmar

2015-05-15

Let (X,F) be a measurable space, and S(X,F) be the set of all probability measures on (X,F) where X is a state space and F is σ - algebraon X. We consider a nonlinear transformation (quadratic stochastic operator) defined by (Vλ)(A) = ∫{sub X}∫{sub X}P(x,y,A)dλ(x)dλ(y), where P(x, y, A) is regarded as a function of two variables x and y with fixed A ∈ F . A quadratic stochastic operator V is called a regular, if for any initial measure the strong limit lim{sub n→∞} V{sup n }(λ) is exists. In this paper, we construct a family of quadratic stochastic operators defined on the segment X = [0,1] with Borel σ - algebra F on X , prove their regularity and show that the limit measure is a Dirac measure.

1. Quadratic expressions by means of summing all the matchsticks'

Faaiz Gierdien, M.

2012-09-01

This note presents demonstrations of quadratic expressions that come about when particular problems are posed with respect to matchsticks that form regular triangles, squares, pentagons and so on. Usually when such 'matchstick' problems are used as ways to foster algebraic thinking, the expressions for the number of matchstick quantities are linear and not quadratic. It will be shown that a pedagogy of 'summing all the matchsticks' is central to the emergence of quadratic expressions. This pedagogy involves generational and transformational activities which are considered as some of the main activities of algebra. Key elements to these activities are processes such as recognizing and extending patterns, and specializing and generalizing particular functional relationships. Implications of these processes in terms of algebraic thinking are considered.

2. On Volterra quadratic stochastic operators with continual state space

Ganikhodjaev, Nasir; Hamzah, Nur Zatul Akmar

2015-05-01

Let (X,F) be a measurable space, and S(X,F) be the set of all probability measures on (X,F) where X is a state space and F is σ - algebraon X. We consider a nonlinear transformation (quadratic stochastic operator) defined by (V λ )(A ) = ∫X ∫X P (x ,y ,A )d λ (x )d λ (y ), where P(x, y, A) is regarded as a function of two variables x and y with fixed A ∈ F . A quadratic stochastic operator V is called a regular, if for any initial measure the strong limit lim n →∞ Vn(λ ) is exists. In this paper, we construct a family of quadratic stochastic operators defined on the segment X = [0,1] with Borel σ - algebra F on X , prove their regularity and show that the limit measure is a Dirac measure.

3. The SWELLS survey - VI. Hierarchical inference of the initial mass functions of bulges and discs

Brewer, Brendon J.; Marshall, Philip J.; Auger, Matthew W.; Treu, Tommaso; Dutton, Aaron A.; Barnabè, Matteo

2014-01-01

The long-standing assumption that the stellar initial mass function (IMF) is universal has recently been challenged by a number of observations. Several studies have shown that a heavy' IMF (e.g. with a Salpeter-like abundance of low-mass stars and thus normalization) is preferred for massive early-type galaxies, while this IMF is inconsistent with the properties of less massive, later-type galaxies. These discoveries motivate the hypothesis that the IMF may vary (possibly very slightly) across galaxies and across components of individual galaxies (e.g. bulges versus discs). In this paper, we use a sample of 19 late-type strong gravitational lenses from the Sloan WFC Edge-on Late-type Lens Survey (SWELLS) to investigate the IMFs of the bulges and discs in late-type galaxies. We perform a joint analysis of the galaxies' total masses (constrained by strong gravitational lensing) and stellar masses (constrained by optical and near-infrared colours in the context of a stellar population synthesis model, up to an IMF normalization parameter). Using minimal assumptions apart from the physical constraint that the total stellar mass m* within any aperture must be less than the total mass mtot within the aperture, we find that the bulges of the galaxies cannot have IMFs heavier (i.e. implying high mass per unit luminosity) than Salpeter, while the disc IMFs are not well constrained by this data set. We also discuss the necessity for hierarchical modelling when combining incomplete information about multiple astronomical objects. This modelling approach allows us to place upper limits on the size of any departures from universality. More data, including spatially resolved kinematics (as in Paper V) and stellar population diagnostics over a range of bulge and disc masses, are needed to robustly quantify how the IMF varies within galaxies.

4. Complex geometry of the subducted Pacific slab inferred from receiver function

Zhang, Ruiqing; Wu, Qingju; Zhang, Guangcheng

2014-05-01

In recent years, slab tear has received considerable attention and been reported in many arc-arc junctures in Pacific plate subdution zones. From 2009 to 2011, we deployed two portable experiments equipped with CMG-3ESPC seismometers and the recorders of REFTEK-130B in NE China. The two linear seismic arrays were designed nearly parallel, and each of them containing about 60 seismic stations extended about 1200 km from west to east spanning all surface geological terrains of NE China. The south one was firstly set up and continually operated over two year, while the north deployment worked only about one year. By using the teleseismic data collected by these two arrays, we calculate the P receiver functions to map topographic variation of the upper mantle discontinuities. Our sampled region is located where the juncture between the subducting Kuril and Japan slabs reaches the 660-km discontinuity. Distinct variation of the 660-km discontinuity is mapped beneath the regions. A deeper-than-normal 660 km discontinuity is observed locally in the southeastern part of our sampled region. The depression of the 660 km discontinuity may be resulted from an oceanic lithospheric slab deflected in the mantle transition zone, in good agreement with the result of earlier tomographic and other seismic studies in this region. The northeastern portion of our sampled region, however, does not show clearly the deflection of the slab. The variation of the tomography of the 660-km discontinuity in our sampled regions may indicate a complex geometry of the subducted Pacific slab.

5. Seismic Discontinuities within the Crust and Mantle Beneath Indonesia as Inferred from P Receiver Functions

Woelbern, I.; Rumpker, G.

2015-12-01

Indonesia is situated at the southern margin of SE Asia, which comprises an assemblage of Gondwana-derived continental terranes, suture zones and volcanic arcs. The formation of SE Asia is believed to have started in Early Devonian. Its complex history involves the opening and closure of three distinct Tethys oceans, each accompanied by the rifting of continental fragments. We apply the receiver function technique to data of the temporary MERAMEX network operated in Central Java from May to October 2004 by the GeoForschungsZentrum Potsdam. The network consisted of 112 mobile stations with a spacing of about 10 km covering the full width of the island between the southern and northern coast lines. The tectonic history is reflected in a complex crustal structure of Central Java exhibiting strong topography of the Moho discontinuity related to different tectonic units. A discontinuity of negative impedance contrast is observed throughout the mid-crust interpreted as the top of a low-velocity layer which shows no depth correlation with the Moho interface. Converted phases generated at greater depth beneath Indonesia indicate the existence of multiple seismic discontinuities within the upper mantle and even below. The strongest signal originates from the base of the mantle transition zone, i.e. the 660 km discontinuity. The phase related to the 410 km discontinuity is less pronounced, but clearly identifiable as well. The derived thickness of the mantle-transition zone is in good agreement with the IASP91 velocity model. Additional phases are observed at roughly 33 s and 90 s relative to the P onset, corresponding to about 300 km and 920 km, respectively. A signal of reversed polarity indicates the top of a low velocity layer at about 370 km depth overlying the mantle transition zone.

6. Why are dunkels sticky? Preschoolers infer functionality and intentional creation for artifact properties learned from generic language.

PubMed

2010-10-01

Artifacts pose a potential learning problem for children because the mapping between their features and their functions is often not transparent. In solving this problem, children are likely to rely on a number of information sources (e.g., others' actions, affordances). We argue that children's sensitivity to nuances in the language used to describe artifacts is an important, but so far unacknowledged, piece of this puzzle. Specifically, we hypothesize that children are sensitive to whether an unfamiliar artifact's features are highlighted using generic (e.g., "Dunkels are sticky") or non-generic (e.g., "This dunkel is sticky") language. Across two studies, older-but not younger-preschoolers who heard such features introduced via generic statements inferred that they are a functional part of the artifact's design more often than children who heard the same features introduced via non-generic statements. The ability to pick up on this linguistic cue may expand considerably the amount of conceptual information about artifacts that children derive from conversations with adults. PMID:20656283

7. A Version of Quadratic Regression with Interpretable Parameters.

ERIC Educational Resources Information Center

Cudeck, Robert; du Toit, Stephen H. C.

2002-01-01

Suggests an alternative form of the quadratic model that has the same expectation function of the original model but has the useful feature that its parameters are interpretable. Provides examples of a simple regression problem and a nonlinear mixed-effects model. (SLD)

8. Geometrical and Graphical Solutions of Quadratic Equations.

ERIC Educational Resources Information Center

Hornsby, E. John, Jr.

1990-01-01

Presented are several geometrical and graphical methods of solving quadratic equations. Discussed are Greek origins, Carlyle's method, von Staudt's method, fixed graph methods and imaginary solutions. (CW)

PubMed Central

Liao, Jie-Qiao; Nori, Franco

2014-01-01

We present exact analytical solutions to study the coherent interaction between a single photon and the mechanical motion of a membrane in quadratic optomechanics. We consider single-photon emission and scattering when the photon is initially inside the cavity and in the fields outside the cavity, respectively. Using our solutions, we calculate the single-photon emission and scattering spectra, and find relations between the spectral features and the system's inherent parameters, such as: the optomechanical coupling strength, the mechanical frequency, and the cavity-field decay rate. In particular, we clarify the conditions for the phonon sidebands to be visible. We also study the photon-phonon entanglement for the long-time emission and scattering states. The linear entropy is employed to characterize this entanglement by treating it as a bipartite one between a single mode of phonons and a single photon. PMID:25200128

10. Large-scale sequential quadratic programming algorithms

SciTech Connect

Eldersveld, S.K.

1992-09-01

The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

11. Maximization of Sums of Quotients of Quadratic Forms and Some Generalizations.

ERIC Educational Resources Information Center

Kiers, Henk A. L.

1995-01-01

Monotonically convergent algorithms are described for maximizing sums of quotients of quadratic forms. Six (constrained) functions are investigated. The general formulation of the functions and the algorithms allow for application of the algorithms in various situations in multivariate analysis. (SLD)

12. POGs2: A Web Portal to Facilitate Cross-Species Inferences About Protein Architecture and Function in Plants

PubMed Central

Tomcal, Michael; Stiffler, Nicholas; Barkan, Alice

2013-01-01

The Putative orthologous Groups 2 Database (POGs2) (http://pogs.uoregon.edu/) integrates information about the inferred proteomes of four plant species (Arabidopsis thaliana, Zea mays, Orza sativa, and Populus trichocarpa) in a display that facilitates comparisons among orthologs and extrapolation of annotations among species. A single-page view collates key functional data for members of each Putative Orthologous Group (POG): graphical representations of InterPro domains, predicted and established intracellular locations, and imported gene descriptions. The display incorporates POGs predicted by two different algorithms as well as gene trees, allowing users to evaluate the validity of POG memberships. The web interface provides ready access to sequences and alignments of POG members, as well as sequences, alignments, and domain architectures of closely-related paralogs. A simple and flexible search interface permits queries by BLAST and by any combination of gene identifier, keywords, domain names, InterPro identifiers, and intracellular location. The concurrent display of domain architectures for orthologous proteins highlights errors in gene models and false-negatives in domain predictions. The POGs2 layout is also useful for exploring candidate genes identified by transposon tagging, QTL mapping, map-based cloning, and proteomics, and for navigating between orthologous groups that belong to the same gene family. PMID:24340041

13. POGs2: a web portal to facilitate cross-species inferences about protein architecture and function in plants.

PubMed

Tomcal, Michael; Stiffler, Nicholas; Barkan, Alice

2013-01-01

The Putative orthologous Groups 2 Database (POGs2) (http://pogs.uoregon.edu/) integrates information about the inferred proteomes of four plant species (Arabidopsis thaliana, Zea mays, Orza sativa, and Populus trichocarpa) in a display that facilitates comparisons among orthologs and extrapolation of annotations among species. A single-page view collates key functional data for members of each Putative Orthologous Group (POG): graphical representations of InterPro domains, predicted and established intracellular locations, and imported gene descriptions. The display incorporates POGs predicted by two different algorithms as well as gene trees, allowing users to evaluate the validity of POG memberships. The web interface provides ready access to sequences and alignments of POG members, as well as sequences, alignments, and domain architectures of closely-related paralogs. A simple and flexible search interface permits queries by BLAST and by any combination of gene identifier, keywords, domain names, InterPro identifiers, and intracellular location. The concurrent display of domain architectures for orthologous proteins highlights errors in gene models and false-negatives in domain predictions. The POGs2 layout is also useful for exploring candidate genes identified by transposon tagging, QTL mapping, map-based cloning, and proteomics, and for navigating between orthologous groups that belong to the same gene family. PMID:24340041

14. Entropic Inference

Caticha, Ariel

2011-03-01

In this tutorial we review the essential arguments behing entropic inference. We focus on the epistemological notion of information and its relation to the Bayesian beliefs of rational agents. The problem of updating from a prior to a posterior probability distribution is tackled through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting method of Maximum relative Entropy (ME), includes as special cases both MaxEnt and Bayes' rule, and therefore unifies the two themes of these workshops—the Maximum Entropy and the Bayesian methods—into a single general inference scheme.

15. Binary Quadratic Forms: A Historical View

ERIC Educational Resources Information Center

Khosravani, Azar N.; Beintema, Mark B.

2006-01-01

We present an expository account of the development of the theory of binary quadratic forms. Beginning with the formulation and proof of the Two-Square Theorem, we show how the study of forms of the type x[squared] + ny[squared] led to the discovery of the Quadratic Reciprocity Law, and how this theorem, along with the concept of reduction relates…

16. Factorising a Quadratic Expression with Geometric Insights

ERIC Educational Resources Information Center

Joarder, Anwar H.

2015-01-01

An algorithm is presented for factorising a quadratic expression to facilitate instruction and learning. It appeals to elementary geometry which may provide better insights to some students or teachers. There have been many methods for factorising a quadratic expression described in school text books. However, students often seem to struggle with…

17. THE PANCHROMATIC HUBBLE ANDROMEDA TREASURY. IV. A PROBABILISTIC APPROACH TO INFERRING THE HIGH-MASS STELLAR INITIAL MASS FUNCTION AND OTHER POWER-LAW FUNCTIONS

SciTech Connect

Weisz, Daniel R.; Fouesneau, Morgan; Dalcanton, Julianne J.; Clifton Johnson, L.; Beerman, Lori C.; Williams, Benjamin F.; Hogg, David W.; Foreman-Mackey, Daniel T.; Rix, Hans-Walter; Gouliermis, Dimitrios; Dolphin, Andrew E.; Lang, Dustin; Bell, Eric F.; Gordon, Karl D.; Kalirai, Jason S.; Skillman, Evan D.

2013-01-10

We present a probabilistic approach for inferring the parameters of the present-day power-law stellar mass function (MF) of a resolved young star cluster. This technique (1) fully exploits the information content of a given data set; (2) can account for observational uncertainties in a straightforward way; (3) assigns meaningful uncertainties to the inferred parameters; (4) avoids the pitfalls associated with binning data; and (5) can be applied to virtually any resolved young cluster, laying the groundwork for a systematic study of the high-mass stellar MF (M {approx}> 1 M {sub Sun }). Using simulated clusters and Markov Chain Monte Carlo sampling of the probability distribution functions, we show that estimates of the MF slope, {alpha}, are unbiased and that the uncertainty, {Delta}{alpha}, depends primarily on the number of observed stars and on the range of stellar masses they span, assuming that the uncertainties on individual masses and the completeness are both well characterized. Using idealized mock data, we compute the theoretical precision, i.e., lower limits, on {alpha}, and provide an analytic approximation for {Delta}{alpha} as a function of the observed number of stars and mass range. Comparison with literature studies shows that {approx}3/4 of quoted uncertainties are smaller than the theoretical lower limit. By correcting these uncertainties to the theoretical lower limits, we find that the literature studies yield ({alpha}) = 2.46, with a 1{sigma} dispersion of 0.35 dex. We verify that it is impossible for a power-law MF to obtain meaningful constraints on the upper mass limit of the initial mass function, beyond the lower bound of the most massive star actually observed. We show that avoiding substantial biases in the MF slope requires (1) including the MF as a prior when deriving individual stellar mass estimates, (2) modeling the uncertainties in the individual stellar masses, and (3) fully characterizing and then explicitly modeling the

18. The Panchromatic Hubble Andromeda Treasury. IV. A Probabilistic Approach to Inferring the High-mass Stellar Initial Mass Function and Other Power-law Functions

Weisz, Daniel R.; Fouesneau, Morgan; Hogg, David W.; Rix, Hans-Walter; Dolphin, Andrew E.; Dalcanton, Julianne J.; Foreman-Mackey, Daniel T.; Lang, Dustin; Johnson, L. Clifton; Beerman, Lori C.; Bell, Eric F.; Gordon, Karl D.; Gouliermis, Dimitrios; Kalirai, Jason S.; Skillman, Evan D.; Williams, Benjamin F.

2013-01-01

We present a probabilistic approach for inferring the parameters of the present-day power-law stellar mass function (MF) of a resolved young star cluster. This technique (1) fully exploits the information content of a given data set; (2) can account for observational uncertainties in a straightforward way; (3) assigns meaningful uncertainties to the inferred parameters; (4) avoids the pitfalls associated with binning data; and (5) can be applied to virtually any resolved young cluster, laying the groundwork for a systematic study of the high-mass stellar MF (M >~ 1 M ⊙). Using simulated clusters and Markov Chain Monte Carlo sampling of the probability distribution functions, we show that estimates of the MF slope, α, are unbiased and that the uncertainty, Δα, depends primarily on the number of observed stars and on the range of stellar masses they span, assuming that the uncertainties on individual masses and the completeness are both well characterized. Using idealized mock data, we compute the theoretical precision, i.e., lower limits, on α, and provide an analytic approximation for Δα as a function of the observed number of stars and mass range. Comparison with literature studies shows that ~3/4 of quoted uncertainties are smaller than the theoretical lower limit. By correcting these uncertainties to the theoretical lower limits, we find that the literature studies yield langαrang = 2.46, with a 1σ dispersion of 0.35 dex. We verify that it is impossible for a power-law MF to obtain meaningful constraints on the upper mass limit of the initial mass function, beyond the lower bound of the most massive star actually observed. We show that avoiding substantial biases in the MF slope requires (1) including the MF as a prior when deriving individual stellar mass estimates, (2) modeling the uncertainties in the individual stellar masses, and (3) fully characterizing and then explicitly modeling the completeness for stars of a given mass. The precision on MF

19. Quadratic invariants for discrete clusters of weakly interacting waves

Harper, Katie L.; Bustamante, Miguel D.; Nazarenko, Sergey V.

2013-06-01

We consider discrete clusters of quasi-resonant triads arising from a Hamiltonian three-wave equation. A cluster consists of N modes forming a total of M connected triads. We investigate the problem of constructing a functionally independent set of quadratic constants of motion. We show that this problem is equivalent to an underlying basic linear problem, consisting of finding the null space of a rectangular M × N matrix {A} with entries 1, -1 and 0. In particular, we prove that the number of independent quadratic invariants is equal to J ≡ N - M* ⩾ N - M, where M* is the number of linearly independent rows in {A}. Thus, the problem of finding all independent quadratic invariants is reduced to a linear algebra problem in the Hamiltonian case. We establish that the properties of the quadratic invariants (e.g., locality) are related to the topological properties of the clusters (e.g., types of linkage). To do so, we formulate an algorithm for decomposing large clusters into smaller ones and show how various invariants are related to certain parts of a cluster, including the basic structures leading to M* < M. We illustrate our findings by presenting examples from the Charney-Hasegawa-Mima wave model, and by showing a classification of small (up to three-triad) clusters.

20. Quadratic boundedness of uncertain nonlinear dynamic systems

Brockman, Mark Lawrence

Physical systems are often perturbed by unknown external disturbances or contain important system parameters which are difficult to model exactly. However, engineers are expected to design systems which perform well even in the presence of uncertainties. For example, an airplane designer can never know the precise direction or magnitude of wind gusts, or the exact mass distribution inside the aircraft, but passengers expect to arrive on time after a smooth ride. This thesis will first present the concept of quadratic boundedness of an uncertain nonlinear dynamic system, and then develop analysis techniques and control design methods for systems containing unknown disturbances and parameters. For a class of nonlinear systems, conditions for quadratic boundedness are given, and the relationship between quadratic boundedness and quadratic stability is explored. An important consequence of quadratic boundedness is the ability to calculate an upper bound on the system gain of an uncertain nonlinear system. For nominally linear systems, necessary and sufficient conditions for quadratic boundedness are given. The innovative use of linear matrix inequalities in an iterative algorithm provides a means to analyze the quadratic boundedness properties of systems containing parameter uncertainties. The analysis results establish a framework for the development of design methods which integrate performance specifications into the control design process for all the types of systems considered. Numerous examples illustrate the major results of the thesis.

1. Perceptual inference.

PubMed

Aggelopoulos, Nikolaos C

2015-08-01

Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience. PMID:25976632

2. Crustal anisotropy in northeastern Tibetan Plateau inferred from receiver functions: Rock textures caused by metamorphic fluids and lower crust flow?

Liu, Zhen; Park, Jeffrey; Rye, Danny M.

2015-10-01

The crust of Tibetan Plateau may have formed via shortening/thickening or large-scale underthrusting, and subsequently modified via lower crust channel flows and volatile-mediated regional metamorphism. The amplitude and distribution of crustal anisotropy record the history of continental deformation, offering clues to its formation and later modification. In this study, we first investigate the back-azimuth dependence of Ps converted phases using multitaper receiver functions (RFs). We analyze teleseismic data for 35 temporary broadband stations in the ASCENT experiment located in northeastern Tibet. We stack receiver functions after a moving-window moveout correction. Major features of RFs include: 1) Ps arrivals at 8-10 s on the radial components, suggesting a 70-90-km crustal thickness in the study area; 2) two-lobed back-azimuth variation for intra-crustal Ps phases in the upper crust (< 20 km), consistent with tilted symmetry axis anisotropy or dipping interfaces; 3) significant Ps arrivals with four-lobed back-azimuth variation distributed in distinct layers in the middle and lower crust (up to 60 km), corresponding to (sub)horizontal-axis anisotropy; and 4) weak or no evidence of azimuthal anisotropy in the lowermost crust. To study the anisotropy, we compare the observed RF stacks with one-dimensional reflectivity synthetic seismograms in anisotropic media, and fit major features by "trial and error" forward modeling. Crustal anisotropy offers few clues on plateau formation, but strong evidence of ongoing deformation and metamorphism. We infer strong horizontal-axis anisotropy concentrated in the middle and lower crust, which could be explained by vertically aligned sheet silicates, open cracks filled with magma or other fluid, vertical vein structures or by 1-10-km-scale chimney structures that have focused metamorphic fluids. Simple dynamic models encounter difficulty in generating vertically aligned sheet silicates. Instead, we interpret our data to

3. Seven Wonders of the Ancient and Modern Quadratic World.

ERIC Educational Resources Information Center

Taylor, Sharon E.; Mittag, Kathleen Cage

2001-01-01

Presents four methods for solving a quadratic equation using graphing calculator technology: (1) graphing with the CALC feature; (2) quadratic formula program; (3) table; and (4) solver. Includes a worksheet for a lab activity on factoring quadratic equations. (KHR)

4. MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma

PubMed Central

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S.; Theis, Fabian J.

2015-01-01

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method “miRlastic”, which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of mi

5. Functional characterization of somatic mutations in cancer using network-based inference of protein activity | Office of Cancer Genomics

Cancer.gov

Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given patient is crucial for developing personalized treatment plans. However, accurate inference of aberrant protein activity in biological samples is still challenging as genetic alterations are only partially predictive and direct measurements of protein activity are generally not feasible.

6. Quadratic Stochastic Operators with Countable State Space

Ganikhodjaev, Nasir

2016-03-01

In this paper, we provide the classes of Poisson and Geometric quadratic stochastic operators with countable state space, study the dynamics of these operators and discuss their application to economics.

7. Schur Stability Regions for Complex Quadratic Polynomials

ERIC Educational Resources Information Center

Cheng, Sui Sun; Huang, Shao Yuan

2010-01-01

Given a quadratic polynomial with complex coefficients, necessary and sufficient conditions are found in terms of the coefficients such that all its roots have absolute values less than 1. (Contains 3 figures.)

8. Quantum integrability of quadratic Killing tensors

SciTech Connect

Duval, C.; Valent, G.

2005-05-01

Quantum integrability of classical integrable systems given by quadratic Killing tensors on curved configuration spaces is investigated. It is proven that, using a 'minimal' quantization scheme, quantum integrability is ensured for a large class of classic examples.

9. Quadratic nonlinear Klein-Gordon equation in one dimension

Hayashi, Nakao; Naumkin, Pavel I.

2012-10-01

We study the initial value problem for the quadratic nonlinear Klein-Gordon equation vtt + v - vxx = λv2, t ∈ R, x ∈ R, with initial conditions v(0, x) = v0(x), vt(0, x) = v1(x), x ∈ R, where v0 and v1 are real-valued functions, λ ∈ R. Using the method of normal forms of Shatah ["Normal forms and quadratic nonlinear Klein-Gordon equations," Commun. Pure Appl. Math. 38, 685-696 (1985)], we obtain a sharp asymptotic behavior of small solutions without the condition of a compact support on the initial data, which was assumed in the previous work of J.-M. Delort ["Existence globale et comportement asymptotique pour l'équation de Klein-Gordon quasi-linéaire á données petites en dimension 1," Ann. Sci. Ec. Normale Super. 34(4), 1-61 (2001)].

Marquette, Ian

2011-06-01

We present a generalized Kaluza-Klein monopole system. We solve this quantum superintegrable system on a Euclidean Taub Nut manifold using the separation of variables of the corresponding Schrödinger equation in spherical and parabolic coordinates. We present the integrals of motion of this system, the quadratic algebra generated by these integrals, the realization in terms of a deformed oscillator algebra using the Daskaloyannis construction and the energy spectrum. The structure constants and the Casimir operator are functions not only of the Hamiltonian but also of other two integrals commuting with all generators of the quadratic algebra and forming an Abelian subalgebra. We present another algebraic derivation of the energy spectrum of this system using the factorization method and ladder operators.

11. Exploring {{W}}_{∞ } in the quadratic basis

Procházka, Tomáš

2015-09-01

We study the operator product expansions in the chiral algebra {W}_{∞ } , first using the associativity conditions in the basis of primary generating fields and then using a different basis coming from the free field representation in which the OPE takes a simpler quadratic form. The results in the quadratic basis can be compactly written using certain bilocal combinations of the generating fields and we conjecture a closed-form expression for the complete OPE in this basis. Next we show that the commutation relations as well as correlation functions can be easily computed using properties of these bilocal fields. In the last part we verify the consistency with results derived previously by studying minimal models of {W}_{∞ } and comparing them to known reductions of {W}_{∞ } to {W}_N . The results we obtain illustrate nicely the role of triality symmetry in the representation theory of {W}_{∞ }.

12. The Factorability of Quadratics: Motivation for More Techniques

ERIC Educational Resources Information Center

Bosse, Michael J.; Nandakumar, N. R.

2005-01-01

Typically, secondary and college algebra students attempt to utilize either completing the square or the quadratic formula as techniques to solve a quadratic equation only after frustration with factoring has arisen. While both completing the square and the quadratic formula are techniques which can determine solutions for all quadratic equations,…

13. Biases in the inferred mass-to-light ratio of globular clusters: no need for variations in the stellar mass function

Shanahan, Rosemary L.; Gieles, Mark

2015-03-01

From a study of the integrated light properties of 200 globular clusters (GCs) in M31, Strader et al. found that the mass-to-light ratios are lower than what is expected from simple stellar population models with a canonical' stellar initial mass function (IMF), with the discrepancy being larger at high metallicities. We use dynamical multimass models, that include a prescription for equipartition, to quantify the bias in the inferred dynamical mass as the result of the assumption that light follows mass. For a universal IMF and a metallicity-dependent present-day mass function, we find that the inferred mass from integrated light properties systematically underestimates the true mass, and that the bias is more important at high metallicities, as was found for the M31 GCs. We show that mass segregation and a flattening of the mass function have opposing effects of similar magnitude on the mass inferred from integrated properties. This makes the mass-to-light ratio as derived from integrated properties an inadequate probe of the low-mass end of the stellar mass function. There is, therefore, no need for variations in the IMF, nor the need to invoke depletion of low-mass stars, to explain the observations. Finally, we find that the retention fraction of stellar-mass black holes (BHs) is an equally important parameter in understanding the mass segregation bias. We speculatively put forward to idea that kinematical data of GCs can in fact be used to constrain the total mass in stellar-mass BHs in GCs.

14. PHYSICAL FOUNDATIONS OF QUANTUM ELECTRONICS: A study of radiation propagation in a medium with quadratic inhomogeneity

Pikulev, A. A.

2001-09-01

The propagation of Hermitian beams in a medium with a distributed quadratic inhomogeneity is studied and is shown that any solution can be represented as a function of some particular solution. This is accomplished by establishing a one-to-one correspondence between optical fields in a homogeneous medium and in a medium with an arbitrary quadratic inhomogeneity. The stability of optical resonators is studied and the condition for their stability is found. Several solutions are found using the method developed.

15. Solution of the Dirac equation with some superintegrable potentials by the quadratic algebra approach

Aghaei, S.; Chenaghlou, A.

2014-02-01

The Dirac equation with scalar and vector potentials of equal magnitude is considered. For the two-dimensional harmonic oscillator superintegrable potential, the superintegrable potentials of E8 (case (3b)), S4 and S2, the Schrödinger-like equations are studied. The quadratic algebras of these quasi-Hamiltonians are derived. By using the realization of the quadratic algebras in a deformed oscillator algebra, the structure function and the energy eigenvalues are obtained.

16. Fast Approximate Quadratic Programming for Graph Matching

PubMed Central

Vogelstein, Joshua T.; Conroy, John M.; Lyzinski, Vince; Podrazik, Louis J.; Kratzer, Steven G.; Harley, Eric T.; Fishkind, Donniell E.; Vogelstein, R. Jacob; Priebe, Carey E.

2015-01-01

Quadratic assignment problems arise in a wide variety of domains, spanning operations research, graph theory, computer vision, and neuroscience, to name a few. The graph matching problem is a special case of the quadratic assignment problem, and graph matching is increasingly important as graph-valued data is becoming more prominent. With the aim of efficiently and accurately matching the large graphs common in big data, we present our graph matching algorithm, the Fast Approximate Quadratic assignment algorithm. We empirically demonstrate that our algorithm is faster and achieves a lower objective value on over 80% of the QAPLIB benchmark library, compared with the previous state-of-the-art. Applying our algorithm to our motivating example, matching C. elegans connectomes (brain-graphs), we find that it efficiently achieves performance. PMID:25886624

17. Limit cycles near hyperbolas in quadratic systems

Artés, Joan C.; Dumortier, Freddy; Llibre, Jaume

In this paper we introduce the notion of infinity strip and strip of hyperbolas as organizing centers of limit cycles in polynomial differential systems on the plane. We study a strip of hyperbolas occurring in some quadratic systems. We deal with the cyclicity of the degenerate graphics DI2a from the programme, set up in [F. Dumortier, R. Roussarie, C. Rousseau, Hilbert's 16th problem for quadratic vector fields, J. Differential Equations 110 (1994) 86-133], to solve the finiteness part of Hilbert's 16th problem for quadratic systems. Techniques from geometric singular perturbation theory are combined with the use of the Bautin ideal. We also rely on the theory of Darboux integrability.

18. Fast approximate quadratic programming for graph matching.

PubMed

Vogelstein, Joshua T; Conroy, John M; Lyzinski, Vince; Podrazik, Louis J; Kratzer, Steven G; Harley, Eric T; Fishkind, Donniell E; Vogelstein, R Jacob; Priebe, Carey E

2015-01-01

Quadratic assignment problems arise in a wide variety of domains, spanning operations research, graph theory, computer vision, and neuroscience, to name a few. The graph matching problem is a special case of the quadratic assignment problem, and graph matching is increasingly important as graph-valued data is becoming more prominent. With the aim of efficiently and accurately matching the large graphs common in big data, we present our graph matching algorithm, the Fast Approximate Quadratic assignment algorithm. We empirically demonstrate that our algorithm is faster and achieves a lower objective value on over 80% of the QAPLIB benchmark library, compared with the previous state-of-the-art. Applying our algorithm to our motivating example, matching C. elegans connectomes (brain-graphs), we find that it efficiently achieves performance. PMID:25886624

19. Quadratic forms of projective spaces over rings

Levchuk, V. M.; Starikova, O. A.

2006-06-01

In the passage from fields to rings of coefficients quadratic forms with invertible matrices lose their decisive role. It turns out that if all quadratic forms over a ring are diagonalizable, then in effect this is always a local principal ideal ring R with 2\\in R^*. The problem of the construction of a normal' diagonal form of a quadratic form over a ring R faces obstacles in the case of indices \\vert R^*:R^{*2}\\vert greater than 1. In the case of index 2 this problem has a solution given in Theorem 2.1 for 1+R^{*2}\\subseteq R^{*2} (an extension of the law of inertia for real quadratic forms) and in Theorem 2.2 for 1+R^2 containing an invertible non-square. Under the same conditions on a ring R with nilpotent maximal ideal the number of classes of projectively congruent quadratic forms of the projective space associated with a free R-module of rank n is explicitly calculated (Proposition 3.2). Up to projectivities, the list of forms is presented for the projective plane over R and also (Theorem 3.3) over the local ring F\\lbrack\\lbrack x,y\\rbrack\\rbrack/\\langle x^{2},xy,y^{2}\\rangle with non-principal maximal ideal, where F=2F is a field with an invertible non-square in 1+F^{2} and \\vert F^{*}:F^{*2}\\vert=2. In the latter case the number of classes of non-diagonalizable quadratic forms of rank 0 depends on one's choice of the field F and is not even always finite; all the other forms make up 21 classes.

20. Quintessence with quadratic coupling to dark matter

SciTech Connect

Boehmer, Christian G.; Chan, Nyein; Caldera-Cabral, Gabriela; Lazkoz, Ruth; Maartens, Roy

2010-04-15

We introduce a new form of coupling between dark energy and dark matter that is quadratic in their energy densities. Then we investigate the background dynamics when dark energy is in the form of exponential quintessence. The three types of quadratic coupling all admit late-time accelerating critical points, but these are not scaling solutions. We also show that two types of coupling allow for a suitable matter era at early times and acceleration at late times, while the third type of coupling does not admit a suitable matter era.

1. Heredity in one-dimensional quadratic maps

Romera, M.; Pastor, G.; Alvarez, G.; Montoya, F.

1998-12-01

In an iterative process, as is the case of a one-dimensional quadratic map, heredity has never been mentioned. In this paper we show that the pattern of a superstable orbit of a one-dimensional quadratic map can be expressed as the sum of the gene of the chaotic band where the pattern is to be found, and the ancestral path that joins all its ancestors. The ancestral path holds all the needed genetic information to calculate the descendants of the pattern. The ancestral path and successive descendant generations of the pattern constitute the family tree of the pattern, which is important to study and understand the orbit's ordering.

2. Quadratic-Like Dynamics of Cubic Polynomials

Blokh, Alexander; Oversteegen, Lex; Ptacek, Ross; Timorin, Vladlen

2016-02-01

A small perturbation of a quadratic polynomial f with a non-repelling fixed point gives a polynomial g with an attracting fixed point and a Jordan curve Julia set, on which g acts like angle doubling. However, there are cubic polynomials with a non-repelling fixed point, for which no perturbation results into a polynomial with Jordan curve Julia set. Motivated by the study of the closure of the Cubic Principal Hyperbolic Domain, we describe such polynomials in terms of their quadratic-like restrictions.

3. On orthogonality preserving quadratic stochastic operators

SciTech Connect

Mukhamedov, Farrukh; Taha, Muhammad Hafizuddin Mohd

2015-05-15

A quadratic stochastic operator (in short QSO) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. In the present paper, we first give a simple characterization of Volterra QSO in terms of absolutely continuity of discrete measures. Further, we introduce a notion of orthogonal preserving QSO, and describe such kind of operators defined on two dimensional simplex. It turns out that orthogonal preserving QSOs are permutations of Volterra QSO. The associativity of genetic algebras generated by orthogonal preserving QSO is studied too.

4. Structured Functional Principal Component Analysis

PubMed Central

Shou, Haochang; Zipunnikov, Vadim; Crainiceanu, Ciprian M.; Greven, Sonja

2015-01-01

Summary Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for high-dimensional data. Methods are used in applications including high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity during sleep. PMID:25327216

5. Structured functional principal component analysis.

PubMed

Shou, Haochang; Zipunnikov, Vadim; Crainiceanu, Ciprian M; Greven, Sonja

2015-03-01

Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for high-dimensional data. Methods are used in applications including high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity during sleep. PMID:25327216

6. Curious Consequences of a Miscopied Quadratic

ERIC Educational Resources Information Center

Poet, Jeffrey L.; Vestal, Donald L., Jr.

2005-01-01

The starting point of this article is a search for pairs of quadratic polynomials x[superscript 2] + bx plus or minus c with the property that they both factor over the integers. The search leads quickly to some number theory in the form of primitive Pythagorean triples, and this paper develops the connection between these two topics.

7. Fourier analysis of quadratic phase interferograms

Muñoz-Maciel, Jesús; Mora-González, Miguel; Casillas-Rodríguez, Francisco J.; Peña-Lecona, Francisco G.

2015-06-01

A phase demodulation method from a single interferogram with a quadratic phase term is developed. The fringe pattern being analysed may contain circular, elliptic or astigmatic fringes. The Fourier transform of such interferograms is seen to be also a sine or a cosine of a second order polynomial in both the real and imaginary parts. In this work we take a discrete Fourier transform of the fringe patterns and then we take separate inverse discrete transforms of the real and imaginary parts of the frequency spectrum. This results in two new interferograms corresponding to the sine and cosine of the quadratic term of the phase modulated by the sine and cosine of the linear term. The linear term of these interferograms may be recovered with similar procedures of fringe analysis from open fringe interferograms. Once the linear term is retrieved the quadratic phase of the interferogram being analysed can also be calculated. The present approach is also being investigated for interferograms with nearly circularly symmetry given that the phase contains some tilt. The described procedure of Fourier analysis from quadratic phase interferograms of nearly symmetric interferograms could be used instead of complex and time consuming algorithms for phase recovery from fringe patterns with closed fringes. Finally, the method is tested in simulated and real data.

8. Quadratic minima and modular forms II

Brent, Barry

We give upper bounds on the size of the gap between a non-zero constant term and the next non-zero Fourier coefficient of an entire level two modular form. We give upper bounds for the minimum positive integer represented by a level two even positive-definite quadratic form. These bounds extend partial results in part I.

Brémond, Éric; Savarese, Marika; Sancho-García, Juan C.; Pérez-Jiménez, Ángel J.; Adamo, Carlo

2016-03-01

We propose two analytical expressions aiming to rationalize the spin-component-scaled (SCS) and spin-opposite-scaled (SOS) schemes for double-hybrid exchange-correlation density-functionals. Their performances are extensively tested within the framework of the nonempirical quadratic integrand double-hybrid (QIDH) model on energetic properties included into the very large GMTKN30 benchmark database, and on structural properties of semirigid medium-sized organic compounds. The SOS variant is revealed as a less computationally demanding alternative to reach the accuracy of the original QIDH model without losing any theoretical background.

10. Improving Students' Ability to Intuitively Infer Resistance from Magnitude of Current and Potential Difference Information: A Functional Learning Approach

ERIC Educational Resources Information Center

Chasseigne, Gerard; Giraudeau, Caroline; Lafon, Peggy; Mullet, Etienne

2011-01-01

The study examined the knowledge of the functional relations between potential difference, magnitude of current, and resistance among seventh graders, ninth graders, 11th graders (in technical schools), and college students. It also tested the efficiency of a learning device named "functional learning" derived from cognitive psychology on the…

11. When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies.

PubMed

Fjell, Anders M; Walhovd, Kristine B; Westlye, Lars T; Østby, Ylva; Tamnes, Christian K; Jernigan, Terry L; Gamst, Anthony; Dale, Anders M

2010-05-01

Many brain structures show a complex, non-linear pattern of maturation and age-related change. Often, quadratic models (beta(0) + beta(1)age + beta(2)age(2) + epsilon) are used to describe such relationships. Here, we demonstrate that the fitting of quadratic models is substantially affected by seemingly irrelevant factors, such as the age-range sampled. Hippocampal volume was measured in 434 healthy participants between 8 and 85 years of age, and quadratic models were fit to subsets of the sample with different age-ranges. It was found that as the bottom of the age-range increased, the age at which volumes appeared to peak was moved upwards and the estimated decline in the last part of the age-span became larger. Thus, whether children were included or not affected the estimated decline between 60 and 85 years. We conclude that caution should be exerted in inferring age-trajectories from global fit models, e.g. the quadratic model. A nonparametric local smoothing technique (the smoothing spline) was found to be more robust to the effects of different starting ages. The results were replicated in an independent sample of 309 participants. PMID:20109562

12. Making Inferences: Comprehension of Physical Causality, Intentionality, and Emotions in Discourse by High-Functioning Older Children, Adolescents, and Adults with Autism

ERIC Educational Resources Information Center

Bodner, Kimberly E.; Engelhardt, Christopher R.; Minshew, Nancy J.; Williams, Diane L.

2015-01-01

Studies investigating inferential reasoning in autism spectrum disorder (ASD) have focused on the ability to make socially-related inferences or inferences more generally. Important variables for intervention planning such as whether inferences depend on physical experiences or the nature of social information have received less consideration. A…

13. Decoding the Role of the Insula in Human Cognition: Functional Parcellation and Large-Scale Reverse Inference

PubMed Central

Yarkoni, Tal; Khaw, Mel Win; Sanfey, Alan G.

2013-01-01

Recent work has indicated that the insula may be involved in goal-directed cognition, switching between networks, and the conscious awareness of affect and somatosensation. However, these findings have been limited by the insula’s remarkably high base rate of activation and considerable functional heterogeneity. The present study used a relatively unbiased data-driven approach combining resting-state connectivity-based parcellation of the insula with large-scale meta-analysis to understand how the insula is anatomically organized based on functional connectivity patterns as well as the consistency and specificity of the associated cognitive functions. Our findings support a tripartite subdivision of the insula and reveal that the patterns of functional connectivity in the resting-state analysis appear to be relatively conserved across tasks in the meta-analytic coactivation analysis. The function of the networks was meta-analytically “decoded” using the Neurosynth framework and revealed that while the dorsoanterior insula is more consistently involved in human cognition than ventroanterior and posterior networks, each parcellated network is specifically associated with a distinct function. Collectively, this work suggests that the insula is instrumental in integrating disparate functional systems involved in processing affect, sensory-motor processing, and general cognition and is well suited to provide an interface between feelings, cognition, and action. PMID:22437053

14. Factorization using the quadratic sieve algorithm

SciTech Connect

Davis, J.A.; Holdridge, D.B.

1983-12-01

Since the cryptosecurity of the RSA two key cryptoalgorithm is no greater than the difficulty of factoring the modulus (product of two secret primes), a code that implements the Quadratic Sieve factorization algorithm on the CRAY I computer has been developed at the Sandia National Laboratories to determine as sharply as possible the current state-of-the-art in factoring. Because all viable attacks on RSA thus far proposed are equivalent to factorization of the modulus, sharper bounds on the computational difficulty of factoring permit improved estimates for the size of RSA parameters needed for given levels of cryptosecurity. Analysis of the Quadratic Sieve indicates that it may be faster than any previously published general purpose algorithm for factoring large integers. The high speed of the CRAY I coupled with the capability of the CRAY to pipeline certain vectorized operations make this algorithm (and code) the front runner in current factoring techniques.

15. Factorization using the quadratic sieve algorithm

SciTech Connect

Davis, J.A.; Holdridge, D.B.

1983-01-01

Since the cryptosecurity of the RSA two key cryptoalgorithm is no greater than the difficulty of factoring the modulus (product of two secret primes), a code that implements the Quadratic Sieve factorization algorithm on the CRAY I computer has been developed at the Sandia National Laboratories to determine as sharply as possible the current state-of-the-art in factoring. Because all viable attacks on RSA thus far proposed are equivalent to factorization of the modulus, sharper bounds on the computational difficulty of factoring permit improved estimates for the size of RSA parameters needed for given levels of cryptosecurity. Analysis of the Quadratic Sieve indicates that it may be faster than any previously published general purpose algorithm for factoring large integers. The high speed of the CRAY I coupled with the capability of the CRAY to pipeline certain vectorized operations make this algorithm (and code) the front runner in current factoring techniques.

16. Communications circuit including a linear quadratic estimator

DOEpatents

Ferguson, Dennis D.

2015-07-07

A circuit includes a linear quadratic estimator (LQE) configured to receive a plurality of measurements a signal. The LQE is configured to weight the measurements based on their respective uncertainties to produce weighted averages. The circuit further includes a controller coupled to the LQE and configured to selectively adjust at least one data link parameter associated with a communication channel in response to receiving the weighted averages.

17. An alternative method on quadratic programming problems

Dasril, Y.; Mohd, I. B.; Mustaffa, I.; Aminuddin, MMM.

2015-05-01

In this paper we proposed an alternative approach to find the optimum solution of quadratic programming problems (QPP) in its original form without additional information such as slack variable, surplus variable or artificial variable as done in other favourite methods. This approached is based on the violated constraints by the unconstrained optimum. The optimal solution of QPP obtained by searching from initial point to another point alongside of feasible region.

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

2000-01-01

A straightforward extension of a solution to the decentralized linear-Quadratic-Gaussian problem is proposed that allows its use for commonly encountered classes of problems that are currently solved with the extended Kalman filter. This extension allows the system to be partitioned in such a way as to exclude the nonlinearities from the essential algebraic relationships that allow the estimation and control to be optimally decentralized.

19. Comparison of f2/f1 ratio functions in rabbit and gerbil: Ear-canal DPOAEs vs noninvasively inferred intracochlear DPs

Martin, Glen K.; Stagner, Barden B.; Dong, Wei; Lonsbury-Martin, Brenda L.

2015-12-01

The properties of distortion product otoacoustic emissions (DPOAEs), i.e., distortion products (DPs) measured in the ear canal, have been thoroughly described. However, considerably less is known about the behavior of intracochlear DPs (iDPs). Detailed comparisons of DPOAEs to iDPs would provide valuable insights on the extent to which ear-canal DPOAEs mirror iDPs. Prior studies described a technique whereby the behavior of iDPs could be inferred by interacting a probe tone (f3) with the iDP of interest to produce a secondary' DPOAE (DPOAÉ). The behavior of DPOAÉ was then used to deduce the characteristics of the iDP. In the present study, this method was used in rabbits and gerbils to simultaneously compare DPOAE f2/f1-ratio functions to their iDP counterparts. The 2f1-f2 and 2f2-f1 DPOAEs were collected with f1 and f2 primary-tone levels varied from 35-75 dB SPL, and with a 50-dB SPL f3 placed at a DP/f3 ratio of 1.25 to evoke a DPOAÉ at 2f3-(2f1-f2) or 2f3-(2f2-f1). Control experiments demonstrated little effect of the f3-probe tone on DPOAE-ratio functions. Substitution experiments were performed to determine any suppressive effects of the f1 and f2 primaries on the generation of DPOAÉ, as well as to infer the intracochlear level of the iDP once the DPOAÉ was corrected for suppression. Results showed that at low primary-tone levels, 2f1-f2 DPOAE f2/f1-ratio functions peaked around f2/f1=1.25, and exhibited an inverted U-shaped function. In contrast, simultaneously measured 2f1-f2 iDP-ratio functions peaked at f2/f1≈1. Similar growth of the inferred iDP was obtained for higher-level primaries when the ratio functions were corrected for suppressive effects. At these higher levels, DPOAE-ratio functions leveled off and no longer showed the steep reduction at narrow f2/f1 ratios. Overall, noninvasive estimates of 2f1-f2 iDP-ratio functions agreed with reports of similar functions directly measured for 2f1-f2 DPs on the basilar membrane (BM) or in

20. Graphical Solution of the Monic Quadratic Equation with Complex Coefficients

ERIC Educational Resources Information Center

Laine, A. D.

2015-01-01

There are many geometrical approaches to the solution of the quadratic equation with real coefficients. In this article it is shown that the monic quadratic equation with complex coefficients can also be solved graphically, by the intersection of two hyperbolas; one hyperbola being derived from the real part of the quadratic equation and one from…

1. THE EFFECTIVENESS OF QUADRATS FOR MEASURING VASCULAR PLANT DIVERSITY

EPA Science Inventory

Quadrats are widely used for measuring characteristics of vascular plant communities. It is well recognized that quadrat size affects measurements of frequency and cover. The ability of quadrats of varying sizes to adequately measure diversity has not been established. An exha...

2. Explorative Learning and Functional Inferences on a Five-Step Means-Means-End Problem in Goffin’s Cockatoos (Cacatua goffini)

PubMed Central

Auersperg, Alice M. I.; Kacelnik, Alex; von Bayern, Auguste M. P.

2013-01-01

To investigate cognitive operations underlying sequential problem solving, we confronted ten Goffin’s cockatoos with a baited box locked by five different inter-locking devices. Subjects were either naïve or had watched a conspecific demonstration, and either faced all devices at once or incrementally. One naïve subject solved the problem without demonstration and with all locks present within the first five sessions (each consisting of one trial of up to 20 minutes), while five others did so after social demonstrations or incremental experience. Performance was aided by species-specific traits including neophilia, a haptic modality and persistence. Most birds showed a ratchet-like progress, rarely failing to solve a stage once they had done it once. In most transfer tests subjects reacted flexibly and sensitively to alterations of the locks’ sequencing and functionality, as expected from the presence of predictive inferences about mechanical interactions between the locks. PMID:23844247

3. Orbital instability of standing waves for the quadratic-cubic Klein-Gordon-Schrödinger system

2015-08-01

We consider the Klein-Gordon-Schrödinger system with quadratic and cubic interactions. Smooth curves of periodic- and solitary-wave solutions are obtained via the implicit function theorem. Orbital instability of such waves is then established.

4. System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome

5. Horizontal Distance Travelled by a Mobile Experiencing a Quadratic Drag Force: Normalized Distance and Parametrization

ERIC Educational Resources Information Center

Vial, Alexandre

2007-01-01

We investigate the problem of the horizontal distance travelled by a mobile experiencing a quadratic drag force. We show that by introducing a normalized distance, the problem can be greatly simplified. In order to parametrize this distance, we use the Pearson VII function, and we find that the optimal launch angle as a function of the initial…

6. QUADRATIC SERENDIPITY FINITE ELEMENTS ON POLYGONS USING GENERALIZED BARYCENTRIC COORDINATES.

PubMed

Rand, Alexander; Gillette, Andrew; Bajaj, Chandrajit

2014-01-01

We introduce a finite element construction for use on the class of convex, planar polygons and show it obtains a quadratic error convergence estimate. On a convex n-gon, our construction produces 2n basis functions, associated in a Lagrange-like fashion to each vertex and each edge midpoint, by transforming and combining a set of n(n + 1)/2 basis functions known to obtain quadratic convergence. The technique broadens the scope of the so-called 'serendipity' elements, previously studied only for quadrilateral and regular hexahedral meshes, by employing the theory of generalized barycentric coordinates. Uniform a priori error estimates are established over the class of convex quadrilaterals with bounded aspect ratio as well as over the class of convex planar polygons satisfying additional shape regularity conditions to exclude large interior angles and short edges. Numerical evidence is provided on a trapezoidal quadrilateral mesh, previously not amenable to serendipity constructions, and applications to adaptive meshing are discussed. PMID:25301974

7. QUADRATIC SERENDIPITY FINITE ELEMENTS ON POLYGONS USING GENERALIZED BARYCENTRIC COORDINATES

PubMed Central

RAND, ALEXANDER; GILLETTE, ANDREW; BAJAJ, CHANDRAJIT

2013-01-01

We introduce a finite element construction for use on the class of convex, planar polygons and show it obtains a quadratic error convergence estimate. On a convex n-gon, our construction produces 2n basis functions, associated in a Lagrange-like fashion to each vertex and each edge midpoint, by transforming and combining a set of n(n + 1)/2 basis functions known to obtain quadratic convergence. The technique broadens the scope of the so-called ‘serendipity’ elements, previously studied only for quadrilateral and regular hexahedral meshes, by employing the theory of generalized barycentric coordinates. Uniform a priori error estimates are established over the class of convex quadrilaterals with bounded aspect ratio as well as over the class of convex planar polygons satisfying additional shape regularity conditions to exclude large interior angles and short edges. Numerical evidence is provided on a trapezoidal quadrilateral mesh, previously not amenable to serendipity constructions, and applications to adaptive meshing are discussed. PMID:25301974

8. AESOP- INTERACTIVE DESIGN OF LINEAR QUADRATIC REGULATORS AND KALMAN FILTERS

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1994-01-01

AESOP was developed to solve a number of problems associated with the design of controls and state estimators for linear time-invariant systems. The systems considered are modeled in state-variable form by a set of linear differential and algebraic equations with constant coefficients. Two key problems solved by AESOP are the linear quadratic regulator (LQR) design problem and the steady-state Kalman filter design problem. AESOP is designed to be used in an interactive manner. The user can solve design problems and analyze the solutions in a single interactive session. Both numerical and graphical information are available to the user during the session. The AESOP program is structured around a list of predefined functions. Each function performs a single computation associated with control, estimation, or system response determination. AESOP contains over sixty functions and permits the easy inclusion of user defined functions. The user accesses these functions either by inputting a list of desired functions in the order they are to be performed, or by specifying a single function to be performed. The latter case is used when the choice of function and function order depends on the results of previous functions. The available AESOP functions are divided into several general areas including: 1) program control, 2) matrix input and revision, 3) matrix formation, 4) open-loop system analysis, 5) frequency response, 6) transient response, 7) transient function zeros, 8) LQR and Kalman filter design, 9) eigenvalues and eigenvectors, 10) covariances, and 11) user-defined functions. The most important functions are those that design linear quadratic regulators and Kalman filters. The user interacts with AESOP when using these functions by inputting design weighting parameters and by viewing displays of designed system response. Support functions obtain system transient and frequency responses, transfer functions, and covariance matrices. AESOP can also provide the user

9. User's guide for SOL/QPSOL: a Fortran package for quadratic programming

SciTech Connect

Gill, P.E.; Murray, W.; Saunders, M.A.; Wright, M.H.

1983-07-01

This report forms the user's guide for Version 3.1 of SOL/QPSOL, a set of Fortran subroutines designed to locate the minimum value of an arbitrary quadratic function subject to linear constraints and simple upper and lower bounds. If the quadratic function is convex, a global minimum is found; otherwise, a local minimum is found. The method used is most efficient when many constraints or bounds are active at the solution. QPSOL treats the Hessian and general constraints as dense matrices, and hence is not intended for large sparse problems. This document replaces the previous user's guide of June 1982.

10. Propagator for the time-dependent charged oscillator via linear and quadratic invariants

SciTech Connect

Abdalla, M. Sebawe Choi, Jeong-Ryeol

2007-12-15

The problem of a charged particle in the presence of a variable magnetic field is considered. Using the linear and the quadratic invariants as a tool, the wave functions in Fock state as well as in coherent state are obtained. The corresponding propagators which propagate the wave functions in the space-time are derived. Using numerical computations we have managed to draw some plots for the real, imaginary, and absolute values of the propagators. This has been used to analyze the properties of the propagators associated with both of the linear and the quadratic invariants. It has been shown that there is no essential difference between the behavior of the absolute value of the propagators in both of the linear and the quadratic invariants.

11. A Function for Representing the Biological Challenge to Respiration Posed by Ocean Acidification and the Geochemical Consequences Inferred

Peltzer, E. T.; Brewer, P. G.

2008-12-01

Increasing levels of dissolved total CO2 in the ocean from the invasion of fossil fuel CO2 via the atmosphere are widely believed to pose challenges to marine life on several fronts. This is most often expressed as a concern from the resulting lower pH, and the impact of this on calcification in marine organisms (coral reefs, calcareous phytoplankton etc.). These concerns are real, but calcification is by no means the only process affected, nor is the fossil fuel CO2 signal the only geochemical driver of the rapidly emerging deep-sea biological stress. Physical climate change is reducing deep-sea ventilation rates, and thereby leading to increasing oxygen deficits and concomitant increased respiratory CO2. We seek to understand the combined effects of the downward penetration of the fossil fuel signal, and the emergence of the depleted O2/increased respiratory CO2 signal at depth. As a first step, we seek to provide a simple function to capture the changing oceanic state. The most basic thermodynamic equation for the functioning of marine animals can be written as Corg + O2 → CO2 , and this results in the simple Gibbs free energy equation: ΔG° = - RT * ln [fCO2]/[Corg]*[fO2], in which the ratio of pO2 to pCO2 emerges as the dominant factor. From this we construct a simple Respiration Index: RI = log10 (pO2/pCO2), which is linear in energy and map this function for key oceanic regions illustrating the expansion of oceanic dead zones. The formal thermodynamic limit for aerobic life is RI = 0; in practice field data shows that at RI ~ 0.7 microbes turn to electron acceptors other than O2, and denitrification begins to occur. This likely represents the lowest limit for the long-term functioning of higher animals, and the zone RI = 0.7 to 1 appears to present challenges to basic functioning of many marine species. In addition, there are large regions of the ocean where denitrification already occurs, and these zones will expand greatly in size as the combined

12. Holographic entropy increases in quadratic curvature gravity

Bhattacharjee, Srijit; Sarkar, Sudipta; Wall, Aron C.

2015-09-01

Standard methods for calculating the black hole entropy beyond general relativity are ambiguous when the horizon is nonstationary. We fix these ambiguities in all quadratic curvature gravity theories, by demanding that the entropy be increasing at every time, for linear perturbations to a stationary black hole. Our result matches with the entropy formula found previously in holographic entanglement entropy calculations. We explicitly calculate the entropy increase for Vaidya-like solutions in Ricci-tensor gravity to show that (unlike the Wald entropy) the holographic entropy obeys a second law.

13. Bayesian inference in physics

von Toussaint, Udo

2011-07-01

Bayesian inference provides a consistent method for the extraction of information from physics experiments even in ill-conditioned circumstances. The approach provides a unified rationale for data analysis, which both justifies many of the commonly used analysis procedures and reveals some of the implicit underlying assumptions. This review summarizes the general ideas of the Bayesian probability theory with emphasis on the application to the evaluation of experimental data. As case studies for Bayesian parameter estimation techniques examples ranging from extra-solar planet detection to the deconvolution of the apparatus functions for improving the energy resolution and change point estimation in time series are discussed. Special attention is paid to the numerical techniques suited for Bayesian analysis, with a focus on recent developments of Markov chain Monte Carlo algorithms for high-dimensional integration problems. Bayesian model comparison, the quantitative ranking of models for the explanation of a given data set, is illustrated with examples collected from cosmology, mass spectroscopy, and surface physics, covering problems such as background subtraction and automated outlier detection. Additionally the Bayesian inference techniques for the design and optimization of future experiments are introduced. Experiments, instead of being merely passive recording devices, can now be designed to adapt to measured data and to change the measurement strategy on the fly to maximize the information of an experiment. The applied key concepts and necessary numerical tools which provide the means of designing such inference chains and the crucial aspects of data fusion are summarized and some of the expected implications are highlighted.

14. Quadratic Reciprocity and the Group Orders of Particle States

SciTech Connect

DAI,YANG; BORISOV,ALEXEY B.; LONGWORTH,JAMES W.; BOYER,KEITH; RHODES,CHARLES K.

2001-06-01

The construction of inverse states in a finite field F{sub P{sub P{alpha}}} enables the organization of the mass scale by associating particle states with residue class designations. With the assumption of perfect flatness ({Omega}total = 1.0), this approach leads to the derivation of a cosmic seesaw congruence which unifies the concepts of space and mass. The law of quadratic reciprocity profoundly constrains the subgroup structure of the multiplicative group of units F{sub P{sub {alpha}}}* defined by the field. Four specific outcomes of this organization are (1) a reduction in the computational complexity of the mass state distribution by a factor of {approximately}10{sup 30}, (2) the extension of the genetic divisor concept to the classification of subgroup orders, (3) the derivation of a simple numerical test for any prospective mass number based on the order of the integer, and (4) the identification of direct biological analogies to taxonomy and regulatory networks characteristic of cellular metabolism, tumor suppression, immunology, and evolution. It is generally concluded that the organizing principle legislated by the alliance of quadratic reciprocity with the cosmic seesaw creates a universal optimized structure that functions in the regulation of a broad range of complex phenomena.

15. Linear-Quadratic-Gaussian Regulator Developed for a Magnetic Bearing

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2002-01-01

Linear-Quadratic-Gaussian (LQG) control is a modern state-space technique for designing optimal dynamic regulators. It enables us to trade off regulation performance and control effort, and to take into account process and measurement noise. The Structural Mechanics and Dynamics Branch at the NASA Glenn Research Center has developed an LQG control for a fault-tolerant magnetic bearing suspension rig to optimize system performance and to reduce the sensor and processing noise. The LQG regulator consists of an optimal state-feedback gain and a Kalman state estimator. The first design step is to seek a state-feedback law that minimizes the cost function of regulation performance, which is measured by a quadratic performance criterion with user-specified weighting matrices, and to define the tradeoff between regulation performance and control effort. The next design step is to derive a state estimator using a Kalman filter because the optimal state feedback cannot be implemented without full state measurement. Since the Kalman filter is an optimal estimator when dealing with Gaussian white noise, it minimizes the asymptotic covariance of the estimation error.

16. What is it like to have type-2 blindsight? Drawing inferences from residual function in type-1 blindsight.

PubMed

Kentridge, Robert W

2015-03-01

Controversy surrounds the question of whether the experience sometimes elicited by visual stimuli in blindsight (type-2 blindsight) is visual in nature or whether it is some sort of non-visual experience. The suggestion that the experience is visual seems, at face value, to make sense. I argue here, however, that the residual abilities found in type-1 blindsight (blindsight in which stimuli elicit no conscious experience) are not aspects of normal vision with consciousness deleted, but are based fragments of visual processes that, in themselves, would not be intelligible as visual experiences. If type-2 blindsight is a conscious manifestation of this residual function then it is not obvious that type-2 blindsight would be phenomenally like vision. PMID:25301438

17. Inferences regarding the diet of extinct hominins: structural and functional trends in dental and mandibular morphology within the hominin clade

PubMed Central

Lucas, Peter W; Constantino, Paul J; Wood, Bernard A

2008-01-01

This contribution investigates the evolution of diet in the Pan–Homo and hominin clades. It does this by focusing on 12 variables (nine dental and three mandibular) for which data are available about extant chimpanzees, modern humans and most extinct hominins. Previous analyses of this type have approached the interpretation of dental and gnathic function by focusing on the identification of the food consumed (i.e. fruits, leaves, etc.) rather than on the physical properties (i.e. hardness, toughness, etc.) of those foods, and they have not specifically addressed the role that the physical properties of foods play in determining dental adaptations. We take the available evidence for the 12 variables, and set out what the expression of each of those variables is in extant chimpanzees, the earliest hominins, archaic hominins, megadont archaic hominins, and an inclusive grouping made up of transitional hominins and pre-modern Homo. We then present hypotheses about what the states of these variables would be in the last common ancestor of the Pan–Homo clade and in the stem hominin. We review the physical properties of food and suggest how these physical properties can be used to investigate the functional morphology of the dentition. We show what aspects of anterior tooth morphology are critical for food preparation (e.g. peeling fruit) prior to its ingestion, which features of the postcanine dentition (e.g. overall and relative size of the crowns) are related to the reduction in the particle size of food, and how information about the macrostructure (e.g. enamel thickness) and microstructure (e.g. extent and location of enamel prism decussation) of the enamel cap might be used to make predictions about the types of foods consumed by extinct hominins. Specifically, we show how thick enamel can protect against the generation and propagation of cracks in the enamel that begin at the enamel–dentine junction and move towards the outer enamel surface. PMID:18380867

18. A Fixed-Point Iteration Method with Quadratic Convergence

SciTech Connect

Walker, Kevin P.; Sham, Sam

2012-01-01

The fixed-point iteration algorithm is turned into a quadratically convergent scheme for a system of nonlinear equations. Most of the usual methods for obtaining the roots of a system of nonlinear equations rely on expanding the equation system about the roots in a Taylor series, and neglecting the higher order terms. Rearrangement of the resulting truncated system then results in the usual Newton-Raphson and Halley type approximations. In this paper the introduction of unit root functions avoids the direct expansion of the nonlinear system about the root, and relies, instead, on approximations which enable the unit root functions to considerably widen the radius of convergence of the iteration method. Methods for obtaining higher order rates of convergence and larger radii of convergence are discussed.

19. Water quality functioning of lowland permeable catchments: inferences from an intensive study of the RIVER KENNEt and upper River Thames.

PubMed

2002-01-23

This paper brings together information on the water quality functioning of the River Kennet and other parts of the upper River Thames in the south east of England. The Kennet represents a groundwater fed riverine environment impacted by agricultural and sewage sources of nutrient pollution. Descriptions of the general water quality of the area, nutrient sources, sinks and within river processes are provided together with biological responses to driving issues of agriculture, sewage treatment and climatic change. Models are developed and applied to assess the key processes involved for a highly dynamic system and to provide initial estimates of the likely responses to environmental change. Furthermore, the economic aspects of pollution control are reviewed, together with legislation issues, which are presented within the context of a landmark case known as the 'Axford Inquiry', the implications of which extend to regional and national dimensions. The paper concludes with a discussion on the present state of knowledge, key issues and future research on the science and management of groundwater fed nutrient impacted riverine systems. PMID:11846085

20. Functional Inference of Methylenetetrahydrofolate Reductase Gene Polymorphisms on Enzyme Stability as a Potential Risk Factor for Down Syndrome in Croatia

PubMed Central

Vraneković, Jadranka; Babić Božović, Ivana; Starčević Čizmarević, Nada; Buretić-Tomljanović, Alena; Ristić, Smiljana; Petrović, Oleg; Kapović, Miljenko; Brajenović-Milić, Bojana

2010-01-01

Understanding the biochemical structure and function of the methylenetetrahydrofolate reductase gene (MTHFR) provides new evidence in elucidating the risk of having a child with Down syndrome (DS) in association with two common MTHFR polymorphisms, C677T and A1298C. The aim of this study was to evaluate the risk for DS according to the presence of MTHFR C677T and A1298C polymorphisms as well as the stability of the enzyme configuration. This study included mothers from Croatia with a liveborn DS child (n = 102) or DS pregnancy (n = 9) and mothers with a healthy child (n = 141). MTHFR C677T and A1298C polymorphisms were assessed by PCR-RFLP. Allele/genotype frequencies differences were determined using χ2 test. Odds ratio and the 95% confidence intervals were calculated to evaluate the effects of different alleles/genotypes. No statistically significant differences were found between the frequencies of allele/genotype or genotype combinations of the MTHFR C677T and A1298C polymorphisms in the case and the control groups. Additionally, the observed frequencies of the stable (677CC/1298AA, 677CC/1298AC, 677CC/1298CC) and unstable (677CT/1298AA, 677CT/1298AC, 677TT/1298AA) enzyme configurations were not significantly different. We found no evidence to support the possibility that MTHFR polymorphisms and the stability of the enzyme configurations were associated with risk of having a child with DS in Croatian population. PMID:20592453

1. Blind deconvolution estimation of fluorescence measurements through quadratic programming

Campos-Delgado, Daniel U.; Gutierrez-Navarro, Omar; Arce-Santana, Edgar R.; Skala, Melissa C.; Walsh, Alex J.; Jo, Javier A.

2015-07-01

Time-deconvolution of the instrument response from fluorescence lifetime imaging microscopy (FLIM) data is usually necessary for accurate fluorescence lifetime estimation. In many applications, however, the instrument response is not available. In such cases, a blind deconvolution approach is required. An iterative methodology is proposed to address the blind deconvolution problem departing from a dataset of FLIM measurements. A linear combination of a base conformed by Laguerre functions models the fluorescence impulse response of the sample at each spatial point in our formulation. Our blind deconvolution estimation (BDE) algorithm is formulated as a quadratic approximation problem, where the decision variables are the samples of the instrument response and the scaling coefficients of the basis functions. In the approximation cost function, there is a bilinear dependence on the decision variables. Hence, due to the nonlinear nature of the estimation process, an alternating least-squares scheme iteratively solves the approximation problem. Our proposal searches for the samples of the instrument response with a global perspective, and the scaling coefficients of the basis functions locally at each spatial point. First, the iterative methodology relies on a least-squares solution for the instrument response, and quadratic programming for the scaling coefficients applied just to a subset of the measured fluorescence decays to initially estimate the instrument response to speed up the convergence. After convergence, the final stage computes the fluorescence impulse response at all spatial points. A comprehensive validation stage considers synthetic and experimental FLIM datasets of ex vivo atherosclerotic plaques and human breast cancer cell samples that highlight the advantages of the proposed BDE algorithm under different noise and initial conditions in the iterative scheme and parameters of the proposal.

2. Hydrous state of the subducting Philippine Sea plate inferred from receiver function image using onshore and offshore data

Akuhara, Takeshi; Mochizuki, Kimihiro

2015-12-01

Exploring the hydrous state of subducting oceanic crust is intriguing because it is considered to affect the strength of megathrust faults that cause various types of earthquakes; however, its state beneath offshore regions remains unclear. In this study, we investigated fluid contents along the subducting Philippine Sea plate around the Kii Peninsula by receiver function (RF) analysis using data from both on-land stations and ocean bottom seismometers (OBSs). The vertical component of OBS records contains dominant water reverberations, and thus, conventional methods fail to estimate RFs correctly. We therefore developed a method to calculate RFs that removes such reverberations. The RFs calculated by our method showed considerable improvement for later phase identification, compared with those obtained using a conventional method. Resultant RF amplitudes suggest the existence of low-velocity zones directly beneath the plate interface of both onshore and offshore regions. We interpreted this as evidence of hydrous oceanic crust, which extends from 5 km to 35 km depth to the plate interface. Reduction of RF amplitudes beneath the Kii Peninsula suggests that dehydration of the oceanic crust increases the seismic velocity, and the accompanying densification makes the plate interface permeable. This permeable plate interface may characterize the location of non-volcanic tremors. This contrasts with long-term slow slip events because it is believed that they occur along the sealed plate interface. Comparison between the plate geometry and local earthquakes reveals the paucity of earthquakes in the oceanic crust below a certain depth, which provides further insight into the dehydration process in the oceanic crust.

3. Melt infiltration of the lower lithosphere beneath the Tanzania craton and the Albertine rift inferred from S receiver functions

WöLbern, Ingo; Rümpker, Georg; Link, Klemens; Sodoudi, Forough

2012-08-01

The transition between the lithosphere and the asthenosphere is subject to numerous contemporary studies as its nature is still poorly understood. The thickest lithosphere is associated with old cratons and platforms and it has been shown that seismic investigations may fail to image the lithosphere-asthenosphere boundary in these areas. Instead, several recent studies have proposed a mid-lithospheric discontinuity of unknown origin existing under several cratons. In this study we investigate the Tanzania craton in East Africa which is enclosed by the eastern and western branches of the East African Rift System. We present evidence from S receiver functions for two consecutive discontinuities at depths of 50-100 km and 140-200 km, which correspond to significant S wave velocity reductions under the Tanzania craton and the Albert and Edward rift segments. By comparison with synthetic waveforms we show that the lower discontinuity coincides with the LAB exhibiting velocity reductions of 6-9%. The shallower interface reveals a velocity drop that varies from 12% beneath the craton to 24% below the Albert-Edward rift. It is interpreted as an infiltration front marking the upper boundary of altered lithosphere due to ascending asthenospheric melts. This is corroborated by computing S velocity variations based on xenolith samples which exhibit a dense system of crystallized veins acting as pathways of the infiltrating melt. Mineral assemblages in these veins are rich in phlogopite and pyroxenite which can explain the reduced shear wave velocities. Melt infiltration represents a suitable mechanism to form a mid-lithospheric discontinuity within cratonic lithosphere that is underlain by anomalously hot mantle.

4. Quadratic formula for determining the drop size in pressure-atomized sprays with and without swirl

Lee, T.-W.; An, Keju

2016-06-01

We use a theoretical framework based on the integral form of the conservation equations, along with a heuristic model of the viscous dissipation, to find a closed-form solution to the liquid atomization problem. The energy balance for the spray renders to a quadratic formula for the drop size as a function, primarily of the liquid velocity. The Sauter mean diameter found using the quadratic formula shows good agreements and physical trends, when compared with experimental observations. This approach is shown to be applicable toward specifying initial drop size in computational fluid dynamics of spray flows.

5. Analytical solution of the Klein Gordon equation for a quadratic exponential-type potential

Ezzatpour, Somayyeh; Akbarieh, Amin Rezaei

2016-07-01

In this research study, analytical solutions of the Klein Gordon equation by considering the potential as a quadratic exponential will be presented. However, the potential is assumed to be within the framework of an approximation for the centrifugal potential in any state. The Nikiforov-Uvarov method is used to calculate the wave function, as well as corresponding exact energy equation, in bound states. We finally concluded that the quadratic exponential-type potential under which the results were deduced, led to outcomes that were comparable to the results obtained from the well-known potentials in some special cases.

6. A study of radiation propagation in a medium with quadratic inhomogeneity

SciTech Connect

Pikulev, A A

2001-09-30

The propagation of Hermitian beams in a medium with a distributed quadratic inhomogeneity is studied and is shown that any solution can be represented as a function of some particular solution. This is accomplished by establishing a one-to-one correspondence between optical fields in a homogeneous medium and in a medium with an arbitrary quadratic inhomogeneity. The stability of optical resonators is studied and the condition for their stability is found. Several solutions are found using the method developed. (physical foundations of quantum electronics)

7. Seismic velocity discontinuities in the crust and uppermost mantle beneath the Tokyo metropolitan area inferred from receiver function analysis

Igarashi, T.; Sakai, S.; Hirata, N.

2010-12-01

We apply receiver function (RF) analyses to estimate the seismic velocity structure and seismic velocity discontinuities in the crust and uppermost mantle beneath the Tokyo metropolitan area, central Japan. Destructive earthquakes often occurred at various places including the subducting Philippine Sea plate (PSP), the subducting Pacific plate (PAP), and inland earthquake in this area. Investigation on the crustal structure and configurations of the subducting plates is the key to understanding the stress and strain concentration process and important to mitigate future earthquake disasters. A RF analysis is widely used to estimate velocity discontinuities in the crust and mantle beneath each seismic station. However, crustal structure beneath the Kanto plain could not be analyzed for lack of applicable seismic stations. Recently, comprehensive surveys are conducted as the Special Project for Earthquake Disaster Mitigation in the Tokyo Metropolitan area from 2007. The Metropolitan Seismic Observation network (MeSO-net) is constructed under this project. In this study, we searched for the best correlated velocity structure model between an observed RF at each station and synthetic ones by using a grid search method. Synthetic RFs calculated from assumed many one-dimensional velocity structures which consisting of four layers. We further constructed the vertical cross-sections of depth converted RF images transformed the lapse time of time series to depth by using the estimated structure models. MeSO-net data and telemetric seismographic network data operated by NIED, JMA and ERI are used. We used events with magnitudes greater or equal to 5.0 and epicentral distances between 30 and 90 degrees based on USGS catalogues. As a result, we clarify spatial distributions of the crustal S-wave velocities. The Boso Peninsula and Kanto plain are covered in the thick low-velocity sediment layers. We image standard velocity distributions in the deep crust of the Boso Peninsula

8. Detection of code spread OFDM based on 0-1 integer quadratic programming

Elghariani, Ali; Zoltowski, Michael D.

2012-05-01

In this paper we introduce Integer Quadratic Programming (MIQP) approach to optimally detect QPSK Code Spread OFDM (CS-OFDM) by formulating the problem as a combinatorial optimization problem. The Branch and Bound (BB) algorithm is utilized to solve this integer quadratic programming problem. Furthermore, we propose combined preprocessing steps that can be applied prior to BB so that the computational complexity of the optimum receiver is reduced. The first step in this combination is to detect as much as possible symbols using procedures presented in [9], which is basically based on the gradient of quadratic function. The second step detects the undetected symbols from the first step using MMSE estimator. The result of the latter step will be used to predict the initial upper bound of the BB algorithm. Simulation results show that the proposed preprocessing combination when applied prior to BB provides optimal performance with a significantly reduced computational complexity.

9. Landau-Zener transition in quadratic nonlinear two-state systems

SciTech Connect

Ishkhanyan, A. M.

2010-05-15

A comprehensive theory of the Landau-Zener transition in quadratic nonlinear two-state systems is developed. A compact analytic formula involving elementary functions only is derived for the final transition probability. The formula provides a highly accurate approximation for the whole rage of the variation of the Landau-Zener parameter.

10. Galactic chemical evolution and nucleocosmochronology - Analytic quadratic models

NASA Technical Reports Server (NTRS)

Clayton, D. D.

1985-01-01

Quadratic models of the chemical evolution of the Galaxy for a star formation rate proportional to the square of the gas mass are studied. The search for analytic solutions to the gas mass and star mass for time-dependent rates of gaseous infall onto the disk is examined. The quadratic models are compared to models having linear star formation rates. The mass, metallicity, number of stars, and U-235/U-238 isotopic ratio for the models which are subjected to the same infall rate, the same initial disk mass, and the same final gas fraction are compared. The results of the comparison indicate that: (1) the average dwarf age is greater in the quadratic model, (2) the metallicity grows initially faster in the quadratic model, (3) the quadratic model has a smaller percentage of low-Z dwarfs, and (4) the U-235/U-238 isotopic ratio indicates a younger quadratic model.

11. Quadratic relations in continuous and discrete Painlevé equations

Ramani, A.; Grammaticos, B.; Tamizhmani, T.

2000-04-01

The quadratic relations between the solutions of a Painlevé equation and that of a different one, or the same one with a different set of parameters, are investigated in the continuous and discrete cases. We show that the quadratic relations existing for the continuous PII , PIII , PV and PVI have analogues as well as consequences in the discrete case. Moreover, the discrete Painlevé equations have quadratic relations of their own without any reference to the continuous case.

12. Inference of Isoforms from Short Sequence Reads

Feng, Jianxing; Li, Wei; Jiang, Tao

13. Exact Solution of Quadratic Fermionic Hamiltonians for Arbitrary Boundary Conditions.

PubMed

Alase, Abhijeet; Cobanera, Emilio; Ortiz, Gerardo; Viola, Lorenza

2016-08-12

We present a procedure for exactly diagonalizing finite-range quadratic fermionic Hamiltonians with arbitrary boundary conditions in one of D dimensions, and periodic in the remaining D-1. The key is a Hamiltonian-dependent separation of the bulk from the boundary. By combining information from the two, we identify a matrix function that fully characterizes the solutions, and may be used to construct an efficiently computable indicator of bulk-boundary correspondence. As an illustration, we show how our approach correctly describes the zero-energy Majorana modes of a time-reversal-invariant s-wave two-band superconductor in a Josephson ring configuration, and predicts that a fractional 4π-periodic Josephson effect can only be observed in phases hosting an odd number of Majorana pairs per boundary. PMID:27563986

14. Exact Solution of Quadratic Fermionic Hamiltonians for Arbitrary Boundary Conditions

Alase, Abhijeet; Cobanera, Emilio; Ortiz, Gerardo; Viola, Lorenza

2016-08-01

We present a procedure for exactly diagonalizing finite-range quadratic fermionic Hamiltonians with arbitrary boundary conditions in one of D dimensions, and periodic in the remaining D -1 . The key is a Hamiltonian-dependent separation of the bulk from the boundary. By combining information from the two, we identify a matrix function that fully characterizes the solutions, and may be used to construct an efficiently computable indicator of bulk-boundary correspondence. As an illustration, we show how our approach correctly describes the zero-energy Majorana modes of a time-reversal-invariant s -wave two-band superconductor in a Josephson ring configuration, and predicts that a fractional 4 π -periodic Josephson effect can only be observed in phases hosting an odd number of Majorana pairs per boundary.

15. Quadratic dynamical decoupling with nonuniform error suppression

SciTech Connect

Quiroz, Gregory; Lidar, Daniel A.

2011-10-15

We analyze numerically the performance of the near-optimal quadratic dynamical decoupling (QDD) single-qubit decoherence errors suppression method [J. West et al., Phys. Rev. Lett. 104, 130501 (2010)]. The QDD sequence is formed by nesting two optimal Uhrig dynamical decoupling sequences for two orthogonal axes, comprising N{sub 1} and N{sub 2} pulses, respectively. Varying these numbers, we study the decoherence suppression properties of QDD directly by isolating the errors associated with each system basis operator present in the system-bath interaction Hamiltonian. Each individual error scales with the lowest order of the Dyson series, therefore immediately yielding the order of decoherence suppression. We show that the error suppression properties of QDD are dependent upon the parities of N{sub 1} and N{sub 2}, and near-optimal performance is achieved for general single-qubit interactions when N{sub 1}=N{sub 2}.

16. Compact stars with quadratic equation of state

Ngubelanga, Sifiso A.; Maharaj, Sunil D.; Ray, Subharthi

2015-05-01

We provide new exact solutions to the Einstein-Maxwell system of equations for matter configurations with anisotropy and charge. The spacetime is static and spherically symmetric. A quadratic equation of state is utilised for the matter distribution. By specifying a particular form for one of the gravitational potentials and the electric field intensity we obtain new exact solutions in isotropic coordinates. In our general class of models, an earlier model with a linear equation of state is regained. For particular choices of parameters we regain the masses of the stars PSR J1614-2230, 4U 1608-52, PSR J1903+0327, EXO 1745-248 and SAX J1808.4-3658. A comprehensive physical analysis for the star PSR J1903+0327 reveals that our model is reasonable.

17. The Middle Miocene Ape Pierolapithecus catalaunicus Exhibits Extant Great Ape-Like Morphometric Affinities on Its Patella: Inferences on Knee Function and Evolution

PubMed Central

Pina, Marta; Almécija, Sergio; Alba, David M.; O'Neill, Matthew C.; Moyà-Solà, Salvador

2014-01-01

The mosaic nature of the Miocene ape postcranium hinders the reconstruction of the positional behavior and locomotion of these taxa based on isolated elements only. The fossil great ape Pierolapithecus catalaunicus (IPS 21350 skeleton; 11.9 Ma) exhibits a relatively wide and shallow thorax with moderate hand length and phalangeal curvature, dorsally-oriented metacarpophalangeal joints, and loss of ulnocarpal articulation. This evidence reveals enhanced orthograde postures without modern ape-like below-branch suspensory adaptations. Therefore, it has been proposed that natural selection enhanced vertical climbing (and not suspension per se) in Pierolapithecus catalaunicus. Although limb long bones are not available for this species, its patella (IPS 21350.37) can potentially provide insights into its knee function and thus on the complexity of its total morphological pattern. Here we provide a detailed description and morphometric analyses of IPS 21350.37, which are based on four external dimensions intended to capture the overall patellar shape. Our results reveal that the patella of Pierolapithecus is similar to that of extant great apes: proximodistally short, mediolaterally broad and anteroposteriorly thin. Previous biomechanical studies of the anthropoid knee based on the same measurements proposed that the modern great ape patella reflects a mobile knee joint while the long, narrow and thick patella of platyrrhine and especially cercopithecoid monkeys would increase the quadriceps moment arm in knee extension during walking, galloping, climbing and leaping. The patella of Pierolapithecus differs not only from that of monkeys and hylobatids, but also from that of basal hominoids (e.g., Proconsul and Nacholapithecus), which display slightly thinner patellae than extant great apes (the previously-inferred plesiomorphic hominoid condition). If patellar shape in Pierolapithecus is related to modern great ape-like knee function, our results suggest that increased

18. Convergence analysis of a finite element skull model of Herpestes javanicus (Carnivora, Mammalia): implications for robust comparative inferences of biomechanical function.

PubMed

Tseng, Zhijie Jack; Flynn, John J

2015-01-21

biomechanical attributes from these simulations are used to infer form-function linkage. PMID:25445190

19. The Middle Miocene ape Pierolapithecus catalaunicus exhibits extant great ape-like morphometric affinities on its patella: inferences on knee function and evolution.

PubMed

Pina, Marta; Almécija, Sergio; Alba, David M; O'Neill, Matthew C; Moyà-Solà, Salvador

2014-01-01

The mosaic nature of the Miocene ape postcranium hinders the reconstruction of the positional behavior and locomotion of these taxa based on isolated elements only. The fossil great ape Pierolapithecus catalaunicus (IPS 21350 skeleton; 11.9 Ma) exhibits a relatively wide and shallow thorax with moderate hand length and phalangeal curvature, dorsally-oriented metacarpophalangeal joints, and loss of ulnocarpal articulation. This evidence reveals enhanced orthograde postures without modern ape-like below-branch suspensory adaptations. Therefore, it has been proposed that natural selection enhanced vertical climbing (and not suspension per se) in Pierolapithecus catalaunicus. Although limb long bones are not available for this species, its patella (IPS 21350.37) can potentially provide insights into its knee function and thus on the complexity of its total morphological pattern. Here we provide a detailed description and morphometric analyses of IPS 21350.37, which are based on four external dimensions intended to capture the overall patellar shape. Our results reveal that the patella of Pierolapithecus is similar to that of extant great apes: proximodistally short, mediolaterally broad and anteroposteriorly thin. Previous biomechanical studies of the anthropoid knee based on the same measurements proposed that the modern great ape patella reflects a mobile knee joint while the long, narrow and thick patella of platyrrhine and especially cercopithecoid monkeys would increase the quadriceps moment arm in knee extension during walking, galloping, climbing and leaping. The patella of Pierolapithecus differs not only from that of monkeys and hylobatids, but also from that of basal hominoids (e.g., Proconsul and Nacholapithecus), which display slightly thinner patellae than extant great apes (the previously-inferred plesiomorphic hominoid condition). If patellar shape in Pierolapithecus is related to modern great ape-like knee function, our results suggest that increased

20. Rays of Small Integer Solutions of Homogeneous Ternary Quadratic Equations

Mishra, Sudhakara

1991-02-01

We have dealt with the general ternary quadratic equation: ax2 + by^ {2} + cz2 + dxy + exz + fyz = 0 with integer coefficients. After giving a matrix-reduction formula for a quadratic equation in any number of variables, of which the reduction of the above ternary equation is an easy consequence, we have devoted our attention to the reduced equation: ax^ {2} + by2 + cz^{2 } = 0. We have devised an algorithm for reducing Dirichlet's possibly larger solutions to this prescribed range of Holzer's. Then we have generalized Holzer's theorem to the case of the ternary equation: ax^{2 } + by2 + cz2 + dxy + exz + fyz = 0, giving in this context a new range called the CM-range, of which the Holzer's range is a particular case when d = e = f = 0. We have described an algorithm for getting a solution of the general ternary within this CM-range. After that we have devised an algorithm for getting all the solutions of the Legendre's equation ax 2 + by2 + cz^ {2} = 0 within the Holzer's range--and have shown that if we regard this Legendre's equation as a double cone, these solutions within the Holzer's range lie along some definite rays, here called the CM-rays, which are completely determined by the prime factors of the coefficients a, b and c. After giving an algorithm for detecting these CM-rays of the reduced equation: ax^2 + by^2 + cz^2 = 0, we have shown how one can produce some similar rays of solutions of the above general ternary quadratic equation: ax2 + by2 + cz2 + dxy + exz + fyz = 0. Note that apart from the method of exhausting all the possibilities, so far there has been no precisely stated algorithm to find the minimum solutions of the above ternary equations. Towards the end, observing in the context of our main result an inequality involving two functions, namely C and PCM from doubz_sp{*} {3} to doubz_+, and simultaneously presenting some tables of these positive CM-rays or PCM-rays lying in the positive octant, we have concluded this work with a number of

1. Inferring Selection Intensity and Allele Age from Multilocus Haplotype Structure

PubMed Central

Chen, Hua; Slatkin, Montgomery

2013-01-01

It is a challenging task to infer selection intensity and allele age from population genetic data. Here we present a method that can efficiently estimate selection intensity and allele age from the multilocus haplotype structure in the vicinity of a segregating mutant under positive selection. We use a structured-coalescent approach to model the effect of directional selection on the gene genealogies of neutral markers linked to the selected mutant. The frequency trajectory of the selected allele follows the Wright-Fisher model. Given the position of the selected mutant, we propose a simplified multilocus haplotype model that can efficiently model the dynamics of the ancestral haplotypes under the joint influence of selection and recombination. This model approximates the ancestral genealogies of the sample, which reduces the number of states from an exponential function of the number of single-nucleotide polymorphism loci to a quadratic function. That allows parameter inference from data covering DNA regions as large as several hundred kilo-bases. Importance sampling algorithms are adopted to evaluate the probability of a sample by exploring the space of both allele frequency trajectories of the selected mutation and gene genealogies of the linked sites. We demonstrate by simulation that the method can accurately estimate selection intensity for moderate and strong positive selection. We apply the method to a data set of the G6PD gene in an African population and obtain an estimate of 0.0456 (95% confidence interval 0.0144−0.0769) for the selection intensity. The proposed method is novel in jointly modeling the multilocus haplotype pattern caused by recombination and mutation, allowing the analysis of haplotype data in recombining regions. Moreover, the method is applicable to data from populations under exponential growth and a variety of other demographic histories. PMID:23797107

2. Inference or Observation?

ERIC Educational Resources Information Center

Finson, Kevin D.

2010-01-01

Learning about what inferences are, and what a good inference is, will help students become more scientifically literate and better understand the nature of science in inquiry. Students in K-4 should be able to give explanations about what they investigate (NSTA 1997) and that includes doing so through inferring. This article provides some tips…

3. Analysis of Students' Error in Learning of Quadratic Equations

ERIC Educational Resources Information Center

Zakaria, Effandi; Ibrahim; Maat, Siti Mistima

2010-01-01

The purpose of the study was to determine the students' error in learning quadratic equation. The samples were 30 form three students from a secondary school in Jambi, Indonesia. Diagnostic test was used as the instrument of this study that included three components: factorization, completing the square and quadratic formula. Diagnostic interview…

4. Tangent Lines without Derivatives for Quadratic and Cubic Equations

ERIC Educational Resources Information Center

Carroll, William J.

2009-01-01

In the quadratic equation, y = ax[superscript 2] + bx + c, the equation y = bx + c is identified as the equation of the line tangent to the parabola at its y-intercept. This is extended to give a convenient method of graphing tangent lines at any point on the graph of a quadratic or a cubic equation. (Contains 5 figures.)

5. Effects of Classroom Instruction on Students' Understanding of Quadratic Equations

ERIC Educational Resources Information Center

Vaiyavutjamai, Pongchawee; Clements, M. A.

2006-01-01

Two hundred and thirty-one students in six Grade 9 classes in two government secondary schools located near Chiang Mai, Thailand, attempted to solve the same 18 quadratic equations before and after participating in 11 lessons on quadratic equations. Data from the students' written responses to the equations, together with data in the form of…

6. Geometric quadratic stochastic operator on countable infinite set

SciTech Connect

Ganikhodjaev, Nasir; Hamzah, Nur Zatul Akmar

2015-02-03

In this paper we construct the family of Geometric quadratic stochastic operators defined on the countable sample space of nonnegative integers and investigate their trajectory behavior. Such operators can be reinterpreted in terms of of evolutionary operator of free population. We show that Geometric quadratic stochastic operators are regular transformations.

7. Visualising the Roots of Quadratic Equations with Complex Coefficients

ERIC Educational Resources Information Center

Bardell, Nicholas S.

2014-01-01

This paper is a natural extension of the root visualisation techniques first presented by Bardell (2012) for quadratic equations with real coefficients. Consideration is now given to the familiar quadratic equation "y = ax[superscript 2] + bx + c" in which the coefficients "a," "b," "c" are generally…

8. Quadratic elongation: A quantitative measure of distortion in coordination polyhedra

USGS Publications Warehouse

Robinson, Kelly F.; Gibbs, G.V.; Ribbe, P.H.

1971-01-01

Quadratic elongation and the variance of bond angles are linearly correlated for distorted octahedral and tetrahedral coordination complexes, both of which show variations in bond length and bond angle. The quadratic elonga tion is dimensionless, giving a quantitative measure of polyhedral distortion which is independent of the effective size of the polyhedron.

9. Quadratic divergences and quantum gravitational contributions to gauge coupling constants

Toms, David J.

2011-10-01

The calculation of quadratic divergences in Einstein-Maxwell theory with a possible cosmological constant is considered. We describe a method of calculation, using the background-field method, that is sensitive to quadratic divergences, is respectful of gauge invariance, and is independent of gauge conditions. A standard renormalization group analysis is applied to the result where it is shown that the quadratic divergences do lead to asymptotic freedom as found in the original paper of Robinson and Wilczek. The role and nature of these quadratic divergences is critically evaluated in light of recent criticism. Within the context of the background-field method, it is shown that it is possible to define the charge in a physically motivated way in which the quadratic divergences do not play a role. This latter view is studied in more depth in a toy model described in an appendix.

10. Time Domain Identification of an Optimal Control Pilot Model with Emphasis on the Objective Function

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1982-01-01

A method for the identification of the pilot's control compensation using time domain techniques is proposed. From this information we hope to infer a quadratic cost function, supported by the data, that represents a reasonable expression for the pilot's control objective in the task being performed, or an inferred piloting strategy. The objectives for this method are: (1) obtain a better understanding of the fundamental piloting techniques in complex tasks, such as landing approach; (2) the development of a metric measurable in simulations and flight test that correlate with subjective pilot opinion; and (3) to further validate pilot models and pilot vehicle analysis methods.

11. Inferring biotic interactions from proxies.

PubMed

Morales-Castilla, Ignacio; Matias, Miguel G; Gravel, Dominique; Araújo, Miguel B

2015-06-01

Inferring biotic interactions from functional, phylogenetic and geographical proxies remains one great challenge in ecology. We propose a conceptual framework to infer the backbone of biotic interaction networks within regional species pools. First, interacting groups are identified to order links and remove forbidden interactions between species. Second, additional links are removed by examination of the geographical context in which species co-occur. Third, hypotheses are proposed to establish interaction probabilities between species. We illustrate the framework using published food-webs in terrestrial and marine systems. We conclude that preliminary descriptions of the web of life can be made by careful integration of data with theory. PMID:25922148

12. Polychromatic solitons in a quadratic medium.

PubMed

Towers, I N; Malomed, B A

2002-10-01

We introduce the simplest model to describe parametric interactions in a quadratically nonlinear optical medium with the fundamental harmonic containing two components with (slightly) different carrier frequencies [which is a direct analog of wavelength-division multiplexed models, well known in media with cubic nonlinearity]. The model takes a closed form with three different second-harmonic components, and it is formulated in the spatial domain. We demonstrate that the model supports both polychromatic solitons (PCSs), with all the components present in them, and two types of mutually orthogonal simple solitons, both types being stable in a broad parametric region. An essential peculiarity of PCS is that its power is much smaller than that of a simple (usual) soliton (taken at the same values of control parameters), which may be an advantage for experimental generation of PCSs. Collisions between the orthogonal simple solitons are simulated in detail, leading to the conclusion that the collisions are strongly inelastic, converting the simple solitons into polychromatic ones, and generating one or two additional PCSs. A collision velocity at which the inelastic effects are strongest is identified, and it is demonstrated that the collision may be used as a basis to design a simple all-optical XOR logic gate. PMID:12443362

13. A Quadratic Closure for Compressible Turbulence

SciTech Connect

Futterman, J A

2008-09-16

We have investigated a one-point closure model for compressible turbulence based on third- and higher order cumulant discard for systems undergoing rapid deformation, such as might occur downstream of a shock or other discontinuity. In so doing, we find the lowest order contributions of turbulence to the mean flow, which lead to criteria for Adaptive Mesh Refinement. Rapid distortion theory (RDT) as originally applied by Herring closes the turbulence hierarchy of moment equations by discarding third order and higher cumulants. This is similar to the fourth-order cumulant discard hypothesis of Millionshchikov, except that the Millionshchikov hypothesis was taken to apply to incompressible homogeneous isotropic turbulence generally, whereas RDT is applied only to fluids undergoing a distortion that is 'rapid' in the sense that the interaction of the mean flow with the turbulence overwhelms the interaction of the turbulence with itself. It is also similar to Gaussian closure, in which both second and fourth-order cumulants are retained. Motivated by RDT, we develop a quadratic one-point closure for rapidly distorting compressible turbulence, without regard to homogeneity or isotropy, and make contact with two equation turbulence models, especially the K-{var_epsilon} and K-L models, and with linear instability growth. In the end, we arrive at criteria for Adaptive Mesh Refinement in Finite Volume simulations.

14. Inference engine using optical array logic

Iwata, Masaya; Tanida, Jun; Ichioka, Yoshiki

1990-07-01

An implementation method for an inference engine using optical array logic is presented. Optical array logic is a technique for parallel neighborhood operation using spatial coding and 2-D correlation. For efficient execution of inference in artificial intelligence problems, a large number of data must be searched effectively. To achieve this demand, a template matching technique is applied to the inference operation. By introducing a new function of data conversion, the inference operation can be implemented with optical array logic, which utilizes parallelism in optical techniques.

15. Statistical inference and string theory

Heckman, Jonathan J.

2015-09-01

In this paper, we expose some surprising connections between string theory and statistical inference. We consider a large collective of agents sweeping out a family of nearby statistical models for an M-dimensional manifold of statistical fitting parameters. When the agents making nearby inferences align along a d-dimensional grid, we find that the pooled probability that the collective reaches a correct inference is the partition function of a nonlinear sigma model in d dimensions. Stability under perturbations to the original inference scheme requires the agents of the collective to distribute along two dimensions. Conformal invariance of the sigma model corresponds to the condition of a stable inference scheme, directly leading to the Einstein field equations for classical gravity. By summing over all possible arrangements of the agents in the collective, we reach a string theory. We also use this perspective to quantify how much an observer can hope to learn about the internal geometry of a superstring compactification. Finally, we present some brief speculative remarks on applications to the AdS/CFT correspondence and Lorentzian signature space-times.

16. Homogeneous systems with quadratic integrals, Lie-Poisson quasibrackets, and Kovalevskaya's method

Bizyaev, I. A.; Kozlov, V. V.

2015-12-01

We consider differential equations with quadratic right-hand sides that admit two quadratic first integrals, one of which is a positive-definite quadratic form. We indicate conditions of general nature under which a linear change of variables reduces this system to a certain 'canonical' form. Under these conditions, the system turns out to be divergenceless and can be reduced to a Hamiltonian form, but the corresponding linear Lie-Poisson bracket does not always satisfy the Jacobi identity. In the three-dimensional case, the equations can be reduced to the classical equations of the Euler top, and in four-dimensional space, the system turns out to be superintegrable and coincides with the Euler-Poincaré equations on some Lie algebra. In the five-dimensional case we find a reducing multiplier after multiplying by which the Poisson bracket satisfies the Jacobi identity. In the general case for n>5 we prove the absence of a reducing multiplier. As an example we consider a system of Lotka-Volterra type with quadratic right-hand sides that was studied by Kovalevskaya from the viewpoint of conditions of uniqueness of its solutions as functions of complex time. Bibliography: 38 titles.

17. Phase recovery based on quadratic programming

Zhang, Quan Bing; Ge, Xiao Juan; Cheng, Ya Dong; Ni, Na

2014-11-01

Most of the information of optical wavefront is encoded in the phase which includes more details of the object. Conventional optical measuring apparatus is relatively easy to record the intensity of light, but can not measure the phase of light directly. Thus it is important to recovery the phase from the intensity measurements of the object. In recent years, the methods based on quadratic programming such as PhaseLift and PhaseCut can recover the phase of general signal exactly for overdetermined system. To retrieve the phase of sparse signal, the Compressive Phase Retrieval (CPR) algorithm combines the l1-minimization in Compressive Sensing (CS) with low-rank matrix completion problem in PhaseLift, but the result is unsatisfied. This paper focus on the recovery of the phase of sparse signal and propose a new method called the Compressive Phase Cut Retrieval (CPCR) by combining the CPR algorithm with the PhaseCut algorithm. To ensure the sparsity of the recovered signal, we use CPR method to solve a semi-definite programming problem firstly. Then apply linear transformation to the recovered signal, and set the phase of the result as the initial value of the PhaseCut problem. We use TFOCS (a library of Matlab-files) to implement the proposed CPCR algorithm in order to improve the recovered results of the CPR algorithm. Experimental results show that the proposed method can improve the accuracy of the CPR algorithm, and overcome the shortcoming of the PhaseCut method that it can not recover the sparse signal effectively.

18. Optimal channels for channelized quadratic estimators.

PubMed

Kupinski, Meredith K; Clarkson, Eric

2016-06-01

We present a new method for computing optimized channels for estimation tasks that is feasible for high-dimensional image data. Maximum-likelihood (ML) parameter estimates are challenging to compute from high-dimensional likelihoods. The dimensionality reduction from M measurements to L channels is a critical advantage of channelized quadratic estimators (CQEs), since estimating likelihood moments from channelized data requires smaller sample sizes and inverting a smaller covariance matrix is easier. The channelized likelihood is then used to form ML estimates of the parameter(s). In this work we choose an imaging example in which the second-order statistics of the image data depend upon the parameter of interest: the correlation length. Correlation lengths are used to approximate background textures in many imaging applications, and in these cases an estimate of the correlation length is useful for pre-whitening. In a simulation study we compare the estimation performance, as measured by the root-mean-squared error (RMSE), of correlation length estimates from CQE and power spectral density (PSD) distribution fitting. To abide by the assumptions of the PSD method we simulate an ergodic, isotropic, stationary, and zero-mean random process. These assumptions are not part of the CQE formalism. The CQE method assumes a Gaussian channelized likelihood that can be a valid for non-Gaussian image data, since the channel outputs are formed from weighted sums of the image elements. We have shown that, for three or more channels, the RMSE of CQE estimates of correlation length is lower than conventional PSD estimates. We also show that computing CQE by using a standard nonlinear optimization method produces channels that yield RMSE within 2% of the analytic optimum. CQE estimates of anisotropic correlation length estimation are reported to demonstrate this technique on a two-parameter estimation problem. PMID:27409452

19. Degenerate nonlinear programming with a quadratic growth condition.

SciTech Connect

Anitescu, M.; Mathematics and Computer Science

2000-01-01

We show that the quadratic growth condition and the Mangasarian-Fromovitz constraint qualification (MFCQ) imply that local minima of nonlinear programs are isolated stationary points. As a result, when started sufficiently close to such points, an L1 exact penalty sequential quadratic programming algorithm will induce at least R-linear convergence of the iterates to such a local minimum. We construct an example of a degenerate nonlinear program with a unique local minimum satisfying the quadratic growth and the MFCQ but for which no positive semidefinite augmented Lagrangian exists. We present numerical results obtained using several nonlinear programming packages on this example and discuss its implications for some algorithms.

20. Physical limits of inference

Wolpert, David H.

2008-07-01

We show that physical devices that perform observation, prediction, or recollection share an underlying mathematical structure. We call devices with that structure “inference devices”. We present a set of existence and impossibility results concerning inference devices. These results hold independent of the precise physical laws governing our universe. In a limited sense, the impossibility results establish that Laplace was wrong to claim that even in a classical, non-chaotic universe the future can be unerringly predicted, given sufficient knowledge of the present. Alternatively, these impossibility results can be viewed as a non-quantum-mechanical “uncertainty principle”. The mathematics of inference devices has close connections to the mathematics of Turing Machines (TMs). In particular, the impossibility results for inference devices are similar to the Halting theorem for TMs. Furthermore, one can define an analog of Universal TMs (UTMs) for inference devices. We call those analogs “strong inference devices”. We use strong inference devices to define the “inference complexity” of an inference task, which is the analog of the Kolmogorov complexity of computing a string. A task-independent bound is derived on how much the inference complexity of an inference task can differ for two different inference devices. This is analogous to the “encoding” bound governing how much the Kolmogorov complexity of a string can differ between two UTMs used to compute that string. However no universe can contain more than one strong inference device. So whereas the Kolmogorov complexity of a string is arbitrary up to specification of the UTM, there is no such arbitrariness in the inference complexity of an inference task. We informally discuss the philosophical implications of these results, e.g., for whether the universe “is” a computer. We also derive some graph-theoretic properties governing any set of multiple inference devices. We also present an

1. Inverse problem of quadratic time-dependent Hamiltonians

Guo, Guang-Jie; Meng, Yan; Chang, Hong; Duan, Hui-Zeng; Di, Bing

2015-08-01

Using an algebraic approach, it is possible to obtain the temporal evolution wave function for a Gaussian wave-packet obeying the quadratic time-dependent Hamiltonian (QTDH). However, in general, most of the practical cases are not exactly solvable, for we need general solutions of the Riccatti equations which are not generally known. We therefore bypass directly solving for the temporal evolution wave function, and study its inverse problem. We start with a particular evolution of the wave-packet, and get the required Hamiltonian by using the inverse method. The inverse approach opens up a new way to find new exact solutions to the QTDH. Some typical examples are studied in detail. For a specific time-dependent periodic harmonic oscillator, the Berry phase is obtained exactly. Project supported by the National Natural Science Foundation of China (Grant No. 11347171), the Natural Science Foundation of Hebei Province of China (Grant No. A2012108003), and the Key Project of Educational Commission of Hebei Province of China (Grant No. ZD2014052).

2. Conditions for the non-negativity of integral quadratic forms with constant coefficients on a half-axis

SciTech Connect

Milyutin, A A

2002-04-30

An integral quadratic functional with constant coefficients on a half-axis is considered. A necessary and sufficient condition for its non-negativity at all square integrable pairs of functions related by a linear ODE is proposed, which is based on the Hamilton-Jacobi inequality. A connection between this condition and the well-known frequency criterion is established.

3. Combinatorics of distance-based tree inference.

PubMed

Pardi, Fabio; Gascuel, Olivier

2012-10-01

Several popular methods for phylogenetic inference (or hierarchical clustering) are based on a matrix of pairwise distances between taxa (or any kind of objects): The objective is to construct a tree with branch lengths so that the distances between the leaves in that tree are as close as possible to the input distances. If we hold the structure (topology) of the tree fixed, in some relevant cases (e.g., ordinary least squares) the optimal values for the branch lengths can be expressed using simple combinatorial formulae. Here we define a general form for these formulae and show that they all have two desirable properties: First, the common tree reconstruction approaches (least squares, minimum evolution), when used in combination with these formulae, are guaranteed to infer the correct tree when given enough data (consistency); second, the branch lengths of all the simple (nearest neighbor interchange) rearrangements of a tree can be calculated, optimally, in quadratic time in the size of the tree, thus allowing the efficient application of hill climbing heuristics. The study presented here is a continuation of that by Mihaescu and Pachter on branch length estimation [Mihaescu R, Pachter L (2008) Proc Natl Acad Sci USA 105:13206-13211]. The focus here is on the inference of the tree itself and on providing a basis for novel algorithms to reconstruct trees from distances. PMID:23012403

4. Combinatorics of distance-based tree inference

PubMed Central

Pardi, Fabio; Gascuel, Olivier

2012-01-01

Several popular methods for phylogenetic inference (or hierarchical clustering) are based on a matrix of pairwise distances between taxa (or any kind of objects): The objective is to construct a tree with branch lengths so that the distances between the leaves in that tree are as close as possible to the input distances. If we hold the structure (topology) of the tree fixed, in some relevant cases (e.g., ordinary least squares) the optimal values for the branch lengths can be expressed using simple combinatorial formulae. Here we define a general form for these formulae and show that they all have two desirable properties: First, the common tree reconstruction approaches (least squares, minimum evolution), when used in combination with these formulae, are guaranteed to infer the correct tree when given enough data (consistency); second, the branch lengths of all the simple (nearest neighbor interchange) rearrangements of a tree can be calculated, optimally, in quadratic time in the size of the tree, thus allowing the efficient application of hill climbing heuristics. The study presented here is a continuation of that by Mihaescu and Pachter on branch length estimation [Mihaescu R, Pachter L (2008) Proc Natl Acad Sci USA 105:13206–13211]. The focus here is on the inference of the tree itself and on providing a basis for novel algorithms to reconstruct trees from distances. PMID:23012403

5. The Notion of Reducing Abstraction in Quadratic Functions

ERIC Educational Resources Information Center

Eraslan, Ali

2008-01-01

One possible approach students can cope with abstract algebra concepts is reducing abstraction. This notion occurs when learners are unable to adopt mental strategies as they deal with abstraction level of a given task. To make these concepts mentally accessible for themselves, learners unconsciously reduce the level of the abstraction of the…

6. Modelling Transformations of Quadratic Functions: A Proposal of Inductive Inquiry

ERIC Educational Resources Information Center

Sokolowski, Andrzej

2013-01-01

This paper presents a study about using scientific simulations to enhance the process of mathematical modelling. The main component of the study is a lesson whose major objective is to have students mathematise a trajectory of a projected object and then apply the model to formulate other trajectories by using the properties of function…

7. Superintegrable deformations of superintegrable systems: Quadratic superintegrability and higher-order superintegrability

2015-04-01

The superintegrability of four Hamiltonians H r ˜ = λ H r , r = a, b, c, d, where Hr are known Hamiltonians and λ is a certain function defined on the configuration space and depended on a parameter κ, is studied. The new Hamiltonians, and the associated constants of motion Jri, i = 1, 2, 3, are continous functions of the parameter κ. The first part is concerned with separability and quadratic superintegrability (the integrals of motion are quadratic in the momenta) and the second part is devoted to the existence of higher-order superintegrability. The results obtained in the second part are related with the Tremblay-Turbiner-Winternitz and the Post-Winternitz systems.

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

NASA Technical Reports Server (NTRS)

Koppang, Paul; Leland, Robert

1996-01-01

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

9. Direct Orthogonal Distance to Quadratic Surfaces in 3D.

PubMed

Lott, Gus K

2014-09-01

Discovering the orthogonal distance to a quadratic surface is a classic geometric task in vision, modeling, and robotics. I describe a simple, efficient, and stable direct solution for the orthogonal distance (foot-point) to an arbitrary quadratic surface from a general finite 3D point. The problem is expressed as the intersection of three quadratic surfaces, two of which are derived from the requirement of orthogonality of two non-coincident planes with the tangent plane to the quadric. A sixth order single-variable polynomial is directly generated in one coordinate of the surface point. The method detects intersection points at infinity and operates smoothly across all real quadratic surface classes. The method also geometrically detects continuums of orthogonal points (i.e., from the exact center of a sphere). I discuss algorithm performance, compare it to a state-of-the-art estimator, demonstrate the algorithm on synthetic data, and describe extension to arbitrary dimension. PMID:26352239

10. On a 'Mysterious' Case of a Quadratic Hamiltonian

Sakovich, Sergei

2006-07-01

We show that one of the five cases of a quadratic Hamiltonian, which were recently selected by Sokolov and Wolf who used the Kovalevskaya-Lyapunov test, fails to pass the Painlevé test for integrability.

11. A non-linear programming approach to the computer-aided design of regulators using a linear-quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1985-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.

SciTech Connect

Guellue, Ibrahim; Sisman, Tahsin Cagri; Tekin, Bayram; Guerses, Metin

2011-04-15

We give an exact solution of the quadratic gravity in D dimensions. The solution is a plane-fronted wave metric with a cosmological constant. This metric solves not only the full quadratic gravity field equations but also the linearized ones which include the linearized equations of the recently found critical gravity. A subset of the solutions change the asymptotic structure of the anti-de Sitter space due to their logarithmic behavior.

13. INFERRING THE ECCENTRICITY DISTRIBUTION

SciTech Connect

Hogg, David W.; Bovy, Jo; Myers, Adam D.

2010-12-20

Standard maximum-likelihood estimators for binary-star and exoplanet eccentricities are biased high, in the sense that the estimated eccentricity tends to be larger than the true eccentricity. As with most non-trivial observables, a simple histogram of estimated eccentricities is not a good estimate of the true eccentricity distribution. Here, we develop and test a hierarchical probabilistic method for performing the relevant meta-analysis, that is, inferring the true eccentricity distribution, taking as input the likelihood functions for the individual star eccentricities, or samplings of the posterior probability distributions for the eccentricities (under a given, uninformative prior). The method is a simple implementation of a hierarchical Bayesian model; it can also be seen as a kind of heteroscedastic deconvolution. It can be applied to any quantity measured with finite precision-other orbital parameters, or indeed any astronomical measurements of any kind, including magnitudes, distances, or photometric redshifts-so long as the measurements have been communicated as a likelihood function or a posterior sampling.

14. Inferring the Eccentricity Distribution

Hogg, David W.; Myers, Adam D.; Bovy, Jo

2010-12-01

Standard maximum-likelihood estimators for binary-star and exoplanet eccentricities are biased high, in the sense that the estimated eccentricity tends to be larger than the true eccentricity. As with most non-trivial observables, a simple histogram of estimated eccentricities is not a good estimate of the true eccentricity distribution. Here, we develop and test a hierarchical probabilistic method for performing the relevant meta-analysis, that is, inferring the true eccentricity distribution, taking as input the likelihood functions for the individual star eccentricities, or samplings of the posterior probability distributions for the eccentricities (under a given, uninformative prior). The method is a simple implementation of a hierarchical Bayesian model; it can also be seen as a kind of heteroscedastic deconvolution. It can be applied to any quantity measured with finite precision—other orbital parameters, or indeed any astronomical measurements of any kind, including magnitudes, distances, or photometric redshifts—so long as the measurements have been communicated as a likelihood function or a posterior sampling.

15. Regularized adelic formulas for string and superstring amplitudes in one-class quadratic fields

2010-09-01

We obtain regularized adelic formulas for gamma and beta functions for fields of rational numbers and the one-class quadratic fields and arbitrary quasicharacters (ramified or not). We consider applications to four-tachyon tree string amplitudes, generalized Veneziano amplitudes (open string), perturbed Virasoro amplitudes (closed string), massless four-particle tree open and closed superstring amplitudes, Ramond-Neveu-Schwarz superstring amplitudes, and charged heterotic superstring amplitudes. We establish certain relations between different string and superstring amplitudes.

16. Inference in poor languages

SciTech Connect

Petrov, S.

1996-10-01

Languages with a solvable implication problem but without complete and consistent systems of inference rules (poor languages) are considered. The problem of existence of finite complete and consistent inference rule system for a poor language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.

17. Phase Transitions in the Quadratic Contact Process on Complex Networks

Varghese, Chris; Durrett, Rick

2013-03-01

The quadratic contact process (QCP) is a natural extension of the well studied linear contact process where a single infected (1) individual can infect a susceptible (0) neighbor and infected individuals are allowed to recover (1 --> 0). In the QCP, a combination of two 1's is required to effect a 0 --> 1 change. We extend the study of the QCP, which so far has been limited to lattices, to complex networks as a model for the change in a population via sexual reproduction and death. We define two versions of the QCP - vertex centered (VQCP) and edge centered (EQCP) with birth events 1 - 0 - 1 --> 1 - 1 - 1 and 1 - 1 - 0 --> 1 - 1 - 1 respectively, where  -' represents an edge. We investigate the effects of network topology by considering the QCP on regular, Erdős-Rényi and power law random graphs. We perform mean field calculations as well as simulations to find the steady state fraction of occupied vertices as a function of the birth rate. We find that on the homogeneous graphs (regular and Erdős-Rényi) there is a discontinuous phase transition with a region of bistability, whereas on the heavy tailed power law graph, the transition is continuous. The critical birth rate is found to be positive in the former but zero in the latter.

18. Quadratic Optimization in the Problems of Active Control of Sound

NASA Technical Reports Server (NTRS)

Loncaric, J.; Tsynkov, S. V.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).

19. Moments for general quadratic densities in n dimensions

SciTech Connect

Furman, Miguel A.

2002-03-20

We present the calculation of the generating functions and the rth-order correlations for densities of the form {rho}(x) {proportional_to} where g(s) is a non-negative function of the quadratic ''action'' s(x)={summation}{sub i,j}H{sub ij}x{sub i}x{sub j}, where x = (x{sub 1},x{sub 2}...,x{sub n}) is a real n-dimensional vector and H is a real, symmetric n x n matrix whose eigenvalues are strictly positive. In particular, we find the connection between the (r+2)th-order and rth-order correlations, which constitutes a generalization of the Gaussian moment theorem, which corresponds to the particular choice g(s)=e{sup -s/2}. We present several examples for specific choices for g(s), including the explicit expression for the generating function for each case and the subspace projection of {rho}(x) in a few cases. We also provide the straightforward generalizations to: (1) the case where g=g(s(x)+a {center_dot} x), where a=(a{sub 1},a{sub 2},...,a{sub n}) is an arbitrary real n-dimensional vector, and (2) the complex case, in which the action is of the form s(z) = {summation}{sub i,j}H{sub ij}z{sup *}{sub i} z{sub j} where z=(z{sub 1},z{sub 2}...z{sub n}) is an n-dimensional complex vector and H is a Hermitian n x n matrix whose eigenvalues are strictly positive.

20. Equation for disentangling time-ordered exponentials with arbitrary quadratic generators

SciTech Connect

Budanov, V.G.

1987-12-01

In many quantum-mechanical constructions, it is necessary to disentangle an operator-valued time-ordered exponential with time-dependent generators quadratic in the creation and annihilation operators. By disentangling, one understands the finding of the matrix elements of the time-ordered exponential or, in a more general formulation. The solution of the problem can also be reduced to calculation of a matrix time-ordered exponential that solves the corresponding classical problem. However, in either case the evolution equations in their usual form do not enable one to take into account explicitly the symmetry of the system. In this paper the methods of Weyl analysis are used to find an ordinary differential equation on a matrix Lie algebra that is invariant with respect to the adjoint action of the dynamical symmetry group of a quadratic Hamiltonian and replaces the operator evolution equation for the Green's function.

1. Learning control for minimizing a quadratic cost during repetitions of a task

NASA Technical Reports Server (NTRS)

Longman, Richard W.; Chang, Chi-Kuang

1990-01-01

In many applications, control systems are asked to perform the same task repeatedly. Learning control laws have been developed over the last few years that allow the controller to improve its performance each repetition, and to converge to zero error in tracking a desired trajectory. This paper generates a new type of learning control law that learns to minimize a quadratic cost function for tracking. Besides being of interest in its own right, this objective alleviates the need to specify a desired trajectory that can actually be performed by the system. The approach used here is to adapt appropriate methods from numerical optimization theory in order to produce learning control algorithms that adjust the system command from repetition to repetition in order to converge to the quadratic cost optimal trajectory.

2. KENO-VI: A Monte Carlo Criticality Program with generalized quadratic geometry

SciTech Connect

Hollenbach, D.F.; Petrie, L.M.; Landers, N.F.

1993-07-01

This report discusses KENO-VI which is a new version of the KENO monte Carlo Criticality Safety developed at Oak Ridge National Laboratory. The purpose of KENO-VI is to provide a criticality safety code similar to KENO-V.a that possesses a more general and flexible geometry package. KENO-VI constructs and processes geometry data as sets of quadratic equations. A lengthy set of simple, easy-to-use geometric functions, similar to those provided in KENO-V.a., and the ability to build more complex geometric shapes represented by sets of quadratic equations are the heart of the geometry package in KENO-VI. The codes flexibility is increased by allowing intersecting geometry regions, hexagonal as well as cuboidal arrays, and the ability to specify an array boundary that intersects the array.

ERIC Educational Resources Information Center

Baron, Lorraine M.

2015-01-01

As students develop algebraic reasoning in grades 5 to 9, they learn to recognize patterns and understand expressions, equations, and variables. Linear functions are a focus in eighth-grade mathematics, and by algebra 1, students must make sense of functions that are not linear. This article describes how students worked through a classroom task…

4. The generalized quadratic covariation for fractional Brownian motion with Hurst index less than 1/2

Yan, Litan; Liu, Junfeng; Chen, Chao

2014-11-01

In this paper, we study the generalized quadratic covariation of f(BH) and BH defined by \$ [f(BH),BH](H)t:=\\lim_\\varepsilon\\downarrow 0}(1)/(\\varepsilon2H)\\int 0t{f(BHs+\\varepsilon) -f(BHs)}(BHs+\\varepsilon-BH_s)ds2H in probability, where f is a Borel function and BH is a fractional Brownian motion with Hurst index 0 < H < 1/2. We construct a Banach space {H} of measurable functions such that the generalized quadratic covariation exists in L2(Ω) and the Bouleau-Yor identity takes the form [f(BH),BH]t(H)=-\\int_ {R}}f(x){L}H(dx,t) provided f\\in {H}, where {L}^{H}(x, t) is the weighted local time of BH. These are also extended to the time-dependent case, and as an application we give the identity between the generalized quadratic covariation and the 4-covariation [g(BH), BH, BH, BH] when H = 1/4.

5. Linguistic Markers of Inference Generation While Reading.

PubMed

Clinton, Virginia; Carlson, Sarah E; Seipel, Ben

2016-06-01

Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students ([Formula: see text]) reading narrative texts were hand-coded for inferences. These data were also processed with a computer text analysis tool, Linguistic Inquiry and Word Count, for percentages of word use in the following categories: cognitive mechanism words, nonfluencies, and nine types of function words. Findings indicate that cognitive mechanisms were an independent, positive predictor of connections to background knowledge (i.e., elaborative inference generation) and nonfluencies were an independent, negative predictor of connections within the text (i.e., bridging inference generation). Function words did not provide unique variance towards predicting inference generation. These findings are discussed in the context of a cognitive reflection model and the differences between bridging and elaborative inference generation. In addition, potential practical implications for intelligent tutoring systems and computer-based methods of inference identification are presented. PMID:25833811

6. Network Plasticity as Bayesian Inference

PubMed Central

Legenstein, Robert; Maass, Wolfgang

2015-01-01

General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing. We propose that inherently stochastic features of synaptic plasticity and spine motility enable cortical networks of neurons to carry out probabilistic inference by sampling from a posterior distribution of network configurations. This model provides a viable alternative to existing models that propose convergence of parameters to maximum likelihood values. It explains how priors on weight distributions and connection probabilities can be merged optimally with learned experience, how cortical networks can generalize learned information so well to novel experiences, and how they can compensate continuously for unforeseen disturbances of the network. The resulting new theory of network plasticity explains from a functional perspective a number of experimental data on stochastic aspects of synaptic plasticity that previously appeared to be quite puzzling. PMID:26545099

7. Interval-parameter robust quadratic programming for water quality management under uncertainty

Li, Y. P.; Huang, G. H.; Nie, S. L.; Mo, D. W.

2008-07-01

Effective planning of water quality management is important for facilitating sustainable socio-economic development in watershed systems. An interval-parameter robust quadratic programming (IRQP) method is developed by incorporating techniques of robust programming and interval quadratic programming within a general optimization framework. The IRQP improves upon existing quadratic programming methods, and can tackle uncertainties presented as interval numbers and fuzzy sets as well as their combinations. Moreover, it can deal with nonlinearities in the objective function such that economies-of-scale effects can be reflected. The developed method is applied to a case study of a water quality management under uncertainty. A number of decision alternatives are generated based on the interval solutions as well as the projected applicable conditions. They represent multiple decision options with various environmental and economic considerations. Willingness to accept a low economic revenue will guarantee satisfying the water quality requirements. A strong desire to acquire a high benefit will run the risk of violating environmental criteria.

8. An Improved Correction for Range Restricted Correlations Under Extreme, Monotonic Quadratic Nonlinearity and Heteroscedasticity.

PubMed

Culpepper, Steven Andrew

2016-06-01

Standardized tests are frequently used for selection decisions, and the validation of test scores remains an important area of research. This paper builds upon prior literature about the effect of nonlinearity and heteroscedasticity on the accuracy of standard formulas for correcting correlations in restricted samples. Existing formulas for direct range restriction require three assumptions: (1) the criterion variable is missing at random; (2) a linear relationship between independent and dependent variables; and (3) constant error variance or homoscedasticity. The results in this paper demonstrate that the standard approach for correcting restricted correlations is severely biased in cases of extreme monotone quadratic nonlinearity and heteroscedasticity. This paper offers at least three significant contributions to the existing literature. First, a method from the econometrics literature is adapted to provide more accurate estimates of unrestricted correlations. Second, derivations establish bounds on the degree of bias attributed to quadratic functions under the assumption of a monotonic relationship between test scores and criterion measurements. New results are presented on the bias associated with using the standard range restriction correction formula, and the results show that the standard correction formula yields estimates of unrestricted correlations that deviate by as much as 0.2 for high to moderate selectivity. Third, Monte Carlo simulation results demonstrate that the new procedure for correcting restricted correlations provides more accurate estimates in the presence of quadratic and heteroscedastic test score and criterion relationships. PMID:25953477

9. A Note on the Linearly and Quadratically Weighted Kappa Coefficients.

PubMed

Li, Pingke

2016-09-01

The linearly and quadratically weighted kappa coefficients are popular statistics in measuring inter-rater agreement on an ordinal scale. It has been recently demonstrated that the linearly weighted kappa is a weighted average of the kappa coefficients of the embedded 2 by 2 agreement matrices, while the quadratically weighted kappa is insensitive to the agreement matrices that are row or column reflection symmetric. A rank-one matrix decomposition approach to the weighting schemes is presented in this note such that these phenomena can be demonstrated in a concise manner. PMID:27246436

10. Analysis of integral controls in linear quadratic regulator design

NASA Technical Reports Server (NTRS)

Slater, G. L.

1979-01-01

The application of linear optimal control to the design of systems with integral control action on specified outputs is considered. Using integral terms in a quadratic performance index, an asymptotic analysis is used to determine the effect of variable quadratic weights on the eigenvalues and eigenvectors of the closed loop system. It is shown that for small integral terms the placement of integrator poles and gain calculation can be effectively decoupled from placement of the primary system eigenvalues. This technique is applied to the design of integral controls for a STOL aircraft outer loop guidance system.

11. CAD of control systems: Application of nonlinear programming to a linear quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1983-01-01

The familiar suboptimal regulator design approach is recast as a constrained optimization problem and incorporated in a Computer Aided Design (CAD) package where both design objective and constraints are quadratic cost functions. This formulation permits the separate consideration of, for example, model following errors, sensitivity measures and control energy as objectives to be minimized or limits to be observed. Efficient techniques for computing the interrelated cost functions and their gradients are utilized in conjunction with a nonlinear programming algorithm. The effectiveness of the approach and the degree of insight into the problem which it affords is illustrated in a helicopter regulation design example.

12. Inferring synaptic structure in presence of neural interaction time scales.

PubMed

Capone, Cristiano; Filosa, Carla; Gigante, Guido; Ricci-Tersenghi, Federico; Del Giudice, Paolo

2015-01-01

Biological networks display a variety of activity patterns reflecting a web of interactions that is complex both in space and time. Yet inference methods have mainly focused on reconstructing, from the network's activity, the spatial structure, by assuming equilibrium conditions or, more recently, a probabilistic dynamics with a single arbitrary time-step. Here we show that, under this latter assumption, the inference procedure fails to reconstruct the synaptic matrix of a network of integrate-and-fire neurons when the chosen time scale of interaction does not closely match the synaptic delay or when no single time scale for the interaction can be identified; such failure, moreover, exposes a distinctive bias of the inference method that can lead to infer as inhibitory the excitatory synapses with interaction time scales longer than the model's time-step. We therefore introduce a new two-step method, that first infers through cross-correlation profiles the delay-structure of the network and then reconstructs the synaptic matrix, and successfully test it on networks with different topologies and in different activity regimes. Although step one is able to accurately recover the delay-structure of the network, thus getting rid of any a priori guess about the time scales of the interaction, the inference method introduces nonetheless an arbitrary time scale, the time-bin dt used to binarize the spike trains. We therefore analytically and numerically study how the choice of dt affects the inference in our network model, finding that the relationship between the inferred couplings and the real synaptic efficacies, albeit being quadratic in both cases, depends critically on dt for the excitatory synapses only, whilst being basically independent of it for the inhibitory ones. PMID:25807389

13. Finding Optimal Gains In Linear-Quadratic Control Problems

NASA Technical Reports Server (NTRS)

Milman, Mark H.; Scheid, Robert E., Jr.

1990-01-01

Analytical method based on Volterra factorization leads to new approximations for optimal control gains in finite-time linear-quadratic control problem of system having infinite number of dimensions. Circumvents need to analyze and solve Riccati equations and provides more transparent connection between dynamics of system and optimal gain.

Hall, Will; Rico-Ramirez, Miguel Angel; Kramer, Stefan

2016-04-01

The aim of this work is to test a method that enables the input of event based drop size distributions to alter a quadratic reflectivity (Z) to rainfall (R) equation that is limited by fixed upper and lower points. Results will be compared to the Marshall-Palmer Z-R relation outputs and validated by a network of gauges and a single polarisation weather radar located close to Essen, Germany. The time window over which the drop size distribution measurements will be collected is varied to note any effect on the generated quadratic Z-R relation. The new quadratic algorithm shows some distinct improvement over the Marshall-Palmer relationship through multiple events. The inclusion of a minimum number of Z-R points helped to decrease the associated error by defaulting back to the Marshall-Palmer equation if the limit was not reached. More research will be done to discover why the quadratic performs poorly in some events as there appears to be little correlation between number of drops or mean rainfall amount and the associated error. In some cases it seems the spatial distribution of the disdrometers has a significant effect as a large percentage of the rain bands pass to the north of two of the three disdrometers, frequently in a slightly north-easterly direction. However during widespread precipitation events the new algorithm works very well with reductions compared to the Marshall-Palmer relation.

15. Analysis of Quadratic Diophantine Equations with Fibonacci Number Solutions

ERIC Educational Resources Information Center

Leyendekkers, J. V.; Shannon, A. G.

2004-01-01

An analysis is made of the role of Fibonacci numbers in some quadratic Diophantine equations. A general solution is obtained for finding factors in sums of Fibonacci numbers. Interpretation of the results is facilitated by the use of a modular ring which also permits extension of the analysis.

16. Tuning a fuzzy controller using quadratic response surfaces

NASA Technical Reports Server (NTRS)

Schott, Brian; Whalen, Thomas

1992-01-01

Response surface methodology, an alternative method to traditional tuning of a fuzzy controller, is described. An example based on a simulated inverted pendulum 'plant' shows that with (only) 15 trial runs, the controller can be calibrated using a quadratic form to approximate the response surface.

17. Solving the Quadratic Capacitated Facilities Location Problem by Computer.

ERIC Educational Resources Information Center

Cote, Leon C.; Smith, Wayland P.

Several computer programs were developed to solve various versions of the quadratic capacitated facilities location problem. Matrices, which represent various business costs, are defined for the factors of sites, facilities, customers, commodities, and production units. The objective of the program is to find an optimization matrix for the lowest…

18. Confidence set interference with a prior quadratic bound. [in geophysics

NASA Technical Reports Server (NTRS)

Backus, George E.

1989-01-01

Neyman's (1937) theory of confidence sets is developed as a replacement for Bayesian interference (BI) and stochastic inversion (SI) when the prior information is a hard quadratic bound. It is recommended that BI and SI be replaced by confidence set interference (CSI) only in certain circumstances. The geomagnetic problem is used to illustrate the general theory of CSI.

19. Quadratic Expressions by Means of "Summing All the Matchsticks"

ERIC Educational Resources Information Center

Gierdien, M. Faaiz

2012-01-01

This note presents demonstrations of quadratic expressions that come about when particular problems are posed with respect to matchsticks that form regular triangles, squares, pentagons and so on. Usually when such "matchstick" problems are used as ways to foster algebraic thinking, the expressions for the number of matchstick quantities are…

20. Visualising the Complex Roots of Quadratic Equations with Real Coefficients

ERIC Educational Resources Information Center

Bardell, Nicholas S.

2012-01-01

The roots of the general quadratic equation y = ax[superscript 2] + bx + c (real a, b, c) are known to occur in the following sets: (i) real and distinct; (ii) real and coincident; and (iii) a complex conjugate pair. Case (iii), which provides the focus for this investigation, can only occur when the values of the real coefficients a, b, and c are…

1. Selfsimilarity in a Class of Quadratic-Quasiperiodic Chains

Kaneko, Masanobu; Odagaki, Takashi

1993-04-01

We prove that quasiperiodic chains associated with a class of quadratic irrational numbers have an inflation symmetry and can be generated from a regular chain by a hyperinflation. We devise the explicit method to find the hyperinflation symmetry and discuss the properties of such a class of quasiperiodic sequences.

2. Unravelling Student Challenges with Quadratics: A Cognitive Approach

ERIC Educational Resources Information Center

Kotsopoulos, Donna

2007-01-01

The author's secondary school mathematics students have often reported to her that quadratic relations are one of the most conceptually challenging aspects of the high school curriculum. From her own classroom experiences there seemed to be several aspects to the students' challenges. Many students, even in their early secondary education, have…

3. A quadratic weight selection algorithm. [for optimal flight control

NASA Technical Reports Server (NTRS)

Broussard, J. R.

1981-01-01

A new numerical algorithm is presented which determines a positive semi-definite state weighting matrix in the linear-quadratic optimal control design problem. The algorithm chooses the weighting matrix by placing closed-loop eigenvalues and eigenvectors near desired locations using optimal feedback gains. A simplified flight control design example is used to illustrate the algorithms capabilities.

4. A Unified Approach to Teaching Quadratic and Cubic Equations.

ERIC Educational Resources Information Center

Ward, A. J. B.

2003-01-01

Presents a simple method for teaching the algebraic solution of cubic equations via completion of the cube. Shows that this method is readily accepted by students already familiar with completion of the square as a method for quadratic equations. (Author/KHR)

5. The Bayes Inference Engine

SciTech Connect

Hanson, K.M.; Cunningham, G.S.

1996-04-01

The authors are developing a computer application, called the Bayes Inference Engine, to provide the means to make inferences about models of physical reality within a Bayesian framework. The construction of complex nonlinear models is achieved by a fully object-oriented design. The models are represented by a data-flow diagram that may be manipulated by the analyst through a graphical programming environment. Maximum a posteriori solutions are achieved using a general, gradient-based optimization algorithm. The application incorporates a new technique of estimating and visualizing the uncertainties in specific aspects of the model.

6. Optimizing nondecomposable loss functions in structured prediction.

PubMed

Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N; Li, Ze-Nian; Mori, Greg

2013-04-01

We develop an algorithm for structured prediction with nondecomposable performance measures. The algorithm learns parameters of Markov Random Fields (MRFs) and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines), and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a Quadratic Program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

7. Linear quadratic tracking problems in Hilbert space - Application to optimal active noise suppression

NASA Technical Reports Server (NTRS)

Banks, H. T.; Silcox, R. J.; Keeling, S. L.; Wang, C.

1989-01-01

A unified treatment of the linear quadratic tracking (LQT) problem, in which a control system's dynamics are modeled by a linear evolution equation with a nonhomogeneous component that is linearly dependent on the control function u, is presented; the treatment proceeds from the theoretical formulation to a numerical approximation framework. Attention is given to two categories of LQT problems in an infinite time interval: the finite energy and the finite average energy. The behavior of the optimal solution for finite time-interval problems as the length of the interval tends to infinity is discussed. Also presented are the formulations and properties of LQT problems in a finite time interval.

8. FIBER OPTIC POINT QUADRAT SYSTEM FOR IMPROVED ACCURACY IN VEGETATION SAMPLING

EPA Science Inventory

An automated, fiber optic point quadrat system for vegetation sampling is described. Because the effective point diameter of the system never exceeds 25um it minimizes the substantial errors which can arise with conventional point quadrats. Automatic contact detection eliminates ...

9. Tandem time-of-flight mass spectrometer (TOF-TOF) with a quadratic-field ion mirror

Giannakopulos, Anastassios E.; Thomas, Benjamin; Colburn, Alex W.; Reynolds, David J.; Raptakis, Emmanuel N.; Makarov, Alexander A.; Derrick, Peter J.

2002-05-01

A tandem time-of-flight (TOF-TOF) mass spectrometer comprised of two ion mirrors is described. The first ion mirror, which is a linear-field, single-stage mirror (MS1) with an intermediate collision cell, has been designed to provide the temporal focus necessary for the second, quadratic-field ion mirror (MS2) to function effectively. Due to the wide energy-range focusing capabilities of the quadratic field employed in the second ion mirror all the fragment ions can be collected in one spectrum without the need to step the reflecting working voltage of the MS2. The size of the active area of the microchannel plate detector used in the preliminary experiments was the limiting factor governing the collection efficiently of fragment ions. The use of the first ion mirror to provide temporal focusing of the precursor ion packet at the first focal point of the quadratic mirror used as the MS2 requires no alteration of the focusing conditions for different masses, in contrast to delayed extraction or postsource pulsed focusing. Precursor ions formed by matrix-assisted laser desorption/ionization were mass-selected with an ion gate located before the collision cell and the fragment ions were mass analyzed using the quadratic-field ion mirror. Experimental results demonstrating effective high-energy collision-induced dissociation of polymer and fullerene molecule-ions are presented.

SciTech Connect

Schneider, Uwe

2009-04-15

A simple mechanistic model for predicting cancer induction after fractionated radiotherapy is developed. The model is based upon the linear-quadratic model. The inductions of carcinomas and sarcomas are modeled separately. The linear-quadratic model of cell kill is applied to normal tissues which are unintentionally irradiated during a cancer treatment with radiotherapy. Tumor induction is modeled such that each transformation process results in a tumor cell. The microscopic transformation parameter was chosen such that in the limit of low dose and acute exposure, the parameters of the linear-no-threshold model for tumor induction were approached. The differential equations describing carcinoma and sarcoma inductions can be solved analytically. Cancer induction in this model is a function of treatment dose, the cell kill parameters ({alpha},{beta}), the tumor induction variable ({mu}), and the repopulation parameter ({xi}). Carcinoma induction shows a bell shaped behavior as long as cell repopulation is small. Assuming large cell repopulation rates, a plateaulike function is approached. In contrast, sarcoma induction is negligible for low doses and increases with increasing dose up to a constant value. The proposed model describes carcinoma and sarcoma inductions after fractionated radiotherapy as an analytical function of four parameters. In the limit of low dose and for an instant irradiation it reproduces the results of the linear-no-threshold model. The obtained dose-response curves for cancer induction can be implemented with other models such as the organ-equivalent dose model to predict second cancers after radiotherapy.

11. Spectral and geographical variability in the oceanic response to atmospheric pressure fluctuations, as inferred from “dynamic barometer” Green's functions

Dey, N.; Dickman, S. R.

2010-09-01

A decade ago, a novel theoretical approach was developed (Dickman, 1998) for determining the dynamic response of the oceans to atmospheric pressure variations, a response nicknamed the "dynamic barometer" (DB), and the effects of that response on Earth's rotation. This approach employed a generalized, spherical harmonic ocean tide model to compute oceanic Green's functions, the oceans' fluid dynamic response to unit-amplitude pressure forcing on various spatial and temporal scales, and then construct rotational Green's functions, representing the rotational effects of that response. When combined with the observed atmospheric pressure field, the rotational Green's functions would yield the effects of the DB on Earth's rotation. The Green's functions reflect in some way the geographical and spectral sensitivity of the oceans to atmospheric pressure forcing. We have formulated a measure of that sensitivity using a simple combination of rotational Green's functions. We find that the DB response of the oceans to atmospheric pressure forcing depends significantly on geographic location and on frequency. Compared to the inverted barometer (IB) (the traditional static model), the DB effects differ slightly at long periods but become very different at shorter periods. Among all the responses, the prograde polar motion effects are the most dynamic, with large portions of the North Atlantic and some of the North Pacific no larger than one third of IB, but most of the Southern Hemisphere oceans at least 50% greater than IB.

12. Quantum integrals of motion for variable quadratic Hamiltonians

SciTech Connect

Cordero-Soto, Ricardo; Suazo, Erwin; Suslov, Sergei K.

2010-09-15

We construct integrals of motion for several models of the quantum damped oscillators in a framework of a general approach to the time-dependent Schroedinger equation with variable quadratic Hamiltonians. An extension of the Lewis-Riesenfeld dynamical invariant is given. The time-evolution of the expectation values of the energy-related positive operators is determined for the oscillators under consideration. A proof of uniqueness of the corresponding Cauchy initial value problem is discussed as an application.

13. Discrete quadratic solitons with competing second-harmonic components

SciTech Connect

Setzpfandt, Frank; Pertsch, Thomas; Sukhorukov, Andrey A.

2011-11-15

We describe families of discrete solitons in quadratic waveguide arrays supported by competing cascaded nonlinear interactions between one fundamental and two second-harmonic modes. We characterize the existence, stability, and excitation dynamics of these solitons and show that their features may resemble those of solitons in saturable media. Our results also demonstrate that a power threshold may appear for soliton formation, leading to a suppression of beam self-focusing which explains recent experimental observations.

14. Construction of Lagrangian Local Symmetries for General Quadratic Theory

Deriglazov, A. A.

We propose a procedure which allows one to construct local symmetry generators of general quadratic Lagrangian theory. Manifest recurrence relations for generators in terms of the so-called structure matrices of the Dirac formalism are obtained. The procedure fulfill in terms of initial variables of the theory, and does not imply either separation of constraints on first and second class subsets or any other choice of basis for constraints.

15. Design of Linear Quadratic Regulators and Kalman Filters

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Geyser, L.

1986-01-01

AESOP solves problems associated with design of controls and state estimators for linear time-invariant systems. Systems considered are modeled in state-variable form by set of linear differential and algebraic equations with constant coefficients. Two key problems solved by AESOP are linear quadratic regulator (LQR) design problem and steady-state Kalman filter design problem. AESOP is interactive. User solves design problems and analyzes solutions in single interactive session. Both numerical and graphical information available to user during the session.

16. Observers for Systems with Nonlinearities Satisfying an Incremental Quadratic Inequality

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Corless, Martin

2004-01-01

We consider the problem of state estimation for nonlinear time-varying systems whose nonlinearities satisfy an incremental quadratic inequality. These observer results unifies earlier results in the literature; and extend it to some additional classes of nonlinearities. Observers are presented which guarantee that the state estimation error exponentially converges to zero. Observer design involves solving linear matrix inequalities for the observer gain matrices. Results are illustrated by application to a simple model of an underwater.

17. INFERENCES FROM ROSSI TRACES

SciTech Connect

KENNETH M. HANSON; JANE M. BOOKER

2000-09-08

The authors an uncertainty analysis of data taken using the Rossi technique, in which the horizontal oscilloscope sweep is driven sinusoidally in time ,while the vertical axis follows the signal amplitude. The analysis is done within a Bayesian framework. Complete inferences are obtained by tilting the Markov chain Monte Carlo technique, which produces random samples from the posterior probability distribution expressed in terms of the parameters.

18. Active inference and learning.

PubMed

Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O'Doherty, John; Pezzulo, Giovanni

2016-09-01

This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity. PMID:27375276

19. Quadratic mutual information for dimensionality reduction and classification

Gray, David M.; Principe, José C.

2010-04-01

A research area based on the application of information theory to machine learning has attracted considerable interest in the last few years. This research area has been coined information-theoretic learning within the community. In this paper we apply elements of information-theoretic learning to the problem of automatic target recognition (ATR). A number of researchers have previously shown the benefits of designing classifiers based on maximizing the mutual information between the class data and the class labels. Following prior research in information-theoretic learning, in the current results we show that quadratic mutual information, derived using a special case of the more general Renyi's entropy, can be used for classifier design. In this implementation, a simple subspace projection classifier is formulated to find the optimal projection weights such that the quadratic mutual information between the class data and the class labels is maximized. This subspace projection accomplishes a dimensionality reduction of the raw data set wherein information about the class membership is retained while irrelevant information is discarded. A subspace projection based on this criterion preserves as much class discriminability as possible within the subspace. For this paper, laser radar images are used to demonstrate the results. Classification performance against this data set is compared for a gradient descent MLP classifier and a quadratic mutual information MLP classifier.

20. Measurement of quadratic electrogyration effect in castor oil

Izdebski, Marek; Ledzion, Rafał; Górski, Piotr

2015-07-01

This work presents a detailed analysis of electrogyration measurement in liquids with the usage of an optical polarimetric technique. Theoretical analysis of the optical response to an applied electric field is illustrated by experimental data for castor oil which exhibits natural optical activity, quadratic electro-optic effect and quadratic electrogyration effect. Moreover, the experimental data show that interaction of the oil with a pair of flat electrodes induces a significant dichroism and natural linear birefringence. The combination of these effects occurring at the same time complicates the procedure of measurements. It has been found that a single measurement is insufficient to separate the contribution of the electrogyration effect, but it is possible on the basis of several measurements performed with various orientations of the polarizer and the analyser. The obtained average values of the quadratic electrogyration coefficient β13 in castor oil at room temperature are from - 0.92 ×10-22 to - 1.44 ×10-22m2V-2 depending on the origin of the oil. Although this study is focused on measurements in castor oil, the presented analysis is much more general.

1. Scene Construction, Visual Foraging, and Active Inference

PubMed Central

Mirza, M. Berk; Adams, Rick A.; Mathys, Christoph D.; Friston, Karl J.

2016-01-01

This paper describes an active inference scheme for visual searches and the perceptual synthesis entailed by scene construction. Active inference assumes that perception and action minimize variational free energy, where actions are selected to minimize the free energy expected in the future. This assumption generalizes risk-sensitive control and expected utility theory to include epistemic value; namely, the value (or salience) of information inherent in resolving uncertainty about the causes of ambiguous cues or outcomes. Here, we apply active inference to saccadic searches of a visual scene. We consider the (difficult) problem of categorizing a scene, based on the spatial relationship among visual objects where, crucially, visual cues are sampled myopically through a sequence of saccadic eye movements. This means that evidence for competing hypotheses about the scene has to be accumulated sequentially, calling upon both prediction (planning) and postdiction (memory). Our aim is to highlight some simple but fundamental aspects of the requisite functional anatomy; namely, the link between approximate Bayesian inference under mean field assumptions and functional segregation in the visual cortex. This link rests upon the (neurobiologically plausible) process theory that accompanies the normative formulation of active inference for Markov decision processes. In future work, we hope to use this scheme to model empirical saccadic searches and identify the prior beliefs that underwrite intersubject variability in the way people forage for information in visual scenes (e.g., in schizophrenia). PMID:27378899

2. Scene Construction, Visual Foraging, and Active Inference.

PubMed

Mirza, M Berk; Adams, Rick A; Mathys, Christoph D; Friston, Karl J

2016-01-01

This paper describes an active inference scheme for visual searches and the perceptual synthesis entailed by scene construction. Active inference assumes that perception and action minimize variational free energy, where actions are selected to minimize the free energy expected in the future. This assumption generalizes risk-sensitive control and expected utility theory to include epistemic value; namely, the value (or salience) of information inherent in resolving uncertainty about the causes of ambiguous cues or outcomes. Here, we apply active inference to saccadic searches of a visual scene. We consider the (difficult) problem of categorizing a scene, based on the spatial relationship among visual objects where, crucially, visual cues are sampled myopically through a sequence of saccadic eye movements. This means that evidence for competing hypotheses about the scene has to be accumulated sequentially, calling upon both prediction (planning) and postdiction (memory). Our aim is to highlight some simple but fundamental aspects of the requisite functional anatomy; namely, the link between approximate Bayesian inference under mean field assumptions and functional segregation in the visual cortex. This link rests upon the (neurobiologically plausible) process theory that accompanies the normative formulation of active inference for Markov decision processes. In future work, we hope to use this scheme to model empirical saccadic searches and identify the prior beliefs that underwrite intersubject variability in the way people forage for information in visual scenes (e.g., in schizophrenia). PMID:27378899

3. Towards Context Sensitive Information Inference.

ERIC Educational Resources Information Center

Song, D.; Bruza, P. D.

2003-01-01

Discusses information inference from a psychologistic stance and proposes an information inference mechanism that makes inferences via computations of information flow through an approximation of a conceptual space. Highlights include cognitive economics of information processing; context sensitivity; and query models for information retrieval.…

4. A Quadratic Spline based Interface (QUASI) reconstruction algorithm for accurate tracking of two-phase flows

Diwakar, S. V.; Das, Sarit K.; Sundararajan, T.

2009-12-01

A new Quadratic Spline based Interface (QUASI) reconstruction algorithm is presented which provides an accurate and continuous representation of the interface in a multiphase domain and facilitates the direct estimation of local interfacial curvature. The fluid interface in each of the mixed cells is represented by piecewise parabolic curves and an initial discontinuous PLIC approximation of the interface is progressively converted into a smooth quadratic spline made of these parabolic curves. The conversion is achieved by a sequence of predictor-corrector operations enforcing function ( C0) and derivative ( C1) continuity at the cell boundaries using simple analytical expressions for the continuity requirements. The efficacy and accuracy of the current algorithm has been demonstrated using standard test cases involving reconstruction of known static interface shapes and dynamically evolving interfaces in prescribed flow situations. These benchmark studies illustrate that the present algorithm performs excellently as compared to the other interface reconstruction methods available in literature. Quadratic rate of error reduction with respect to grid size has been observed in all the cases with curved interface shapes; only in situations where the interface geometry is primarily flat, the rate of convergence becomes linear with the mesh size. The flow algorithm implemented in the current work is designed to accurately balance the pressure gradients with the surface tension force at any location. As a consequence, it is able to minimize spurious flow currents arising from imperfect normal stress balance at the interface. This has been demonstrated through the standard test problem of an inviscid droplet placed in a quiescent medium. Finally, the direct curvature estimation ability of the current algorithm is illustrated through the coupled multiphase flow problem of a deformable air bubble rising through a column of water.

5. Scattering Properties of Jovian Tropospheric Cloud Particles Inferred from Cassini/ISS: Mie Scattering Phase Function and Particle Size in South Tropical Zone III

Sato, T.; Satoh, T.; Kasaba, Y.

2010-12-01

The three distinct cloud layers were predicted by an equilibrium cloud condensation model (ECCM) of Jupiter. An ammonia ice cloud (NH3), an ammonia hydrosulfide cloud (NH4SH), and a water ice (H2O) cloud would be based at altitudes corresponding to pressures of about 0.7, 2.2 and 6 bars, respectively. However, there are significant gaps in our knowledge of the vertical cloud structure, despite the continuing effort by numerous ground-based, space-based, and in-situ observations and theory. Methane (CH4) is considered that its altitude distribution is globally uniform because it does not condense in Jovian atmosphere. Therefore, it is possible to derive the vertical cloud structure and the optical properties of clouds (i.e., optical thickness and single scattering albedo) by observing reflected sunlight in CH4 bands (727, 890 nm) and continuum in visible to near-infrared spectral ranges. Since we need to consider multiple scattering by clouds, it is essential to know scattering properties (e.g., scattering phase function) of clouds for determination of vertical cloud structure. However, we cannot derive those from ground-based and Earth-orbit observations because of the limitation of solar phase angle as viewed from the Earth. Then, most previous studies have used the scattering phase function deduced from the Pioneer 10/IPP data (blue: 440 nm, red: 640nm) [Tomasko et al., 1978]. There are two shortcomings in the Pioneer scattering phase function. One is that we have to use this scattering phase function at red as a substitute for analyses of imaging photometry using CH4 bands (center: 727 and 890 nm), although clouds should have wavelength dependency. The other is that the red pass band of IPP was so broad (595-720 nm) that this scattering phase function in red just show wavelength-averaged scattering properties of clouds. To provide a new reference scattering phase function with wavelength dependency, we have analyzed the Cassini/ISS data in BL1 (451 nm), CB1 (619

6. Gene-network inference by message passing

Braunstein, A.; Pagnani, A.; Weigt, M.; Zecchina, R.

2008-01-01

The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.

7. Mental state inference using visual control parameters.

PubMed

Oztop, Erhan; Wolpert, Daniel; Kawato, Mitsuo

2005-02-01

Although we can often infer the mental states of others by observing their actions, there are currently no computational models of this remarkable ability. Here we develop a computational model of mental state inference that builds upon a generic visuomanual feedback controller, and implements mental simulation and mental state inference functions using circuitry that subserves sensorimotor control. Our goal is (1) to show that control mechanisms developed for manual manipulation are readily endowed with visual and predictive processing capabilities and thus allows a natural extension to the understanding of movements performed by others; and (2) to give an explanation on how cortical regions, in particular the parietal and premotor cortices, may be involved in such dual mechanism. To analyze the model, we simulate tasks in which an observer watches an actor performing either a reaching or a grasping movement. The observer's goal is to estimate the 'mental state' of the actor: the goal of the reaching movement or the intention of the agent performing the grasping movement. We show that the motor modules of the observer can be used in a 'simulation mode' to infer the mental state of the actor. The simulations with different grasping and non-straight line reaching strategies show that the mental state inference model is applicable to complex movements. Moreover, we simulate deceptive reaching, where an actor imposes false beliefs about his own mental state on an observer. The simulations show that computational elements developed for sensorimotor control are effective in inferring the mental states of others. The parallels between the model and cortical organization of movement suggest that primates might have developed a similar resource utilization strategy for action understanding, and thus lead to testable predictions about the brain mechanisms of mental state inference. PMID:15653289

8. Functional interactions between OCA2 and the protein complexes BLOC-1, BLOC-2, and AP-3 inferred from epistatic analyses of mouse coat pigmentation.

PubMed

Hoyle, Diego J; Rodriguez-Fernandez, Imilce A; Dell'angelica, Esteban C

2011-04-01

The biogenesis of melanosomes is a multistage process that requires the function of cell-type-specific and ubiquitously expressed proteins. OCA2, the product of the gene defective in oculocutaneous albinism type 2, is a melanosomal membrane protein with restricted expression pattern and a potential role in the trafficking of other proteins to melanosomes. The ubiquitous protein complexes AP-3, BLOC-1, and BLOC-2, which contain as subunits the products of genes defective in various types of Hermansky-Pudlak syndrome, have been likewise implicated in trafficking to melanosomes. We have tested for genetic interactions between mutant alleles causing deficiency in OCA2 (pink-eyed dilution unstable), AP-3 (pearl), BLOC-1 (pallid), and BLOC-2 (cocoa) in C57BL/6J mice. The pallid allele was epistatic to pink-eyed dilution, and the latter behaved as a semi-dominant phenotypic enhancer of cocoa and, to a lesser extent, of pearl. These observations suggest functional links between OCA2 and these three protein complexes involved in melanosome biogenesis. PMID:21392365

9. Visual Inference Programming

NASA Technical Reports Server (NTRS)

Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter

2002-01-01

The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

10. THE ABUNDANCES OF HYDROCARBON FUNCTIONAL GROUPS IN THE INTERSTELLAR MEDIUM INFERRED FROM LABORATORY SPECTRA OF HYDROGENATED AND METHYLATED POLYCYCLIC AROMATIC HYDROCARBONS

SciTech Connect

Steglich, M.; Jäger, C.; Huisken, F.; Friedrich, M.; Plass, W.; Räder, H.-J.; Müllen, K.; Henning, Th.

2013-10-01

Infrared (IR) absorption spectra of individual polycyclic aromatic hydrocarbons (PAHs) containing methyl (-CH{sub 3}), methylene (CH{sub 2}), or diamond-like CH groups and IR spectra of mixtures of methylated and hydrogenated PAHs prepared by gas-phase condensation were measured at room temperature (as grains in pellets) and at low temperature (isolated in Ne matrices). In addition, the PAH blends were subjected to an in-depth molecular structure analysis by means of high-performance liquid chromatography, nuclear magnetic resonance spectroscopy, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Supported by calculations at the density functional theory level, the laboratory results were applied to analyze in detail the aliphatic absorption complex of the diffuse interstellar medium at 3.4 μm and to determine the abundances of hydrocarbon functional groups. Assuming that the PAHs are mainly locked in grains, aliphatic CH {sub x} groups (x = 1, 2, 3) would contribute approximately in equal quantities to the 3.4 μm feature (N {sub CHx}/N {sub H} ≈ 10{sup –5}-2 × 10{sup –5}). The abundances, however, may be two to four times lower if a major contribution to the 3.4 μm feature comes from molecules in the gas phase. Aromatic ≅CH groups seem to be almost absent from some lines of sight, but can be nearly as abundant as each of the aliphatic components in other directions (N{sub ≅CH}/N {sub H} ∼< 2 × 10{sup –5}; upper value for grains). Due to comparatively low binding energies, astronomical IR emission sources do not display such heavy excess hydrogenation. At best, especially in protoplanetary nebulae, CH{sub 2} groups bound to aromatic molecules, i.e., excess hydrogens on the molecular periphery only, can survive the presence of a nearby star.

11. Source mechanism of long-period events at Kusatsu-Shirane Volcano, Japan, inferred from waveform inversion of the effective excitation functions

USGS Publications Warehouse

Nakano, M.; Kumagai, H.; Chouet, B.A.

2003-01-01

We investigate the source mechanism of long-period (LP) events observed at Kusatsu-Shirane Volcano, Japan, based on waveform inversions of their effective excitation functions. The effective excitation function, which represents the apparent excitation observed at individual receivers, is estimated by applying an autoregressive filter to the LP waveform. Assuming a point source, we apply this method to seven LP events the waveforms of which are characterized by simple decaying and nearly monochromatic oscillations with frequency in the range 1-3 Hz. The results of the waveform inversions show dominant volumetric change components accompanied by single force components, common to all the events analyzed, and suggesting a repeated activation of a sub-horizontal crack located 300 m beneath the summit crater lakes. Based on these results, we propose a model of the source process of LP seismicity, in which a gradual buildup of steam pressure in a hydrothermal crack in response to magmatic heat causes repeated discharges of steam from the crack. The rapid discharge of fluid causes the collapse of the fluid-filled crack and excites acoustic oscillations of the crack, which produce the characteristic waveforms observed in the LP events. The presence of a single force synchronous with the collapse of the crack is interpreted as the release of gravitational energy that occurs as the slug of steam ejected from the crack ascends toward the surface and is replaced by cooler water flowing downward in a fluid-filled conduit linking the crack and the base of the crater lake. ?? 2003 Elsevier Science B.V. All rights reserved.

12. Parameter inference with estimated covariance matrices

Sellentin, Elena; Heavens, Alan F.

2016-02-01

When inferring parameters from a Gaussian-distributed data set by computing a likelihood, a covariance matrix is needed that describes the data errors and their correlations. If the covariance matrix is not known a priori, it may be estimated and thereby becomes a random object with some intrinsic uncertainty itself. We show how to infer parameters in the presence of such an estimated covariance matrix, by marginalizing over the true covariance matrix, conditioned on its estimated value. This leads to a likelihood function that is no longer Gaussian, but rather an adapted version of a multivariate t-distribution, which has the same numerical complexity as the multivariate Gaussian. As expected, marginalization over the true covariance matrix improves inference when compared with Hartlap et al.'s method, which uses an unbiased estimate of the inverse covariance matrix but still assumes that the likelihood is Gaussian.

13. Single board system for fuzzy inference

NASA Technical Reports Server (NTRS)

Symon, James R.; Watanabe, Hiroyuki

1991-01-01

The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.

14. Deep Learning for Population Genetic Inference

PubMed Central

Sheehan, Sara; Song, Yun S.

2016-01-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

15. Computationally efficient Bayesian inference for inverse problems.

SciTech Connect

Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.

2007-10-01

Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.

16. Deep Learning for Population Genetic Inference.

PubMed

Sheehan, Sara; Song, Yun S

2016-03-01

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

17. Circular inferences in schizophrenia.

PubMed

Jardri, Renaud; Denève, Sophie

2013-11-01

A considerable number of recent experimental and computational studies suggest that subtle impairments of excitatory to inhibitory balance or regulation are involved in many neurological and psychiatric conditions. The current paper aims to relate, specifically and quantitatively, excitatory to inhibitory imbalance with psychotic symptoms in schizophrenia. Considering that the brain constructs hierarchical causal models of the external world, we show that the failure to maintain the excitatory to inhibitory balance results in hallucinations as well as in the formation and subsequent consolidation of delusional beliefs. Indeed, the consequence of excitatory to inhibitory imbalance in a hierarchical neural network is equated to a pathological form of causal inference called 'circular belief propagation'. In circular belief propagation, bottom-up sensory information and top-down predictions are reverberated, i.e. prior beliefs are misinterpreted as sensory observations and vice versa. As a result, these predictions are counted multiple times. Circular inference explains the emergence of erroneous percepts, the patient's overconfidence when facing probabilistic choices, the learning of 'unshakable' causal relationships between unrelated events and a paradoxical immunity to perceptual illusions, which are all known to be associated with schizophrenia. PMID:24065721

18. Moment inference from tomograms

USGS Publications Warehouse

Day-Lewis, F. D.; Chen, Y.; Singha, K.

2007-01-01

Time-lapse geophysical tomography can provide valuable qualitative insights into hydrologic transport phenomena associated with aquifer dynamics, tracer experiments, and engineered remediation. Increasingly, tomograms are used to infer the spatial and/or temporal moments of solute plumes; these moments provide quantitative information about transport processes (e.g., advection, dispersion, and rate-limited mass transfer) and controlling parameters (e.g., permeability, dispersivity, and rate coefficients). The reliability of moments calculated from tomograms is, however, poorly understood because classic approaches to image appraisal (e.g., the model resolution matrix) are not directly applicable to moment inference. Here, we present a semi-analytical approach to construct a moment resolution matrix based on (1) the classic model resolution matrix and (2) image reconstruction from orthogonal moments. Numerical results for radar and electrical-resistivity imaging of solute plumes demonstrate that moment values calculated from tomograms depend strongly on plume location within the tomogram, survey geometry, regularization criteria, and measurement error. Copyright 2007 by the American Geophysical Union.

19. AESOP: An interactive computer program for the design of linear quadratic regulators and Kalman filters

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Geyser, L. C.

1984-01-01

AESOP is a computer program for use in designing feedback controls and state estimators for linear multivariable systems. AESOP is meant to be used in an interactive manner. Each design task that the program performs is assigned a "function" number. The user accesses these functions either (1) by inputting a list of desired function numbers or (2) by inputting a single function number. In the latter case the choice of the function will in general depend on the results obtained by the previously executed function. The most important of the AESOP functions are those that design,linear quadratic regulators and Kalman filters. The user interacts with the program when using these design functions by inputting design weighting parameters and by viewing graphic displays of designed system responses. Supporting functions are provided that obtain system transient and frequency responses, transfer functions, and covariance matrices. The program can also compute open-loop system information such as stability (eigenvalues), eigenvectors, controllability, and observability. The program is written in ANSI-66 FORTRAN for use on an IBM 3033 using TSS 370. Descriptions of all subroutines and results of two test cases are included in the appendixes.

20. Design of a functional calcium channel protein: inferences about an ion channel-forming motif derived from the primary structure of voltage-gated calcium channels.

PubMed Central

Grove, A.; Tomich, J. M.; Iwamoto, T.; Montal, M.

1993-01-01

To identify sequence-specific motifs associated with the formation of an ionic pore, we systematically evaluated the channel-forming activity of synthetic peptides with sequence of predicted transmembrane segments of the voltage-gated calcium channel. The amino acid sequence of voltage-gated, dihydropyridine (DHP)-sensitive calcium channels suggests the presence in each of four homologous repeats (I-IV) of six segments (S1-S6) predicted to form membrane-spanning, alpha-helical structures. Only peptides representing amphipathic segments S2 or S3 form channels in lipid bilayers. To generate a functional calcium channel based on a four-helix bundle motif, four-helix bundle proteins representing IVS2 (T4CaIVS2) or IVS3 (T4CaIVS3) were synthesized. Both proteins form cation-selective channels, but with distinct characteristics: the single-channel conductance in 50 mM BaCl2 is 3 pS and 10 pS. For T4CaIVS3, the conductance saturates with increasing concentration of divalent cation. The dissociation constants for Ba2+, Ca2+, and Sr2+ are 13.6 mM, 17.7 mM, and 15.0 mM, respectively. The conductance of T4CaIVS2 does not saturate up to 150 mM salt. Whereas T4CaIVS3 is blocked by microM Ca2+ and Cd2+, T4CaIVS2 is not blocked by divalent cations. Only T4CaIVS3 is modulated by enantiomers of the DHP derivative BayK 8644, demonstrating sequence requirement for specific drug action. Thus, only T4CaIVS3 exhibits pore properties characteristic also of authentic calcium channels. The designed functional calcium channel may provide insights into fundamental mechanisms of ionic permeation and drug action, information that may in turn further our understanding of molecular determinants underlying authentic pore structures. PMID:7505682

1. The Abundances of Hydrocarbon Functional Groups in the Interstellar Medium Inferred from Laboratory Spectra of Hydrogenated and Methylated Polycyclic Aromatic Hydrocarbons

Steglich, M.; Jäger, C.; Huisken, F.; Friedrich, M.; Plass, W.; Räder, H.-J.; Müllen, K.; Henning, Th.

2013-10-01

Infrared (IR) absorption spectra of individual polycyclic aromatic hydrocarbons (PAHs) containing methyl (\\sbondCH3), methylene (\\protect{\\epsfbox{art/apjs484229un01.eps}}CH2), or diamond-like \\protect{\\epsfbox{art/apjs484229un02.eps}}CH groups and IR spectra of mixtures of methylated and hydrogenated PAHs prepared by gas-phase condensation were measured at room temperature (as grains in pellets) and at low temperature (isolated in Ne matrices). In addition, the PAH blends were subjected to an in-depth molecular structure analysis by means of high-performance liquid chromatography, nuclear magnetic resonance spectroscopy, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Supported by calculations at the density functional theory level, the laboratory results were applied to analyze in detail the aliphatic absorption complex of the diffuse interstellar medium at 3.4 μm and to determine the abundances of hydrocarbon functional groups. Assuming that the PAHs are mainly locked in grains, aliphatic CH x groups (x = 1, 2, 3) would contribute approximately in equal quantities to the 3.4 μm feature (N CHx /N H ≈ 10-5-2 × 10-5). The abundances, however, may be two to four times lower if a major contribution to the 3.4 μm feature comes from molecules in the gas phase. Aromatic \\epsfbox{art/apjs484229un03.eps} CH groups seem to be almost absent from some lines of sight, but can be nearly as abundant as each of the aliphatic components in other directions (N_{\\epsfbox{art/apjs484229un03.eps} CH}/N H lsim 2 × 10-5 upper value for grains). Due to comparatively low binding energies, astronomical IR emission sources do not display such heavy excess hydrogenation. At best, especially in protoplanetary nebulae, \\protect{\\epsfbox{art/apjs484229un01.eps}}CH2 groups bound to aromatic molecules, i.e., excess hydrogens on the molecular periphery only, can survive the presence of a nearby star.

2. Armored geckos: A histological investigation of osteoderm development in Tarentola (Phyllodactylidae) and Gekko (Gekkonidae) with comments on their regeneration and inferred function.

PubMed

Vickaryous, M K; Meldrum, G; Russell, A P

2015-11-01

Osteoderms are bone-rich organs found in the dermis of many scleroglossan lizards sensu lato, but are only known for two genera of gekkotans (geckos): Tarentola and Gekko. Here, we investigate their sequence of appearance, mode of development, structural diversity and ability to regenerate following tail loss. Osteoderms were present in all species of Tarentola sampled (Tarentola annularis, T. mauritanica, T. americana, T. crombei, T. chazaliae) as well as Gekko gecko, but not G. smithii. Gekkotan osteoderms first appear within the integument dorsal to the frontal bone or within the supraocular scales. They then manifest as mineralized structures in other positions across the head. In Tarentola and G. gecko, discontinuous clusters subsequently form dorsal to the pelvis/base of the tail, and then dorsal to the pectoral apparatus. Gekkotan osteoderm formation begins once the dermis is fully formed. Early bone deposition appears to involve populations of fibroblast-like cells, which are gradually replaced by more rounded osteoblasts. In T. annularis and T. mauritanica, an additional skeletal tissue is deposited across the superficial surface of the osteoderm. This tissue is vitreous, avascular, cell-poor, lacks intrinsic collagen, and is herein identified as osteodermine. We also report that following tail loss, both T. annularis and T. mauritanica are capable of regenerating osteoderms, including osteodermine, in the regenerated part of the tail. We propose that osteoderms serve roles in defense against combative prey and intraspecific aggression, along with anti-predation functions. PMID:26248595

3. Analysis of electroperforated materials using the quadrat counts method

Miranda, E.; Garzón, C.; Martínez-Cisneros, C.; Alonso, J.; García-García, J.

2011-06-01

The electroperforation distribution in thin porous materials is investigated using the quadrat counts method (QCM), a classical statistical technique aimed to evaluate the deviation from complete spatial randomness (CSR). Perforations are created by means of electrical discharges generated by needle-like tungsten electrodes. The objective of perforating a thin porous material is to enhance its air permeability, a critical issue in many industrial applications involving paper, plastics, textiles, etc. Using image analysis techniques and specialized statistical software it is shown that the perforation locations follow, beyond a certain length scale, a homogeneous 2D Poisson distribution.

4. Reaction Wheel Control Design Using Linear Quadratic Controller

Nubli Muhamad, Nur; Susanto, Erwin; Syihabuddin, Budi; Prasetya Dwi Wibawa, Ig.

2016-01-01

This paper studies the design of active attitude control system of a nanosatellite in a single axis. In this paper, we consider dc motor based reaction wheel as an actuator, because of its pointing accuracy. However, the power consumption of the dc motor is often relatively large and needed to be optimized. Linear quadratic controller is supposed to have an ability to minimize power consumption and able to enhance the system performance. To show the advantage of this method, simulation result of attitude response, state trajectory, and trajectory of DC motor voltage are presented.

5. Rigorous performance bounds for quadratic and nested dynamical decoupling

SciTech Connect

Xia, Yuhou; Uhrig, Goetz S.; Lidar, Daniel A.

2011-12-15

We present rigorous performance bounds for the quadratic dynamical decoupling pulse sequence which protects a qubit from general decoherence, and for its nested generalization to an arbitrary number of qubits. Our bounds apply under the assumptions of instantaneous pulses and of bounded perturbing environment and qubit-environment Hamiltonians such as those realized by baths of nuclear spins in quantum dots. We prove that if the total sequence time is fixed then the trace-norm distance between the unperturbed and protected system states can be made arbitrarily small by increasing the number of applied pulses.

6. Frontogenesis driven by horizontally quadratic distributions of density

NASA Technical Reports Server (NTRS)

Jacqmin, David

1991-01-01

Attention is given to the quadratic density distribution in a channel, which has been established by Simpson and Linden to be the simplest case of the horizontally nonlinear distribution of fluid density required for the production of frontogenesis. The porous-media and Boussinesq flow models are examined, and their evolution equations are reduced to one-dimensional systems. While both the porous-media and the inviscid/nondiffusive Boussinesq systems exhibit classic frontogenesis behavior, the viscous Boussinesq system exhibits a more complex behavior: boundary-layer effects force frontogenesis away from the lower boundary, and at late times the steepest density gradients are close to mid-channel.

7. Nios II hardware acceleration of the epsilon quadratic sieve algorithm

Meyer-Bäse, Uwe; Botella, Guillermo; Castillo, Encarnacion; García, Antonio

2010-04-01

The quadratic sieve (QS) algorithm is one of the most powerful algorithms to factor large composite primes used to break RSA cryptographic systems. The hardware structure of the QS algorithm seems to be a good fit for FPGA acceleration. Our new ɛ-QS algorithm further simplifies the hardware architecture making it an even better candidate for C2H acceleration. This paper shows our design results in FPGA resource and performance when implementing very long arithmetic on the Nios microprocessor platform with C2H acceleration for different libraries (GMP, LIP, FLINT, NRMP) and QS architecture choices for factoring 32-2048 bit RSA numbers.

De Maesschalck, P.; Rebollo-Perdomo, S.; Torregrosa, J.

2015-01-01

This paper concerns the study of small-amplitude limit cycles that appear in the phase portrait near an unfolded fake saddle singularity. This degenerate singularity is also known as an impassable grain. The canonical form of the unperturbed vector field is like a degenerate flow box. Near the singularity, the phase portrait consists of parallel fibers, all but one of which have no singular points, and at the singular fiber, there is one node. We demonstrate different techniques in order to show that the cyclicity is bigger than or equal to two when the canonical form is quadratic.

9. On a quadratic transformation due to Kummer and its generalizations

Shekhawat, Nidhi; Rathie, Arjun K.; Prakash, Om

2016-05-01

The aim of this paper is to obtain explicit expressions of (1-x ) -a2F1[a ,b 2 b +j ; -2/x 1 -x ] for j = 0, ±1,…, ±9. For j = 0, we have a well-known quadratic transformations formula of Kummer. The results are obtained by using the known hypergeometric identities available in the literature. Several known results obtained earlier by Kim, et al. follow special cases of our main findings. The results derived in this paper are simple, interesting and potentially useful in the applicable sciences.

NASA Technical Reports Server (NTRS)

Dehoff, R. L.; Hall, W. E., Jr.

1978-01-01

A digital controller for an advanced turbofan engine utilizing multivariate feedback is described. The theoretical background of locally linearized control synthesis is reviewed briefly. The application of linear quadratic regulator techniques to the practical control problem is presented. The design procedure has been applied to the F100 turbofan engine, and details of the structure of this system are explained. Selected results from simulations of the engine and controller are utilized to illustrate the operation of the system. It is shown that the general multivariable design procedure will produce practical and implementable controllers for modern, high-performance turbine engines.

11. Approximation theory for LQG (Linear-Quadratic-Gaussian) optimal control of flexible structures

NASA Technical Reports Server (NTRS)

1988-01-01

An approximation theory is presented for the LQG (Linear-Quadratic-Gaussian) optimal control problem for flexible structures whose distributed models have bounded input and output operators. The main purpose of the theory is to guide the design of finite dimensional compensators that approximate closely the optimal compensator. The optimal LQG problem separates into an optimal linear-quadratic regulator problem and an optimal state estimation problem. The solution of the former problem lies in the solution to an infinite dimensional Riccati operator equation. The approximation scheme approximates the infinite dimensional LQG problem with a sequence of finite dimensional LQG problems defined for a sequence of finite dimensional, usually finite element or modal, approximations of the distributed model of the structure. Two Riccati matrix equations determine the solution to each approximating problem. The finite dimensional equations for numerical approximation are developed, including formulas for converting matrix control and estimator gains to their functional representation to allow comparison of gains based on different orders of approximation. Convergence of the approximating control and estimator gains and of the corresponding finite dimensional compensators is studied. Also, convergence and stability of the closed-loop systems produced with the finite dimensional compensators are discussed. The convergence theory is based on the convergence of the solutions of the finite dimensional Riccati equations to the solutions of the infinite dimensional Riccati equations. A numerical example with a flexible beam, a rotating rigid body, and a lumped mass is given.

12. Quadratic programming-based approach for autonomous vehicle path planning in space

Chen, Yang; Han, Jianda; Wu, Huaiyu

2012-07-01

Path planning for space vehicles is still a challenging problem although considerable progress has been made over the past decades. The major difficulties are that most of existing methods only adapt to static environment instead of dynamic one, and also can not solve the inherent constraints arising from the robot body and the exterior environment. To address these difficulties, this research aims to provide a feasible trajectory based on quadratic programming(QP) for path planning in three-dimensional space where an autonomous vehicle is requested to pursue a target while avoiding static or dynamic obstacles. First, the objective function is derived from the pursuit task which is defined in terms of the relative distance to the target, as well as the angle between the velocity and the position in the relative velocity coordinates(RVCs). The optimization is in quadratic polynomial form according to QP formulation. Then, the avoidance task is modeled with linear constraints in RVCs. Some other constraints, such as kinematics, dynamics, and sensor range, are included. Last, simulations with typical multiple obstacles are carried out, including in static and dynamic environments and one of human-in-the-loop. The results indicate that the optimal trajectories of the autonomous robot in three-dimensional space satisfy the required performances. Therefore, the QP model proposed in this paper not only adapts to dynamic environment with uncertainty, but also can satisfy all kinds of constraints, and it provides an efficient approach to solve the problems of path planning in three-dimensional space.

13. A reduced successive quadratic programming strategy for errors-in-variables estimation.

SciTech Connect

Tjoa, I.-B.; Biegler, L. T.; Carnegie-Mellon Univ.

1992-01-01

Parameter estimation problems in process engineering represent a special class of nonlinear optimization problems, because the maximum likelihood structure of the objective function can be exploited. Within this class, the errors in variables method (EVM) is particularly interesting. Here we seek a weighted least-squares fit to the measurements with an underdetermined process model. Thus, both the number of variables and degrees of freedom available for optimization increase linearly with the number of data sets. Large optimization problems of this type can be particularly challenging and expensive to solve because, for general-purpose nonlinear programming (NLP) algorithms, the computational effort increases at least quadratically with problem size. In this study we develop a tailored NLP strategy for EVM problems. The method is based on a reduced Hessian approach to successive quadratic programming (SQP), but with the decomposition performed separately for each data set. This leads to the elimination of all variables but the model parameters, which are determined by a QP coordination step. In this way the computational effort remains linear in the number of data sets. Moreover, unlike previous approaches to the EVM problem, global and superlinear properties of the SQP algorithm apply naturally. Also, the method directly incorporates inequality constraints on the model parameters (although not on the fitted variables). This approach is demonstrated on five example problems with up to 102 degrees of freedom. Compared to general-purpose NLP algorithms, large improvements in computational performance are observed.

14. Formalism for the solution of quadratic Hamiltonians with large cosine terms

Ganeshan, Sriram; Levin, Michael

2016-02-01

We consider quantum Hamiltonians of the form H =H0-U ∑jcos(Cj) , where H0 is a quadratic function of position and momentum variables {x1,p1,x2,p2,⋯} and the Cj's are linear in these variables. We allow H0 and Cj to be completely general with only two restrictions: we require that (1) the Cj's are linearly independent and (2) [Cj,Ck] is an integer multiple of 2 π i for all j ,k so that the different cosine terms commute with one another. Our main result is a recipe for solving these Hamiltonians and obtaining their exact low-energy spectrum in the limit U →∞ . This recipe involves constructing creation and annihilation operators and is similar in spirit to the procedure for diagonalizing quadratic Hamiltonians. In addition to our exact solution in the infinite U limit, we also discuss how to analyze these systems when U is large but finite. Our results are relevant to a number of different physical systems, but one of the most natural applications is to understanding the effects of electron scattering on quantum Hall edge modes. To demonstrate this application, we use our formalism to solve a toy model for a fractional quantum spin Hall edge with different types of impurities.

15. Can Change in Prolonged Walking Be Inferred From a Short Test of Gait Speed Among Older Adults Who Are Initially Well-Functioning?

PubMed Central

Neogi, Tuhina; King, Wendy C.; LaValley, Michael P.; Kritchevsky, Stephen B.; Nevitt, Michael C.; Harris, Tamara B.; Ferrucci, Luigi; Simonsick, Eleanor M.; Satterfield, Suzanne; Strotmeyer, Elsa S.; Zhang, Yuqing

2014-01-01

Background The ability to walk for short and prolonged periods of time is often measured with separate walking tests. It is unclear whether decline in the 2-minute walk coincides with decline in a shorter 20-m walk among older adults. Objective The aim of this study was to describe patterns of change in the 20-m walk and 2-minute walk over 8 years among a large cohort of older adults. Should change be similar between tests of walking ability, separate retesting of prolonged walking may need to be reconsidered. Design A longitudinal, observational cohort study was conducted. Methods Data were from 1,893 older adults who were well-functioning (≥70 years of age). The 20-m walk and 2-minute walk were repeatedly measured over 8 years to measure change during short and prolonged periods of walking, respectively. Change was examined using a dual group-based trajectory model (dual model), and agreement between walking trajectories was quantified with a weighted kappa statistic. Results Three trajectory groups for the 20-m walk and 2-minute walk were identified. More than 86% of the participants were in similar trajectory groups for both tests from the dual model. There was high chance-corrected agreement (kappa=.84; 95% confidence interval=.82, .86) between the 20-m walk and 2-minute walk trajectory groups. Limitations One-third of the original Health, Aging and Body Composition (Health ABC) study cohort was excluded from analysis due to missing clinic visits, followed by being excluded for health reasons for performing the 2-minute walk, limiting generalizability to healthy older adults. Conclusions Patterns of change in the 2-minute walk are similar to those in the 20-m walk. Thus, separate retesting of the 2-minute walk may need to be reconsidered to gauge change in prolonged walking. PMID:24786943

16. On the necessity of dissecting sequence similarity scores into segment-specific contributions for inferring protein homology, function prediction and annotation

PubMed Central

2014-01-01

Background Protein sequence similarities to any types of non-globular segments (coiled coils, low complexity regions, transmembrane regions, long loops, etc. where either positional sequence conservation is the result of a very simple, physically induced pattern or rather integral sequence properties are critical) are pertinent sources for mistaken homologies. Regretfully, these considerations regularly escape attention in large-scale annotation studies since, often, there is no substitute to manual handling of these cases. Quantitative criteria are required to suppress events of function annotation transfer as a result of false homology assignments. Results The sequence homology concept is based on the similarity comparison between the structural elements, the basic building blocks for conferring the overall fold of a protein. We propose to dissect the total similarity score into fold-critical and other, remaining contributions and suggest that, for a valid homology statement, the fold-relevant score contribution should at least be significant on its own. As part of the article, we provide the DissectHMMER software program for dissecting HMMER2/3 scores into segment-specific contributions. We show that DissectHMMER reproduces HMMER2/3 scores with sufficient accuracy and that it is useful in automated decisions about homology for instructive sequence examples. To generalize the dissection concept for cases without 3D structural information, we find that a dissection based on alignment quality is an appropriate surrogate. The approach was applied to a large-scale study of SMART and PFAM domains in the space of seed sequences and in the space of UniProt/SwissProt. Conclusions Sequence similarity core dissection with regard to fold-critical and other contributions systematically suppresses false hits and, additionally, recovers previously obscured homology relationships such as the one between aquaporins and formate/nitrite transporters that, so far, was only

17. Estimating uncertainty of inference for validation

SciTech Connect

Booker, Jane M; Langenbrunner, James R; Hemez, Francois M; Ross, Timothy J

2010-09-30

We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the

18. Optimizing Non-Decomposable Loss Functions in Structured Prediction

PubMed Central

Ranjbar, Mani; Lan, Tian; Wang, Yang; Robinovitch, Steven N.; Li, Ze-Nian; Mori, Greg

2012-01-01

We develop an algorithm for structured prediction with non-decomposable performance measures. The algorithm learns parameters of Markov random fields and can be applied to multivariate performance measures. Examples include performance measures such as Fβ score (natural language processing), intersection over union (object category segmentation), Precision/Recall at k (search engines) and ROC area (binary classifiers). We attack this optimization problem by approximating the loss function with a piecewise linear function. The loss augmented inference forms a quadratic program (QP), which we solve using LP relaxation. We apply this approach to two tasks: object class-specific segmentation and human action retrieval from videos. We show significant improvement over baseline approaches that either use simple loss functions or simple scoring functions on the PASCAL VOC and H3D Segmentation datasets, and a nursing home action recognition dataset. PMID:22868650

19. Lie algebraic approach of a charged particle in presence of a constant magnetic field via the quadratic invariant

SciTech Connect

Abdalla, M. Sebawe; Elkasapy, A.I.

2010-08-15

In this paper we consider the problem of a charged harmonic oscillator under the influence of a constant magnetic field. The system is assumed to be isotropic and the magnetic field is applied along the z-axis. The canonical transformation is invoked to remove the interaction term and the system is reduced to a model containing the second harmonic generation. Two classes of the real and complex quadratic invariants (constants of motion) are obtained. We have employed the Lie algebraic technique to find the most general solution for the wave function for both real and complex invariants. Some discussions related to the advantage of using the quadratic invariants to solve the Cauchy problem instead of the direct use of the Hamiltonian itself are also given.

20. Modeling and performance analysis of the fractional order quadratic Boost converter in discontinuous conduction mode-discontinuous conduction mode

Tan, Cheng; Liang, Zhi-Shan

2016-03-01

In this paper, based on the fact that the inductors and capacitors are of fractional order in nature, the four-order mathematical model of the fractional order quadratic Boost converter in type I and type II discontinuous conduction mode (DCM) — DCM is established by using fractional calculus theory. Direct current (DC) analysis is conducted by using the DC equivalent model and the transfer functions are derived from the corresponding alternating current (AC) equivalent model. The DCM-DCM regions of type I and type II are obtained and the relations between the regions and the orders are found. The influence of the orders on the performance of the quadratic Boost converter in DCM-DCM is verified by numerical and circuit simulations. Simulation results demonstrate the correctness of the fractional order model and the efficiency of the proposed theoretical analysis.

1. BIE: Bayesian Inference Engine

Weinberg, Martin D.

2013-12-01

The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates heta distributed according to P( heta|D) so moments are trivially obtained by summing of the ensemble of variates.

2. Bayesian inference in geomagnetism

NASA Technical Reports Server (NTRS)

Backus, George E.

1988-01-01

The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.

3. Bayesian Inference of Tumor Hypoxia

Gunawan, R.; Tenti, G.; Sivaloganathan, S.

2009-12-01

automatically that the inference from the data could not be summarized by just two numbers, but the full posterior probability density function (pdf) had to be used.

4. An Instability Index Theory for Quadratic Pencils and Applications

Bronski, Jared; Johnson, Mathew A.; Kapitula, Todd

2014-04-01

Primarily motivated by the stability analysis of nonlinear waves in second-order in time Hamiltonian systems, in this paper we develop an instability index theory for quadratic operator pencils acting on a Hilbert space. In an extension of the known theory for linear pencils, explicit connections are made between the number of eigenvalues of a given quadratic operator pencil with positive real parts to spectral information about the individual operators comprising the coefficients of the spectral parameter in the pencil. As an application, we apply the general theory developed here to yield spectral and nonlinear stability/instability results for abstract second-order in time wave equations. More specifically, we consider the problem of the existence and stability of spatially periodic waves for the "good" Boussinesq equation. In the analysis our instability index theory provides an explicit, and somewhat surprising, connection between the stability of a given periodic traveling wave solution of the "good" Boussinesq equation and the stability of the same periodic profile, but with different wavespeed, in the nonlinear dynamics of a related generalized Korteweg-de Vries equation.

5. Sequential quadratic programming method for determining the minimum energy path.

PubMed

Burger, Steven K; Yang, Weitao

2007-10-28

A new method, referred to as the sequential quadratic programming method, is presented for determining minimum energy paths. The method is based on minimizing the points representing the path in the subspace perpendicular to the tangent of the path while using a penalty term to prevent kinks from forming. Rather than taking one full step, the minimization is divided into a number of sequential steps on an approximate quadratic surface. The resulting method can efficiently determine the reaction mechanism, from which transition state can be easily identified and refined with other methods. To improve the resolution of the path close to the transition state, points are clustered close to this region with a reparametrization scheme. The usefulness of the algorithm is demonstrated for the Muller-Brown potential, amide hydrolysis, and an 89 atom cluster taken from the active site of 4-oxalocrotonate tautomerase for the reaction which catalyzes 2-oxo-4-hexenedioate to the intermediate 2-hydroxy-2,4-hexadienedioate. PMID:17979319

6. Hidden and Nonstandard Bifurcation Diagram of an Alternate Quadratic System

Pastor, G.; Romera, M.; Danca, M.-F.; Martin, A.; Orue, A. B.; Montoya, F.; Encinas, L. Hernández

Alternate quadratic systems A : xn+1 = 1 - axn2,if n is even 1 - a∗xn2,if n is odd andB : xn+1 = 1 - a∗xn2,if n is even 1 - axn2, if n is odd, where a and a∗ are different parameters, seem to be interval maps in a range of the parameter values. However, after a careful graphical analysis of their bifurcation diagrams we conclude that this is true only for system B, but not for system A. In system A we find a hidden and nonstandard bifurcation diagram (“hidden” because it is not visible at normal resolution and “nonstandard” because the bifurcation diagram is empty for some ranges of the parameter values). The different behavior of the underlying critical polynomial in the range of parameter values in both alternate quadratic systems explains why the hidden and nonstandard bifurcation diagram is present in system A and not in system B. The analysis of the Lyapunov exponent also shows both the existence and the different behavior of the hidden bifurcation diagram of system A.

7. A formal model of interpersonal inference

PubMed Central

Moutoussis, Michael; Trujillo-Barreto, Nelson J.; El-Deredy, Wael; Dolan, Raymond J.; Friston, Karl J.

2014-01-01

Introduction: We propose that active Bayesian inference—a general framework for decision-making—can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory. Results: (1) Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to “mentalizing” in the psychological literature, is based upon the outcomes of interpersonal exchanges. (2) We show how some well-known social-psychological phenomena (e.g., self-serving biases) can be explained in terms of active interpersonal inference. (3) Mentalizing naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one's own qualities and preferences. Conclusion: We inaugurate a Bayes optimal framework for modeling intersubject variability in mentalizing during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalizing is distorted. PMID:24723872

8. Bayes factors and multimodel inference

USGS Publications Warehouse

2009-01-01

Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

9. On the cost of approximating and recognizing a noise perturbed straight line or a quadratic curve segment in the plane. [central processing units

NASA Technical Reports Server (NTRS)

Cooper, D. B.; Yalabik, N.

1975-01-01

Approximation of noisy data in the plane by straight lines or elliptic or single-branch hyperbolic curve segments arises in pattern recognition, data compaction, and other problems. The efficient search for and approximation of data by such curves were examined. Recursive least-squares linear curve-fitting was used, and ellipses and hyperbolas are parameterized as quadratic functions in x and y. The error minimized by the algorithm is interpreted, and central processing unit (CPU) times for estimating parameters for fitting straight lines and quadratic curves were determined and compared. CPU time for data search was also determined for the case of straight line fitting. Quadratic curve fitting is shown to require about six times as much CPU time as does straight line fitting, and curves relating CPU time and fitting error were determined for straight line fitting. Results are derived on early sequential determination of whether or not the underlying curve is a straight line.

10. Causal Inference and Explaining Away in a Spiking Network

PubMed Central

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

11. Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1979-01-01

Results are given on the relationships between closed loop eigenstructures, state feedback gain matrices of the linear state feedback problem, and quadratic weights of the linear quadratic regulator. Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used for the first time to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalues and the directional derivatives of closed loop eigenvectors (with respect to a scalar multiplying the feedback gain matrix or the quadratic control weight). An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, sufficient conditions to be in it are given, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties.

12. Causal Inference in Retrospective Studies.

ERIC Educational Resources Information Center

Holland, Paul W.; Rubin, Donald B.

1988-01-01

The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

13. Improving Inferences from Multiple Methods.

ERIC Educational Resources Information Center

Shotland, R. Lance; Mark, Melvin M.

1987-01-01

Multiple evaluation methods (MEMs) can cause an inferential challenge, although there are strategies to strengthen inferences. Practical and theoretical issues involved in the use by social scientists of MEMs, three potential problems in drawing inferences from MEMs, and short- and long-term strategies for alleviating these problems are outlined.…

14. Causal Inference and Developmental Psychology

ERIC Educational Resources Information Center

Foster, E. Michael

2010-01-01

Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

15. Learning to Observe "and" Infer

ERIC Educational Resources Information Center

Hanuscin, Deborah L.; Park Rogers, Meredith A.

2008-01-01

Researchers describe the need for students to have multiple opportunities and social interaction to learn about the differences between observation and inference and their role in developing scientific explanations (Harlen 2001; Simpson 2000). Helping children develop their skills of observation and inference in science while emphasizing the…

16. Social Inference Through Technology

Oulasvirta, Antti

Awareness cues are computer-mediated, real-time indicators of people’s undertakings, whereabouts, and intentions. Already in the mid-1970 s, UNIX users could use commands such as “finger” and “talk” to find out who was online and to chat. The small icons in instant messaging (IM) applications that indicate coconversants’ presence in the discussion space are the successors of “finger” output. Similar indicators can be found in online communities, media-sharing services, Internet relay chat (IRC), and location-based messaging applications. But presence and availability indicators are only the tip of the iceberg. Technological progress has enabled richer, more accurate, and more intimate indicators. For example, there are mobile services that allow friends to query and follow each other’s locations. Remote monitoring systems developed for health care allow relatives and doctors to assess the wellbeing of homebound patients (see, e.g., Tang and Venables 2000). But users also utilize cues that have not been deliberately designed for this purpose. For example, online gamers pay attention to other characters’ behavior to infer what the other players are like “in real life.” There is a common denominator underlying these examples: shared activities rely on the technology’s representation of the remote person. The other human being is not physically present but present only through a narrow technological channel.

17. Inference from aging information.

PubMed

de Oliveira, Evaldo Araujo; Caticha, Nestor

2010-06-01

For many learning tasks the duration of the data collection can be greater than the time scale for changes of the underlying data distribution. The question we ask is how to include the information that data are aging. Ad hoc methods to achieve this include the use of validity windows that prevent the learning machine from making inferences based on old data. This introduces the problem of how to define the size of validity windows. In this brief, a new adaptive Bayesian inspired algorithm is presented for learning drifting concepts. It uses the analogy of validity windows in an adaptive Bayesian way to incorporate changes in the data distribution over time. We apply a theoretical approach based on information geometry to the classification problem and measure its performance in simulations. The uncertainty about the appropriate size of the memory windows is dealt with in a Bayesian manner by integrating over the distribution of the adaptive window size. Thus, the posterior distribution of the weights may develop algebraic tails. The learning algorithm results from tracking the mean and variance of the posterior distribution of the weights. It was found that the algebraic tails of this posterior distribution give the learning algorithm the ability to cope with an evolving environment by permitting the escape from local traps. PMID:20421181

18. Optimal representation and processing of optical signals in quadratic-phase systems

Arık, Sercan Ö.; Ozaktas, Haldun M.

2016-05-01

Optical fields propagating through quadratic-phase systems (QPSs) can be modeled as magnified fractional Fourier transforms (FRTs) of the input field, provided we observe them on suitably defined spherical reference surfaces. Non-redundant representation of the fields with the minimum number of samples becomes possible by appropriate choice of sample points on these surfaces. Longitudinally, these surfaces should not be spaced equally with the distance of propagation, but with respect to the FRT order. The non-uniform sampling grid that emerges mirrors the fundamental structure of propagation through QPSs. By providing a means to effectively handle the sampling of chirp functions, it allows for accurate and efficient computation of optical fields propagating in QPSs.

19. Skyrmions with quadratic band touching fermions: A way to achieve charge 4e superconductivity

Moon, Eun-Gook

2012-06-01

We study Skyrmion quantum numbers, charge, and statistics, in (2+1) dimension induced by quadratic band touching (QBT) fermions. It is shown that induced charge of Skyrmions is twice bigger than corresponding Dirac particles’ and their statistics are always bosonic. Applying to the Bernal stacking bilayer graphene, we show that Skyrmions of quantum spin Hall are charge 4e bosons, so their condensation realizes charge 4e superconductivity. The phase transition could be of second order, and one candidate theory of the transition is an O(5) nonlinear sigma model with a nonzero Wess-Zumino-Witten term. We calculate the renormalization group beta function of the model perturbatively and propose a possible phase diagram. We also discuss how QBT fermions are different from two copies of Dirac particles.

20. Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

NASA Technical Reports Server (NTRS)

Milman, Mark H.

1987-01-01

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary systems. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

1. Quadratic resonance in the three-dimensional oscillations of inviscid drops with surface tension

NASA Technical Reports Server (NTRS)

Natarajan, R.; Brown, R. A.

1986-01-01

The moderate-amplitude, three-dimensional oscillations of an inviscid drop are described in terms of spherical harmonics. Specific oscillation modes are resonantly coupled by quadratic nonlinearities caused by inertia, capillarity, and drop deformation. The equations describing the interactions of these modes are derived from the variational principle for the appropriate Lagrangian by expressing the modal amplitudes to be functions of a slow time scale and by preaveraging the Lagrangian over the time scale of the primary oscillations. Stochastic motions are predicted for nonaxisymmetric deformations starting from most initial conditions, even those arbitrarily close to the axisymmetric shapes. The stochasticity is characterized by a redistribution of the energy contained in the initial deformation over all the degrees of freedom of the interacting modes.

2. Regions of attraction and ultimate boundedness for linear quadratic regulators with nonlinearities

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1984-01-01

The closed-loop stability of multivariable linear time-invariant systems controlled by optimal linear quadratic (LQ) regulators is investigated for the case when the feedback loops have nonlinearities N(sigma) that violate the standard stability condition, sigma N(sigma) or = 0.5 sigma(2). The violations of the condition are assumed to occur either (1) for values of sigma away from the origin (sigma = 0) or (2) for values of sigma in a neighborhood of the origin. It is proved that there exists a region of attraction for case (1) and a region of ultimate boundedness for case (2), and estimates are obtained for these regions. The results provide methods for selecting the performance function parameters to design LQ regulators with better tolerance to nonlinearities. The results are demonstrated by application to the problem of attitude and vibration control of a large, flexible space antenna in the presence of actuator nonlinearities.

3. Singular linear-quadratic control problem for systems with linear delay

SciTech Connect

Sesekin, A. N.

2013-12-18

A singular linear-quadratic optimization problem on the trajectories of non-autonomous linear differential equations with linear delay is considered. The peculiarity of this problem is the fact that this problem has no solution in the class of integrable controls. To ensure the existence of solutions is required to expand the class of controls including controls with impulse components. Dynamical systems with linear delay are used to describe the motion of pantograph from the current collector with electric traction, biology, etc. It should be noted that for practical problems fact singularity criterion of quality is quite commonly occurring, and therefore the study of these problems is surely important. For the problem under discussion optimal programming control contained impulse components at the initial and final moments of time is constructed under certain assumptions on the functional and the right side of the control system.

4. Spectral likelihood expansions for Bayesian inference

Nagel, Joseph B.; Sudret, Bruno

2016-03-01

A spectral approach to Bayesian inference is presented. It pursues the emulation of the posterior probability density. The starting point is a series expansion of the likelihood function in terms of orthogonal polynomials. From this spectral likelihood expansion all statistical quantities of interest can be calculated semi-analytically. The posterior is formally represented as the product of a reference density and a linear combination of polynomial basis functions. Both the model evidence and the posterior moments are related to the expansion coefficients. This formulation avoids Markov chain Monte Carlo simulation and allows one to make use of linear least squares instead. The pros and cons of spectral Bayesian inference are discussed and demonstrated on the basis of simple applications from classical statistics and inverse modeling.

5. Cosmology for quadratic gravity in generalized Weyl geometry

Beltrán Jiménez, Jose; Heisenberg, Lavinia; Koivisto, Tomi S.

2016-04-01

A class of vector-tensor theories arises naturally in the framework of quadratic gravity in spacetimes with linear vector distortion. Requiring the absence of ghosts for the vector field imposes an interesting condition on the allowed connections with vector distortion: the resulting one-parameter family of connections generalises the usual Weyl geometry with polar torsion. The cosmology of this class of theories is studied, focusing on isotropic solutions wherein the vector field is dominated by the temporal component. De Sitter attractors are found and inhomogeneous perturbations around such backgrounds are analysed. In particular, further constraints on the models are imposed by excluding pathologies in the scalar, vector and tensor fluctuations. Various exact background solutions are presented, describing a constant and an evolving dark energy, a bounce and a self-tuning de Sitter phase. However, the latter two scenarios are not viable under a closer scrutiny.

6. Absence of the Gribov ambiguity in a quadratic gauge

Raval, Haresh

2016-05-01

The Gribov ambiguity exists in various gauges. Algebraic gauges are likely to be ambiguity free. However, algebraic gauges are not Lorentz invariant, which is their fundamental flaw. In addition, they are not generally compatible with the boundary conditions on the gauge fields, which are needed to compactify the space i.e., the ambiguity continues to exist on a compact manifold. Here we discuss a quadratic gauge fixing, which is Lorentz invariant. We consider an example of a spherically symmetric gauge field configuration in which we prove that this Lorentz invariant gauge removes the ambiguity on a compact manifold S^3, when a proper boundary condition on the gauge configuration is taken into account. Thus, we provide one example where the ambiguity is absent on a compact manifold in the algebraic gauge. We also show that the BRST invariance is preserved in this gauge.

7. Wind turbine power tracking using an improved multimodel quadratic approach.

PubMed

2010-07-01

In this paper, an improved multimodel optimal quadratic control structure for variable speed, pitch regulated wind turbines (operating at high wind speeds) is proposed in order to integrate high levels of wind power to actively provide a primary reserve for frequency control. On the basis of the nonlinear model of the studied plant, and taking into account the wind speed fluctuations, and the electrical power variation, a multimodel linear description is derived for the wind turbine, and is used for the synthesis of an optimal control law involving a state feedback, an integral action and an output reference model. This new control structure allows a rapid transition of the wind turbine generated power between different desired set values. This electrical power tracking is ensured with a high-performance behavior for all other state variables: turbine and generator rotational speeds and mechanical shaft torque; and smooth and adequate evolution of the control variables. PMID:20434153

Azreg-Aïnou, Mustapha

2010-01-01

We develop and modify the Adomian decomposition method (ADecM) to work for a new type of nonlinear matrix differential equations (MDE's) which arise in general relativity (GR) and possibly in other applications. The approach consists in modifying both the ADecM linear operator with highest order derivative and ADecM polynomials. We specialize in the case of a 4 × 4 nonlinear MDE along with a scalar one describing stationary cylindrically symmetric metrics in quadratic five-dimensional GR, derive some of their properties using ADecM and construct the most general unique power series solutions. However, because of the constraint imposed on the MDE by the scalar one, the series solutions terminate in closed forms exhausting all possible solutions.

9. Quadratic Forms for the Fermionic Unitary Gas Model

Finco, Domenico; Teta, Alessandro

2012-04-01

We consider a quantum system in dimension three composed by a group of N identical fermions, with mass 1/2, interacting via zero-range interaction with a group of M identical fermions of a different type, with mass m/2. Exploiting a renormalization procedure, we construct the corresponding quadratic form and define the so-called Skornyakov-Ter-Martirosyan extension Hα, which is the natural candidate as a possible Hamiltonian of the system. It is shown that if the form is unbounded from below then Hα is not a self-adjoint and bounded from below operator, and this in particular suggests that the so-called Thomas effect could occur. In the special case N = 2, M = 1 we prove that this is in fact the case when a suitable condition on the parameter m is satisfied.

10. Quadratic Finite Element Method for 1D Deterministic Transport

SciTech Connect

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.

11. Recognition of Graphs with Convex Quadratic Stability Number

Pacheco, Maria F.; Cardoso, Domingos M.

2009-09-01

A stable set of a graph is a set of mutually non-adjacent vertices. The determination of a maximum size stable set, which is called maximum stable set, and the determination of its size, which is called stability number, are central combinatorial optimization problems. However, given a nonnegative integer k, to determine if a graph G has a stable set of size k is NP-complete. In this paper we deal with graphs for which the stability number can be determined by solving a convex quadratic programming problem. Such graphs were introduced in [13] and are called graphs with convex-QP stability number. A few algorithmic techniques for the recognition of this type of graphs in particular families are presented.

12. Motion corrected intracranial MRA using PROPELLER with RF quadratic encoding.

PubMed

Zwart, Nicholas R; Pipe, James G

2009-06-01

A new motion corrected Time-of-Flight MRA technique named Variable Pitch PROPELLER is presented. This technique employs the PROPELLER acquisition and reconstruction scheme for in-plane bulk motion correction. A non- Fourier through-plane encoding mechanism called quadratic encoding boosts SNR, relative to conventional 2D MRA, in lieu of traditional 3D encoding. Partial Fourier encoding is applied in the slice direction for a further reduction in scan time. This work details the construction and optimization of this technique. VPPROP MRAs are compared with a clinical MOTSA protocol. Initial results show promising robustness to bulk motion effects. The comparisons with MOTSA provide insight as to the additions required to create a comparable scan. PMID:19353668

13. Robust linear quadratic designs with respect to parameter uncertainty

NASA Technical Reports Server (NTRS)

Douglas, Joel; Athans, Michael

1992-01-01

The authors derive a linear quadratic regulator (LQR) which is robust to parametric uncertainty by using the overbounding method of I. R. Petersen and C. V. Hollot (1986). The resulting controller is determined from the solution of a single modified Riccati equation. It is shown that, when applied to a structural system, the controller gains add robustness by minimizing the potential energy of uncertain stiffness elements, and minimizing the rate of dissipation of energy through uncertain damping elements. A worst-case disturbance in the direction of the uncertainty is also considered. It is proved that performance robustness has been increased with the robust LQR when compared to a mismatched LQR design where the controller is designed on the nominal system, but applied to the actual uncertain system.

14. Schwarz and multilevel methods for quadratic spline collocation

SciTech Connect

Christara, C.C.; Smith, B.

1994-12-31

Smooth spline collocation methods offer an alternative to Galerkin finite element methods, as well as to Hermite spline collocation methods, for the solution of linear elliptic Partial Differential Equations (PDEs). Recently, optimal order of convergence spline collocation methods have been developed for certain degree splines. Convergence proofs for smooth spline collocation methods are generally more difficult than for Galerkin finite elements or Hermite spline collocation, and they require stronger assumptions and more restrictions. However, numerical tests indicate that spline collocation methods are applicable to a wider class of problems, than the analysis requires, and are very competitive to finite element methods, with respect to efficiency. The authors will discuss Schwarz and multilevel methods for the solution of elliptic PDEs using quadratic spline collocation, and compare these with domain decomposition methods using substructuring. Numerical tests on a variety of parallel machines will also be presented. In addition, preliminary convergence analysis using Schwarz and/or maximum principle techniques will be presented.

15. Dark state in a nonlinear optomechanical system with quadratic coupling

Huang, Yue-Xin; Zhou, Xiang-Fa; Guo, Guang-Can; Zhang, Yong-Sheng

We consider a hybrid system consisting of a cavity optomechanical device with nonlinear quadratic radiation pressure coupled to an atomic ensemble. By considering the collective excitation, we show that this system supports nontrivial, nonlinear dark states. The coupling strength can be tuned via the lasers that ensure the population transfer adiabatically between the mechanical modes and the collective atomic excitations in a controlled way. In addition, we show how to detect the dark-state resonance by calculating the single-photon spectrum of the output fields and the transmission of the probe beam based on two-phonon optomechanically induced transparency. Possible application and extension of the dark states are also discussed. Supported by the National Fundamental Research Program of China (Grants No. 2011CB921200 and No. 2011CBA00200), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB01030200), and NSFC (Grants No. 61275122 and 11474266).

SciTech Connect

Fowler, Jack F.

2009-04-01

Purpose: Radiobiologic modeling is increasingly used to estimate the effects of altered treatment plans, especially for dose escalation. The present article shows how much the linear-quadratic (LQ) (calculated biologically equivalent dose [BED] varies when individual parameters of the LQ formula are varied by {+-}20% and by 1%. Methods: Equivalent total doses (EQD2 = normalized total doses (NTD) in 2-Gy fractions for tumor control, acute mucosal reactions, and late complications were calculated using the linear- quadratic formula with overall time: BED = nd (1 + d/ [{alpha}/{beta}]) - log{sub e}2 (T - Tk) / {alpha}Tp, where BED is BED = total dose x relative effectiveness (RE = nd (1 + d/ [{alpha}/{beta}]). Each of the five biologic parameters in turn was altered by {+-}10%, and the altered EQD2s tabulated; the difference was finally divided by 20. EQD2 or NTD is obtained by dividing BED by the RE for 2-Gy fractions, using the appropriate {alpha}/{beta} ratio. Results: Variations in tumor and acute mucosal EQD ranged from 0.1% to 0.45% per 1% change in each parameter for conventional schedules, the largest variation being caused by overall time. Variations in 'late' EQD were 0.4% to 0.6% per 1% change in the only biologic parameter, the {alpha}/{beta} ratio. For stereotactic body radiotherapy schedules, variations were larger, up to 0.6 to 0.9 for tumor and 1.6% to 1.9% for late, per 1% change in parameter. Conclusions: Robustness occurs similar to that of equivalent uniform dose (EUD), for the same reasons. Total dose, dose per fraction, and dose-rate cause their major effects, as well known.

17. Spectroscopy of one-dimensionally inhomogeneous media with quadratic nonlinearity

SciTech Connect

Golubkov, A A; Makarov, Vladimir A

2011-11-30

We present a brief review of the results of fifty years of development efforts in spectroscopy of one-dimensionally inhomogeneous media with quadratic nonlinearity. The recent original results obtained by the authors show the fundamental possibility of determining, from experimental data, the coordinate dependences of complex quadratic susceptibility tensor components of a onedimensionally inhomogeneous (along the z axis) medium with an arbitrary frequency dispersion, if the linear dielectric properties of the medium also vary along the z axis and are described by a diagonal tensor of the linear dielectric constant. It is assumed that the medium in question has the form of a plane-parallel plate, whose surfaces are perpendicular to the direction of the inhomogeneity. Using the example of several components of the tensors X{sup (2)}(z, {omega}{sub 1} {+-} {omega}{sub 2}; {omega}{sub 1}, {+-} {omega}{sub 2}), we describe two methods for finding their spatial profiles, which differ in the interaction geometry of plane monochromatic fundamental waves with frequencies {omega}{sub 1} and {omega}{sub 2}. The both methods are based on assessing the intensity of the waves propagating from the plate at the sum or difference frequency and require measurements over a range of angles of incidence of the fundamental waves. Such measurements include two series of additional estimates of the intensities of the waves generated under special conditions by using the test and additional reference plates, which eliminates the need for complicated phase measurements of the complex amplitudes of the waves at the sum (difference) frequency.

18. Identifiability and inference of pathway motifs by epistasis analysis.

PubMed

Phenix, Hilary; Perkins, Theodore; Kærn, Mads

2013-06-01

The accuracy of genetic network inference is limited by the assumptions used to determine if one hypothetical model is better than another in explaining experimental observations. Most previous work on epistasis analysis-in which one attempts to infer pathway relationships by determining equivalences among traits following mutations-has been based on Boolean or linear models. Here, we delineate the ultimate limits of epistasis-based inference by systematically surveying all two-gene network motifs and use symbolic algebra with arbitrary regulation functions to examine trait equivalences. Our analysis divides the motifs into equivalence classes, where different genetic perturbations result in indistinguishable experimental outcomes. We demonstrate that this partitioning can reveal important information about network architecture, and show, using simulated data, that it greatly improves the accuracy of genetic network inference methods. Because of the minimal assumptions involved, equivalence partitioning has broad applicability for gene network inference. PMID:23822501

19. Identifiability and inference of pathway motifs by epistasis analysis

Phenix, Hilary; Perkins, Theodore; Kærn, Mads

2013-06-01

The accuracy of genetic network inference is limited by the assumptions used to determine if one hypothetical model is better than another in explaining experimental observations. Most previous work on epistasis analysis—in which one attempts to infer pathway relationships by determining equivalences among traits following mutations—has been based on Boolean or linear models. Here, we delineate the ultimate limits of epistasis-based inference by systematically surveying all two-gene network motifs and use symbolic algebra with arbitrary regulation functions to examine trait equivalences. Our analysis divides the motifs into equivalence classes, where different genetic perturbations result in indistinguishable experimental outcomes. We demonstrate that this partitioning can reveal important information about network architecture, and show, using simulated data, that it greatly improves the accuracy of genetic network inference methods. Because of the minimal assumptions involved, equivalence partitioning has broad applicability for gene network inference.

20. Solutions of the Schrödinger equation with inversely quadratic Hellmann plus inversely quadratic potential using Nikiforov-Uvarov method

SciTech Connect

Ita, B. I.

2014-11-12

By using the Nikiforov-Uvarov (NU) method, the Schrödinger equation has been solved for the interaction of inversely quadratic Hellmann (IQHP) and inversely quadratic potential (IQP) for any angular momentum quantum number, l. The energy eigenvalues and their corresponding eigenfunctions have been obtained in terms of Laguerre polynomials. Special cases of the sum of these potentials have been considered and their energy eigenvalues also obtained.

1. Ensemble Inference and Inferability of Gene Regulatory Networks

PubMed Central

Ud-Dean, S. M. Minhaz; Gunawan, Rudiyanto

2014-01-01

The inference of gene regulatory network (GRN) from gene expression data is an unsolved problem of great importance. This inference has been stated, though not proven, to be underdetermined implying that there could be many equivalent (indistinguishable) solutions. Motivated by this fundamental limitation, we have developed new framework and algorithm, called TRaCE, for the ensemble inference of GRNs. The ensemble corresponds to the inherent uncertainty associated with discriminating direct and indirect gene regulations from steady-state data of gene knock-out (KO) experiments. We applied TRaCE to analyze the inferability of random GRNs and the GRNs of E. coli and yeast from single- and double-gene KO experiments. The results showed that, with the exception of networks with very few edges, GRNs are typically not inferable even when the data are ideal (unbiased and noise-free). Finally, we compared the performance of TRaCE with top performing methods of DREAM4 in silico network inference challenge. PMID:25093509

2. PPN Metric and PPN torsion in the quadratic poincaré gauge theory of gravity

Gladchenko, M. S.; Ponomariov, V. N.; Zhytnikov, V. V.

1990-05-01

The post-newtonian approximation of the quadratic Poincaré gauge theory of gravity is studied. As a result of this investigation the modified PPN metric and PPN torsion is obtained. Post-newtonian equations of motion for different test bodies are analyzed and some restrictions on the parameters of the quadratic lagrangian are found.

3. The cyclicity of period annulus of a quadratic reversible Lotka-Volterra system

Li, Chengzhi; Llibre, Jaume

2009-12-01

We prove that by perturbing the periodic annulus of the quadratic polynomial reversible Lotka-Volterra differential system \\dot x=y+\\case{3}{2}(x^2-y^2) , \\dot y=-x(1-y) , inside the class of all quadratic polynomial differential systems we can obtain at most two limit cycles.

4. The use of quadratic forms in the calculation of ground state electronic structures

SciTech Connect

Keller, Jaime; Weinberger, Peter

2006-08-15

There are many examples in theoretical physics where a fundamental quantity can be considered a quadratic form {rho}={sigma}{sub i}{rho}{sub i}=vertical bar {psi} vertical bar{sup 2} and the corresponding linear form {psi}={sigma}{sub i}{psi}{sub i} is highly relevant for the physical problem under study. This, in particular, is the case of the density and the wave function in quantum mechanics. In the study of N-identical-fermion systems we have the additional feature that {psi} is a function of the 3N configuration space coordinates and {rho} is defined in three-dimensional real space. For many-electron systems in the ground state the wave function and the Hamiltonian are to be expressed in terms of the configuration space (CS), a replica of real space for each electron. Here we present a geometric formulation of the CS, of the wave function, of the density, and of the Hamiltonian to compute the electronic structure of the system. Then, using the new geometric notation and the indistinguishability and equivalence of the electrons, we obtain an alternative computational method for the ground state of the system. We present the method and discuss its usefulness and relation to other approaches.

5. The empirical accuracy of uncertain inference models

NASA Technical Reports Server (NTRS)

Vaughan, David S.; Yadrick, Robert M.; Perrin, Bruce M.; Wise, Ben P.

1987-01-01

Uncertainty is a pervasive feature of the domains in which expert systems are designed to function. Research design to test uncertain inference methods for accuracy and robustness, in accordance with standard engineering practice is reviewed. Several studies were conducted to assess how well various methods perform on problems constructed so that correct answers are known, and to find out what underlying features of a problem cause strong or weak performance. For each method studied, situations were identified in which performance deteriorates dramatically. Over a broad range of problems, some well known methods do only about as well as a simple linear regression model, and often much worse than a simple independence probability model. The results indicate that some commercially available expert system shells should be used with caution, because the uncertain inference models that they implement can yield rather inaccurate results.

6. Bayesian Inference: with ecological applications

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2010-01-01

This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

7. Pathway network inference from gene expression data

PubMed Central

2014-01-01

Background The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules. Results We present a novel computational methodology to study the functional interconnections among the molecular elements of a biological system. The PANA approach uses high-throughput genomics measurements and a functional annotation scheme to extract an activity profile from each functional block -or pathway- followed by machine-learning methods to infer the relationships between these functional profiles. The result is a global, interconnected network of pathways that represents the functional cross-talk within the molecular system. We have applied this approach to describe the functional transcriptional connections during the yeast cell cycle and to identify pathways that change their connectivity in a disease condition using an Alzheimer example. Conclusions PANA is a useful tool to deepen in our understanding of the functional interdependences that operate within complex biological systems. We show the approach is algorithmically consistent and the inferred network is well supported by the available functional data. The method allows the dissection of the molecular basis of the functional connections and we describe the different regulatory mechanisms that explain the network's topology obtained for the yeast cell cycle data. PMID:25032889

8. Active inference, communication and hermeneutics.

PubMed

Friston, Karl J; Frith, Christopher D

2015-07-01

Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. PMID:25957007

9. Causal inference and developmental psychology.

PubMed

Foster, E Michael

2010-11-01

Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference-tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development. PMID:20677855

10. Active inference, communication and hermeneutics☆

PubMed Central

Friston, Karl J.; Frith, Christopher D.

2015-01-01

Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others – during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions – both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then – in principle – they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. PMID:25957007

11. Quadratic Measurement and Conditional State Preparation in an Optomechanical System

Brawley, George; Vanner, Michael; Bowen, Warwick; Schmid, Silvan; Boisen, Anja

2014-03-01

An important requirement in the study of quantum systems is the ability to measure non-linear observables at the level of quantum fluctuations. Such measurements enable the conditional preparation of highly non-classical states. Nonlinear measurement, although achieved in a variety of quantum systems including microwave cavity modes and optical fields, remains an outstanding problem in both electromechanical and optomechanical systems. To the best of our knowledge, previous experimental efforts to achieve nonlinear measurement of mechanical motion have not yielded strong coupling, nor the observation of quadratic mechanical motion. Here using a new technique reliant on the intrinsic nonlinearity of the optomechanical interaction, we experimentally observe for the first time a position squared (x2) measurement of the room-temperature Brownian motion of a nanomechanical oscillator. We utilize this measurement to conditionally prepare non-Gaussian bimodal states, which are the high temperature classical analogue of quantum macroscopic superposition states, or cat states. In the future with the aid of cryogenics and state-of-the-art optical cavities, our approach will provide a viable method of generating quantum superposition states of mechanical oscillators. This research was funded by the ARC Center of Excellence for Engineered Quantum Systems.

12. Quadratic Fermi node in a 3D strongly correlated semimetal

SciTech Connect

Kondo, Takeshi; Nakayama, M.; Chen, R.; Ishikawa, J. J.; Moon, E. -G.; Yamamoto, T.; Ota, Y.; Malaeb, W.; Kanai, H.; Nakashima, Y.; Ishida, Y.; Yoshida, R.; Yamamoto, H.; Matsunami, M.; Kimura, S.; Inami, N.; Ono, K.; Kumigashira, H.; Nakatsuji, S.; Balents, L.; Shin, S.

2015-12-07

We report that strong spin–orbit coupling fosters exotic electronic states such as topological insulators and superconductors, but the combination of strong spin–orbit and strong electron–electron interactions is just beginning to be understood. Central to this emerging area are the 5d transition metal iridium oxides. Here, in the pyrochlore iridate Pr2Ir2O7, we identify a non-trivial state with a single-point Fermi node protected by cubic and time-reversal symmetries, using a combination of angle-resolved photoemission spectroscopy and first-principles calculations. Owing to its quadratic dispersion, the unique coincidence of four degenerate states at the Fermi energy, and strong Coulomb interactions, non-Fermi liquid behaviour is predicted, for which we observe some evidence. Lastly, our discovery implies that Pr2Ir2O7 is a parent state that can be manipulated to produce other strongly correlated topological phases, such as topological Mott insulator, Weyl semimetal, and quantum spin and anomalous Hall states.

13. Quadratic Fermi node in a 3D strongly correlated semimetal

PubMed Central

Kondo, Takeshi; Nakayama, M.; Chen, R.; Ishikawa, J. J.; Moon, E.-G.; Yamamoto, T.; Ota, Y.; Malaeb, W.; Kanai, H.; Nakashima, Y.; Ishida, Y.; Yoshida, R.; Yamamoto, H.; Matsunami, M.; Kimura, S.; Inami, N.; Ono, K.; Kumigashira, H.; Nakatsuji, S.; Balents, L.; Shin, S.

2015-01-01

Strong spin–orbit coupling fosters exotic electronic states such as topological insulators and superconductors, but the combination of strong spin–orbit and strong electron–electron interactions is just beginning to be understood. Central to this emerging area are the 5d transition metal iridium oxides. Here, in the pyrochlore iridate Pr2Ir2O7, we identify a non-trivial state with a single-point Fermi node protected by cubic and time-reversal symmetries, using a combination of angle-resolved photoemission spectroscopy and first-principles calculations. Owing to its quadratic dispersion, the unique coincidence of four degenerate states at the Fermi energy, and strong Coulomb interactions, non-Fermi liquid behaviour is predicted, for which we observe some evidence. Our discovery implies that Pr2Ir2O7 is a parent state that can be manipulated to produce other strongly correlated topological phases, such as topological Mott insulator, Weyl semimetal, and quantum spin and anomalous Hall states. PMID:26640114

14. Gap solitons in a nonlinear quadratic negative-index cavity.

PubMed

Scalora, Michael; de Ceglia, Domenico; D'Aguanno, Giuseppe; Mattiucci, Nadia; Akozbek, Neset; Centini, Marco; Bloemer, Mark J

2007-06-01

We predict the existence of gap solitons in a nonlinear, quadratic Fabry-Pérot negative index cavity. A peculiarity of a single negative index layer is that if magnetic and electric plasma frequencies are different it forms a photonic band structure similar to that of a multilayer stack composed of ordinary, positive index materials. This similarity also results in comparable field localization and enhancement properties that under appropriate conditions may be used to either dynamically shift the band edge, or for efficient energy conversion. We thus report that an intense, fundamental pump pulse is able to shift the band edge of a negative index cavity, and make it possible for a weak second harmonic pulse initially tuned inside the gap to be transmitted, giving rise to a gap soliton. The process is due to cascading, a well-known phenomenon that occurs far from phase matching conditions that limits energy conversion rates, it resembles a nonlinear third-order process, and causes pulse compression due to self-phase modulation. The symmetry of the equations of motion under the action of either an electric or a magnetic nonlinearity suggests that both nonlinear polarization and magnetization, or a combination of both, can lead to solitonlike pulses. More specifically, the antisymmetric localization properties of the electric and magnetic fields cause a nonlinear polarization to generate a dark soliton, while a nonlinear magnetization spawns a bright soliton. PMID:17677375

15. Impact of a global quadratic potential on galactic rotation curves.

PubMed

Mannheim, Philip D; O'Brien, James G

2011-03-25

We present a conformal gravity fit to the 20 largest of a sample of 110 spiral galaxies. We identify the presence of a universal quadratic potential V(κ)(r)=-κc²r²/2 with κ=9.54×10⁻⁵⁴ cm⁻² induced by cosmic inhomogeneities. When V(κ)(r) is taken in conjunction with both a universal linear potential V(γ₀)(r)=γ₀c²r/2 with γ₀=3.06×10⁻³⁰ cm⁻¹ generated by the homogeneous cosmic background and the contribution generated by the local luminous matter in galaxies, the theory then accounts for the rotation curve systematics observed in the entire 110 galaxies, without the need for any dark matter whatsoever. Our study suggests that using dark matter may be nothing more than an attempt to describe global effects in purely local galactic terms. With V(κ)(r) being negative, galaxies can only support bound orbits up to distances of order γ₀/κ=100kpc, with global physics imposing a limit on the size of galaxies. PMID:21517292

16. Quadratic Fermi node in a 3D strongly correlated semimetal

Kondo, Takeshi; Nakayama, M.; Chen, R.; Ishikawa, J. J.; Moon, E.-G.; Yamamoto, T.; Ota, Y.; Malaeb, W.; Kanai, H.; Nakashima, Y.; Ishida, Y.; Yoshida, R.; Yamamoto, H.; Matsunami, M.; Kimura, S.; Inami, N.; Ono, K.; Kumigashira, H.; Nakatsuji, S.; Balents, L.; Shin, S.

2015-12-01

Strong spin-orbit coupling fosters exotic electronic states such as topological insulators and superconductors, but the combination of strong spin-orbit and strong electron-electron interactions is just beginning to be understood. Central to this emerging area are the 5d transition metal iridium oxides. Here, in the pyrochlore iridate Pr2Ir2O7, we identify a non-trivial state with a single-point Fermi node protected by cubic and time-reversal symmetries, using a combination of angle-resolved photoemission spectroscopy and first-principles calculations. Owing to its quadratic dispersion, the unique coincidence of four degenerate states at the Fermi energy, and strong Coulomb interactions, non-Fermi liquid behaviour is predicted, for which we observe some evidence. Our discovery implies that Pr2Ir2O7 is a parent state that can be manipulated to produce other strongly correlated topological phases, such as topological Mott insulator, Weyl semimetal, and quantum spin and anomalous Hall states.

17. GR angular momentum in the quadratic spinor Lagrangian formulation

Li, Siao-Jing

2016-08-01

We inquire into the question of whether the quadratic spinor Lagrangian (QSL) formulation can describe the angular momentum for a general-relativistic system. The QSL Hamiltonian has previously been shown to be able to yield an energy-momentum quasilocalization which brings a proof of the positive gravitational energy when the spinor satisfies the conformal Witten equation. After inspection, we find that, under the constraint that the spinor on the asymptotic boundary is a constant, the QSL Hamiltonian is successful in giving an angular momentum quasilocalization. We also make certain the spinor in the Hamiltonian plays the role of a gauge field, a warrant of our permission to impose constraints on the spinor. Then, by some adjustment of the QSL Hamiltonian, we gain a covariant center-of-mass moment quasilocalization only under the condition that the displacement on the asymptotic boundary is a Killing boost vector. We expect the spinor expression will bring a proof of some connection between the gravitational energy and angular momentum.

18. Quadratic Fermi node in a 3D strongly correlated semimetal

DOE PAGESBeta

Kondo, Takeshi; Nakayama, M.; Chen, R.; Ishikawa, J. J.; Moon, E. -G.; Yamamoto, T.; Ota, Y.; Malaeb, W.; Kanai, H.; Nakashima, Y.; et al

2015-12-07

We report that strong spin–orbit coupling fosters exotic electronic states such as topological insulators and superconductors, but the combination of strong spin–orbit and strong electron–electron interactions is just beginning to be understood. Central to this emerging area are the 5d transition metal iridium oxides. Here, in the pyrochlore iridate Pr2Ir2O7, we identify a non-trivial state with a single-point Fermi node protected by cubic and time-reversal symmetries, using a combination of angle-resolved photoemission spectroscopy and first-principles calculations. Owing to its quadratic dispersion, the unique coincidence of four degenerate states at the Fermi energy, and strong Coulomb interactions, non-Fermi liquid behaviour ismore » predicted, for which we observe some evidence. Lastly, our discovery implies that Pr2Ir2O7 is a parent state that can be manipulated to produce other strongly correlated topological phases, such as topological Mott insulator, Weyl semimetal, and quantum spin and anomalous Hall states.« less

19. Linear versus quadratic portfolio optimization model with transaction cost

Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah

2014-06-01

Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.

20. Linear quadratic optimal controller for cable-driven parallel robots

Abdolshah, Saeed; Shojaei Barjuei, Erfan

2015-12-01

In recent years, various cable-driven parallel robots have been investigated for their advantages, such as low structural weight, high acceleration, and large work-space, over serial and conventional parallel systems. However, the use of cables lowers the stiffness of these robots, which in turn may decrease motion accuracy. A linear quadratic (LQ) optimal controller can provide all the states of a system for the feedback, such as position and velocity. Thus, the application of such an optimal controller in cable-driven parallel robots can result in more efficient and accurate motion compared to the performance of classical controllers such as the proportional- integral-derivative controller. This paper presents an approach to apply the LQ optimal controller on cable-driven parallel robots. To employ the optimal control theory, the static and dynamic modeling of a 3-DOF planar cable-driven parallel robot (Feriba-3) is developed. The synthesis of the LQ optimal control is described, and the significant experimental results are presented and discussed.

1. Junction conditions in quadratic gravity: thin shells and double layers

Reina, Borja; Senovilla, José M. M.; Vera, Raül

2016-05-01

The junction conditions for the most general gravitational theory with a Lagrangian containing terms quadratic in the curvature are derived. We include the cases with a possible concentration of matter on the joining hypersurface—termed as thin shells, domain walls or braneworlds in the literature—as well as the proper matching conditions where only finite jumps of the energy-momentum tensor are allowed. In the latter case we prove that the matching conditions are more demanding than in general relativity. In the former case, we show that generically the shells/domain walls are of a new kind because they possess, in addition to the standard energy-momentum tensor, a double layer energy-momentum contribution which actually induces an external energy flux vector and an external scalar pressure/tension on the shell. We prove that all these contributions are necessary to make the entire energy-momentum tensor divergence-free, and we present the field equations satisfied by these energy-momentum quantities. The consequences of all these results are briefly analyzed.

2. Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2012-01-01

A technique is presented for initializing multiple discrete finite element model (FEM) mode sets for certain types of flight dynamics formulations that rely on superposition of orthogonal modes for modeling the elastic response. Such approaches are commonly used for modeling launch vehicle dynamics, and challenges arise due to the rapidly time-varying nature of the rigid-body and elastic characteristics. By way of an energy argument, a quadratic inequality constrained least squares (LSQI) algorithm is employed to e ect a smooth transition from one set of FEM eigenvectors to another with no requirement that the models be of similar dimension or that the eigenvectors be correlated in any particular way. The physically unrealistic and controversial method of eigenvector interpolation is completely avoided, and the discrete solution approximates that of the continuously varying system. The real-time computational burden is shown to be negligible due to convenient features of the solution method. Simulation results are presented, and applications to staging and other discontinuous mass changes are discussed

3. Quadratic Fermi node in a 3D strongly correlated semimetal.

PubMed

Kondo, Takeshi; Nakayama, M; Chen, R; Ishikawa, J J; Moon, E-G; Yamamoto, T; Ota, Y; Malaeb, W; Kanai, H; Nakashima, Y; Ishida, Y; Yoshida, R; Yamamoto, H; Matsunami, M; Kimura, S; Inami, N; Ono, K; Kumigashira, H; Nakatsuji, S; Balents, L; Shin, S

2015-01-01

Strong spin-orbit coupling fosters exotic electronic states such as topological insulators and superconductors, but the combination of strong spin-orbit and strong electron-electron interactions is just beginning to be understood. Central to this emerging area are the 5d transition metal iridium oxides. Here, in the pyrochlore iridate Pr2Ir2O7, we identify a non-trivial state with a single-point Fermi node protected by cubic and time-reversal symmetries, using a combination of angle-resolved photoemission spectroscopy and first-principles calculations. Owing to its quadratic dispersion, the unique coincidence of four degenerate states at the Fermi energy, and strong Coulomb interactions, non-Fermi liquid behaviour is predicted, for which we observe some evidence. Our discovery implies that Pr2Ir2O7 is a parent state that can be manipulated to produce other strongly correlated topological phases, such as topological Mott insulator, Weyl semimetal, and quantum spin and anomalous Hall states. PMID:26640114

4. Quadratic isothermal amplification for the detection of microRNA.

PubMed

Duan, Ruixue; Zuo, Xiaolei; Wang, Shutao; Quan, Xiyun; Chen, Dongliang; Chen, Zhifei; Jiang, Lei; Fan, Chunhai; Xia, Fan

2014-03-01

This protocol describes an isothermal amplification approach for ultrasensitive detection of specific microRNAs (miRNAs). It achieves this level of sensitivity through quadratic amplification of the target oligonucleotide by using a Bst DNA polymerase-induced strand-displacement reaction and a lambda exonuclease-aided recycling reaction. First, the target miRNA binds to a specifically designed molecular beacon, causing it to become a fluorescence emitter. A primer then binds to the activated beacon, and Bst polymerase initiates the synthesis of a double-stranded DNA segment templated on the molecular beacon. This causes the concomitant release of the target miRNA from the beacon--the first round of 'recycling'. Second, the duplex beacon thus produced is a suitable substrate for a nicking enzyme present in solution. After the duplex beacon is nicked, the lambda exonuclease digests the beacon and releases the DNA single strand just synthesized, which is complementary to the molecular beacon, inducing the second round of recycling. The miRNA detection limit of this protocol is 10 fmol at 37 °C and 1 amol at 4 °C. This approach also affords high selectivity when applied to miRNA extracted from MCF-7 and PC3 cell lines and even from breast cancer tissue samples. Upon isolation of miRNA, the detection process can be completed in ∼2 h. PMID:24525753

5. Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm.

PubMed

Palamara, Gian Marco; Childs, Dylan Z; Clements, Christopher F; Petchey, Owen L; Plebani, Marco; Smith, Matthew J

2014-12-01

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important

6. Investigation on probing quadratic electro-optic coefficient of tantalum potassium niobate crystal based on Fourier transform

Gao, Ch. Y.; Yu, H. T.; Wen, J.; Zhao, M.; Shang, J. J.; Li, X. L.

2016-02-01

A method for probing quadratic electro-optic(QEO) coefficient of tantalum potassium niobate crystal based on Fourier transform was proposed. We acquired all the independent component of QEO coefficient tensor of crystal, they are h11 = 1.56 ×10-14m2 /V2 , h12 = 1.24 ×10-14m2 /V2 and h44 = 0.160 ×10-14m2 /V2 respectively. With the help of the computer digital image processing technology, this method should have further application prospect in the areas of optical properties parameters measuring to the optical functional materials.

7. Physics of Inference

Toroczkai, Zoltan

Jaynes's maximum entropy method provides a family of principled models that allow the prediction of a system's properties as constrained by empirical data (observables). However, their use is often hindered by the degeneracy problem characterized by spontaneous symmetry breaking, where predictions fail. Here we show that degeneracy appears when the corresponding density of states function is not log-concave, which is typically the consequence of nonlinear relationships between the constraining observables. We illustrate this phenomenon on several examples, including from complex networks, combinatorics and classical spin systems (e.g., Blume-Emery-Griffiths lattice-spin models). Exploiting these nonlinear relationships we then propose a solution to the degeneracy problem for a large class of systems via transformations that render the density of states function log-concave. The effectiveness of the method is demonstrated on real-world network data. Finally, we discuss the implications of these findings on the relationship between the geometrical properties of the density of states function and phase transitions in spin systems. Supported in part by Grant No. FA9550-12-1-0405 from AFOSR/DARPA and by Grant No. HDTRA 1-09-1-0039 from DTRA.

8. Optimal inference with suboptimal models: Addiction and active Bayesian inference

PubMed Central

Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl

2015-01-01

When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321

9. Differential-geometric aspects of a nonholonomic Dirac mechanics: Lessons of a model quadratic in velocities

Pavlov, V. P.

2014-03-01

Faddeev and Vershik proposed the Hamiltonian and Lagrangian formulations of constrained mechanical systems that are invariant from the differential geometry standpoint. In both formulations, the description is based on a nondegenerate symplectic 2-form defined on a cotangent bundle T*Q (in the Hamiltonian formulation) or on a tangent bundle TQ (in the Lagrangian formulation), and constraints are sets of functions in involution on these manifolds. We demonstrate that this technique does not allow "invariantization" of the Dirac procedure of constraint "proliferation." We show this in an example of a typical quantum field model in which the original Lagrange function is a quadratic form in velocities with a degenerate coefficient matrix. We postulate that the initial phase space is a manifold where all arguments of the action functional including the Lagrange multipliers are defined. The Lagrange multipliers can then be naturally interpreted physically as velocities (in the Hamiltonian formulation) or momenta (in the Lagrangian formulation) related to "nonphysical" degrees of freedom. A quasisymplectic 2-form invariantly defined on such a manifold is degenerate. We propose new differential-geometric structures that allow formulating the Dirac procedure invariantly.

10. Quality of Computationally Inferred Gene Ontology Annotations

PubMed Central

Škunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

2012-01-01

Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation. PMID:22693439

11. Evolutionary inferences from the analysis of exchangeability

PubMed Central

Hendry, Andrew P.; Kaeuffer, Renaud; Crispo, Erika; Peichel, Catherine L.; Bolnick, Daniel I.

2013-01-01

Evolutionary inferences are usually based on statistical models that compare mean genotypes and phenotypes (or their frequencies) among populations. An alternative is to use the actual distribution of genotypes and phenotypes to infer the “exchangeability” of individuals among populations. We illustrate this approach by using discriminant functions on principal components to classify individuals among paired lake and stream populations of threespine stickleback in each of six independent watersheds. Classification based on neutral and non-neutral microsatellite markers was highest to the population of origin and next-highest to populations in the same watershed. These patterns are consistent with the influence of historical contingency (separate colonization of each watershed) and subsequent gene flow (within but not between watersheds). In comparison to this low genetic exchangeability, ecological (diet) and morphological (trophic and armor traits) exchangeability was relatively high – particularly among populations from similar habitats. These patterns reflect the role of natural selection in driving parallel changes adaptive changes when independent populations colonize similar habitats. Importantly, however, substantial non-parallelism was also evident. Our results show that analyses based on exchangeability can confirm inferences based on statistical analyses of means or frequencies, while also refining insights into the drivers of – and constraints on – evolutionary diversification. PMID:24299398

12. CAUSAL INFERENCE IN BIOLOGY NETWORKS WITH INTEGRATED BELIEF PROPAGATION

PubMed Central

CHANG, RUI; KARR, JONATHAN R; SCHADT, ERIC E

2014-01-01

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the ‘fitness’ of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot. PMID:25592596

13. New type of Weyl semimetal with quadratic double Weyl fermions.

PubMed

Huang, Shin-Ming; Xu, Su-Yang; Belopolski, Ilya; Lee, Chi-Cheng; Chang, Guoqing; Chang, Tay-Rong; Wang, BaoKai; Alidoust, Nasser; Bian, Guang; Neupane, Madhab; Sanchez, Daniel; Zheng, Hao; Jeng, Horng-Tay; Bansil, Arun; Neupert, Titus; Lin, Hsin; Hasan, M Zahid

2016-02-01

Weyl semimetals have attracted worldwide attention due to their wide range of exotic properties predicted in theories. The experimental realization had remained elusive for a long time despite much effort. Very recently, the first Weyl semimetal has been discovered in an inversion-breaking, stoichiometric solid TaAs. So far, the TaAs class remains the only Weyl semimetal available in real materials. To facilitate the transition of Weyl semimetals from the realm of purely theoretical interest to the realm of experimental studies and device applications, it is of crucial importance to identify other robust candidates that are experimentally feasible to be realized. In this paper, we propose such a Weyl semimetal candidate in an inversion-breaking, stoichiometric compound strontium silicide, SrSi2, with many new and novel properties that are distinct from TaAs. We show that SrSi2 is a Weyl semimetal even without spin-orbit coupling and that, after the inclusion of spin-orbit coupling, two Weyl fermions stick together forming an exotic double Weyl fermion with quadratic dispersions and a higher chiral charge of ±2. Moreover, we find that the Weyl nodes with opposite charges are located at different energies due to the absence of mirror symmetry in SrSi2, paving the way for the realization of the chiral magnetic effect. Our systematic results not only identify a much-needed robust Weyl semimetal candidate but also open the door to new topological Weyl physics that is not possible in TaAs. PMID:26787914

14. A decentralized linear quadratic control design method for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1990-01-01

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass

15. New type of Weyl semimetal with quadratic double Weyl fermions

PubMed Central

Huang, Shin-Ming; Xu, Su-Yang; Belopolski, Ilya; Lee, Chi-Cheng; Chang, Guoqing; Chang, Tay-Rong; Wang, BaoKai; Alidoust, Nasser; Bian, Guang; Neupane, Madhab; Sanchez, Daniel; Zheng, Hao; Jeng, Horng-Tay; Bansil, Arun; Neupert, Titus; Lin, Hsin; Hasan, M. Zahid

2016-01-01

Weyl semimetals have attracted worldwide attention due to their wide range of exotic properties predicted in theories. The experimental realization had remained elusive for a long time despite much effort. Very recently, the first Weyl semimetal has been discovered in an inversion-breaking, stoichiometric solid TaAs. So far, the TaAs class remains the only Weyl semimetal available in real materials. To facilitate the transition of Weyl semimetals from the realm of purely theoretical interest to the realm of experimental studies and device applications, it is of crucial importance to identify other robust candidates that are experimentally feasible to be realized. In this paper, we propose such a Weyl semimetal candidate in an inversion-breaking, stoichiometric compound strontium silicide, SrSi2, with many new and novel properties that are distinct from TaAs. We show that SrSi2 is a Weyl semimetal even without spin–orbit coupling and that, after the inclusion of spin–orbit coupling, two Weyl fermions stick together forming an exotic double Weyl fermion with quadratic dispersions and a higher chiral charge of ±2. Moreover, we find that the Weyl nodes with opposite charges are located at different energies due to the absence of mirror symmetry in SrSi2, paving the way for the realization of the chiral magnetic effect. Our systematic results not only identify a much-needed robust Weyl semimetal candidate but also open the door to new topological Weyl physics that is not possible in TaAs. PMID:26787914

16. Gravity waves from non-minimal quadratic inflation

SciTech Connect

Pallis, Constantinos; Shafi, Qaisar

2015-03-12

We discuss non-minimal quadratic inflation in supersymmetric (SUSY) and non-SUSY models which entails a linear coupling of the inflaton to gravity. Imposing a lower bound on the parameter c{sub R}, involved in the coupling between the inflaton and the Ricci scalar curvature, inflation can be attained even for subplanckian values of the inflaton while the corresponding effective theory respects the perturbative unitarity up to the Planck scale. Working in the non-SUSY context we also consider radiative corrections to the inflationary potential due to a possible coupling of the inflaton to bosons or fermions. We find ranges of the parameters, depending mildly on the renormalization scale, with adjustable values of the spectral index n{sub s}, tensor-to-scalar ratio r≃(2−4)⋅10{sup −3}, and an inflaton mass close to 3⋅10{sup 13} GeV. In the SUSY framework we employ two gauge singlet chiral superfields, a logarithmic Kähler potential including all the allowed terms up to fourth order in powers of the various fields, and determine uniquely the superpotential by applying a continuous R and a global U(1) symmetry. When the Kähler manifold exhibits a no-scale-type symmetry, the model predicts n{sub s}≃0.963 and r≃0.004. Beyond no-scale SUGRA, n{sub s} and r depend crucially on the coefficient involved in the fourth order term, which mixes the inflaton with the accompanying non-inflaton field in the Kähler potential, and the prefactor encountered in it. Increasing slightly the latter above (−3), an efficient enhancement of the resulting r can be achieved putting it in the observable range. The inflaton mass in the last case is confined in the range (5−9)⋅10{sup 13} GeV.

17. Post-Newtonian, quasicircular binary inspirals in quadratic modified gravity

Yagi, Kent; Stein, Leo C.; Yunes, Nicolás; Tanaka, Takahiro

2012-03-01

We consider a general class of quantum gravity-inspired, modified gravity theories, where the Einstein-Hilbert action is extended through the addition of all terms quadratic in the curvature tensor coupled to scalar fields with standard kinetic energy. This class of theories includes Einstein-Dilaton-Gauss-Bonnet and Chern-Simons modified gravity as special cases. We analytically derive and solve the coupled field equations in the post-Newtonian approximation, assuming a comparable-mass, spinning black hole binary source in a quasicircular, weak-field/slow-motion orbit. We find that a naive subtraction of divergent piece associated with the point-particle approximation is ill-suited to represent compact objects in these theories. Instead, we model them by appropriate effective sources built so that known strong-field solutions are reproduced in the far-field limit. In doing so, we prove that black holes in Einstein-Dilaton-Gauss-Bonnet and Chern-Simons theory can have hair, while neutron stars have no scalar monopole charge, in diametrical opposition to results in scalar-tensor theories. We then employ techniques similar to the direct integration of the relaxed Einstein equations to obtain analytic expressions for the scalar field, metric perturbation, and the associated gravitational wave luminosity measured at infinity. We find that scalar field emission mainly dominates the energy flux budget, sourcing electric-type (even-parity) dipole scalar radiation and magnetic-type (odd-parity) quadrupole scalar radiation, correcting the General Relativistic prediction at relative -1PN and 2PN orders. Such modifications lead to corrections in the emitted gravitational waves that can be mapped to the parameterized post-Einsteinian framework. Such modifications could be strongly constrained with gravitational wave observations.

18. Reduced order parameter estimation using quasilinearization and quadratic programming

2012-06-01

The ability of a particular model to accurately predict how a system responds to forcing is predicated on various model parameters that must be appropriately identified. There are many algorithms whose purpose is to solve this inverse problem, which is often computationally intensive. In this study, we propose a new algorithm that significantly reduces the computational burden associated with parameter identification. The algorithm is an extension of the quasilinearization approach where the governing system of differential equations is linearized with respect to the parameters. The resulting inverse problem therefore becomes a linear regression or quadratic programming problem (QP) for minimizing the sum of squared residuals; the solution becomes an update on the parameter set. This process of linearization and regression is repeated until convergence takes place. This algorithm has not received much attention, as the QPs can become quite large, often infeasible for real-world systems. To alleviate this drawback, proper orthogonal decomposition is applied to reduce the size of the linearized model, thereby reducing the computational burden of solving each QP. In fact, this study shows that the snapshots need only be calculated once at the very beginning of the algorithm, after which no further calculations of the reduced-model subspace are required. The proposed algorithm therefore only requires one linearized full-model run per parameter at the first iteration followed by a series of reduced-order QPs. The method is applied to a groundwater model with about 30,000 computation nodes where as many as 15 zones of hydraulic conductivity are estimated.

19. Thermodynamics of cellular statistical inference

Lang, Alex; Fisher, Charles; Mehta, Pankaj

2014-03-01

Successful organisms must be capable of accurately sensing the surrounding environment in order to locate nutrients and evade toxins or predators. However, single cell organisms face a multitude of limitations on their accuracy of sensing. Berg and Purcell first examined the canonical example of statistical limitations to cellular learning of a diffusing chemical and established a fundamental limit to statistical accuracy. Recent work has shown that the Berg and Purcell learning limit can be exceeded using Maximum Likelihood Estimation. Here, we recast the cellular sensing problem as a statistical inference problem and discuss the relationship between the efficiency of an estimator and its thermodynamic properties. We explicitly model a single non-equilibrium receptor and examine the constraints on statistical inference imposed by noisy biochemical networks. Our work shows that cells must balance sample number, specificity, and energy consumption when performing statistical inference. These tradeoffs place significant constraints on the practical implementation of statistical estimators in a cell.

20. Causal inference from observational data.

PubMed

Listl, Stefan; Jürges, Hendrik; Watt, Richard G

2016-10-01

Randomized controlled trials have long been considered the 'gold standard' for causal inference in clinical research. In the absence of randomized experiments, identification of reliable intervention points to improve oral health is often perceived as a challenge. But other fields of science, such as social science, have always been challenged by ethical constraints to conducting randomized controlled trials. Methods have been established to make causal inference using observational data, and these methods are becoming increasingly relevant in clinical medicine, health policy and public health research. This study provides an overview of state-of-the-art methods specifically designed for causal inference in observational data, including difference-in-differences (DiD) analyses, instrumental variables (IV), regression discontinuity designs (RDD) and fixed-effects panel data analysis. The described methods may be particularly useful in dental research, not least because of the increasing availability of routinely collected administrative data and electronic health records ('big data'). PMID:27111146

1. We infer light in space.

PubMed

Schirillo, James A

2013-10-01

In studies of lightness and color constancy, the terms lightness and brightness refer to the qualia corresponding to perceived surface reflectance and perceived luminance, respectively. However, what has rarely been considered is the fact that the volume of space containing surfaces appears neither empty, void, nor black, but filled with light. Helmholtz (1866/1962) came closest to describing this phenomenon when discussing inferred illumination, but previous theoretical treatments have fallen short by restricting their considerations to the surfaces of objects. The present work is among the first to explore how we infer the light present in empty space. It concludes with several research examples supporting the theory that humans can infer the differential levels and chromaticities of illumination in three-dimensional space. PMID:23435628

2. Randomized parcellation based inference.

PubMed

Da Mota, Benoit; Fritsch, Virgile; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Conrod, Patricia; Gallinat, Jürgen; Garavan, Hugh; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Smolka, Michael N; Ströhle, Andreas; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

2014-04-01

Neuroimaging group analyses are used to relate inter-subject signal differences observed in brain imaging with behavioral or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. We introduce a new approach to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on synthetic and real data, this approach shows higher sensitivity, better accuracy and higher reproducibility than state-of-the-art methods. In a neuroimaging-genetic application, we find that it succeeds in detecting a significant association between a genetic variant next to the COMT gene and the BOLD signal in the left thalamus for a functional Magnetic Resonance Imaging contrast associated with incorrect responses of the subjects from a Stop Signal Task protocol. PMID:24262376

3. Stability and monotone convergence of generalised policy iteration for discrete-time linear quadratic regulations

Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2016-03-01

In this paper, we analyse the convergence and stability properties of generalised policy iteration (GPI) applied to discrete-time linear quadratic regulation problems. GPI is one kind of the generalised adaptive dynamic programming methods used for solving optimal control problems, and is composed of policy evaluation and policy improvement steps. To analyse the convergence and stability of GPI, the dynamic programming (DP) operator is defined. Then, GPI and its equivalent formulas are presented based on the notation of DP operator. The convergence of the approximate value function to the exact one in policy evaluation is proven based on the equivalent formulas. Furthermore, the positive semi-definiteness, stability, and the monotone convergence (PI-mode and VI-mode convergence) of GPI are presented under certain conditions on the initial value function. The online least square method is also presented for the implementation of GPI. Finally, some numerical simulations are carried out to verify the effectiveness of GPI as well as to further investigate the convergence and stability properties.

4. LOWER LEVEL INFERENCE CONTROL IN STATISTICAL DATABASE SYSTEMS

SciTech Connect

Lipton, D.L.; Wong, H.K.T.

1984-02-01

An inference is the process of transforming unclassified data values into confidential data values. Most previous research in inference control has studied the use of statistical aggregates to deduce individual records. However, several other types of inference are also possible. Unknown functional dependencies may be apparent to users who have 'expert' knowledge about the characteristics of a population. Some correlations between attributes may be concluded from 'commonly-known' facts about the world. To counter these threats, security managers should use random sampling of databases of similar populations, as well as expert systems. 'Expert' users of the DATABASE SYSTEM may form inferences from the variable performance of the user interface. Users may observe on-line turn-around time, accounting statistics. the error message received, and the point at which an interactive protocol sequence fails. One may obtain information about the frequency distributions of attribute values, and the validity of data object names from this information. At the back-end of a database system, improved software engineering practices will reduce opportunities to bypass functional units of the database system. The term 'DATA OBJECT' should be expanded to incorporate these data object types which generate new classes of threats. The security of DATABASES and DATABASE SySTEMS must be recognized as separate but related problems. Thus, by increased awareness of lower level inferences, system security managers may effectively nullify the threat posed by lower level inferences.

5. Bayesian inferences about the self (and others): A review

PubMed Central

Moutoussis, Michael; Fearon, Pasco; El-Deredy, Wael; Dolan, Raymond J.; Friston, Karl J.

2014-01-01

Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising surprise – under the prior belief that one will end up in states with high utility. Interpersonal representations thus serve to render interactions more predictable, while the affective valence of interpersonal inference renders self-perception evaluative. Distortions of self-representation contribute to major psychiatric disorders such as depression, personality disorder and paranoia. The approach we review may therefore operationalise the study of interpersonal representations in pathological states. PMID:24583455

6. Eight challenges in phylodynamic inference

PubMed Central

Frost, Simon D.W.; Pybus, Oliver G.; Gog, Julia R.; Viboud, Cecile; Bonhoeffer, Sebastian; Bedford, Trevor

2015-01-01

The field of phylodynamics, which attempts to enhance our understanding of infectious disease dynamics using pathogen phylogenies, has made great strides in the past decade. Basic epidemiological and evolutionary models are now well characterized with inferential frameworks in place. However, significant challenges remain in extending phylodynamic inference to more complex systems. These challenges include accounting for evolutionary complexities such as changing mutation rates, selection, reassortment, and recombination, as well as epidemiological complexities such as stochastic population dynamics, host population structure, and different patterns at the within-host and between-host scales. An additional challenge exists in making efficient inferences from an ever increasing corpus of sequence data. PMID:25843391

7. Bayesian Inference in Satellite Gravity Inversion

NASA Technical Reports Server (NTRS)

Kis, K. I.; Taylor, Patrick T.; Wittmann, G.; Kim, Hyung Rae; Torony, B.; Mayer-Guerr, T.

2005-01-01

To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

8. Inferring differentiation pathways from gene expression

PubMed Central

Costa, Ivan G.; Roepcke, Stefan; Hafemeister, Christoph; Schliep, Alexander

2008-01-01

Motivation: The regulation of proliferation and differentiation of embryonic and adult stem cells into mature cells is central to developmental biology. Gene expression measured in distinguishable developmental stages helps to elucidate underlying molecular processes. In previous work we showed that functional gene modules, which act distinctly in the course of development, can be represented by a mixture of trees. In general, the similarities in the gene expression programs of cell populations reflect the similarities in the differentiation path. Results: We propose a novel model for gene expression profiles and an unsupervised learning method to estimate developmental similarity and infer differentiation pathways. We assess the performance of our model on simulated data and compare it with favorable results to related methods. We also infer differentiation pathways and predict functional modules in gene expression data of lymphoid development. Conclusions: We demonstrate for the first time how, in principal, the incorporation of structural knowledge about the dependence structure helps to reveal differentiation pathways and potentially relevant functional gene modules from microarray datasets. Our method applies in any area of developmental biology where it is possible to obtain cells of distinguishable differentiation stages. Availability: The implementation of our method (GPL license), data and additional results are available at http://algorithmics.molgen.mpg.de/Supplements/InfDif/ Contact: filho@molgen.mpg.de, schliep@molgen.mpg.de Supplementary information: Supplementary data is available at Bioinformatics online. PMID:18586709

9. Minitrack tracking function description, volume 2

NASA Technical Reports Server (NTRS)

Englar, T. S.; Mango, S. A.; Roettcher, C. A.; Watters, D. L.

1973-01-01

The minitrack tracking function is described and specific operations are identified. The subjects discussed are: (1) preprocessor listing, (2) minitrack hardware, (3) system calibration, (4) quadratic listing, and (5) quadratic flow diagram. Detailed information is provided on the construction of the tracking system and its operation. The calibration procedures are supported by mathematical models to show the application of the computer programs.

10. Stability of the equilibrium positions of an engine with nonlinear quadratic springs

Stănescu, Nicolae-Doru; Popa, Dinel

2014-06-01

Our paper realizes a study of the equilibrium positions for an engine supported by four identical nonlinear springs of quadratic characteristic. The systems with quadratic characteristic are generally avoided because they lead to mathematical complications. Our goal is to realize such a study for an engine supported on quadratic springs. For the model purposed, we established the equations of motion and we discussed the possibilities for the equilibrium positions. Because of the quadratic characteristic of the springs and of the approximations made for the small rotations, the equations obtained for the equilibrium lead us to a paradox, which consists in the existence of an open neighborhood in which there exists an infinity of positions of indifferent equilibrium, or a curve where the equilibrium positions are situated. Moreover, the study of the stability shows that the stability is assured for the position at which the springs are not compressed. Finally, a numerical example is presented and completely solved.

11. The Existence of Periodic Orbits and Invariant Tori for Some 3-Dimensional Quadratic Systems

PubMed Central

Jiang, Yanan; Han, Maoan; Xiao, Dongmei

2014-01-01

We use the normal form theory, averaging method, and integral manifold theorem to study the existence of limit cycles in Lotka-Volterra systems and the existence of invariant tori in quadratic systems in ℝ3. PMID:24982980

12. On ideal structure in quadratic DDS in R{sup 2}

SciTech Connect

Kutnjak, Milan

2008-11-13

We consider the dynamics in a special case of two-dimensional quadratic homogeneous discrete dynamical systems. It is well known (c.f. [1, 2]) that homogeneous quadratic maps are in one to one correspondence with two-dimensional commutative (nonassociative) algebras. Algebraic concepts (such as the structure of algebra and existence of special elements like idempotents and nilpotents) help us to study the dynamics of the corresponding discrete homogeneous quadratic maps. It is well-known that such systems can exhibit chaotic behavior [3], In this article we consider the influence of the existence of an algebra ideal on the dynamics of the corresponding discrete homogeneous quadratic system. We also present some examples in the plane.

13. The existence of periodic orbits and invariant tori for some 3-dimensional quadratic systems.

PubMed

Jiang, Yanan; Han, Maoan; Xiao, Dongmei

2014-01-01

We use the normal form theory, averaging method, and integral manifold theorem to study the existence of limit cycles in Lotka-Volterra systems and the existence of invariant tori in quadratic systems in ℝ(3). PMID:24982980

14. Observers for a class of systems with nonlinearities satisfying an incremental quadratic inequality

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Martin, Corless

2004-01-01

We consider the problem of state estimation from nonlinear time-varying system whose nonlinearities satisfy an incremental quadratic inequality. Observers are presented which guarantee that the state estimation error exponentially converges to zero.

15. Line integral formulation of energy and QUadratic invariants preserving (EQUIP) methods for Hamiltonian systems

Brugnano, Luigi; Caccia, Gianluca Frasca; Iavernaro, Felice

2016-06-01

The family of EQUIP (Energy and QUadratic Invariants Preserving) methods for Hamiltonian systems is here recasted in the framework of Line Integral Methods, in order to provide a more efficient discrete problem.

16. cosmoabc: Likelihood-free inference for cosmology

Ishida, Emille E. O.; Vitenti, Sandro D. P.; Penna-Lima, Mariana; Trindade, Arlindo M.; Cisewski, Jessi; M.; de Souza, Rafael; Cameron, Ewan; Busti, Vinicius C.

2015-05-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

17. Bianchi type-I cosmological model with quadratic equation of state

Reddy, D. R. K.; Adhav, K. S.; Purandare, M. A.

2015-05-01

Bianchi type-I cosmological model containing perfect fluid with quadratic equation of state has been studied in general theory of relativity. The general solutions of the Einstein's field equations for Bianchi type-I space-time have been obtained under the assumption of quadratic equation of state (EoS) p= αρ 2- ρ, where α is constant and strictly α≠0. The physical and geometrical aspects of the model are discussed.

18. Science Shorts: Observation versus Inference

ERIC Educational Resources Information Center

Leager, Craig R.

2008-01-01

When you observe something, how do you know for sure what you are seeing, feeling, smelling, or hearing? Asking students to think critically about their encounters with the natural world will help to strengthen their understanding and application of the science-process skills of observation and inference. In the following lesson, students make…

19. Sample Size and Correlational Inference

ERIC Educational Resources Information Center

Anderson, Richard B.; Doherty, Michael E.; Friedrich, Jeff C.

2008-01-01

In 4 studies, the authors examined the hypothesis that the structure of the informational environment makes small samples more informative than large ones for drawing inferences about population correlations. The specific purpose of the studies was to test predictions arising from the signal detection simulations of R. B. Anderson, M. E. Doherty,…

20. Word Learning as Bayesian Inference

ERIC Educational Resources Information Center

Xu, Fei; Tenenbaum, Joshua B.

2007-01-01

The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…

1. The mechanisms of temporal inference

NASA Technical Reports Server (NTRS)

Fox, B. R.; Green, S. R.

1987-01-01

The properties of a temporal language are determined by its constituent elements: the temporal objects which it can represent, the attributes of those objects, the relationships between them, the axioms which define the default relationships, and the rules which define the statements that can be formulated. The methods of inference which can be applied to a temporal language are derived in part from a small number of axioms which define the meaning of equality and order and how those relationships can be propagated. More complex inferences involve detailed analysis of the stated relationships. Perhaps the most challenging area of temporal inference is reasoning over disjunctive temporal constraints. Simple forms of disjunction do not sufficiently increase the expressive power of a language while unrestricted use of disjunction makes the analysis NP-hard. In many cases a set of disjunctive constraints can be converted to disjunctive normal form and familiar methods of inference can be applied to the conjunctive sub-expressions. This process itself is NP-hard but it is made more tractable by careful expansion of a tree-structured search space.

2. Perceptual Inference and Autistic Traits

ERIC Educational Resources Information Center

Skewes, Joshua C; Jegindø, Else-Marie; Gebauer, Line

2015-01-01

Autistic people are better at perceiving details. Major theories explain this in terms of bottom-up sensory mechanisms or in terms of top-down cognitive biases. Recently, it has become possible to link these theories within a common framework. This framework assumes that perception is implicit neural inference, combining sensory evidence with…

3. Improving Explanatory Inferences from Assessments

ERIC Educational Resources Information Center

Diakow, Ronli Phyllis

2013-01-01

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

4. Inference for interacting linear waves in ordered and random media

Tyagi, P.; Pagnani, A.; Antenucci, F.; Ibánez Berganza, M.; Leuzzi, L.

2015-05-01

A statistical inference method is developed and tested for pairwise interacting systems whose degrees of freedom are continuous angular variables, such as planar spins in magnetic systems or wave phases in optics and acoustics. We investigate systems with both deterministic and quenched disordered couplings on two extreme topologies: complete and sparse graphs. To match further applications in optics also complex couplings and external fields are considered and general inference formulas are derived for real and imaginary parts of Hermitian coupling matrices from real and imaginary parts of complex correlation functions. The whole procedure is, eventually, tested on numerically generated correlation functions and local magnetizations by means of Monte Carlo simulations.

5. Unified inference for sparse and dense longitudinal models.

PubMed

Kim, Seonjin; Zhao, Zhibiao

2013-03-01

In longitudinal data analysis, statistical inference for sparse data and dense data could be substantially different. For kernel smoothing estimate of the mean function, the convergence rates and limiting variance functions are different under the two scenarios. The latter phenomenon poses challenges for statistical inference as a subjective choice between the sparse and dense cases may lead to wrong conclusions. We develop self-normalization based methods that can adapt to the sparse and dense cases in a unified framework. Simulations show that the proposed methods outperform some existing methods. PMID:24966413

6. Differentiable exact penalty functions via Hestenis-Powell-Rockafellars augmented Lagrangian function

SciTech Connect

Li, Wu

1994-12-31

We study differentiable exact penalty functions, depending only on x, derived from Hestenes-Powell-Rockafellars quadratic augmented Lagrangian function for a minimization problem with two-sided inequality constraints by using Fletcher`s Lagrangian multiplier estimate. We also consider new penalty functions, depending only on the Lagrangian multiplier, derived from the augmented Lagrangian function. These penalty functions are particularly useful for quadratic programming problems.

7. Fast and accurate computation of two-dimensional non-separable quadratic-phase integrals.

PubMed

Koç, Aykut; Ozaktas, Haldun M; Hesselink, Lambertus

2010-06-01

We report a fast and accurate algorithm for numerical computation of two-dimensional non-separable linear canonical transforms (2D-NS-LCTs). Also known as quadratic-phase integrals, this class of integral transforms represents a broad class of optical systems including Fresnel propagation in free space, propagation in graded-index media, passage through thin lenses, and arbitrary concatenations of any number of these, including anamorphic/astigmatic/non-orthogonal cases. The general two-dimensional non-separable case poses several challenges which do not exist in the one-dimensional case and the separable two-dimensional case. The algorithm takes approximately N log N time, where N is the two-dimensional space-bandwidth product of the signal. Our method properly tracks and controls the space-bandwidth products in two dimensions, in order to achieve information theoretically sufficient, but not wastefully redundant, sampling required for the reconstruction of the underlying continuous functions at any stage of the algorithm. Additionally, we provide an alternative definition of general 2D-NS-LCTs that shows its kernel explicitly in terms of its ten parameters, and relate these parameters bidirectionally to conventional ABCD matrix parameters. PMID:20508697

8. Degradation reliability modeling based on an independent increment process with quadratic variance

Wang, Zhihua; Zhang, Yongbo; Wu, Qiong; Fu, Huimin; Liu, Chengrui; Krishnaswamy, Sridhar

2016-03-01

Degradation testing is an important technique for assessing life time information of complex systems and highly reliable products. Motivated by fatigue crack growth (FCG) data and our previous study, this paper develops a novel degradation modeling approach, in which degradation is represented by an independent increment process with linear mean and general quadratic variance functions of test time or transformed test time if necessary. Based on the constructed degradation model, closed-form expressions of failure time distribution (FTD) and its percentiles can be straightforwardly derived and calculated. A one-stage method is developed to estimate model parameters and FTD. Simulation studies are conducted to validate the proposed approach, and the results illustrate that the approach can provide reasonable estimates even for small sample size situations. Finally, the method is verified by the FCG data set given as the motivating example, and the results show that it can be considered as an effective degradation modeling approach compared with the multivariate normal model and graphic approach.

9. Application of Sequential Quadratic Programming to Minimize Smart Active Flap Rotor Hub Loads

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi; Leyland, Jane

2014-01-01

In an analytical study, SMART active flap rotor hub loads have been minimized using nonlinear programming constrained optimization methodology. The recently developed NLPQLP system (Schittkowski, 2010) that employs Sequential Quadratic Programming (SQP) as its core algorithm was embedded into a driver code (NLP10x10) specifically designed to minimize active flap rotor hub loads (Leyland, 2014). Three types of practical constraints on the flap deflections have been considered. To validate the current application, two other optimization methods have been used: i) the standard, linear unconstrained method, and ii) the nonlinear Generalized Reduced Gradient (GRG) method with constraints. The new software code NLP10x10 has been systematically checked out. It has been verified that NLP10x10 is functioning as desired. The following are briefly covered in this paper: relevant optimization theory; implementation of the capability of minimizing a metric of all, or a subset, of the hub loads as well as the capability of using all, or a subset, of the flap harmonics; and finally, solutions for the SMART rotor. The eventual goal is to implement NLP10x10 in a real-time wind tunnel environment.

10. Phosphorus-31 MRI of bones using quadratic echo line-narrowing

Frey, Merideth; Barrett, Sean; Insogna, Karl; Vanhouten, Joshua

2012-02-01

There is a great need to probe the internal composition of bone on the sub-0.1 mm length scale, both to study normal features and to look for signs of disease. Despite the obvious importance of the mineral fraction to the biomechanical properties of skeletal tissue, few non-destructive techniques are available to evaluate changes in its chemical structure and functional microarchitecture on the interior of bones. MRI would be an excellent candidate, but bone is a particularly challenging tissue to study given the relatively low water density and wider linewidths of its solid components. Recent fundamental research in quantum computing gave rise to a new NMR pulse sequence - the quadratic echo - that can be used to narrow the broad NMR spectrum of solids. This offers a new route to do high spatial resolution, 3D ^31P MRI of bone that complements conventional MRI and x-ray based techniques to study bone physiology and structure. We have used our pulse sequence to do 3D ^31P MRI of ex vivo bones with a spatial resolution of (sub-450 μm)^3, limited only by the specifications of a conventional 4 Tesla liquid-state MRI system. We will describe our plans to push this technique towards the factor of 1000 increase in spatial resolution imposed by fundamental limits.

11. Detection of Replication Origin Sites in Herpesvirus Genomes by Clustering and Scoring of Palindromes with Quadratic Entropy Measures.

PubMed

Rizvi, Ahsan Z; Bhattacharya, C

2014-01-01

Replication in herpesvirus genomes is a major concern of public health as they multiply rapidly during the lytic phase of infection that cause maximum damage to the host cells. Earlier research has established that sites of replication origin are dominated by high concentration of rare palindrome sequences of DNA. Computational methods are devised based on scoring to determine the concentration of palindromes. In this paper, we propose both extraction and localization of rare palindromes in an automated manner. Discrete Cosine Transform (DCT-II), a widely recognized image compression algorithm is utilized here to extract palindromic sequences based on their reverse complimentary symmetry property of existence. We formulate a novel approach to localize the rare palindrome clusters by devising a Minimum Quadratic Entropy (MQE) measure based on the Renyi's Quadratic Entropy (RQE) function. Experimental results over a large number of herpesvirus genomes show that the RQE based scoring of rare palindromes have higher order of sensitivity, and lesser false alarm in detecting concentration of rare palindromes and thereby sites of replication origin. PMID:26357048

12. Inferring the spatiotemporal DNA replication program from noisy data

Baker, A.; Bechhoefer, J.

2014-03-01

We generalize a stochastic model of DNA replication to the case where replication-origin-initiation rates vary locally along the genome and with time. Using this generalized model, we address the inverse problem of inferring initiation rates from experimental data concerning replication in cell populations. Previous work based on curve fitting depended on arbitrarily chosen functional forms for the initiation rate, with free parameters that were constrained by the data. We introduce a nonparametric method of inference that is based on Gaussian process regression. The method replaces specific assumptions about the functional form of the initiation rate with more general prior expectations about the smoothness of variation of this rate, along the genome and in time. Using this inference method, we recover, with high precision, simulated replication schemes from noisy data that are typical of current experiments.

13. Bayesian Inference on Proportional Elections

PubMed Central

Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio

2015-01-01

Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259

14. Bayesian inference on proportional elections.

PubMed

Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio

2015-01-01

Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259

15. System Support for Forensic Inference

Gehani, Ashish; Kirchner, Florent; Shankar, Natarajan

Digital evidence is playing an increasingly important role in prosecuting crimes. The reasons are manifold: financially lucrative targets are now connected online, systems are so complex that vulnerabilities abound and strong digital identities are being adopted, making audit trails more useful. If the discoveries of forensic analysts are to hold up to scrutiny in court, they must meet the standard for scientific evidence. Software systems are currently developed without consideration of this fact. This paper argues for the development of a formal framework for constructing “digital artifacts” that can serve as proxies for physical evidence; a system so imbued would facilitate sound digital forensic inference. A case study involving a filesystem augmentation that provides transparent support for forensic inference is described.

16. Statistical learning and selective inference

PubMed Central

Taylor, Jonathan; Tibshirani, Robert J.

2015-01-01

We describe the problem of “selective inference.” This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have “cherry-picked”—searched for the strongest associations—means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis. PMID:26100887

17. Causal inference based on counterfactuals

PubMed Central

Höfler, M

2005-01-01

Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept. PMID:16159397

18. Nonparametric inference of network structure and dynamics

Peixoto, Tiago P.

The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among

19. On the two-dimensional classical motion of a charged particle in an electromagnetic field with an additional quadratic integral of motion

Marikhin, V. G.

2013-06-01

The problem of quadratic Hamiltonians with an electromagnetic field commuting in the sense of the standard Poisson brackets has been considered. It has been shown that, as in the quantum case, any such pair can be reduced to the canonical form, which makes it possible to construct the complete classification of the solutions in the class of meromorphic solutions for the main function of one variable. The transformation to the canonical form is performed through the change of variables to the Kovalevskaya-type variables, which is similar to that in the theory of integrable tops. This transformation has been considered for the two-dimensional Hamiltonian of a charged particle with an additional quadratic integral of motion.

20. Self-enforcing Private Inference Control

Yang, Yanjiang; Li, Yingjiu; Weng, Jian; Zhou, Jianying; Bao, Feng

Private inference control enables simultaneous enforcement of inference control and protection of users' query privacy. Private inference control is a useful tool for database applications, especially when users are increasingly concerned about individual privacy nowadays. However, protection of query privacy on top of inference control is a double-edged sword: without letting the database server know the content of user queries, users can easily launch DoS attacks. To assuage DoS attacks in private inference control, we propose the concept of self-enforcing private inference control, whose intuition is to force users to only make inference-free queries by enforcing inference control themselves; otherwise, penalty will inflict upon the violating users.

1. The Probabilistic Convolution Tree: Efficient Exact Bayesian Inference for Faster LC-MS/MS Protein Inference

PubMed Central

Serang, Oliver

2014-01-01

Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called “causal independence”). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to and the space to where is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions. PMID:24626234

2. Inferring epigenetic dynamics from kin correlations.

PubMed

Hormoz, Sahand; Desprat, Nicolas; Shraiman, Boris I

2015-05-01

Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal--a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available. PMID:25902540

3. A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

PubMed Central

Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

2014-01-01

The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features. PMID:24473281

4. Classification of the quantum two-dimensional superintegrable systems with quadratic integrals and the Staeckel transforms

SciTech Connect

2008-05-15

The two-dimensional quantum superintegrable systems with quadratic integrals of motion on a manifold are classified by using the quadratic associative algebra of the integrals of motion. There are six general fundamental classes of quantum superintegrable systems corresponding to the classical ones. Analytic formulas for the involved integrals are calculated in all the cases. All the known quantum superintegrable systems with quadratic integrals are classified as special cases of these six general classes. The coefficients of the quadratic associative algebra of integrals are calculated and they are compared to the coefficients of the corresponding coefficients of the Poisson quadratic algebra of the classical systems. The quantum coefficients are similar to the classical ones multiplied by a quantum coefficient -{h_bar}{sup 2} plus a quantum deformation of order {h_bar}{sup 4} and {h_bar}{sup 6}. The systems inside the classes are transformed using Staeckel transforms in the quantum case as in the classical case. The general form of the Staeckel transform between superintegrable systems is discussed.

5. A wavelet bicoherence-based quadratic nonlinearity feature for translational axis condition monitoring.

PubMed

Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

2014-01-01

The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM) has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features. PMID:24473281

6. How Far Is "Near"? Inferring Distance from Spatial Descriptions

ERIC Educational Resources Information Center

Carlson, Laura A.; Covey, Eric S.

2005-01-01

A word may mean different things in different contexts. The current study explored the changing denotations of spatial terms, focusing on how the distance inferred from a spatial description varied as a function of the size of the objects being spatially related. We examined both terms that explicitly convey distance (i.e., topological terms such…

7. Resurrecting quadratic inflation in no-scale supergravity in light of BICEP2

SciTech Connect

Ellis, John; García, Marcos A.G.; Olive, Keith A.; Nanopoulos, Dimitri V. E-mail: garciagarcia@physics.umn.edu E-mail: olive@physics.umn.edu

2014-05-01

The magnitude of primordial tensor perturbations reported by the BICEP2 experiment is consistent with simple models of chaotic inflation driven by a single scalar field with a power-law potential ∝ φ{sup n} : n ≅ 2, in contrast to the WMAP and Planck results, which favored models resembling the Starobinsky R+R{sup 2} model if running of the scalar spectral index could be neglected. While models of inflation with a quadratic potential may be constructed in simple N = 1 supergravity, these constructions are more challenging in no-scale supergravity. We discuss here how quadratic inflation can be accommodated within supergravity, focusing primarily on the no-scale case. We also argue that the quadratic inflaton may be identified with the supersymmetric partner of a singlet (right-handed) neutrino, whose subsequent decay could have generated the baryon asymmetry via leptogenesis.

8. Clifford group, stabilizer states, and linear and quadratic operations over GF(2)

SciTech Connect

Dehaene, Jeroen; Moor, Bart de

2003-10-01

We describe stabilizer states and Clifford group operations using linear operations and quadratic forms over binary vector spaces. We show how the n-qubit Clifford group is isomorphic to a group with an operation that is defined in terms of a (2n+1)x(2n+1) binary matrix product and binary quadratic forms. As an application we give two schemes to efficiently decompose Clifford group operations into one- and two-qubit operations. We also show how the coefficients of stabilizer states and Clifford group operations in a standard basis expansion can be described by binary quadratic forms. Our results are useful for quantum error correction, entanglement distillation, and possibly quantum computing.

9. Directional passability and quadratic steering logic for pyramid-type single gimbal control moment gyros

2014-09-01

Singularity analysis and the steering logic of pyramid-type single gimbal control moment gyros are studied. First, a new concept of directional passability in a specified direction is introduced to investigate the structure of an elliptic singular surface. The differences between passability and directional passability are discussed in detail and are visualized for 0H, 2H, and 4H singular surfaces. Second, quadratic steering logic (QSL), a new steering logic for passing the singular surface, is investigated. The algorithm is based on the quadratic constrained quadratic optimization problem and is reduced to the Newton method by using Gröbner bases. The proposed steering logic is demonstrated through numerical simulations for both constant torque maneuvering examples and attitude control examples.

10. Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

SciTech Connect

Shafii, Mohammad Ali Meidianti, Rahma Wildian, Fitriyani, Dian; Tongkukut, Seni H. J.; Arkundato, Artoto

2014-09-30

Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation.

11. sick: The Spectroscopic Inference Crank

Casey, Andrew R.

2016-03-01

There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal

12. Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding

PubMed Central

Poldrack, Russell A.

2011-01-01

A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference”, has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference, and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data. PMID:22153367

13. Finite element simulation of articular contact mechanics with quadratic tetrahedral elements.

PubMed

Maas, Steve A; Ellis, Benjamin J; Rawlins, David S; Weiss, Jeffrey A

2016-03-21

Although it is easier to generate finite element discretizations with tetrahedral elements, trilinear hexahedral (HEX8) elements are more often used in simulations of articular contact mechanics. This is due to numerical shortcomings of linear tetrahedral (TET4) elements, limited availability of quadratic tetrahedron elements in combination with effective contact algorithms, and the perceived increased computational expense of quadratic finite elements. In this study we implemented both ten-node (TET10) and fifteen-node (TET15) quadratic tetrahedral elements in FEBio (www.febio.org) and compared their accuracy, robustness in terms of convergence behavior and computational cost for simulations relevant to articular contact mechanics. Suitable volume integration and surface integration rules were determined by comparing the results of several benchmark contact problems. The results demonstrated that the surface integration rule used to evaluate the contact integrals for quadratic elements affected both convergence behavior and accuracy of predicted stresses. The computational expense and robustness of both quadratic tetrahedral formulations compared favorably to the HEX8 models. Of note, the TET15 element demonstrated superior convergence behavior and lower computational cost than both the TET10 and HEX8 elements for meshes with similar numbers of degrees of freedom in the contact problems that we examined. Finally, the excellent accuracy and relative efficiency of these quadratic tetrahedral elements was illustrated by comparing their predictions with those for a HEX8 mesh for simulation of articular contact in a fully validated model of the hip. These results demonstrate that TET10 and TET15 elements provide viable alternatives to HEX8 elements for simulation of articular contact mechanics. PMID:26900037

14. A duality theorem-based algorithm for inexact quadratic programming problems: Application to waste management under uncertainty

Kong, X. M.; Huang, G. H.; Fan, Y. R.; Li, Y. P.

2016-04-01

In this study, a duality theorem-based algorithm (DTA) for inexact quadratic programming (IQP) is developed for municipal solid waste (MSW) management under uncertainty. It improves upon the existing numerical solution method for IQP problems. The comparison between DTA and derivative algorithm (DAM) shows that the DTA method provides better solutions than DAM with lower computational complexity. It is not necessary to identify the uncertain relationship between the objective function and decision variables, which is required for the solution process of DAM. The developed method is applied to a case study of MSW management and planning. The results indicate that reasonable solutions have been generated for supporting long-term MSW management and planning. They could provide more information as well as enable managers to make better decisions to identify desired MSW management policies in association with minimized cost under uncertainty.

15. A new family of N dimensional superintegrable double singular oscillators and quadratic algebra Q(3) ⨁ so(n) ⨁ so(N-n)

Fazlul Hoque, Md; Marquette, Ian; Zhang, Yao-Zhong

2015-11-01

We introduce a new family of N dimensional quantum superintegrable models consisting of double singular oscillators of type (n, N-n). The special cases (2,2) and (4,4) have previously been identified as the duals of 3- and 5-dimensional deformed Kepler-Coulomb systems with u(1) and su(2) monopoles, respectively. The models are multiseparable and their wave functions are obtained in (n, N-n) double-hyperspherical coordinates. We obtain the integrals of motion and construct the finitely generated polynomial algebra that is the direct sum of a quadratic algebra Q(3) involving three generators, so(n), so(N-n) (i.e. Q(3) ⨁ so(n) ⨁ so(N-n)). The structure constants of the quadratic algebra itself involve the Casimir operators of the two Lie algebras so(n) and so(N-n). Moreover, we obtain the finite dimensional unitary representations (unirreps) of the quadratic algebra and present an algebraic derivation of the degenerate energy spectrum of the superintegrable model.

16. Inference of fitness from genealogical trees

Vucelja, Marija; Dayarian, Adel; Shraiman, Boris

2013-03-01

Natural populations are fitness diverse and can have numerous genes under selection. The genealogical trees, that one obtains by sampling, often bear hallmarks of selection, such multiple mergers, asymmetric tree branches and long terminal branches (the trees are squished towards the root). These are qualitative differences compared to trees in the absence of selection. We propose a theoretical model that links the morphology of a tree with the fitness of the leaves. We obtain multipoint correlation functions of the fitness along the tree. In this way we are able extract some quantitative information about the strength of selection from data-reconstructed trees. The extensions of this approach can potentially be useful for inferring relative fitness of sequenced genomes of tumors and for predicting viral outbreaks.

17. An efficient algorithm for computing the roots of general quadratic, cubic and quartic equations

Mahmood, Munir; Hammad, Sali; Mahmood, Ibtihal

2014-10-01

While the solution to deriving the roots of the general quadratic equation is adequately covered in a typical classroom environment, the same is not true for the general cubic and quartic equations. To the best of our knowledge, we do not see the roots of the general cubic or quartic equation discussed in any typical algebra textbook at the undergraduate level. In this paper, we propose an efficient algorithm in order to calculate the roots of the general quadratic, cubic and quartic equations. Examples are given to demonstrate the usefulness of this proposed algorithm.

18. Nonadiabatic effects in ultracold molecules via anomalous linear and quadratic Zeeman shifts.

PubMed

McGuyer, B H; Osborn, C B; McDonald, M; Reinaudi, G; Skomorowski, W; Moszynski, R; Zelevinsky, T

2013-12-13

Anomalously large linear and quadratic Zeeman shifts are measured for weakly bound ultracold 88Sr2 molecules near the intercombination-line asymptote. Nonadiabatic Coriolis coupling and the nature of long-range molecular potentials explain how this effect arises and scales roughly cubically with the size of the molecule. The linear shifts yield nonadiabatic mixing angles of the molecular states. The quadratic shifts are sensitive to nearby opposite f-parity states and exhibit fourth-order corrections, providing a stringent test of a state-of-the-art ab initio model. PMID:24483652

19. Contractions and deformations of quasiclassical Lie algebras preserving a nondegenerate quadratic Casimir operator

SciTech Connect

Campoamor-Stursberg, R.

2008-05-15

By means of contractions of Lie algebras, we obtain new classes of indecomposable quasiclassical Lie algebras that satisfy the Yang-Baxter equations in its reformulation in terms of triple products. These algebras are shown to arise naturally from noncompact real simple algebras with nonsimple complexification, where we impose that a nondegenerate quadratic Casimir operator is preserved by the limiting process. We further consider the converse problem and obtain sufficient conditions on integrable cocycles of quasiclassical Lie algebras in order to preserve nondegenerate quadratic Casimir operators by the associated linear deformations.

20. Haar wavelet operational matrix method for solving constrained nonlinear quadratic optimal control problem